WEBVTT 00:00:00.000 --> 00:00:00.976 align:middle line:90% 00:00:00.976 --> 00:00:02.880 align:middle line:90% [SQUEAKING] 00:00:02.880 --> 00:00:04.308 align:middle line:90% [RUSTLING] 00:00:04.308 --> 00:00:08.738 align:middle line:90% [CLICKING] 00:00:08.738 --> 00:00:10.280 align:middle line:84% JOSH MCDERMOTT: So today, we're going 00:00:10.280 --> 00:00:11.697 align:middle line:84% to wrap up talking about attention 00:00:11.697 --> 00:00:13.440 align:middle line:90% and then talk about touch. 00:00:13.440 --> 00:00:17.440 align:middle line:84% So last time, we got started talking 00:00:17.440 --> 00:00:21.640 align:middle line:84% about effects of attention that you can see in the brain. 00:00:21.640 --> 00:00:25.242 align:middle line:84% So we went over this general finding 00:00:25.242 --> 00:00:27.200 align:middle line:84% that when you're paying attention to something, 00:00:27.200 --> 00:00:28.500 align:middle line:90% it can be a part of space. 00:00:28.500 --> 00:00:30.680 align:middle line:84% It could be a type of feature, a type of object. 00:00:30.680 --> 00:00:35.840 align:middle line:84% You usually get an increase in neural activity in the region 00:00:35.840 --> 00:00:37.440 align:middle line:84% that we think is processing whatever 00:00:37.440 --> 00:00:40.280 align:middle line:90% it is that you're attending. 00:00:40.280 --> 00:00:43.480 align:middle line:84% So this is a case where attention is directed 00:00:43.480 --> 00:00:46.200 align:middle line:90% to particular parts of space. 00:00:46.200 --> 00:00:48.760 align:middle line:84% And the way in which it's directed to those parts of space 00:00:48.760 --> 00:00:52.840 align:middle line:84% is people are asked to perform tasks that on stimuli that can 00:00:52.840 --> 00:00:54.500 align:middle line:90% appear at those parts of space. 00:00:54.500 --> 00:00:56.520 align:middle line:84% So they know that there's stuff happening 00:00:56.520 --> 00:00:58.480 align:middle line:90% in those regions that matters. 00:00:58.480 --> 00:01:00.480 align:middle line:84% And then you can measure with fMRI activity 00:01:00.480 --> 00:01:02.560 align:middle line:84% in the visual cortex and see that there's 00:01:02.560 --> 00:01:06.280 align:middle line:84% increases in activity in those regions of visual cortex 00:01:06.280 --> 00:01:08.840 align:middle line:84% that represent the parts of space 00:01:08.840 --> 00:01:12.260 align:middle line:90% that attention is directed to. 00:01:12.260 --> 00:01:16.380 align:middle line:84% We also saw how you can attend to particular types of objects. 00:01:16.380 --> 00:01:18.760 align:middle line:84% So this is an experiment where images of objects 00:01:18.760 --> 00:01:20.240 align:middle line:90% are superimposed. 00:01:20.240 --> 00:01:21.800 align:middle line:90% One of them is moving. 00:01:21.800 --> 00:01:24.000 align:middle line:84% And you're directed to attend to either the moving 00:01:24.000 --> 00:01:25.600 align:middle line:90% one or the static one. 00:01:25.600 --> 00:01:27.320 align:middle line:84% And in this particular case, these 00:01:27.320 --> 00:01:31.040 align:middle line:84% are images of faces or houses which preferentially activate 00:01:31.040 --> 00:01:36.240 align:middle line:84% these two distinct regions of the ventral visual cortex, 00:01:36.240 --> 00:01:39.960 align:middle line:84% the fusiform face area and the parahippocampal place area. 00:01:39.960 --> 00:01:43.920 align:middle line:84% And so the bottom line is that when 00:01:43.920 --> 00:01:48.600 align:middle line:84% you're attending to the face image, the activity in the FFA 00:01:48.600 --> 00:01:49.460 align:middle line:90% is higher. 00:01:49.460 --> 00:01:51.168 align:middle line:84% When you're attending to the house image, 00:01:51.168 --> 00:01:53.040 align:middle line:84% the activity in the PPA is higher-- so 00:01:53.040 --> 00:01:58.160 align:middle line:84% same sort of idea as back here but now with respect 00:01:58.160 --> 00:01:59.860 align:middle line:90% to types of objects. 00:01:59.860 --> 00:02:02.320 align:middle line:84% So that's where we left off last time. 00:02:02.320 --> 00:02:04.320 align:middle line:84% So what I want to do now is talk a little bit 00:02:04.320 --> 00:02:07.140 align:middle line:84% about what happens at the level of single neurons. 00:02:07.140 --> 00:02:14.200 align:middle line:84% So fMRI is a very, very coarse measure of brain activity. 00:02:14.200 --> 00:02:17.560 align:middle line:84% You're measuring the signal that is indirectly 00:02:17.560 --> 00:02:20.280 align:middle line:84% related to blood flow and attributed 00:02:20.280 --> 00:02:26.160 align:middle line:84% to small cubes of tissue known as voxels that each contain 00:02:26.160 --> 00:02:27.780 align:middle line:84% hundreds of thousands of neurons. 00:02:27.780 --> 00:02:31.218 align:middle line:84% If you want to measure the activity of single neurons, 00:02:31.218 --> 00:02:33.260 align:middle line:84% you usually have to do this in non-human animals. 00:02:33.260 --> 00:02:35.640 align:middle line:84% And so this is a very influential study 00:02:35.640 --> 00:02:38.480 align:middle line:84% that was conducted by our own Bob Desimone, who's 00:02:38.480 --> 00:02:41.080 align:middle line:84% now a professor here in BCS and director of the McGovern 00:02:41.080 --> 00:02:41.660 align:middle line:90% Institute. 00:02:41.660 --> 00:02:46.360 align:middle line:84% So he did this when he was at the NIH in the early '80s. 00:02:46.360 --> 00:02:49.360 align:middle line:84% So it was a very early study of the effects of attention 00:02:49.360 --> 00:02:51.080 align:middle line:90% on neural responses. 00:02:51.080 --> 00:02:54.280 align:middle line:84% This was done with macaque monkeys. 00:02:54.280 --> 00:02:57.290 align:middle line:84% So again, the methodology here is 00:02:57.290 --> 00:02:59.890 align:middle line:84% you've got an electrode in the monkey brain 00:02:59.890 --> 00:03:02.630 align:middle line:90% in a particular visual region. 00:03:02.630 --> 00:03:04.310 align:middle line:90% You isolate a particular neuron. 00:03:04.310 --> 00:03:07.130 align:middle line:84% And you can measure its response while the monkey is looking 00:03:07.130 --> 00:03:09.690 align:middle line:90% at stuff and doing things. 00:03:09.690 --> 00:03:12.370 align:middle line:84% And so in these experiments, the monkey 00:03:12.370 --> 00:03:15.450 align:middle line:84% was trained to make a discrimination 00:03:15.450 --> 00:03:19.010 align:middle line:90% on a particular stimulus. 00:03:19.010 --> 00:03:27.050 align:middle line:84% And so specifically, there were two stimuli-- 00:03:27.050 --> 00:03:29.670 align:middle line:84% a sample and a test presented sequentially. 00:03:29.670 --> 00:03:31.170 align:middle line:84% And the monkey responded differently 00:03:31.170 --> 00:03:32.970 align:middle line:84% depending on whether the two stimuli were 00:03:32.970 --> 00:03:34.050 align:middle line:90% the same or different. 00:03:34.050 --> 00:03:35.930 align:middle line:84% So they're doing a discrimination test 00:03:35.930 --> 00:03:38.110 align:middle line:84% on stimuli that are presented sequentially. 00:03:38.110 --> 00:03:40.130 align:middle line:84% And so the purpose of that is, again, 00:03:40.130 --> 00:03:43.430 align:middle line:84% to incentivize the monkey to pay attention to one of the stimuli 00:03:43.430 --> 00:03:45.472 align:middle line:84% because that's the one that they're going to have 00:03:45.472 --> 00:03:47.370 align:middle line:90% to make this discrimination on. 00:03:47.370 --> 00:03:48.090 align:middle line:90% All right. 00:03:48.090 --> 00:03:51.210 align:middle line:84% And the way that they set this experiment up 00:03:51.210 --> 00:03:54.810 align:middle line:84% is that the stimuli are chosen to either 00:03:54.810 --> 00:03:58.090 align:middle line:84% be an effective stimulus for the neuron that they're 00:03:58.090 --> 00:04:00.970 align:middle line:84% recording from or an ineffective stimulus. 00:04:00.970 --> 00:04:03.810 align:middle line:84% So effective here means that it produces a big response 00:04:03.810 --> 00:04:07.630 align:middle line:84% in the neuron, and ineffective means that it doesn't. 00:04:07.630 --> 00:04:13.530 align:middle line:84% So here's a picture from the paper that shows how this works. 00:04:13.530 --> 00:04:17.290 align:middle line:84% So the dashed line here represents 00:04:17.290 --> 00:04:19.410 align:middle line:84% the approximate boundaries of the receptive 00:04:19.410 --> 00:04:23.310 align:middle line:84% field of the neuron that's being recorded from. 00:04:23.310 --> 00:04:26.970 align:middle line:84% So initially, the way the experiment works is you 00:04:26.970 --> 00:04:28.070 align:middle line:90% isolate a neuron. 00:04:28.070 --> 00:04:29.390 align:middle line:90% You map its receptive field. 00:04:29.390 --> 00:04:32.330 align:middle line:84% So you figure out where the boundaries are. 00:04:32.330 --> 00:04:34.570 align:middle line:84% And then you set up your stimuli so 00:04:34.570 --> 00:04:37.050 align:middle line:84% that there are two stimuli that are appearing 00:04:37.050 --> 00:04:39.142 align:middle line:90% within the receptive field. 00:04:39.142 --> 00:04:40.850 align:middle line:84% One of them is chosen so that it produces 00:04:40.850 --> 00:04:41.933 align:middle line:90% a big response on its own. 00:04:41.933 --> 00:04:44.210 align:middle line:84% And the other one is chosen so that it doesn't. 00:04:44.210 --> 00:04:46.890 align:middle line:84% But they're both inside the receptive field. 00:04:46.890 --> 00:04:49.890 align:middle line:84% And then the key manipulation here-- 00:04:49.890 --> 00:04:51.670 align:middle line:84% so there's two key manipulations here. 00:04:51.670 --> 00:04:53.450 align:middle line:84% In this particular case shown here 00:04:53.450 --> 00:04:55.330 align:middle line:84% at the top, what they're manipulating 00:04:55.330 --> 00:04:58.610 align:middle line:84% is which of the two stimuli the animal is attending to. 00:04:58.610 --> 00:05:02.550 align:middle line:84% So on one set of trials, this stimulus, 00:05:02.550 --> 00:05:03.967 align:middle line:84% the effective stimulus, is the one 00:05:03.967 --> 00:05:05.758 align:middle line:84% that the animal is going to have to perform 00:05:05.758 --> 00:05:06.710 align:middle line:90% the discrimination on. 00:05:06.710 --> 00:05:08.210 align:middle line:84% And on the other set of trials, it's 00:05:08.210 --> 00:05:10.205 align:middle line:84% the other stimulus, the ineffective stimulus, 00:05:10.205 --> 00:05:12.330 align:middle line:84% that they'll have to perform the discrimination on. 00:05:12.330 --> 00:05:16.370 align:middle line:84% So they're interested in what does this change in what you're 00:05:16.370 --> 00:05:19.650 align:middle line:84% paying attention to do to the response of the single neuron 00:05:19.650 --> 00:05:20.810 align:middle line:90% in the brain. 00:05:20.810 --> 00:05:27.010 align:middle line:84% And the responses for this particular example 00:05:27.010 --> 00:05:29.030 align:middle line:84% neuron instead of stimuli are shown down here. 00:05:29.030 --> 00:05:30.230 align:middle line:90% These are raster plots. 00:05:30.230 --> 00:05:32.190 align:middle line:84% Anybody remember what raster plots are? 00:05:32.190 --> 00:05:34.810 align:middle line:90% 00:05:34.810 --> 00:05:38.490 align:middle line:84% What's this dimension represent in a raster plot? 00:05:38.490 --> 00:05:39.410 align:middle line:90% Time. 00:05:39.410 --> 00:05:43.210 align:middle line:84% What does this dimension represent? 00:05:43.210 --> 00:05:44.252 align:middle line:90% AUDIENCE: Neurons firing. 00:05:44.252 --> 00:05:45.877 align:middle line:84% JOSH MCDERMOTT: No, this dimension just 00:05:45.877 --> 00:05:47.150 align:middle line:90% represents different trials. 00:05:47.150 --> 00:05:50.710 align:middle line:84% So each row here is like-- is a different repeat of the trial. 00:05:50.710 --> 00:05:54.850 align:middle line:84% And the dot-- what do the dots represent? 00:05:54.850 --> 00:05:55.737 align:middle line:90% Spikes, yeah. 00:05:55.737 --> 00:05:58.070 align:middle line:84% So there's a dot every time there's an action potential. 00:05:58.070 --> 00:06:00.210 align:middle line:84% And so what you're supposed to be looking at 00:06:00.210 --> 00:06:03.810 align:middle line:84% is like whether there's a lot of dots or not very many dots. 00:06:03.810 --> 00:06:10.695 align:middle line:90% And so the S here is the sample. 00:06:10.695 --> 00:06:12.070 align:middle line:84% So that's the first presentation. 00:06:12.070 --> 00:06:12.790 align:middle line:90% The T is the test. 00:06:12.790 --> 00:06:14.082 align:middle line:90% That's the second presentation. 00:06:14.082 --> 00:06:17.490 align:middle line:84% So let's just look at when the sample is presented. 00:06:17.490 --> 00:06:20.130 align:middle line:84% And the point here is that the stimuli are 00:06:20.130 --> 00:06:21.990 align:middle line:90% identical in these two cases. 00:06:21.990 --> 00:06:25.250 align:middle line:84% But attention can be directed towards the effective stimulus 00:06:25.250 --> 00:06:27.010 align:middle line:90% or the ineffective stimulus. 00:06:27.010 --> 00:06:29.010 align:middle line:84% And the result is that when attention 00:06:29.010 --> 00:06:31.110 align:middle line:84% is directed towards the effective stimulus, 00:06:31.110 --> 00:06:32.390 align:middle line:90% you get a larger response. 00:06:32.390 --> 00:06:34.250 align:middle line:84% So there's more dots here than when 00:06:34.250 --> 00:06:36.350 align:middle line:84% it's directed towards the ineffective stimulus. 00:06:36.350 --> 00:06:40.410 align:middle line:90% So there's fewer dots here. 00:06:40.410 --> 00:06:44.010 align:middle line:84% Interestingly, these effects are really 00:06:44.010 --> 00:06:47.210 align:middle line:84% most pronounced when both of the stimuli 00:06:47.210 --> 00:06:49.160 align:middle line:90% are in the same receptive field. 00:06:49.160 --> 00:06:51.120 align:middle line:84% So this is one of the findings from this paper. 00:06:51.120 --> 00:06:54.320 align:middle line:84% So here's another thing that was manipulated. 00:06:54.320 --> 00:06:56.860 align:middle line:84% So in this situation, the two stimuli 00:06:56.860 --> 00:06:59.260 align:middle line:84% are positioned that one is inside the receptive field, 00:06:59.260 --> 00:07:01.180 align:middle line:90% and one is outside. 00:07:01.180 --> 00:07:03.092 align:middle line:84% So it's the same attentional manipulation. 00:07:03.092 --> 00:07:05.300 align:middle line:84% People are either attending to the affective stimulus 00:07:05.300 --> 00:07:06.740 align:middle line:90% or the ineffective stimulus. 00:07:06.740 --> 00:07:09.160 align:middle line:84% And the argument is that in this setting, 00:07:09.160 --> 00:07:11.100 align:middle line:84% there's much less of a difference 00:07:11.100 --> 00:07:13.220 align:middle line:90% between the responses. 00:07:13.220 --> 00:07:16.720 align:middle line:90% So that's the empirical finding. 00:07:16.720 --> 00:07:18.980 align:middle line:84% So there is this effect of what you're 00:07:18.980 --> 00:07:21.820 align:middle line:84% attending to on the response of single neurons. 00:07:21.820 --> 00:07:24.020 align:middle line:84% And those effects are most pronounced 00:07:24.020 --> 00:07:25.700 align:middle line:84% when there are multiple stimuli that 00:07:25.700 --> 00:07:28.000 align:middle line:90% are within the receptive field. 00:07:28.000 --> 00:07:30.100 align:middle line:84% And so one way to think about this 00:07:30.100 --> 00:07:35.060 align:middle line:84% is that attention is causing the receptive field effectively 00:07:35.060 --> 00:07:40.000 align:middle line:84% to shrink-- to shrink around the attended stimulus. 00:07:40.000 --> 00:07:42.420 align:middle line:84% And so in this particular case, it 00:07:42.420 --> 00:07:44.670 align:middle line:84% shrinks around the effective stimulus. 00:07:44.670 --> 00:07:45.920 align:middle line:90% And so you get a big response. 00:07:45.920 --> 00:07:48.295 align:middle line:84% In this case, it shrinks around the ineffective stimulus, 00:07:48.295 --> 00:07:51.100 align:middle line:90% and you get a smaller response. 00:07:51.100 --> 00:07:51.600 align:middle line:90% All right. 00:07:51.600 --> 00:07:54.700 align:middle line:90% So that's just one example. 00:07:54.700 --> 00:07:58.460 align:middle line:84% This is a summary of that effect for three 00:07:58.460 --> 00:07:59.880 align:middle line:90% different visual areas. 00:07:59.880 --> 00:08:03.500 align:middle line:84% And so what they're doing here is computing this thing 00:08:03.500 --> 00:08:06.180 align:middle line:84% that they call an attenuation index, which 00:08:06.180 --> 00:08:12.420 align:middle line:84% is a ratio between these two responses. 00:08:12.420 --> 00:08:16.420 align:middle line:84% So it's going to tell you the extent to which attention is 00:08:16.420 --> 00:08:18.080 align:middle line:90% causing the response to change. 00:08:18.080 --> 00:08:20.580 align:middle line:84% And so if attention is not having any effect, 00:08:20.580 --> 00:08:22.980 align:middle line:84% this ratio is going to tend to be one. 00:08:22.980 --> 00:08:25.140 align:middle line:84% And if it is having an effect, it 00:08:25.140 --> 00:08:28.020 align:middle line:90% will tend to be less than one. 00:08:28.020 --> 00:08:28.520 align:middle line:90% All right. 00:08:28.520 --> 00:08:32.380 align:middle line:84% And so here's that ratio plotted for area V4. 00:08:32.380 --> 00:08:35.840 align:middle line:84% Here it is for TE, and here it is for V1. 00:08:35.840 --> 00:08:40.460 align:middle line:84% Now for V4, they did two versions of the experiment. 00:08:40.460 --> 00:08:43.179 align:middle line:84% One in which both of the stimuli, the one that's attended 00:08:43.179 --> 00:08:45.637 align:middle line:84% and the one that's ignored, are inside the receptive field, 00:08:45.637 --> 00:08:46.846 align:middle line:90% and that's what's shown here. 00:08:46.846 --> 00:08:48.940 align:middle line:84% And what you're supposed to take away from this 00:08:48.940 --> 00:08:53.900 align:middle line:84% is that the histogram is peaked down here near zero. 00:08:53.900 --> 00:08:57.620 align:middle line:84% So most of the neurons are modulated by attention. 00:08:57.620 --> 00:09:00.940 align:middle line:90% 00:09:00.940 --> 00:09:04.980 align:middle line:84% Here is the variant of the experiment where one stimulus is 00:09:04.980 --> 00:09:07.720 align:middle line:84% inside the receptive field, and one stimulus is outside. 00:09:07.720 --> 00:09:09.640 align:middle line:84% And so here the result looks fairly different. 00:09:09.640 --> 00:09:10.640 align:middle line:90% Now you get a histogram. 00:09:10.640 --> 00:09:12.740 align:middle line:90% It's kind of peaked near one-- 00:09:12.740 --> 00:09:16.060 align:middle line:84% so much less attentional modulation. 00:09:16.060 --> 00:09:17.860 align:middle line:84% Now they looked at the same thing 00:09:17.860 --> 00:09:22.740 align:middle line:84% in area TE, which is part of inferotemporal cortex, one 00:09:22.740 --> 00:09:25.500 align:middle line:90% or two stages beyond V4. 00:09:25.500 --> 00:09:27.480 align:middle line:84% Now, when you get to inferotemporal cortex, 00:09:27.480 --> 00:09:30.500 align:middle line:84% you probably remember that the receptive fields are very large. 00:09:30.500 --> 00:09:32.745 align:middle line:84% So it's actually not easy to do the condition 00:09:32.745 --> 00:09:34.620 align:middle line:84% where one stimulus is in the receptive field, 00:09:34.620 --> 00:09:35.720 align:middle line:90% and one is outside. 00:09:35.720 --> 00:09:38.260 align:middle line:84% So all they've got is a situation where both stimuli 00:09:38.260 --> 00:09:40.220 align:middle line:90% are inside the receptive field. 00:09:40.220 --> 00:09:43.580 align:middle line:84% And again, you've got a histogram where most of the mass 00:09:43.580 --> 00:09:45.580 align:middle line:84% is down here at small numbers, so you're getting 00:09:45.580 --> 00:09:48.380 align:middle line:90% lots of attentional modulation. 00:09:48.380 --> 00:09:51.340 align:middle line:84% They also did the experiment measuring responses 00:09:51.340 --> 00:09:52.440 align:middle line:90% from neurons in V1. 00:09:52.440 --> 00:09:56.280 align:middle line:84% That's panel D. Now in V1, the receptive fields are very small. 00:09:56.280 --> 00:09:58.335 align:middle line:84% And so you can't really fit two stimuli 00:09:58.335 --> 00:09:59.960 align:middle line:84% inside the receptive field very easily. 00:09:59.960 --> 00:10:02.860 align:middle line:84% So they only did the condition where one stimulus was inside 00:10:02.860 --> 00:10:04.380 align:middle line:90% and one was outside. 00:10:04.380 --> 00:10:08.113 align:middle line:84% And there again, the histogram is peaked kind of at one, 00:10:08.113 --> 00:10:10.780 align:middle line:84% indicating that you can't really get much attentional modulation 00:10:10.780 --> 00:10:11.500 align:middle line:90% in V1. 00:10:11.500 --> 00:10:15.220 align:middle line:90% 00:10:15.220 --> 00:10:22.500 align:middle line:84% So take-home message is that you can see attentional modulation 00:10:22.500 --> 00:10:23.780 align:middle line:90% in single neurons. 00:10:23.780 --> 00:10:26.780 align:middle line:84% The effects seem to be biggest when multiple stimuli are 00:10:26.780 --> 00:10:28.700 align:middle line:90% in the receptive field. 00:10:28.700 --> 00:10:30.980 align:middle line:84% And it's kind of as though attention causes receptive 00:10:30.980 --> 00:10:34.240 align:middle line:84% fields to shrink around the attended stimulus. 00:10:34.240 --> 00:10:36.660 align:middle line:84% And so I'll just note that this is loosely 00:10:36.660 --> 00:10:39.100 align:middle line:84% consistent with that effect that we talked 00:10:39.100 --> 00:10:43.030 align:middle line:84% about last time of attentional queuing 00:10:43.030 --> 00:10:44.383 align:middle line:90% on texture discrimination. 00:10:44.383 --> 00:10:46.550 align:middle line:84% So remember, we looked at those results with texture 00:10:46.550 --> 00:10:49.270 align:middle line:84% discrimination where you put up a queue, 00:10:49.270 --> 00:10:52.310 align:middle line:84% and the pattern of results is consistent with the idea 00:10:52.310 --> 00:10:55.350 align:middle line:84% that the queue causes the receptive fields to shrink, 00:10:55.350 --> 00:10:58.310 align:middle line:84% which when the target is presented at the fovea 00:10:58.310 --> 00:11:01.110 align:middle line:84% makes you worse, and it causes the eccentricity 00:11:01.110 --> 00:11:03.110 align:middle line:84% at which you get the best performance to shift 00:11:03.110 --> 00:11:06.430 align:middle line:90% towards greater eccentricities. 00:11:06.430 --> 00:11:06.930 align:middle line:90% All right. 00:11:06.930 --> 00:11:08.010 align:middle line:90% Questions about that? 00:11:08.010 --> 00:11:13.490 align:middle line:90% 00:11:13.490 --> 00:11:13.990 align:middle line:90% Yeah. 00:11:13.990 --> 00:11:17.110 align:middle line:90% 00:11:17.110 --> 00:11:19.290 align:middle line:84% AUDIENCE: We've done texture discrimination. 00:11:19.290 --> 00:11:23.390 align:middle line:84% [INAUDIBLE] Can you describe this effect again? 00:11:23.390 --> 00:11:25.750 align:middle line:84% JOSH MCDERMOTT: The thing that I'm referring to here? 00:11:25.750 --> 00:11:26.430 align:middle line:90% Oh, yeah. 00:11:26.430 --> 00:11:30.910 align:middle line:84% I'll just go back quickly to that slide. 00:11:30.910 --> 00:11:33.550 align:middle line:84% That's this experiment with this result 00:11:33.550 --> 00:11:39.970 align:middle line:84% where people have to detect the distinct texture region. 00:11:39.970 --> 00:11:42.630 align:middle line:84% And when you cue people to the location 00:11:42.630 --> 00:11:45.550 align:middle line:84% and you look at performance as a function of eccentricity, 00:11:45.550 --> 00:11:48.972 align:middle line:84% you find that cuing shifts the location 00:11:48.972 --> 00:11:51.430 align:middle line:84% on the screen where you get the best performance to greater 00:11:51.430 --> 00:11:52.590 align:middle line:90% eccentricities. 00:11:52.590 --> 00:11:55.308 align:middle line:84% And this is the task where there's 00:11:55.308 --> 00:11:57.350 align:middle line:84% reason to think that the variation in performance 00:11:57.350 --> 00:12:00.790 align:middle line:84% with eccentricity is really due to the scale of the filters 00:12:00.790 --> 00:12:02.990 align:middle line:90% at that eccentricity. 00:12:02.990 --> 00:12:04.090 align:middle line:90% Make sense? 00:12:04.090 --> 00:12:04.590 align:middle line:90% Yeah. 00:12:04.590 --> 00:12:07.590 align:middle line:90% 00:12:07.590 --> 00:12:10.470 align:middle line:84% Let's talk a little bit about attention and eye movements. 00:12:10.470 --> 00:12:15.630 align:middle line:84% So normally in vision, attention and eye movements 00:12:15.630 --> 00:12:17.550 align:middle line:90% are very closely linked. 00:12:17.550 --> 00:12:19.750 align:middle line:84% So you typically are kind of paying attention 00:12:19.750 --> 00:12:21.670 align:middle line:90% to whatever you're looking at. 00:12:21.670 --> 00:12:25.110 align:middle line:84% And that's in part because usually, 00:12:25.110 --> 00:12:26.630 align:middle line:84% if you're attending to something, 00:12:26.630 --> 00:12:29.390 align:middle line:84% it's because you want to see it well. 00:12:29.390 --> 00:12:31.050 align:middle line:84% And normally, to see something well, 00:12:31.050 --> 00:12:32.550 align:middle line:84% you move your fovea to that location 00:12:32.550 --> 00:12:34.230 align:middle line:84% because that's where you got the highest 00:12:34.230 --> 00:12:35.530 align:middle line:90% density of retinal sampling. 00:12:35.530 --> 00:12:38.070 align:middle line:90% 00:12:38.070 --> 00:12:40.217 align:middle line:84% So attention often accompanies eye movements, 00:12:40.217 --> 00:12:42.550 align:middle line:84% but there are some important and interesting differences 00:12:42.550 --> 00:12:44.170 align:middle line:84% between attention and eye movements. 00:12:44.170 --> 00:12:48.430 align:middle line:84% So one is that you can attend to different spatial scales. 00:12:48.430 --> 00:12:51.230 align:middle line:84% So you could direct your attention 00:12:51.230 --> 00:12:55.230 align:middle line:84% to a particular location, but I could indicate to you 00:12:55.230 --> 00:12:57.070 align:middle line:84% that whatever is going to be happening 00:12:57.070 --> 00:12:59.850 align:middle line:84% is going to be happening in a very small spatial region, 00:12:59.850 --> 00:13:02.017 align:middle line:84% or it could also indicate that it could be happening 00:13:02.017 --> 00:13:02.990 align:middle line:90% in a spatial region. 00:13:02.990 --> 00:13:08.110 align:middle line:84% And you can show that there will be a benefit that 00:13:08.110 --> 00:13:11.670 align:middle line:84% would occur at different scales depending on those instructions. 00:13:11.670 --> 00:13:14.280 align:middle line:84% As we saw earlier in the lecture, 00:13:14.280 --> 00:13:16.030 align:middle line:84% you can also attend to more than one thing 00:13:16.030 --> 00:13:17.530 align:middle line:84% at once, whereas you can only really 00:13:17.530 --> 00:13:19.750 align:middle line:90% look at one thing at a time. 00:13:19.750 --> 00:13:24.070 align:middle line:84% And of course, you can attend to things in other modalities 00:13:24.070 --> 00:13:26.350 align:middle line:84% where eye movements are not relevant, possibly 00:13:26.350 --> 00:13:28.770 align:middle line:90% via some central mechanism. 00:13:28.770 --> 00:13:33.790 align:middle line:84% So these differences imply that the brain mechanisms 00:13:33.790 --> 00:13:37.150 align:middle line:84% of attention must in part be distinct from those 00:13:37.150 --> 00:13:40.550 align:middle line:84% for eye movements, but it remains likely 00:13:40.550 --> 00:13:43.750 align:middle line:84% that attentional mechanisms overlap to some extent 00:13:43.750 --> 00:13:45.630 align:middle line:90% with those for eye movements. 00:13:45.630 --> 00:13:49.510 align:middle line:84% And maybe actually attention evolved 00:13:49.510 --> 00:13:52.690 align:middle line:84% as an extension of the mechanisms for eye movement. 00:13:52.690 --> 00:13:55.390 align:middle line:84% So that's one reasonable hypothesis. 00:13:55.390 --> 00:13:58.710 align:middle line:84% So just to give you a taste of some of what we know about this. 00:13:58.710 --> 00:14:00.710 align:middle line:84% This is a pretty interesting study 00:14:00.710 --> 00:14:05.790 align:middle line:84% by Tirin Moore, who was once a post-doc here in BCS 00:14:05.790 --> 00:14:11.350 align:middle line:84% and is now a professor at Stanford. 00:14:11.350 --> 00:14:15.310 align:middle line:84% And in this study, they looked at the effect 00:14:15.310 --> 00:14:18.470 align:middle line:84% of stimulating in a part of the brain that 00:14:18.470 --> 00:14:24.350 align:middle line:84% controls eye movements on visual responses in visual cortex. 00:14:24.350 --> 00:14:27.725 align:middle line:84% So we haven't really talked about the brain circuits 00:14:27.725 --> 00:14:28.850 align:middle line:90% that control eye movements. 00:14:28.850 --> 00:14:30.890 align:middle line:84% It's a little bit beyond the scope of the course. 00:14:30.890 --> 00:14:32.848 align:middle line:84% But there's a few different parts of your brain 00:14:32.848 --> 00:14:34.840 align:middle line:84% that control your eyes, and one of them 00:14:34.840 --> 00:14:38.240 align:middle line:84% is called the frontal eye fields, or FEF. 00:14:38.240 --> 00:14:39.620 align:middle line:90% So that's like up there. 00:14:39.620 --> 00:14:40.980 align:middle line:90% So it exists in the macaque. 00:14:40.980 --> 00:14:43.600 align:middle line:90% It exists in humans. 00:14:43.600 --> 00:14:48.760 align:middle line:84% And one of the reasons why we believe that that brain 00:14:48.760 --> 00:14:51.160 align:middle line:84% region controls eye movements is that if you 00:14:51.160 --> 00:14:53.360 align:middle line:84% have an electrode positioned in that brain region 00:14:53.360 --> 00:14:55.120 align:middle line:90% and you stimulate-- 00:14:55.120 --> 00:14:57.380 align:middle line:84% so you put some current into the electrode, 00:14:57.380 --> 00:15:01.360 align:middle line:84% which causes neurons at the tip of the electrode to fire-- 00:15:01.360 --> 00:15:05.240 align:middle line:84% that has the consequence of causing the animal 00:15:05.240 --> 00:15:08.000 align:middle line:84% to move its eyes to a particular location. 00:15:08.000 --> 00:15:11.940 align:middle line:84% So you stimulate the particular site in the frontal eye fields. 00:15:11.940 --> 00:15:16.160 align:middle line:84% Boom, the eyes go to a particular retinal location. 00:15:16.160 --> 00:15:17.620 align:middle line:90% And that's what's shown here. 00:15:17.620 --> 00:15:21.097 align:middle line:84% So this is an experiment where there's an electrode positioned 00:15:21.097 --> 00:15:22.180 align:middle line:90% in the frontal eye fields. 00:15:22.180 --> 00:15:24.185 align:middle line:84% There's also an electrode positioned in V4 00:15:24.185 --> 00:15:25.560 align:middle line:84% that's recording responses, which 00:15:25.560 --> 00:15:27.240 align:middle line:90% we'll talk about in a second. 00:15:27.240 --> 00:15:30.240 align:middle line:84% But when you stimulate the electrode in the frontal eye 00:15:30.240 --> 00:15:33.580 align:middle line:84% fields, this is a plot of what happens to the eyes. 00:15:33.580 --> 00:15:36.200 align:middle line:84% So each of these different lines is like a different trial. 00:15:36.200 --> 00:15:38.117 align:middle line:84% And what you're supposed to derive from this-- 00:15:38.117 --> 00:15:41.240 align:middle line:84% so this is the fixation point, and the animal's eyes 00:15:41.240 --> 00:15:44.820 align:middle line:84% move kind of down and to the left by about the same amount. 00:15:44.820 --> 00:15:47.560 align:middle line:90% 00:15:47.560 --> 00:15:50.000 align:middle line:84% And so the idea is that normally, 00:15:50.000 --> 00:15:53.640 align:middle line:84% like when you're moving your eyes around, what's happening 00:15:53.640 --> 00:15:55.960 align:middle line:84% is there's this sequence of activity in the frontal eye 00:15:55.960 --> 00:15:56.300 align:middle line:90% fields. 00:15:56.300 --> 00:15:58.008 align:middle line:84% It's like planning all your eye movements 00:15:58.008 --> 00:16:00.720 align:middle line:84% and then sending these motor commands to your eye muscles 00:16:00.720 --> 00:16:04.200 align:middle line:84% to cause them to move in particular ways. 00:16:04.200 --> 00:16:08.700 align:middle line:84% So in this experiment, as it says on the slides, 00:16:08.700 --> 00:16:11.460 align:middle line:84% there's electrodes in both the frontal eye fields and V4. 00:16:11.460 --> 00:16:14.120 align:middle line:84% And they're recording from pairs of neurons. 00:16:14.120 --> 00:16:15.680 align:middle line:84% And they move the electrodes around 00:16:15.680 --> 00:16:18.060 align:middle line:84% until they find pairs of neurons that are matched. 00:16:18.060 --> 00:16:21.462 align:middle line:84% And they're matched in the following sense. 00:16:21.462 --> 00:16:23.920 align:middle line:84% So they're finding a pair of pairs of neurons, one of which 00:16:23.920 --> 00:16:28.520 align:middle line:84% is in V4, that has a receptive field at a particular location, 00:16:28.520 --> 00:16:31.080 align:middle line:84% and that receptive field location is approximately 00:16:31.080 --> 00:16:36.740 align:middle line:84% matched to where the eye movements go to 00:16:36.740 --> 00:16:39.120 align:middle line:84% when you stimulate at that location in the frontal eye 00:16:39.120 --> 00:16:39.700 align:middle line:90% fields. 00:16:39.700 --> 00:16:42.440 align:middle line:90% 00:16:42.440 --> 00:16:44.480 align:middle line:84% You're at this locus in the frontal eye fields 00:16:44.480 --> 00:16:48.040 align:middle line:84% where the neurons are coding for eye movements 00:16:48.040 --> 00:16:49.720 align:middle line:90% to a particular location. 00:16:49.720 --> 00:16:53.080 align:middle line:84% And then you're recording from the same-- the corresponding 00:16:53.080 --> 00:16:55.760 align:middle line:84% place in V4 whose neurons are representing 00:16:55.760 --> 00:16:59.280 align:middle line:90% that location in space. 00:16:59.280 --> 00:16:59.780 align:middle line:90% All right. 00:16:59.780 --> 00:17:01.520 align:middle line:90% So that's the setup. 00:17:01.520 --> 00:17:03.920 align:middle line:84% And this is a hard experiment to do because you've 00:17:03.920 --> 00:17:06.088 align:middle line:84% got to get each of the electrodes in the right place 00:17:06.088 --> 00:17:07.380 align:middle line:90% in order to find these neurons. 00:17:07.380 --> 00:17:09.720 align:middle line:90% But that's what they did. 00:17:09.720 --> 00:17:12.480 align:middle line:84% And I've just told you how if you stimulate in the frontal eye 00:17:12.480 --> 00:17:17.440 align:middle line:84% field above a certain threshold causes saccades. 00:17:17.440 --> 00:17:21.560 align:middle line:84% And so what they did in this study 00:17:21.560 --> 00:17:26.359 align:middle line:84% is to stimulate but below the threshold that evoked a saccade. 00:17:26.359 --> 00:17:28.300 align:middle line:84% So they stimulate the frontal eye fields 00:17:28.300 --> 00:17:32.160 align:middle line:84% but not so much as to cause an eye movement. 00:17:32.160 --> 00:17:35.920 align:middle line:84% And what they found is that subthreshold stimulation 00:17:35.920 --> 00:17:39.280 align:middle line:84% of the frontal eye field at that particular location 00:17:39.280 --> 00:17:41.880 align:middle line:84% causes attention-like enhancements 00:17:41.880 --> 00:17:44.040 align:middle line:90% of the response in V4. 00:17:44.040 --> 00:17:46.260 align:middle line:90% And so that's what's shown here. 00:17:46.260 --> 00:17:51.520 align:middle line:84% So they've got stimuli that are being presented in the receptive 00:17:51.520 --> 00:17:53.640 align:middle line:90% field of the V4 neuron. 00:17:53.640 --> 00:17:56.400 align:middle line:84% And they're measuring the responses 00:17:56.400 --> 00:17:59.880 align:middle line:84% with and without frontal eye field microstimulation. 00:17:59.880 --> 00:18:02.440 align:middle line:84% And so the red response is what happens 00:18:02.440 --> 00:18:03.817 align:middle line:90% following the microstimulation. 00:18:03.817 --> 00:18:05.400 align:middle line:84% And the black response is what happens 00:18:05.400 --> 00:18:07.760 align:middle line:90% without the microstimulation. 00:18:07.760 --> 00:18:10.320 align:middle line:84% And the eye traces-- so the H and the V 00:18:10.320 --> 00:18:13.580 align:middle line:84% represent the horizontal and vertical position of the eye. 00:18:13.580 --> 00:18:15.320 align:middle line:84% And so what that's supposed to tell you 00:18:15.320 --> 00:18:18.660 align:middle line:84% is that the stimulation is not causing the eyes to move. 00:18:18.660 --> 00:18:21.840 align:middle line:84% So the effect is not because the eyes are moving. 00:18:21.840 --> 00:18:23.320 align:middle line:90% It's something else. 00:18:23.320 --> 00:18:29.130 align:middle line:84% And the claim is that that kind of enhancement of the response 00:18:29.130 --> 00:18:33.770 align:middle line:84% is a lot like what you would see if you were paying attention 00:18:33.770 --> 00:18:35.030 align:middle line:90% to that location. 00:18:35.030 --> 00:18:36.623 align:middle line:84% And this is showing that if there's 00:18:36.623 --> 00:18:38.290 align:middle line:84% no stimulus in the receptive field, then 00:18:38.290 --> 00:18:41.490 align:middle line:84% you don't really get much of an effect. 00:18:41.490 --> 00:18:45.530 align:middle line:84% And so the inference here is that the circuitry that 00:18:45.530 --> 00:18:48.010 align:middle line:84% controls eye movements could mediate 00:18:48.010 --> 00:18:50.770 align:middle line:90% some attentional effects. 00:18:50.770 --> 00:18:54.150 align:middle line:84% So you might say, well, why is that? 00:18:54.150 --> 00:18:58.810 align:middle line:84% Well, possibly because normally, attention 00:18:58.810 --> 00:19:00.530 align:middle line:84% does move with the eyes, so they should 00:19:00.530 --> 00:19:03.170 align:middle line:90% be coordinated in some way. 00:19:03.170 --> 00:19:05.130 align:middle line:84% The eye movement circuitry also has 00:19:05.130 --> 00:19:08.170 align:middle line:84% some of the characteristics that you might want attention 00:19:08.170 --> 00:19:10.743 align:middle line:84% to have, in the sense that it can be spatially directed. 00:19:10.743 --> 00:19:12.410 align:middle line:84% Because you can look at-- move your eyes 00:19:12.410 --> 00:19:14.190 align:middle line:84% in all these different directions. 00:19:14.190 --> 00:19:17.010 align:middle line:90% 00:19:17.010 --> 00:19:20.290 align:middle line:84% So it's an interesting hypothesis. 00:19:20.290 --> 00:19:27.555 align:middle line:84% So far, we've been talking about neural correlates of attention. 00:19:27.555 --> 00:19:29.930 align:middle line:84% So what changes in the brain when you're paying attention 00:19:29.930 --> 00:19:30.710 align:middle line:90% to something? 00:19:30.710 --> 00:19:34.370 align:middle line:84% And what we just discussed about eye movements kind of 00:19:34.370 --> 00:19:39.210 align:middle line:84% is one potential proposal for where attentional effects might 00:19:39.210 --> 00:19:40.890 align:middle line:90% originate from. 00:19:40.890 --> 00:19:43.950 align:middle line:84% But there's another part of the brain, the parietal lobe, 00:19:43.950 --> 00:19:46.030 align:middle line:84% that also seems to be really important. 00:19:46.030 --> 00:19:48.850 align:middle line:84% So the parietal lobe is typically active 00:19:48.850 --> 00:19:52.250 align:middle line:84% when people are asked to move their attention around. 00:19:52.250 --> 00:19:54.890 align:middle line:84% And when the parietal lobe is damaged, 00:19:54.890 --> 00:19:57.890 align:middle line:84% you see disorders that are often interpreted 00:19:57.890 --> 00:20:00.010 align:middle line:90% as disorders of attention. 00:20:00.010 --> 00:20:04.890 align:middle line:84% So remember, think of the visual system 00:20:04.890 --> 00:20:08.630 align:middle line:84% as having the ventral and dorsal stream organization. 00:20:08.630 --> 00:20:10.770 align:middle line:90% The parietal lobe is up here. 00:20:10.770 --> 00:20:13.690 align:middle line:84% So it's where the dorsal stream kind of ends up. 00:20:13.690 --> 00:20:19.090 align:middle line:84% And lesions to the parietal lobe result 00:20:19.090 --> 00:20:23.210 align:middle line:84% in a phenomenon that's typically referred to as neglect. 00:20:23.210 --> 00:20:28.890 align:middle line:84% And it's called neglect because one of the key symptoms 00:20:28.890 --> 00:20:32.230 align:middle line:84% is that people neglect one side of space. 00:20:32.230 --> 00:20:33.810 align:middle line:90% It's like they ignore it. 00:20:33.810 --> 00:20:38.250 align:middle line:84% So this is an excerpt of a case study. 00:20:38.250 --> 00:20:42.450 align:middle line:84% It says Mr. P neglected the left side of his body 00:20:42.450 --> 00:20:43.790 align:middle line:90% and of the world. 00:20:43.790 --> 00:20:47.650 align:middle line:84% When asked to lift up his arms, he failed to lift his left arm, 00:20:47.650 --> 00:20:51.410 align:middle line:84% but could do so if one took his arm and asked him to lift it. 00:20:51.410 --> 00:20:54.730 align:middle line:84% When asked to draw a clock face, he crowded all the numbers 00:20:54.730 --> 00:20:56.850 align:middle line:84% onto the right side of the clock. 00:20:56.850 --> 00:20:59.490 align:middle line:84% When asked to read compound words such as ice cream 00:20:59.490 --> 00:21:02.112 align:middle line:84% and football, he read cream and ball. 00:21:02.112 --> 00:21:03.570 align:middle line:84% When he dressed, he did not attempt 00:21:03.570 --> 00:21:06.270 align:middle line:84% to put on the left side of his clothing, and when he shaved, 00:21:06.270 --> 00:21:08.890 align:middle line:84% he shaved only the right side of his face. 00:21:08.890 --> 00:21:12.210 align:middle line:84% He ignored tactile sensation on the left side of his body. 00:21:12.210 --> 00:21:14.810 align:middle line:84% Finally, he appeared unaware that anything was wrong with him 00:21:14.810 --> 00:21:17.690 align:middle line:84% and was uncertain as to what all the fuss was about. 00:21:17.690 --> 00:21:22.870 align:middle line:84% So this is interpreted as an attentional disorder 00:21:22.870 --> 00:21:27.330 align:middle line:84% because it's not the case that this individual is 00:21:27.330 --> 00:21:31.570 align:middle line:90% blind on the left side of space. 00:21:31.570 --> 00:21:33.690 align:middle line:84% If you do things to direct their attention over 00:21:33.690 --> 00:21:37.210 align:middle line:84% to that side of space, they can see things. 00:21:37.210 --> 00:21:40.490 align:middle line:84% But it's like they don't on their own pay attention to it 00:21:40.490 --> 00:21:41.850 align:middle line:90% and don't notice it. 00:21:41.850 --> 00:21:45.090 align:middle line:84% So here's an example of what happens if you 00:21:45.090 --> 00:21:46.850 align:middle line:90% ask them to do certain things. 00:21:46.850 --> 00:21:49.090 align:middle line:84% So this is a line cancelation task-- so 00:21:49.090 --> 00:21:50.778 align:middle line:90% part of a standard assessment. 00:21:50.778 --> 00:21:52.570 align:middle line:84% So you give them a sheet-- a piece of paper 00:21:52.570 --> 00:21:54.490 align:middle line:84% that's got all these line segments. 00:21:54.490 --> 00:21:58.030 align:middle line:84% And you ask them to put a mark through every line segment. 00:21:58.030 --> 00:22:00.530 align:middle line:84% And this is what somebody with neglect would do. 00:22:00.530 --> 00:22:04.310 align:middle line:84% So they X out a lot of the line segments on the right, 00:22:04.310 --> 00:22:07.890 align:middle line:84% but none of the ones that are on the left. 00:22:07.890 --> 00:22:10.710 align:middle line:84% You can ask them also to do a line bisection task. 00:22:10.710 --> 00:22:14.970 align:middle line:84% So put a marker through the middle of the line segment, 00:22:14.970 --> 00:22:19.450 align:middle line:90% and they're way off the center. 00:22:19.450 --> 00:22:22.310 align:middle line:84% You can ask them to copy pictures. 00:22:22.310 --> 00:22:23.150 align:middle line:90% So here's the model. 00:22:23.150 --> 00:22:24.330 align:middle line:90% It's a clock. 00:22:24.330 --> 00:22:29.530 align:middle line:84% This is an actual drawing by a patient with neglect. 00:22:29.530 --> 00:22:30.550 align:middle line:90% Here's another example. 00:22:30.550 --> 00:22:32.370 align:middle line:90% This is a house. 00:22:32.370 --> 00:22:35.810 align:middle line:84% They leave out a lot of the stuff that's on the left side. 00:22:35.810 --> 00:22:40.250 align:middle line:84% Flower-- and again leaving out some of the stuff that's 00:22:40.250 --> 00:22:42.050 align:middle line:90% on the left side. 00:22:42.050 --> 00:22:47.450 align:middle line:84% So neglect typically and the parietal lobe 00:22:47.450 --> 00:22:49.050 align:middle line:84% lesions that result from it typically 00:22:49.050 --> 00:22:51.170 align:middle line:90% would result from a stroke. 00:22:51.170 --> 00:22:53.490 align:middle line:84% So remember what happens when people have a stroke? 00:22:53.490 --> 00:22:57.530 align:middle line:84% The brain is deprived of blood flow and oxygen 00:22:57.530 --> 00:22:59.870 align:middle line:90% and dies pretty quickly. 00:22:59.870 --> 00:23:01.990 align:middle line:84% And so depending on what type of stroke you have, 00:23:01.990 --> 00:23:04.407 align:middle line:84% there'll be different parts of the brain that are damaged. 00:23:04.407 --> 00:23:06.690 align:middle line:84% And so parietal lobe lesions cause this phenomenon 00:23:06.690 --> 00:23:09.730 align:middle line:90% of neglect. 00:23:09.730 --> 00:23:13.250 align:middle line:84% Now one of the things that often characterizes brain damage 00:23:13.250 --> 00:23:14.390 align:middle line:90% is that there's plasticity. 00:23:14.390 --> 00:23:16.840 align:middle line:84% So there's often some process of recovery. 00:23:16.840 --> 00:23:21.580 align:middle line:84% So this is a really interesting example of somebody 00:23:21.580 --> 00:23:25.900 align:middle line:84% who is an artist who suffered right parietal damage. 00:23:25.900 --> 00:23:29.900 align:middle line:84% And this is a series of self-portraits over the course 00:23:29.900 --> 00:23:30.920 align:middle line:90% of their recovery. 00:23:30.920 --> 00:23:33.500 align:middle line:84% And so initially, you can see that they're entirely 00:23:33.500 --> 00:23:36.540 align:middle line:84% just drawing stuff that's on the right side. 00:23:36.540 --> 00:23:38.340 align:middle line:84% And then as they recover, they're 00:23:38.340 --> 00:23:43.180 align:middle line:84% able to get more and more of the stuff that's on the left. 00:23:43.180 --> 00:23:43.680 align:middle line:90% All right. 00:23:43.680 --> 00:23:45.500 align:middle line:90% So you might ask, so what is it? 00:23:45.500 --> 00:23:48.580 align:middle line:90% What's special about the left? 00:23:48.580 --> 00:23:50.860 align:middle line:84% I think that's not totally well understood. 00:23:50.860 --> 00:23:55.980 align:middle line:84% So in general, neglect tends to be much more 00:23:55.980 --> 00:24:00.420 align:middle line:90% a left visual hemifield thing. 00:24:00.420 --> 00:24:04.900 align:middle line:84% But it's just a phenomenon at this point. 00:24:04.900 --> 00:24:06.260 align:middle line:90% Yeah. 00:24:06.260 --> 00:24:08.240 align:middle line:84% AUDIENCE: Like the line bisection task-- 00:24:08.240 --> 00:24:11.660 align:middle line:84% if you move the paper over to the right, 00:24:11.660 --> 00:24:13.477 align:middle line:90% they will do the whole thing? 00:24:13.477 --> 00:24:16.060 align:middle line:84% JOSH MCDERMOTT: So OK, so one of the really interesting things 00:24:16.060 --> 00:24:18.920 align:middle line:84% about neglect is that it's often, at least to some extent, 00:24:18.920 --> 00:24:20.180 align:middle line:90% object-based. 00:24:20.180 --> 00:24:22.940 align:middle line:84% So it's not just about whether the stuff 00:24:22.940 --> 00:24:26.900 align:middle line:84% is in the left hemifield-- so to the left of fixation. 00:24:26.900 --> 00:24:29.500 align:middle line:84% So they'll neglect the left part of objects. 00:24:29.500 --> 00:24:33.120 align:middle line:84% So you can have an object that's in the good hemifield. 00:24:33.120 --> 00:24:36.360 align:middle line:84% And they'll still tend to neglect the left side of it. 00:24:36.360 --> 00:24:38.760 align:middle line:90% Yeah. 00:24:38.760 --> 00:24:44.180 align:middle line:84% And so it's yeah, one of many pieces of evidence in support 00:24:44.180 --> 00:24:48.000 align:middle line:84% of the idea that attention is kind of object-based, 00:24:48.000 --> 00:24:51.480 align:middle line:84% that you tend to direct your attention to objects. 00:24:51.480 --> 00:24:53.960 align:middle line:84% But yeah, you can neglect sides of objects too. 00:24:53.960 --> 00:24:56.620 align:middle line:90% 00:24:56.620 --> 00:24:58.160 align:middle line:90% Any other questions about that? 00:24:58.160 --> 00:25:01.920 align:middle line:90% 00:25:01.920 --> 00:25:05.980 align:middle line:84% So we talked about a lot of stuff 00:25:05.980 --> 00:25:08.460 align:middle line:84% because attention is kind of rich and diverse and not 00:25:08.460 --> 00:25:11.300 align:middle line:84% very theoretically unified at this point. 00:25:11.300 --> 00:25:14.060 align:middle line:90% So this is just a quick recap. 00:25:14.060 --> 00:25:16.860 align:middle line:84% So we talked about how attention has been studied with lots 00:25:16.860 --> 00:25:18.260 align:middle line:90% of different paradigms. 00:25:18.260 --> 00:25:21.460 align:middle line:84% We just discussed queuing and the distinction 00:25:21.460 --> 00:25:24.820 align:middle line:84% between exogenous and endogenous queuing. 00:25:24.820 --> 00:25:28.520 align:middle line:84% Talked about how queuing results gave rise to a spotlight 00:25:28.520 --> 00:25:31.380 align:middle line:90% metaphor of attention. 00:25:31.380 --> 00:25:33.680 align:middle line:84% Talked about exceptions to the spotlight metaphor, 00:25:33.680 --> 00:25:35.180 align:middle line:84% like multiple object tracking, where 00:25:35.180 --> 00:25:37.013 align:middle line:84% you seem to be able to direct your attention 00:25:37.013 --> 00:25:39.260 align:middle line:90% to multiple locations at once. 00:25:39.260 --> 00:25:42.020 align:middle line:84% We talked about the paradigm of visual search, 00:25:42.020 --> 00:25:44.402 align:middle line:84% where there's an array of elements, 00:25:44.402 --> 00:25:45.860 align:middle line:84% and you have to find the one that's 00:25:45.860 --> 00:25:48.380 align:middle line:84% kind of different from the others. 00:25:48.380 --> 00:25:50.780 align:middle line:84% Talked about differences between feature and conjunction 00:25:50.780 --> 00:25:54.020 align:middle line:84% searches, where feature searches tend to be fast, 00:25:54.020 --> 00:25:56.620 align:middle line:84% and the reaction time tends not to scale with the number 00:25:56.620 --> 00:25:57.720 align:middle line:90% of items in the display. 00:25:57.720 --> 00:26:00.100 align:middle line:84% Whereas conjunction searches tend to be slow, 00:26:00.100 --> 00:26:03.460 align:middle line:84% and reaction time increases as the number of elements 00:26:03.460 --> 00:26:05.260 align:middle line:90% in the display increases. 00:26:05.260 --> 00:26:08.500 align:middle line:84% Talked about the idea of feature integration theory, which 00:26:08.500 --> 00:26:11.060 align:middle line:84% was traditionally used to explain 00:26:11.060 --> 00:26:13.580 align:middle line:84% the differences between feature and conjunction searches 00:26:13.580 --> 00:26:15.780 align:middle line:84% and illusory conjunctions as evidence 00:26:15.780 --> 00:26:18.660 align:middle line:84% that you need attention to bind features. 00:26:18.660 --> 00:26:21.420 align:middle line:84% Talked about evidence that attention 00:26:21.420 --> 00:26:25.920 align:middle line:84% improves spatial resolution and increases apparent contrast. 00:26:25.920 --> 00:26:30.380 align:middle line:84% Talked about evidence that attention seems to dilate time. 00:26:30.380 --> 00:26:35.020 align:middle line:84% Saw that it speeds responses, integrates features. 00:26:35.020 --> 00:26:37.120 align:middle line:84% Talked about how there is an attentional blink. 00:26:37.120 --> 00:26:38.880 align:middle line:84% So if you select something with your attention, 00:26:38.880 --> 00:26:40.672 align:middle line:84% there's a little bit of a refractory period 00:26:40.672 --> 00:26:43.620 align:middle line:84% before you can grab the next thing. 00:26:43.620 --> 00:26:45.040 align:middle line:90% Talked about change blindness. 00:26:45.040 --> 00:26:47.500 align:middle line:84% These are instances where you don't see changes 00:26:47.500 --> 00:26:49.300 align:middle line:90% without attention. 00:26:49.300 --> 00:26:52.180 align:middle line:84% So you can miss really salient things in the image. 00:26:52.180 --> 00:26:56.522 align:middle line:84% Talked about selective listening and evidence that there-- 00:26:56.522 --> 00:26:58.480 align:middle line:84% for things that you're not paying attention to, 00:26:58.480 --> 00:27:01.740 align:middle line:84% there's pretty strict limits on the extent 00:27:01.740 --> 00:27:05.420 align:middle line:90% to which it gets processed. 00:27:05.420 --> 00:27:08.123 align:middle line:84% And we talked about the neural basis of attention. 00:27:08.123 --> 00:27:10.790 align:middle line:84% So some of the key findings here are that attention to something 00:27:10.790 --> 00:27:14.270 align:middle line:84% generally increases the response to that something. 00:27:14.270 --> 00:27:16.790 align:middle line:84% Attention often acts as though it shrinks receptive fields 00:27:16.790 --> 00:27:18.990 align:middle line:90% around the attended stimulus. 00:27:18.990 --> 00:27:21.550 align:middle line:84% Eye movement circuits seem to be able to mediate 00:27:21.550 --> 00:27:23.710 align:middle line:90% attention-like neural effects. 00:27:23.710 --> 00:27:25.470 align:middle line:84% The phenomenon of neglect results 00:27:25.470 --> 00:27:28.390 align:middle line:84% from lesions to parietal cortex presumably, 00:27:28.390 --> 00:27:32.550 align:middle line:84% which is the locus of some critical attentional mechanism. 00:27:32.550 --> 00:27:35.230 align:middle line:84% And so I'll emphasize that we're using this one word 00:27:35.230 --> 00:27:37.710 align:middle line:84% attention to talk about all this different stuff. 00:27:37.710 --> 00:27:40.750 align:middle line:84% But it's probably not just one thing, but rather 00:27:40.750 --> 00:27:45.470 align:middle line:84% a loose assortment of related phenomena. 00:27:45.470 --> 00:27:48.830 align:middle line:84% We mostly lack computational models of attention at present. 00:27:48.830 --> 00:27:51.330 align:middle line:84% I think this is a really important next frontier. 00:27:51.330 --> 00:27:53.710 align:middle line:84% And we're actually well-positioned as a field 00:27:53.710 --> 00:27:57.750 align:middle line:84% to really be able to make progress on that. 00:27:57.750 --> 00:28:01.750 align:middle line:84% And that's where we'll leave things. 00:28:01.750 --> 00:28:06.230 align:middle line:84% We got 1 and 1/2 classes left, and we've covered two 00:28:06.230 --> 00:28:08.750 align:middle line:90% of the five senses. 00:28:08.750 --> 00:28:12.750 align:middle line:84% So we spent about the first third of the class on audition. 00:28:12.750 --> 00:28:14.750 align:middle line:84% Since then, we've been talking about vision. 00:28:14.750 --> 00:28:16.730 align:middle line:84% So you may ask, well, why is that? 00:28:16.730 --> 00:28:19.750 align:middle line:90% That doesn't seem fair. 00:28:19.750 --> 00:28:21.330 align:middle line:84% But our coverage is, I would say, 00:28:21.330 --> 00:28:25.750 align:middle line:84% arguably proportional to the density of research 00:28:25.750 --> 00:28:26.890 align:middle line:90% on the different senses. 00:28:26.890 --> 00:28:31.030 align:middle line:84% So vision is by far the best-studied sense. 00:28:31.030 --> 00:28:33.710 align:middle line:84% I mean, audition is pretty well-studied. 00:28:33.710 --> 00:28:36.370 align:middle line:84% Touch, taste, and smell are much less well studied. 00:28:36.370 --> 00:28:40.830 align:middle line:84% And I mean, it's mostly because they're harder, I would say. 00:28:40.830 --> 00:28:43.050 align:middle line:84% The stimulus is like a lot harder to manipulate. 00:28:43.050 --> 00:28:46.427 align:middle line:84% So if you want to study vision, you just make a picture, 00:28:46.427 --> 00:28:47.510 align:middle line:90% and you show it to people. 00:28:47.510 --> 00:28:49.765 align:middle line:84% And we have computer screens and stuff 00:28:49.765 --> 00:28:50.890 align:middle line:90% that make that really easy. 00:28:50.890 --> 00:28:54.790 align:middle line:84% And if you want to study sound, give people headphones, 00:28:54.790 --> 00:28:57.410 align:middle line:84% and you can make a sound waveform and play it to them. 00:28:57.410 --> 00:28:58.790 align:middle line:90% You all have done that. 00:28:58.790 --> 00:29:00.630 align:middle line:84% If you want to study touch, you have 00:29:00.630 --> 00:29:03.810 align:middle line:90% to generate tactile stimulation. 00:29:03.810 --> 00:29:08.230 align:middle line:84% And that's hard to do with a cheap device that 00:29:08.230 --> 00:29:12.850 align:middle line:84% would be easily available-- same with taste and smell. 00:29:12.850 --> 00:29:15.030 align:middle line:84% You got to generate this chemical or something 00:29:15.030 --> 00:29:16.190 align:middle line:90% and give it to people. 00:29:16.190 --> 00:29:18.990 align:middle line:84% So everything is a little bit more complicated. 00:29:18.990 --> 00:29:20.590 align:middle line:84% But they're all really interesting 00:29:20.590 --> 00:29:22.150 align:middle line:90% and really important. 00:29:22.150 --> 00:29:26.150 align:middle line:84% And the sense of touch is critical to all kinds of things 00:29:26.150 --> 00:29:27.490 align:middle line:90% that we do on a daily basis. 00:29:27.490 --> 00:29:30.630 align:middle line:84% So this is a slide that shows a bunch of things 00:29:30.630 --> 00:29:33.790 align:middle line:84% that we do that utilizes our sense of touch. 00:29:33.790 --> 00:29:38.230 align:middle line:84% So if you are holding a pen to write, 00:29:38.230 --> 00:29:42.270 align:middle line:84% you have to grip the thing with the appropriate grip strength 00:29:42.270 --> 00:29:44.830 align:middle line:84% so that you hang on to it, that you can still-- 00:29:44.830 --> 00:29:47.950 align:middle line:84% and move it around in the way that you want to. 00:29:47.950 --> 00:29:51.718 align:middle line:84% And so there's feedback that you get from your sense of touch. 00:29:51.718 --> 00:29:53.510 align:middle line:84% It's kind of critical for holding the thing 00:29:53.510 --> 00:29:54.750 align:middle line:90% in the right way. 00:29:54.750 --> 00:29:57.510 align:middle line:84% So if you're playing instrument, like a guitar, 00:29:57.510 --> 00:29:59.230 align:middle line:84% in order to pluck those strings, you 00:29:59.230 --> 00:30:01.790 align:middle line:84% have to be able to feel like the position of the string 00:30:01.790 --> 00:30:03.090 align:middle line:90% with respect to your fingertip. 00:30:03.090 --> 00:30:06.310 align:middle line:90% The sense of touch is critical. 00:30:06.310 --> 00:30:08.190 align:middle line:90% You want to throw a baseball? 00:30:08.190 --> 00:30:10.650 align:middle line:84% Again, you got to be able to grip it exactly the right way, 00:30:10.650 --> 00:30:12.567 align:middle line:84% position your fingers in exactly the right way 00:30:12.567 --> 00:30:17.270 align:middle line:84% if you want to throw a curveball or a slider or whatever. 00:30:17.270 --> 00:30:19.590 align:middle line:90% You're holding a tweezers. 00:30:19.590 --> 00:30:21.790 align:middle line:84% Got to again, have to grip that in the right way. 00:30:21.790 --> 00:30:23.790 align:middle line:84% Manipulating a mouse-- getting the mouse kind of 00:30:23.790 --> 00:30:25.250 align:middle line:84% positioned in your hand correctly. 00:30:25.250 --> 00:30:27.147 align:middle line:84% That depends on a sense of touch. 00:30:27.147 --> 00:30:29.230 align:middle line:84% If you're typing on a keyboard, the sense of touch 00:30:29.230 --> 00:30:31.350 align:middle line:84% is what helps you get your fingers 00:30:31.350 --> 00:30:34.910 align:middle line:90% on the keys in the right way. 00:30:34.910 --> 00:30:38.430 align:middle line:84% If you'd like to play video games, these controllers, 00:30:38.430 --> 00:30:41.430 align:middle line:84% you have to hold and get your fingers on the button. 00:30:41.430 --> 00:30:43.390 align:middle line:84% Playing golf-- sense of touch helps 00:30:43.390 --> 00:30:47.150 align:middle line:84% you figure out how to hold the golf 00:30:47.150 --> 00:30:50.390 align:middle line:90% club in exactly the right way. 00:30:50.390 --> 00:30:52.090 align:middle line:84% Holding a phone and so on and so forth. 00:30:52.090 --> 00:30:54.270 align:middle line:84% So we do lots of things on a daily basis 00:30:54.270 --> 00:30:57.430 align:middle line:90% that uses our sense of touch. 00:30:57.430 --> 00:31:01.960 align:middle line:84% This has got some other examples of what kinds of information 00:31:01.960 --> 00:31:04.240 align:middle line:90% we get from touch. 00:31:04.240 --> 00:31:10.320 align:middle line:84% So take your fingers and move them over something. 00:31:10.320 --> 00:31:13.440 align:middle line:84% So I'm moving them over my shirt. 00:31:13.440 --> 00:31:17.200 align:middle line:84% You can get a sense of what the material is just 00:31:17.200 --> 00:31:19.760 align:middle line:90% by that lateral motion. 00:31:19.760 --> 00:31:22.360 align:middle line:84% So you get a lot of information about texture. 00:31:22.360 --> 00:31:25.518 align:middle line:84% We were talking about texture and in vision and hearing. 00:31:25.518 --> 00:31:27.060 align:middle line:84% It's also really important for touch. 00:31:27.060 --> 00:31:29.760 align:middle line:90% 00:31:29.760 --> 00:31:35.480 align:middle line:84% Take your finger and push it into something around you. 00:31:35.480 --> 00:31:38.320 align:middle line:84% So you get a sense of how hard something is just 00:31:38.320 --> 00:31:40.940 align:middle line:90% by kind of tapping it. 00:31:40.940 --> 00:31:45.040 align:middle line:84% So that's again giving you information about material. 00:31:45.040 --> 00:31:46.380 align:middle line:90% Take your finger. 00:31:46.380 --> 00:31:48.340 align:middle line:84% And again, put it on something around you, 00:31:48.340 --> 00:31:51.560 align:middle line:84% and you'll be able to get a sense of the temperature. 00:31:51.560 --> 00:31:55.360 align:middle line:84% So the metal thing on the chair might be a little bit cold. 00:31:55.360 --> 00:31:56.820 align:middle line:84% Your body is probably pretty warm. 00:31:56.820 --> 00:31:58.487 align:middle line:84% A cup of coffee is probably pretty warm. 00:31:58.487 --> 00:32:01.040 align:middle line:84% So again, there are sensors in your skin 00:32:01.040 --> 00:32:05.000 align:middle line:84% that give you information about temperature. 00:32:05.000 --> 00:32:09.320 align:middle line:84% Grab something and hold it in the palm of your hand. 00:32:09.320 --> 00:32:12.800 align:middle line:84% Just from holding it, you get a sense of how heavy it is. 00:32:12.800 --> 00:32:18.480 align:middle line:84% Again, that's a sense of touch in conjunction with information 00:32:18.480 --> 00:32:20.520 align:middle line:90% from your muscles. 00:32:20.520 --> 00:32:24.220 align:middle line:84% Just by grabbing something like this cup, 00:32:24.220 --> 00:32:28.967 align:middle line:84% you have a sense of how big it is, what the shape is. 00:32:28.967 --> 00:32:30.800 align:middle line:84% We also get a lot of information about shape 00:32:30.800 --> 00:32:34.100 align:middle line:84% by kind of running our fingers around stuff. 00:32:34.100 --> 00:32:36.660 align:middle line:90% 00:32:36.660 --> 00:32:38.320 align:middle line:84% So these are all different things 00:32:38.320 --> 00:32:42.440 align:middle line:84% that we do with our body to give us 00:32:42.440 --> 00:32:44.440 align:middle line:84% different kinds of tactile stimulation 00:32:44.440 --> 00:32:48.960 align:middle line:84% and derive different kinds of information about the world. 00:32:48.960 --> 00:32:53.640 align:middle line:84% So this is a graph that shows some surface depth maps 00:32:53.640 --> 00:32:55.560 align:middle line:90% for three different materials. 00:32:55.560 --> 00:32:57.760 align:middle line:90% So the y-axis here is depth. 00:32:57.760 --> 00:33:02.800 align:middle line:84% The x-axis is lateral position along the surface. 00:33:02.800 --> 00:33:06.597 align:middle line:84% Or well, and yeah, in this case, this is being swept along. 00:33:06.597 --> 00:33:09.180 align:middle line:84% So it's as though you're moving your finger across something-- 00:33:09.180 --> 00:33:11.080 align:middle line:90% so time and/or space. 00:33:11.080 --> 00:33:14.260 align:middle line:84% The point is that for a surface that's very, very smooth-- 00:33:14.260 --> 00:33:17.500 align:middle line:84% I mean, there are variations in the surface depth, 00:33:17.500 --> 00:33:19.340 align:middle line:90% but they're kind of small. 00:33:19.340 --> 00:33:21.840 align:middle line:84% So glass and silk, you have these pretty small indentations. 00:33:21.840 --> 00:33:24.080 align:middle line:84% Or something that's a lot rougher, like sandpaper-- 00:33:24.080 --> 00:33:26.120 align:middle line:84% indeed, if you look at it a fine scale, 00:33:26.120 --> 00:33:29.640 align:middle line:84% you can see these variations in the surface depth map. 00:33:29.640 --> 00:33:31.840 align:middle line:84% And that's something that you can sense if you 00:33:31.840 --> 00:33:33.520 align:middle line:90% move your finger over it. 00:33:33.520 --> 00:33:34.020 align:middle line:90% All right. 00:33:34.020 --> 00:33:36.320 align:middle line:90% So how does all this work? 00:33:36.320 --> 00:33:38.560 align:middle line:84% So big picture here is like you've got 00:33:38.560 --> 00:33:40.920 align:middle line:90% sensors that are in your skin. 00:33:40.920 --> 00:33:44.780 align:middle line:90% Those sensors send signals. 00:33:44.780 --> 00:33:49.360 align:middle line:84% They travel up very long nerve fibers to the spinal cord. 00:33:49.360 --> 00:33:53.680 align:middle line:84% The spinal cord relays that information to the thalamus. 00:33:53.680 --> 00:33:59.360 align:middle line:84% The thalamus projects to primary somatosensory cortex 00:33:59.360 --> 00:34:01.680 align:middle line:84% or secondary somatosensory cortex, 00:34:01.680 --> 00:34:04.720 align:middle line:84% and that is involved in the analysis of that touch 00:34:04.720 --> 00:34:07.040 align:middle line:90% information. 00:34:07.040 --> 00:34:08.797 align:middle line:84% So a lot of what we know about touch, 00:34:08.797 --> 00:34:11.380 align:middle line:84% and a lot of what I'm going to talk about today-- and in fact, 00:34:11.380 --> 00:34:14.620 align:middle line:84% this is true for all three of the remaining senses. 00:34:14.620 --> 00:34:17.239 align:middle line:84% A lot of the action is at the level of receptors. 00:34:17.239 --> 00:34:22.719 align:middle line:84% So much less is known about what's happening cortically 00:34:22.719 --> 00:34:25.179 align:middle line:84% to analyze the information that comes from the receptors. 00:34:25.179 --> 00:34:27.360 align:middle line:84% So a lot of what we'll talk about is the receptors 00:34:27.360 --> 00:34:29.420 align:middle line:84% and what kinds of information they capture, 00:34:29.420 --> 00:34:30.620 align:middle line:90% but not exclusively. 00:34:30.620 --> 00:34:36.800 align:middle line:84% So in the somatosensory system, like at least within the skin, 00:34:36.800 --> 00:34:43.400 align:middle line:84% skin simulation is measured by four main types of receptors. 00:34:43.400 --> 00:34:47.280 align:middle line:84% So they each have different names. 00:34:47.280 --> 00:34:50.920 align:middle line:84% You don't have to memorize the names 00:34:50.920 --> 00:34:54.090 align:middle line:84% but should be familiar with the conceptual distinctions 00:34:54.090 --> 00:34:55.730 align:middle line:90% between the different receptors. 00:34:55.730 --> 00:34:57.230 align:middle line:84% So we've got the Meissner corpuscle, 00:34:57.230 --> 00:35:00.570 align:middle line:84% the Pacinian corpuscle, the Merkel disk, and the Ruffini 00:35:00.570 --> 00:35:01.070 align:middle line:90% ending. 00:35:01.070 --> 00:35:02.510 align:middle line:90% So is a picture of the skin. 00:35:02.510 --> 00:35:04.930 align:middle line:84% So skin's got a few different layers to it-- 00:35:04.930 --> 00:35:06.770 align:middle line:90% the epidermis and the dermis. 00:35:06.770 --> 00:35:08.450 align:middle line:84% So the touch receptors are kind of 00:35:08.450 --> 00:35:10.350 align:middle line:90% beneath the outer layer of skin. 00:35:10.350 --> 00:35:13.630 align:middle line:84% And then they're situated at different depth within the skin. 00:35:13.630 --> 00:35:18.090 align:middle line:84% And that will impart-- give them kind of different properties. 00:35:18.090 --> 00:35:21.810 align:middle line:84% And then each of these has axons that then travel up 00:35:21.810 --> 00:35:23.850 align:middle line:90% to the spinal cord. 00:35:23.850 --> 00:35:29.250 align:middle line:84% So there's different kinds of mechanical stimulation 00:35:29.250 --> 00:35:32.010 align:middle line:84% that can result that these things will sense. 00:35:32.010 --> 00:35:33.875 align:middle line:84% And the color-coding here-- and then 00:35:33.875 --> 00:35:35.250 align:middle line:84% the color-coding of the receptors 00:35:35.250 --> 00:35:37.792 align:middle line:84% is supposed to indicate that the different types of receptors 00:35:37.792 --> 00:35:41.190 align:middle line:84% are differentially sensitive to different types of stimulation. 00:35:41.190 --> 00:35:43.230 align:middle line:90% So you can have heavy pressure. 00:35:43.230 --> 00:35:44.350 align:middle line:90% You can have vibration. 00:35:44.350 --> 00:35:45.670 align:middle line:90% You can have light touch. 00:35:45.670 --> 00:35:47.947 align:middle line:84% You can have stretching of the skin. 00:35:47.947 --> 00:35:49.530 align:middle line:84% And these different types of receptors 00:35:49.530 --> 00:35:54.730 align:middle line:84% are maximally sensitive to each of those. 00:35:54.730 --> 00:35:57.710 align:middle line:84% Here's another picture that more or less shows the same thing. 00:35:57.710 --> 00:36:00.210 align:middle line:84% So this is like a little chunk-- a zoom-in 00:36:00.210 --> 00:36:03.905 align:middle line:84% on a little chunk of skin and say, the fingertip, 00:36:03.905 --> 00:36:05.530 align:middle line:84% and you've got these different receptor 00:36:05.530 --> 00:36:08.170 align:middle line:84% types that are situated at different depths 00:36:08.170 --> 00:36:09.930 align:middle line:90% within the skin. 00:36:09.930 --> 00:36:14.750 align:middle line:84% So you will remember how at various points in the class, 00:36:14.750 --> 00:36:17.250 align:middle line:84% we dealt with some kind of annoying nomenclature issues 00:36:17.250 --> 00:36:19.470 align:middle line:84% where you have things that are given 00:36:19.470 --> 00:36:20.970 align:middle line:84% different names by different people, 00:36:20.970 --> 00:36:23.990 align:middle line:84% and they're often not used very consistently. 00:36:23.990 --> 00:36:26.750 align:middle line:84% And so it's the same situation here. 00:36:26.750 --> 00:36:29.250 align:middle line:84% The nomenclature that has been used to refer to these things 00:36:29.250 --> 00:36:31.930 align:middle line:90% kind of has evolved over time. 00:36:31.930 --> 00:36:33.430 align:middle line:84% And with most of these receptors, 00:36:33.430 --> 00:36:35.770 align:middle line:84% there's a few different ways that they're referred to. 00:36:35.770 --> 00:36:38.450 align:middle line:84% And so the Meissner corpuscle is often 00:36:38.450 --> 00:36:43.550 align:middle line:84% referred to as the RA receptors or RA fibers. 00:36:43.550 --> 00:36:46.530 align:middle line:84% That stands for rapidly adapting. 00:36:46.530 --> 00:36:49.130 align:middle line:84% Pacinian corpuscles are usually just called PCs, 00:36:49.130 --> 00:36:53.490 align:middle line:84% and then the Merkel disks are usually called the SA1 receptors 00:36:53.490 --> 00:36:56.170 align:middle line:90% because they slowly adapt. 00:36:56.170 --> 00:37:01.490 align:middle line:84% Sometimes they're referred to in functional terms, other times 00:37:01.490 --> 00:37:04.430 align:middle line:84% with the name of somebody who discovered them. 00:37:04.430 --> 00:37:08.450 align:middle line:90% 00:37:08.450 --> 00:37:13.130 align:middle line:84% So tactile receptors are called mechanoreceptors 00:37:13.130 --> 00:37:15.730 align:middle line:84% because they respond to mechanical stimulation-- so 00:37:15.730 --> 00:37:18.890 align:middle line:84% pressure, vibration, or movement. 00:37:18.890 --> 00:37:23.730 align:middle line:84% And the four main types of mechanoreceptors, they 00:37:23.730 --> 00:37:25.427 align:middle line:84% kind of vary on two main dimensions. 00:37:25.427 --> 00:37:27.010 align:middle line:84% So that's the kind of conceptual thing 00:37:27.010 --> 00:37:28.810 align:middle line:90% that everybody should know. 00:37:28.810 --> 00:37:31.090 align:middle line:84% They vary in terms of how quickly they adapt 00:37:31.090 --> 00:37:34.010 align:middle line:84% to stimulation, and they also vary in the size 00:37:34.010 --> 00:37:35.410 align:middle line:90% of the receptive field. 00:37:35.410 --> 00:37:38.130 align:middle line:84% So you end up with a 2 by 2 grid, which in fact, we'll 00:37:38.130 --> 00:37:39.610 align:middle line:90% see on the next slide. 00:37:39.610 --> 00:37:41.970 align:middle line:84% So the Meissner corpuscles exhibit fast adaptation 00:37:41.970 --> 00:37:44.530 align:middle line:90% and have small receptive fields. 00:37:44.530 --> 00:37:47.030 align:middle line:84% The Merkel complexes is a bit slow adaptation 00:37:47.030 --> 00:37:48.630 align:middle line:90% but with small receptive fields. 00:37:48.630 --> 00:37:51.290 align:middle line:84% And then the Pacinian corpuscles and Ruffini endings 00:37:51.290 --> 00:37:53.550 align:middle line:84% have fast and slow adaptation, respectively, 00:37:53.550 --> 00:37:55.010 align:middle line:90% and large receptive fields. 00:37:55.010 --> 00:38:00.850 align:middle line:84% Now one complexity here is the Ruffini receptors supposedly 00:38:00.850 --> 00:38:04.890 align:middle line:84% don't exist in monkeys, and a lot of the research on touch, 00:38:04.890 --> 00:38:08.043 align:middle line:84% of the neurophysiology of touch, happens in monkeys. 00:38:08.043 --> 00:38:10.210 align:middle line:84% And so you're not going to see the Ruffini receptors 00:38:10.210 --> 00:38:11.930 align:middle line:90% on a lot of the slides. 00:38:11.930 --> 00:38:14.210 align:middle line:84% So with monkeys, you mostly study the three. 00:38:14.210 --> 00:38:14.710 align:middle line:90% All right. 00:38:14.710 --> 00:38:17.330 align:middle line:84% So each of these receptors has a different range 00:38:17.330 --> 00:38:20.970 align:middle line:84% of responsiveness and functionality. 00:38:20.970 --> 00:38:23.950 align:middle line:84% And then, to further complicate things-- 00:38:23.950 --> 00:38:27.610 align:middle line:84% so sometimes they use the word fast to refer to adaptation, 00:38:27.610 --> 00:38:28.930 align:middle line:90% sometimes use rapid. 00:38:28.930 --> 00:38:30.330 align:middle line:90% So you'll have RA and FA. 00:38:30.330 --> 00:38:31.590 align:middle line:90% Those mean the same thing. 00:38:31.590 --> 00:38:36.790 align:middle line:84% But the main point here is that we've got a 2 by 2 grid. 00:38:36.790 --> 00:38:38.650 align:middle line:84% So we have different rates of adaptation 00:38:38.650 --> 00:38:42.650 align:middle line:84% and different sizes of receptive fields. 00:38:42.650 --> 00:38:43.150 align:middle line:90% All right. 00:38:43.150 --> 00:38:45.440 align:middle line:90% So what do we mean by this? 00:38:45.440 --> 00:38:48.100 align:middle line:84% Well, the receptive field is just what it sounds like. 00:38:48.100 --> 00:38:51.260 align:middle line:84% So this is like the area of the skin that would 00:38:51.260 --> 00:38:53.900 align:middle line:90% evoke a response on a receptor. 00:38:53.900 --> 00:38:57.440 align:middle line:84% And some of the receptive fields are small, and some are larger. 00:38:57.440 --> 00:39:00.820 align:middle line:84% And that's mostly a function of how deeply the receptor is 00:39:00.820 --> 00:39:01.960 align:middle line:90% positioned in the skin. 00:39:01.960 --> 00:39:04.660 align:middle line:84% So the ones that are more deeply positioned in the skin 00:39:04.660 --> 00:39:07.313 align:middle line:84% will be sensitive to stimulation over a wider area. 00:39:07.313 --> 00:39:09.480 align:middle line:84% If they're kind of close to the surface of the skin, 00:39:09.480 --> 00:39:11.940 align:middle line:84% the receptive field will typically be kind of small. 00:39:11.940 --> 00:39:17.780 align:middle line:84% So this picture is showing some example receptive fields 00:39:17.780 --> 00:39:21.200 align:middle line:84% for the four main types of receptors. 00:39:21.200 --> 00:39:22.740 align:middle line:84% So we've got the Merkel receptors, 00:39:22.740 --> 00:39:26.260 align:middle line:90% which are also known as SA1. 00:39:26.260 --> 00:39:30.500 align:middle line:84% The Meissner corpuscles, which are known as RA. 00:39:30.500 --> 00:39:34.600 align:middle line:84% And the point is that those receptive fields are small. 00:39:34.600 --> 00:39:36.100 align:middle line:84% And then we have the Ruffini endings 00:39:36.100 --> 00:39:38.960 align:middle line:84% and the Pacinian corpuscles, or the PC receptors, 00:39:38.960 --> 00:39:41.620 align:middle line:84% and those are large receptive fields. 00:39:41.620 --> 00:39:47.420 align:middle line:84% And this is a plot that shows the density of these receptors 00:39:47.420 --> 00:39:48.320 align:middle line:90% across the hand. 00:39:48.320 --> 00:39:51.260 align:middle line:84% And we're going to return to this in a moment 00:39:51.260 --> 00:39:54.320 align:middle line:84% because the density varies quite enormously over your body. 00:39:54.320 --> 00:39:56.082 align:middle line:90% So there's some areas of skin. 00:39:56.082 --> 00:39:58.040 align:middle line:84% And so it's a bit like the fovea in the retina. 00:39:58.040 --> 00:40:00.460 align:middle line:84% So there's the fovea is this particular part 00:40:00.460 --> 00:40:03.680 align:middle line:84% of the retina, which has got a ton of receptors. 00:40:03.680 --> 00:40:06.740 align:middle line:84% So you get really high-resolution sensing there. 00:40:06.740 --> 00:40:10.263 align:middle line:84% The fingertips are sort of like the fovea for touch. 00:40:10.263 --> 00:40:12.180 align:middle line:84% It's got tons of receptors in your fingertips. 00:40:12.180 --> 00:40:14.420 align:middle line:84% But there are other areas of the body that are also 00:40:14.420 --> 00:40:16.483 align:middle line:90% pretty densely innervated. 00:40:16.483 --> 00:40:18.400 align:middle line:84% And the hands in general are pretty sensitive, 00:40:18.400 --> 00:40:21.500 align:middle line:84% but the fingertips are very sensitive. 00:40:21.500 --> 00:40:24.880 align:middle line:84% And so in particular, these two receptor types, 00:40:24.880 --> 00:40:27.060 align:middle line:84% the ones that have small receptive fields, 00:40:27.060 --> 00:40:29.258 align:middle line:84% are very dense in the fingertips. 00:40:29.258 --> 00:40:31.300 align:middle line:84% So they're doing kind of high-resolution analysis 00:40:31.300 --> 00:40:32.860 align:middle line:90% of touch. 00:40:32.860 --> 00:40:34.780 align:middle line:84% Whereas the Ruffini and the Pacinian 00:40:34.780 --> 00:40:37.605 align:middle line:84% are not really as densely concentrated in the fingertips 00:40:37.605 --> 00:40:39.480 align:middle line:84% because their receptor fields are-- receptive 00:40:39.480 --> 00:40:41.063 align:middle line:84% fields are bigger, and I guess there's 00:40:41.063 --> 00:40:44.180 align:middle line:84% less point to having them be very dense. 00:40:44.180 --> 00:40:44.680 align:middle line:90% All right. 00:40:44.680 --> 00:40:46.180 align:middle line:84% So the adaptation that we were talking 00:40:46.180 --> 00:40:48.430 align:middle line:84% about that also differentiates these receptors, that's 00:40:48.430 --> 00:40:54.620 align:middle line:84% shown in the top right, panel C. So there's a stimulus. 00:40:54.620 --> 00:40:57.477 align:middle line:84% That red line indicates pressure that's 00:40:57.477 --> 00:40:58.560 align:middle line:90% being exerted on the skin. 00:40:58.560 --> 00:41:03.300 align:middle line:84% So you have a little rod, and it gives you a poke. 00:41:03.300 --> 00:41:04.880 align:middle line:90% So it presses into the skin. 00:41:04.880 --> 00:41:06.300 align:middle line:84% That's when the red thing goes up. 00:41:06.300 --> 00:41:08.820 align:middle line:90% 00:41:08.820 --> 00:41:12.140 align:middle line:84% The two graphs below that are showing the response 00:41:12.140 --> 00:41:16.120 align:middle line:84% of a slowly adapting receptor and a rapidly adapting receptor. 00:41:16.120 --> 00:41:19.260 align:middle line:84% And the vertical lines there indicate spikes. 00:41:19.260 --> 00:41:22.060 align:middle line:84% And so the point is that if you have this fixed pressure 00:41:22.060 --> 00:41:26.460 align:middle line:84% stimulus, the slowly adapting receptor responds a lot, 00:41:26.460 --> 00:41:28.080 align:middle line:90% and the response decreases. 00:41:28.080 --> 00:41:29.840 align:middle line:84% But it kind of continues constantly. 00:41:29.840 --> 00:41:31.780 align:middle line:84% Whereas the rapidly adapting ones, 00:41:31.780 --> 00:41:34.220 align:middle line:84% the response kind of goes away very, very quickly. 00:41:34.220 --> 00:41:37.680 align:middle line:84% So mostly our signaling changes in pressure. 00:41:37.680 --> 00:41:44.780 align:middle line:90% 00:41:44.780 --> 00:41:45.280 align:middle line:90% All right. 00:41:45.280 --> 00:41:47.420 align:middle line:84% So the different receptors are maximally 00:41:47.420 --> 00:41:51.380 align:middle line:84% sensitive to different features of touch stimulation. 00:41:51.380 --> 00:41:56.340 align:middle line:84% And so this is a table that is showing the type of stimulation 00:41:56.340 --> 00:42:00.220 align:middle line:84% that the four different types of mechanoreceptors 00:42:00.220 --> 00:42:04.420 align:middle line:84% are maximally sensitive to-- so sustained pressure, very 00:42:04.420 --> 00:42:07.580 align:middle line:84% low frequency, sustained downward pressure, 00:42:07.580 --> 00:42:09.650 align:middle line:84% temporal changes in skin deformation. 00:42:09.650 --> 00:42:11.900 align:middle line:84% And so essentially, the ones that are rapidly adapting 00:42:11.900 --> 00:42:13.700 align:middle line:84% are very sensitive to temperature changes 00:42:13.700 --> 00:42:15.480 align:middle line:84% but in different frequency ranges. 00:42:15.480 --> 00:42:23.580 align:middle line:90% 00:42:23.580 --> 00:42:25.820 align:middle line:84% So the receptor sensitivities constrain 00:42:25.820 --> 00:42:27.620 align:middle line:90% perceptual sensitivity. 00:42:27.620 --> 00:42:30.700 align:middle line:84% So this is a graph that I like to show because it's 00:42:30.700 --> 00:42:32.700 align:middle line:84% got some interesting analogies to stuff that we 00:42:32.700 --> 00:42:35.620 align:middle line:90% have seen elsewhere. 00:42:35.620 --> 00:42:42.700 align:middle line:84% So this is kind of analogous to the contrast sensitivity 00:42:42.700 --> 00:42:43.460 align:middle line:90% function. 00:42:43.460 --> 00:42:46.700 align:middle line:84% So what's being plotted on the y-axis is threshold. 00:42:46.700 --> 00:42:47.840 align:middle line:90% So it's a little different. 00:42:47.840 --> 00:42:49.215 align:middle line:84% The contrast sensitivity function 00:42:49.215 --> 00:42:50.990 align:middle line:84% is like plotting the inverse of threshold. 00:42:50.990 --> 00:42:52.240 align:middle line:90% So this is just the threshold. 00:42:52.240 --> 00:42:53.677 align:middle line:90% So now, down is better. 00:42:53.677 --> 00:42:56.260 align:middle line:84% And it's applying the threshold as a function of the frequency 00:42:56.260 --> 00:42:57.420 align:middle line:90% of stimulation. 00:42:57.420 --> 00:42:59.900 align:middle line:84% So you've got a little rod that's 00:42:59.900 --> 00:43:01.320 align:middle line:90% making contact with the skin. 00:43:01.320 --> 00:43:04.760 align:middle line:84% And it's vibrating back and forth at some frequency. 00:43:04.760 --> 00:43:06.380 align:middle line:84% And then you can control the amplitude 00:43:06.380 --> 00:43:12.020 align:middle line:84% of the vibration and measure what that amplitude needs to be 00:43:12.020 --> 00:43:13.620 align:middle line:90% in order for you to detect it. 00:43:13.620 --> 00:43:19.220 align:middle line:84% And so the dots here are plotting human thresholds. 00:43:19.220 --> 00:43:22.020 align:middle line:84% And so what this is showing is that peak sensitivity 00:43:22.020 --> 00:43:24.805 align:middle line:84% is actually occurring for fairly high frequencies. 00:43:24.805 --> 00:43:26.180 align:middle line:84% And then it gets a bit worse when 00:43:26.180 --> 00:43:27.400 align:middle line:90% the frequencies get too high. 00:43:27.400 --> 00:43:29.720 align:middle line:84% And it's worse when the frequencies are low. 00:43:29.720 --> 00:43:33.140 align:middle line:90% 00:43:33.140 --> 00:43:36.470 align:middle line:84% Superimposed on this graph of human thresholds, which 00:43:36.470 --> 00:43:39.450 align:middle line:84% are the solid dots, are the dashed lines, 00:43:39.450 --> 00:43:42.190 align:middle line:84% which are the sensitivities of the individual types 00:43:42.190 --> 00:43:43.550 align:middle line:90% of receptors-- 00:43:43.550 --> 00:43:46.750 align:middle line:90% SA1, FA1, and FA2. 00:43:46.750 --> 00:43:48.950 align:middle line:84% And what you're supposed to take away from this 00:43:48.950 --> 00:43:52.670 align:middle line:84% is that at any given frequency, there 00:43:52.670 --> 00:43:54.510 align:middle line:84% is a receptor that's kind of maximally 00:43:54.510 --> 00:43:56.630 align:middle line:84% sensitive to that frequency, and that's 00:43:56.630 --> 00:43:59.910 align:middle line:84% what ends up dictating your perceptual sensitivity. 00:43:59.910 --> 00:44:05.990 align:middle line:84% So it's like the contrast sensitivity function 00:44:05.990 --> 00:44:09.710 align:middle line:84% being determined by a combination of spatial frequency 00:44:09.710 --> 00:44:11.870 align:middle line:90% channels. 00:44:11.870 --> 00:44:17.436 align:middle line:84% Is there anything else that this kind of is vaguely evocative of? 00:44:17.436 --> 00:44:21.470 align:middle line:84% AUDIENCE: The psychometric curve but like two of them 00:44:21.470 --> 00:44:22.370 align:middle line:90% are connected. 00:44:22.370 --> 00:44:25.030 align:middle line:90% 00:44:25.030 --> 00:44:27.330 align:middle line:84% JOSH MCDERMOTT: Which psychometric curve? 00:44:27.330 --> 00:44:29.623 align:middle line:84% AUDIENCE: The one that we always-- 00:44:29.623 --> 00:44:30.790 align:middle line:90% JOSH MCDERMOTT: The classic. 00:44:30.790 --> 00:44:32.082 align:middle line:90% AUDIENCE: Where you [INAUDIBLE] 00:44:32.082 --> 00:44:33.390 align:middle line:90% JOSH MCDERMOTT: Two sigmoids. 00:44:33.390 --> 00:44:34.830 align:middle line:90% Yeah, OK, a little bit, yeah. 00:44:34.830 --> 00:44:37.890 align:middle line:84% There's something else that this is kind of reminiscent of. 00:44:37.890 --> 00:44:38.920 align:middle line:90% Yeah. 00:44:38.920 --> 00:44:40.118 align:middle line:90% AUDIENCE: Rods and cones. 00:44:40.118 --> 00:44:41.410 align:middle line:90% JOSH MCDERMOTT: Exactly-- yeah. 00:44:41.410 --> 00:44:43.590 align:middle line:84% So it's a little bit like the dark adaptation curve. 00:44:43.590 --> 00:44:46.430 align:middle line:84% So remember, if you walk into a dark room 00:44:46.430 --> 00:44:48.390 align:middle line:84% and then you measure your sensitivity 00:44:48.390 --> 00:44:51.030 align:middle line:84% to light as a function of the amount of time you spent 00:44:51.030 --> 00:44:53.750 align:middle line:84% in the room, the thresholds kind of drop a little bit, 00:44:53.750 --> 00:44:55.010 align:middle line:90% and then they drop again. 00:44:55.010 --> 00:45:00.150 align:middle line:84% And so that curve is explained by the sensitivity 00:45:00.150 --> 00:45:01.613 align:middle line:90% of the cones and the rods. 00:45:01.613 --> 00:45:03.030 align:middle line:84% And so initially, your sensitivity 00:45:03.030 --> 00:45:04.490 align:middle line:90% is determined by the cones. 00:45:04.490 --> 00:45:06.365 align:middle line:84% And then when the rods become more sensitive, 00:45:06.365 --> 00:45:07.290 align:middle line:90% the rods take over. 00:45:07.290 --> 00:45:08.910 align:middle line:90% So it's a little bit like that. 00:45:08.910 --> 00:45:11.510 align:middle line:84% So the point is that these different receptor 00:45:11.510 --> 00:45:15.070 align:middle line:84% types are sensitive to different kinds of stimulation 00:45:15.070 --> 00:45:18.790 align:middle line:84% and collectively determine your perceptual sensitivity. 00:45:18.790 --> 00:45:21.830 align:middle line:84% So now is the time for an experiment. 00:45:21.830 --> 00:45:26.830 align:middle line:84% So I mentioned to you that there is 00:45:26.830 --> 00:45:29.890 align:middle line:84% variation in the density of receptors over the body. 00:45:29.890 --> 00:45:33.290 align:middle line:84% So we saw some examples of this in the fingertips. 00:45:33.290 --> 00:45:37.710 align:middle line:90% 00:45:37.710 --> 00:45:40.550 align:middle line:84% But there's variation across the entire body. 00:45:40.550 --> 00:45:45.590 align:middle line:84% And this causes very large variations in how-- 00:45:45.590 --> 00:45:49.030 align:middle line:84% in the acuity of your touch perception. 00:45:49.030 --> 00:45:52.670 align:middle line:84% And so this is standardly measured 00:45:52.670 --> 00:45:56.410 align:middle line:84% with a two-point sensitivity test. 00:45:56.410 --> 00:45:59.550 align:middle line:84% So the idea is that you stimulate the person 00:45:59.550 --> 00:46:02.870 align:middle line:84% with either kind of one poke or two pokes that 00:46:02.870 --> 00:46:05.070 align:middle line:90% can be some distance apart. 00:46:05.070 --> 00:46:09.750 align:middle line:84% And you're trying to measure the threshold, the threshold 00:46:09.750 --> 00:46:12.670 align:middle line:84% for the distance between the two points 00:46:12.670 --> 00:46:15.150 align:middle line:84% at which you can tell that you're being poked twice 00:46:15.150 --> 00:46:17.590 align:middle line:90% instead of being poked once. 00:46:17.590 --> 00:46:21.430 align:middle line:84% So clearly, eventually, if you move the things far enough 00:46:21.430 --> 00:46:23.830 align:middle line:84% apart, you'll be able to tell that there are two pokes. 00:46:23.830 --> 00:46:26.330 align:middle line:84% But then it also clearly, if they get really close together, 00:46:26.330 --> 00:46:28.390 align:middle line:84% it would be indistinguishable from one poke. 00:46:28.390 --> 00:46:33.430 align:middle line:84% And so this graph is plotting the threshold for distinguishing 00:46:33.430 --> 00:46:38.350 align:middle line:84% 1 and 2 pokes at all these different places on the body. 00:46:38.350 --> 00:46:43.110 align:middle line:84% And you can see that the fingers and the thumbs, the threshold 00:46:43.110 --> 00:46:44.410 align:middle line:90% is pretty good. 00:46:44.410 --> 00:46:45.890 align:middle line:90% So this is 5 millimeters. 00:46:45.890 --> 00:46:48.750 align:middle line:84% So that's saying that if things are 3 millimeters apart, 00:46:48.750 --> 00:46:53.470 align:middle line:84% you can tell whether you got two pokes or one. 00:46:53.470 --> 00:46:57.790 align:middle line:84% By contrast, the arms, lower arm and upper arm, 00:46:57.790 --> 00:47:00.990 align:middle line:84% that's like 40 millimeters, so 4 centimeters apart. 00:47:00.990 --> 00:47:03.790 align:middle line:90% 00:47:03.790 --> 00:47:05.930 align:middle line:84% If things are 3 centimeters apart, in general, 00:47:05.930 --> 00:47:07.472 align:middle line:84% you won't be able to tell whether you 00:47:07.472 --> 00:47:08.910 align:middle line:90% got one or two pokes. 00:47:08.910 --> 00:47:10.790 align:middle line:90% Seems kind of crazy. 00:47:10.790 --> 00:47:16.930 align:middle line:84% And the back and the thigh and the calf are also pretty bad. 00:47:16.930 --> 00:47:19.750 align:middle line:84% So the other place where sensitivity is really good 00:47:19.750 --> 00:47:22.050 align:middle line:84% is the face-- so in particular, the lips. 00:47:22.050 --> 00:47:26.190 align:middle line:84% So the lips have to have very good touch acuity, 00:47:26.190 --> 00:47:28.800 align:middle line:84% presumably because in order to eat and make sure the food goes 00:47:28.800 --> 00:47:30.175 align:middle line:84% in your mouth and stuff, you have 00:47:30.175 --> 00:47:34.305 align:middle line:84% to know where food is relative to stuff. 00:47:34.305 --> 00:47:35.680 align:middle line:84% And I guess the rest of your face 00:47:35.680 --> 00:47:37.480 align:middle line:84% is very sensitive, just because there's 00:47:37.480 --> 00:47:39.060 align:middle line:84% a lot of important stuff on the face, 00:47:39.060 --> 00:47:41.420 align:middle line:84% and you want to know if something's on you, I guess. 00:47:41.420 --> 00:47:43.900 align:middle line:84% So all right, let's do a demonstration. 00:47:43.900 --> 00:47:46.440 align:middle line:84% So would anyone like to volunteer 00:47:46.440 --> 00:47:48.380 align:middle line:90% to be tested for touch acuity? 00:47:48.380 --> 00:47:53.000 align:middle line:90% 00:47:53.000 --> 00:47:54.400 align:middle line:90% It'll be a lot of fun. 00:47:54.400 --> 00:47:55.620 align:middle line:90% Do you want to volunteer? 00:47:55.620 --> 00:47:56.640 align:middle line:90% Yeah, come on. 00:47:56.640 --> 00:47:59.040 align:middle line:84% Oh, the only thing is you're going 00:47:59.040 --> 00:48:01.068 align:middle line:90% to have to have a bare arm. 00:48:01.068 --> 00:48:01.860 align:middle line:90% Yeah, that'll work. 00:48:01.860 --> 00:48:03.040 align:middle line:90% Yeah, that'll work, yeah. 00:48:03.040 --> 00:48:04.840 align:middle line:90% Come on up here. 00:48:04.840 --> 00:48:05.980 align:middle line:90% Thanks for volunteering. 00:48:05.980 --> 00:48:10.140 align:middle line:90% This will be painless. 00:48:10.140 --> 00:48:14.000 align:middle line:90% 00:48:14.000 --> 00:48:17.160 align:middle line:84% OK, yeah, I don't want to draw on her. 00:48:17.160 --> 00:48:21.380 align:middle line:84% So just make sure this doesn't hurt. 00:48:21.380 --> 00:48:23.040 align:middle line:90% Is that OK? 00:48:23.040 --> 00:48:23.540 align:middle line:90% OK, good. 00:48:23.540 --> 00:48:25.440 align:middle line:84% All right, so we have two pencils here-- 00:48:25.440 --> 00:48:26.420 align:middle line:90% mechanical pencils. 00:48:26.420 --> 00:48:27.780 align:middle line:90% So the tips are pretty thin. 00:48:27.780 --> 00:48:32.580 align:middle line:84% So we're going to measure two-point discrimination. 00:48:32.580 --> 00:48:36.140 align:middle line:90% So turn your hand upside-down. 00:48:36.140 --> 00:48:38.360 align:middle line:84% And move it back just a little bit. 00:48:38.360 --> 00:48:39.640 align:middle line:90% There we go. 00:48:39.640 --> 00:48:41.600 align:middle line:90% So close your eyes. 00:48:41.600 --> 00:48:44.680 align:middle line:84% And we're going to do this first on the fingertip. 00:48:44.680 --> 00:48:47.640 align:middle line:84% So you're going to tell me if there's one poke or two poke. 00:48:47.640 --> 00:48:51.400 align:middle line:90% 00:48:51.400 --> 00:48:52.240 align:middle line:90% STUDENT: One 00:48:52.240 --> 00:48:55.578 align:middle line:90% JOSH MCDERMOTT: Yep, very good. 00:48:55.578 --> 00:48:56.120 align:middle line:90% STUDENT: Two. 00:48:56.120 --> 00:48:58.280 align:middle line:90% JOSH MCDERMOTT: Very good. 00:48:58.280 --> 00:49:01.320 align:middle line:90% STUDENT: One. 00:49:01.320 --> 00:49:14.920 align:middle line:84% I can't really tell-- maybe 2, 2, 1, 2, 2. 00:49:14.920 --> 00:49:16.920 align:middle line:84% JOSH MCDERMOTT: So she's able to tell them apart 00:49:16.920 --> 00:49:19.800 align:middle line:84% when they're about this far apart, a few millimeters-- so 00:49:19.800 --> 00:49:22.500 align:middle line:84% pretty consistent with the graph up there. 00:49:22.500 --> 00:49:25.882 align:middle line:84% So now we're going to repeat the experiment on your forearm. 00:49:25.882 --> 00:49:26.840 align:middle line:90% Got to close your eyes. 00:49:26.840 --> 00:49:32.000 align:middle line:90% 00:49:32.000 --> 00:49:33.860 align:middle line:90% STUDENT: Oh, I don't know. 00:49:33.860 --> 00:49:36.180 align:middle line:90% One or two, I can't really tell. 00:49:36.180 --> 00:49:38.000 align:middle line:90% JOSH MCDERMOTT: OK, that's fine. 00:49:38.000 --> 00:49:38.568 align:middle line:90% STUDENT: Two. 00:49:38.568 --> 00:49:39.360 align:middle line:90% JOSH MCDERMOTT: OK. 00:49:39.360 --> 00:50:01.400 align:middle line:84% STUDENT: 2, 2, 2, 1, 1, 1, 2, 1, 2, 1. 00:50:01.400 --> 00:50:05.418 align:middle line:84% JOSH MCDERMOTT: So the threshold is about that. 00:50:05.418 --> 00:50:06.460 align:middle line:90% STUDENT: Oh, interesting. 00:50:06.460 --> 00:50:08.540 align:middle line:84% JOSH MCDERMOTT: Yeah, maybe two or two or three centimeters. 00:50:08.540 --> 00:50:09.040 align:middle line:90% All right. 00:50:09.040 --> 00:50:10.990 align:middle line:90% 00:50:10.990 --> 00:50:13.240 align:middle line:84% Yeah, you're a little bit better than the participants 00:50:13.240 --> 00:50:14.100 align:middle line:90% in the textbook. 00:50:14.100 --> 00:50:15.900 align:middle line:90% So yeah, but you get the point. 00:50:15.900 --> 00:50:18.000 align:middle line:84% So there are these huge differences 00:50:18.000 --> 00:50:19.860 align:middle line:90% in perceptual sensitivity. 00:50:19.860 --> 00:50:22.300 align:middle line:84% And it's a function of the touch receptors. 00:50:22.300 --> 00:50:25.840 align:middle line:84% Thanks very much for volunteering. 00:50:25.840 --> 00:50:26.900 align:middle line:90% Any questions about that? 00:50:26.900 --> 00:50:28.100 align:middle line:90% Yeah, round of applause. 00:50:28.100 --> 00:50:30.080 align:middle line:90% All right. 00:50:30.080 --> 00:50:31.760 align:middle line:90% Any questions about that? 00:50:31.760 --> 00:50:32.560 align:middle line:90% Yeah. 00:50:32.560 --> 00:50:37.440 align:middle line:84% AUDIENCE: Is this related to the amount of muscular control? 00:50:37.440 --> 00:50:40.960 align:middle line:84% Do you think fingers have a lot of fine muscles, 00:50:40.960 --> 00:50:43.100 align:middle line:84% and the face has a lot of fine muscles? 00:50:43.100 --> 00:50:47.100 align:middle line:84% But then, like the legs, I guess they have fine muscles, 00:50:47.100 --> 00:50:52.667 align:middle line:84% but you don't do as many dexterous things with them. 00:50:52.667 --> 00:50:55.000 align:middle line:84% JOSH MCDERMOTT: I mean, they're not related in the sense 00:50:55.000 --> 00:50:58.160 align:middle line:84% that what's mediating your sensitivity 00:50:58.160 --> 00:50:59.903 align:middle line:84% are mechanoreceptors in the skin. 00:50:59.903 --> 00:51:01.820 align:middle line:84% I mean, you do have receptors in your muscles, 00:51:01.820 --> 00:51:03.612 align:middle line:84% as we'll talk about in a second, but that's 00:51:03.612 --> 00:51:07.400 align:middle line:84% not what's determining your discrimination 00:51:07.400 --> 00:51:08.800 align:middle line:90% in this particular case. 00:51:08.800 --> 00:51:11.848 align:middle line:84% So they're not proximally causally related in that sense. 00:51:11.848 --> 00:51:13.640 align:middle line:84% But they might be related just in the sense 00:51:13.640 --> 00:51:16.960 align:middle line:84% that the places where you need to have a lot of fine motor 00:51:16.960 --> 00:51:19.040 align:middle line:84% control are probably also places where 00:51:19.040 --> 00:51:21.910 align:middle line:84% you want a lot of information about what you're touching. 00:51:21.910 --> 00:51:26.450 align:middle line:84% So those things probably go hand in hand. 00:51:26.450 --> 00:51:29.792 align:middle line:84% And the places that are like the phobias for touch 00:51:29.792 --> 00:51:32.250 align:middle line:84% are also places where you want to have a lot of musculature 00:51:32.250 --> 00:51:33.370 align:middle line:84% because you want to be able to move them 00:51:33.370 --> 00:51:35.870 align:middle line:84% around to be able to touch things and so forth. 00:51:35.870 --> 00:51:37.370 align:middle line:90% Yeah. 00:51:37.370 --> 00:51:38.590 align:middle line:90% Yeah, any other questions? 00:51:38.590 --> 00:51:41.150 align:middle line:90% 00:51:41.150 --> 00:51:41.650 align:middle line:90% OK. 00:51:41.650 --> 00:51:45.530 align:middle line:90% 00:51:45.530 --> 00:51:52.130 align:middle line:84% So your skin is covered with these receptors. 00:51:52.130 --> 00:51:56.210 align:middle line:84% Actually, some of them have pretty small receptive fields. 00:51:56.210 --> 00:51:59.890 align:middle line:84% And the set of all of the receptors on your skin 00:51:59.890 --> 00:52:02.570 align:middle line:84% is, in a sense, going to give you an image. 00:52:02.570 --> 00:52:06.650 align:middle line:84% And so there's been a lot of experiments showing 00:52:06.650 --> 00:52:10.250 align:middle line:84% that the receptive field-- the receptors accurately transmit 00:52:10.250 --> 00:52:12.330 align:middle line:84% spatial structure to some extent. 00:52:12.330 --> 00:52:16.610 align:middle line:84% And the way that these experiments typically 00:52:16.610 --> 00:52:19.610 align:middle line:84% work-- so you might imagine that what you'd actually want to do 00:52:19.610 --> 00:52:21.290 align:middle line:84% is be able to simultaneously record 00:52:21.290 --> 00:52:23.470 align:middle line:84% from all of the receptors in the skin, 00:52:23.470 --> 00:52:25.290 align:middle line:84% and that's not technically feasible. 00:52:25.290 --> 00:52:27.370 align:middle line:84% So typically, the way these experiments will work 00:52:27.370 --> 00:52:32.370 align:middle line:84% is there's an electrode that will be in the arm of the animal 00:52:32.370 --> 00:52:33.750 align:middle line:90% subject. 00:52:33.750 --> 00:52:38.050 align:middle line:84% And you isolate the nerve that contains all of the nerve fibers 00:52:38.050 --> 00:52:40.420 align:middle line:84% that are carrying signals up to the spinal cord. 00:52:40.420 --> 00:52:41.670 align:middle line:90% And you hook into one of them. 00:52:41.670 --> 00:52:44.450 align:middle line:84% So you're typically recording from one receptor at a time. 00:52:44.450 --> 00:52:49.290 align:middle line:84% But what you can do is you can measure the response of that one 00:52:49.290 --> 00:52:56.890 align:middle line:84% receptor as it is swept across, like a tactile image, if you 00:52:56.890 --> 00:52:58.170 align:middle line:90% will. 00:52:58.170 --> 00:53:03.130 align:middle line:84% This is a classic experimental paradigm for doing just that. 00:53:03.130 --> 00:53:06.690 align:middle line:84% So the way that this works, this is the monkey's hand. 00:53:06.690 --> 00:53:09.610 align:middle line:84% And this is a cylinder that is embossed. 00:53:09.610 --> 00:53:11.570 align:middle line:84% In this case, it's embossed with letters. 00:53:11.570 --> 00:53:12.410 align:middle line:90% All right. 00:53:12.410 --> 00:53:15.010 align:middle line:84% And so the cylinder rotates around, 00:53:15.010 --> 00:53:18.130 align:middle line:84% sweeping over the monkey's finger. 00:53:18.130 --> 00:53:23.450 align:middle line:84% And then you move the cylinder back and forth such 00:53:23.450 --> 00:53:26.190 align:middle line:84% that the finger stays in one place, 00:53:26.190 --> 00:53:29.370 align:middle line:84% and with different sweeps of-- rotations of the cylinder, 00:53:29.370 --> 00:53:35.050 align:middle line:84% the finger comes in contact with different points on the image. 00:53:35.050 --> 00:53:37.250 align:middle line:84% And each of those kind of gets swept around. 00:53:37.250 --> 00:53:39.770 align:middle line:84% And so the consequence is that you can effectively 00:53:39.770 --> 00:53:43.170 align:middle line:84% measure the response of the receptor like at every point 00:53:43.170 --> 00:53:44.330 align:middle line:90% in this image. 00:53:44.330 --> 00:53:47.730 align:middle line:84% And the inference is that would capture 00:53:47.730 --> 00:53:49.570 align:middle line:84% what the full set of receptors would 00:53:49.570 --> 00:53:55.910 align:middle line:84% be capturing when the thing gets swept over the fingertips once. 00:53:55.910 --> 00:53:57.730 align:middle line:90% Everybody get that? 00:53:57.730 --> 00:53:59.990 align:middle line:84% So what happens here when you do this? 00:53:59.990 --> 00:54:03.370 align:middle line:84% And so this is a schematic of how this works. 00:54:03.370 --> 00:54:06.930 align:middle line:84% So the green circle is the receptive field 00:54:06.930 --> 00:54:09.130 align:middle line:84% of the receptor that's being recorded from. 00:54:09.130 --> 00:54:13.810 align:middle line:84% And these different sweeps are kind of different rotations 00:54:13.810 --> 00:54:16.970 align:middle line:84% of the cylinder positioned at different locations 00:54:16.970 --> 00:54:20.130 align:middle line:90% with respect to the finger. 00:54:20.130 --> 00:54:23.730 align:middle line:84% And so the idea is that when there's 00:54:23.730 --> 00:54:26.290 align:middle line:84% a ridge on the surface that comes 00:54:26.290 --> 00:54:27.790 align:middle line:84% in contact with the receptive field, 00:54:27.790 --> 00:54:29.490 align:middle line:90% you're going to get a response. 00:54:29.490 --> 00:54:33.090 align:middle line:84% And so you can display those responses spatially 00:54:33.090 --> 00:54:37.410 align:middle line:84% to get a visual sense of the extent to which the action 00:54:37.410 --> 00:54:42.170 align:middle line:84% potentials from the receptor are actually accurately capturing 00:54:42.170 --> 00:54:46.570 align:middle line:84% the spatial structure of the tactile stimulus. 00:54:46.570 --> 00:54:49.010 align:middle line:84% And so in this case, the point is that this kind of 00:54:49.010 --> 00:54:52.570 align:middle line:90% looks like a letter G. 00:54:52.570 --> 00:54:58.570 align:middle line:84% So this is a summary figure that shows the responses of the three 00:54:58.570 --> 00:54:59.830 align:middle line:90% main types of receptors. 00:54:59.830 --> 00:55:01.413 align:middle line:84% So remember how I told you in monkeys, 00:55:01.413 --> 00:55:03.950 align:middle line:84% they don't have the Ruffini receptor as far as people know? 00:55:03.950 --> 00:55:06.290 align:middle line:84% So there's really three main types of receptors-- 00:55:06.290 --> 00:55:08.885 align:middle line:90% SA1, RA, and PC. 00:55:08.885 --> 00:55:11.010 align:middle line:84% So it's the response of those three different types 00:55:11.010 --> 00:55:15.582 align:middle line:84% of receptors to the first few letters of the alphabet. 00:55:15.582 --> 00:55:17.540 align:middle line:84% And what you're supposed to take away from this 00:55:17.540 --> 00:55:22.640 align:middle line:84% is that the receptor types that have small receptive fields, 00:55:22.640 --> 00:55:26.020 align:middle line:84% so the SA1 and the RA, are doing a pretty good job 00:55:26.020 --> 00:55:29.260 align:middle line:84% of capturing the spatial structure of the letters. 00:55:29.260 --> 00:55:30.820 align:middle line:84% But you can see that the responses 00:55:30.820 --> 00:55:32.660 align:middle line:90% are qualitatively different. 00:55:32.660 --> 00:55:34.900 align:middle line:84% So they're kind of responding to different things. 00:55:34.900 --> 00:55:37.162 align:middle line:84% You can also see that the PC receptors-- 00:55:37.162 --> 00:55:39.120 align:middle line:84% those are the ones that are deeper in the skin. 00:55:39.120 --> 00:55:41.000 align:middle line:84% They've got bigger receptive fields. 00:55:41.000 --> 00:55:42.900 align:middle line:84% Those are actually not doing such a great job 00:55:42.900 --> 00:55:44.420 align:middle line:90% of capturing the letters. 00:55:44.420 --> 00:55:46.060 align:middle line:84% They're responding to larger-scale 00:55:46.060 --> 00:55:49.000 align:middle line:84% spatial structure rather than fine-scale spatial structure. 00:55:49.000 --> 00:55:52.340 align:middle line:90% 00:55:52.340 --> 00:55:52.840 align:middle line:90% All right. 00:55:52.840 --> 00:55:54.160 align:middle line:90% So this is for letters. 00:55:54.160 --> 00:55:56.020 align:middle line:84% And the main reason to use letters 00:55:56.020 --> 00:55:59.240 align:middle line:84% is that they're familiar visually to humans. 00:55:59.240 --> 00:56:01.620 align:middle line:84% And so you can kind of just glance at the picture 00:56:01.620 --> 00:56:05.220 align:middle line:90% and easily understand it. 00:56:05.220 --> 00:56:09.020 align:middle line:84% A more typical tactile stimulus would be a texture. 00:56:09.020 --> 00:56:14.420 align:middle line:84% So we use our sense of touch to identify material. 00:56:14.420 --> 00:56:17.500 align:middle line:84% And a big part of that is texture. 00:56:17.500 --> 00:56:19.600 align:middle line:90% So these are different textures. 00:56:19.600 --> 00:56:23.040 align:middle line:84% So these are like Braille dot patterns on one of these drums. 00:56:23.040 --> 00:56:24.800 align:middle line:84% So it's the same kind of experiment. 00:56:24.800 --> 00:56:27.140 align:middle line:84% You've got this rotating cylinder 00:56:27.140 --> 00:56:30.580 align:middle line:90% with an embossed surface on it. 00:56:30.580 --> 00:56:33.620 align:middle line:84% But now, the embossing is these dot patterns, 00:56:33.620 --> 00:56:35.780 align:middle line:90% and they vary in their density. 00:56:35.780 --> 00:56:38.500 align:middle line:84% And again, we've got the three main receptor types 00:56:38.500 --> 00:56:41.727 align:middle line:90% that you see in monkeys. 00:56:41.727 --> 00:56:42.560 align:middle line:90% And what do you see? 00:56:42.560 --> 00:56:45.700 align:middle line:84% Well, when the dots are very sparse, 00:56:45.700 --> 00:56:48.900 align:middle line:84% you get spatially localized responses 00:56:48.900 --> 00:56:54.080 align:middle line:84% to the individual dots in the SA and RA receptors, 00:56:54.080 --> 00:56:56.060 align:middle line:84% the ones with the smaller receptive fields. 00:56:56.060 --> 00:56:59.660 align:middle line:84% You don't really see much of anything in the PC receptors. 00:56:59.660 --> 00:57:05.020 align:middle line:84% But you can also see that as the dots become more dense, 00:57:05.020 --> 00:57:08.100 align:middle line:84% you stop being able to see of individual responses 00:57:08.100 --> 00:57:10.380 align:middle line:90% to the individual dots. 00:57:10.380 --> 00:57:12.740 align:middle line:84% It's like the texture kind of gets too fine 00:57:12.740 --> 00:57:15.540 align:middle line:84% for there to be a spatial representation of the texture 00:57:15.540 --> 00:57:17.200 align:middle line:90% in the receptor responses. 00:57:17.200 --> 00:57:24.070 align:middle line:90% 00:57:24.070 --> 00:57:27.300 align:middle line:84% So that's for some artificial textures. 00:57:27.300 --> 00:57:32.080 align:middle line:84% These are a few examples of real-world textures. 00:57:32.080 --> 00:57:36.820 align:middle line:84% So well, this one is artificial embossed dots. 00:57:36.820 --> 00:57:38.840 align:middle line:84% This is something called Huck towel. 00:57:38.840 --> 00:57:40.860 align:middle line:90% I guess it's a type of fabric. 00:57:40.860 --> 00:57:43.420 align:middle line:90% Got nylon and chiffon. 00:57:43.420 --> 00:57:45.940 align:middle line:84% So these are all things that if you felt them, 00:57:45.940 --> 00:57:47.120 align:middle line:90% they would feel different. 00:57:47.120 --> 00:57:52.980 align:middle line:84% But you can see that really it's only the very kind 00:57:52.980 --> 00:57:56.660 align:middle line:84% of coarse texture features that end up 00:57:56.660 --> 00:58:00.260 align:middle line:84% showing up in this spatial pattern of the responses. 00:58:00.260 --> 00:58:02.180 align:middle line:84% And so this fine-grained stuff that you 00:58:02.180 --> 00:58:04.580 align:middle line:84% can see in nylon and chiffon just 00:58:04.580 --> 00:58:07.780 align:middle line:84% doesn't really make it into the receptor responses 00:58:07.780 --> 00:58:09.560 align:middle line:90% as analyzed spatially. 00:58:09.560 --> 00:58:12.900 align:middle line:90% 00:58:12.900 --> 00:58:14.740 align:middle line:84% So how can we account for the fact 00:58:14.740 --> 00:58:16.760 align:middle line:84% that these things all feel differently? 00:58:16.760 --> 00:58:21.300 align:middle line:84% So what we believe is the key is that there 00:58:21.300 --> 00:58:24.420 align:middle line:84% is temporal information in the receptor responses, 00:58:24.420 --> 00:58:28.340 align:middle line:84% even in cases where things are not resolved spatially. 00:58:28.340 --> 00:58:33.780 align:middle line:84% So these are, again, kind of depth maps of, in this case, 00:58:33.780 --> 00:58:35.080 align:middle line:90% three types of cloth. 00:58:35.080 --> 00:58:37.460 align:middle line:90% So there's premiere velvet-- 00:58:37.460 --> 00:58:39.900 align:middle line:84% sounds like it might be very smooth-- 00:58:39.900 --> 00:58:44.420 align:middle line:84% drapery tape, and blizzard fleece, which I guess 00:58:44.420 --> 00:58:45.700 align:middle line:90% is a little bit rougher. 00:58:45.700 --> 00:58:50.520 align:middle line:90% These are spectrograms. 00:58:50.520 --> 00:58:51.920 align:middle line:90% Remember spectrograms? 00:58:51.920 --> 00:58:53.180 align:middle line:90% We all love spectrograms. 00:58:53.180 --> 00:58:56.660 align:middle line:84% So we use those to analyze audio. 00:58:56.660 --> 00:58:58.600 align:middle line:84% So what happens when you're feeling a texture 00:58:58.600 --> 00:59:01.100 align:middle line:84% is that spatial depth map kind of gets 00:59:01.100 --> 00:59:03.620 align:middle line:84% turned into a time series because you're sweeping 00:59:03.620 --> 00:59:05.480 align:middle line:90% this thing across the receptor. 00:59:05.480 --> 00:59:10.180 align:middle line:84% So if you assume that it's moving at a certain rate, 00:59:10.180 --> 00:59:11.220 align:middle line:90% you can then plot-- 00:59:11.220 --> 00:59:13.020 align:middle line:84% turn it into a spectrogram where you 00:59:13.020 --> 00:59:18.420 align:middle line:84% have the frequency as a content as a function of time. 00:59:18.420 --> 00:59:21.540 align:middle line:84% And the point of showing you it in this way 00:59:21.540 --> 00:59:26.020 align:middle line:84% is that in the frequency domain, these three materials kind of 00:59:26.020 --> 00:59:28.380 align:middle line:84% have pretty different signatures. 00:59:28.380 --> 00:59:32.500 align:middle line:84% So the premier velvet has got like a lot of power 00:59:32.500 --> 00:59:35.300 align:middle line:84% fairly consistently at this one particular frequency. 00:59:35.300 --> 00:59:38.740 align:middle line:84% The drapery tape has got some higher frequency and then 00:59:38.740 --> 00:59:40.880 align:middle line:90% some stuff at lower frequencies. 00:59:40.880 --> 00:59:43.508 align:middle line:84% And then the blizzard fleece is kind of a little bit more 00:59:43.508 --> 00:59:44.300 align:middle line:90% generally low-pass. 00:59:44.300 --> 00:59:48.920 align:middle line:90% 00:59:48.920 --> 00:59:51.320 align:middle line:84% So this is just like in the physical stimulus. 00:59:51.320 --> 00:59:53.340 align:middle line:84% So these different materials, when 00:59:53.340 --> 00:59:55.700 align:middle line:84% you look at them in the frequency domain, 00:59:55.700 --> 01:00:00.620 align:middle line:90% they have different signatures. 01:00:00.620 --> 01:00:02.620 align:middle line:90% So how would this be transduced? 01:00:02.620 --> 01:00:05.470 align:middle line:90% So remember phase locking? 01:00:05.470 --> 01:00:06.830 align:middle line:90% We all love phase locking. 01:00:06.830 --> 01:00:09.550 align:middle line:84% It's a characteristic of the auditory nerve 01:00:09.550 --> 01:00:13.833 align:middle line:84% where the action potentials are time locked to the stimulus. 01:00:13.833 --> 01:00:16.250 align:middle line:84% What's the upper limit of phase locking, roughly speaking, 01:00:16.250 --> 01:00:18.313 align:middle line:90% in the auditory nerve? 01:00:18.313 --> 01:00:19.230 align:middle line:90% AUDIENCE: That's 4000. 01:00:19.230 --> 01:00:23.990 align:middle line:84% JOSH MCDERMOTT: 4000 hertz-- yep, exactly, roughly. 01:00:23.990 --> 01:00:27.130 align:middle line:84% So this is phase locking in touch receptors. 01:00:27.130 --> 01:00:29.250 align:middle line:84% So we've got a sinusoidal stimulus. 01:00:29.250 --> 01:00:31.770 align:middle line:84% So here you can see the stimulator here. 01:00:31.770 --> 01:00:33.550 align:middle line:90% It's like a little piston-- 01:00:33.550 --> 01:00:35.390 align:middle line:84% just goes poke, poke, poke, poke, poke, 01:00:35.390 --> 01:00:37.910 align:middle line:84% moves back and forth sinusoidally. 01:00:37.910 --> 01:00:40.970 align:middle line:84% You can vary the amplitude of stimulation and the frequency. 01:00:40.970 --> 01:00:43.830 align:middle line:84% So this is a sinusoid at 400 hertz 01:00:43.830 --> 01:00:47.770 align:middle line:84% at three different amplitudes measured in micrometers. 01:00:47.770 --> 01:00:52.110 align:middle line:84% And this is a plot of action potentials. 01:00:52.110 --> 01:00:54.070 align:middle line:84% And what you're supposed to take away from this 01:00:54.070 --> 01:00:57.350 align:middle line:84% is that the action potentials here are time 01:00:57.350 --> 01:00:58.330 align:middle line:90% locked to the stimulus. 01:00:58.330 --> 01:01:00.413 align:middle line:84% So this is phase locking a lot like what you would 01:01:00.413 --> 01:01:03.190 align:middle line:90% see in the auditory nerve. 01:01:03.190 --> 01:01:03.690 align:middle line:90% All right. 01:01:03.690 --> 01:01:08.790 align:middle line:84% So there's some temporal information in the response. 01:01:08.790 --> 01:01:10.750 align:middle line:84% So does this actually have relevance 01:01:10.750 --> 01:01:13.530 align:middle line:90% for real-world textures? 01:01:13.530 --> 01:01:16.670 align:middle line:84% So this is one of those textures we 01:01:16.670 --> 01:01:19.850 align:middle line:84% were looking at before, nylon, along with a couple others-- 01:01:19.850 --> 01:01:24.610 align:middle line:84% stretch denim and silk jacquard, different cloths. 01:01:24.610 --> 01:01:28.150 align:middle line:90% 01:01:28.150 --> 01:01:30.853 align:middle line:84% At least the top ones have pretty fine-grained structure. 01:01:30.853 --> 01:01:33.270 align:middle line:84% And so that wouldn't really show up in the spatial pattern 01:01:33.270 --> 01:01:34.550 align:middle line:90% very clearly. 01:01:34.550 --> 01:01:36.210 align:middle line:90% These are raster plots. 01:01:36.210 --> 01:01:37.790 align:middle line:90% So remember, this is time. 01:01:37.790 --> 01:01:41.190 align:middle line:84% And the different rows are different trials. 01:01:41.190 --> 01:01:43.830 align:middle line:84% And then this is the frequency spectrum 01:01:43.830 --> 01:01:46.990 align:middle line:84% that you see here from those rasters. 01:01:46.990 --> 01:01:49.550 align:middle line:84% And what you're supposed to take away from this. 01:01:49.550 --> 01:01:53.070 align:middle line:84% So this is the frequency spectrum of the neural response. 01:01:53.070 --> 01:01:57.030 align:middle line:84% And what you're supposed to take away from this 01:01:57.030 --> 01:01:59.430 align:middle line:84% is that there is information that differentiates 01:01:59.430 --> 01:02:02.350 align:middle line:84% these different textures in the temporal pattern 01:02:02.350 --> 01:02:04.630 align:middle line:84% of the response, specifically in the frequency 01:02:04.630 --> 01:02:06.110 align:middle line:90% at which the spikes are fired. 01:02:06.110 --> 01:02:09.590 align:middle line:84% So the nylon gives you some peaks 01:02:09.590 --> 01:02:11.227 align:middle line:84% at these two points in the spectrum. 01:02:11.227 --> 01:02:13.310 align:middle line:84% The stretch denim has a peak at a different place, 01:02:13.310 --> 01:02:15.230 align:middle line:84% and it's a little bit more spread out. 01:02:15.230 --> 01:02:18.950 align:middle line:84% The silk jacquard has got some other kind of pattern to it. 01:02:18.950 --> 01:02:22.030 align:middle line:84% So even though the spatial pattern 01:02:22.030 --> 01:02:23.470 align:middle line:84% isn't really enough to tell apart 01:02:23.470 --> 01:02:25.390 align:middle line:84% these very fine-grained textures, 01:02:25.390 --> 01:02:26.670 align:middle line:90% the temporal pattern is. 01:02:26.670 --> 01:02:32.310 align:middle line:90% 01:02:32.310 --> 01:02:35.430 align:middle line:84% And so the general idea here is that there 01:02:35.430 --> 01:02:38.710 align:middle line:84% are these two components by which we 01:02:38.710 --> 01:02:43.070 align:middle line:84% sense texture and probably just other kinds of patterns 01:02:43.070 --> 01:02:45.350 align:middle line:90% more generally. 01:02:45.350 --> 01:02:48.590 align:middle line:84% There are fingertip deformations that 01:02:48.590 --> 01:02:53.430 align:middle line:84% cause a spatial image in the receptors that have 01:02:53.430 --> 01:02:56.350 align:middle line:90% very small receptive fields. 01:02:56.350 --> 01:02:59.110 align:middle line:84% And then there are high-frequency skin oscillations 01:02:59.110 --> 01:03:03.970 align:middle line:84% that cause spike patterns in the rapidly adapting receptors, 01:03:03.970 --> 01:03:07.750 align:middle line:84% the ones that are very sensitive to rapid changes in stimulation. 01:03:07.750 --> 01:03:10.990 align:middle line:84% And those get combined in some unspecified way 01:03:10.990 --> 01:03:16.750 align:middle line:90% that to yield the percept. 01:03:16.750 --> 01:03:20.370 align:middle line:84% So texture is important in touch. 01:03:20.370 --> 01:03:22.730 align:middle line:84% We've talked a lot about it in vision and audition. 01:03:22.730 --> 01:03:23.830 align:middle line:84% Now in vision and audition, there 01:03:23.830 --> 01:03:25.430 align:middle line:84% are actually pretty well-developed theories 01:03:25.430 --> 01:03:26.090 align:middle line:90% of texture. 01:03:26.090 --> 01:03:28.010 align:middle line:84% So we don't really have that yet for touch. 01:03:28.010 --> 01:03:31.030 align:middle line:84% All we're talking about here is this idea 01:03:31.030 --> 01:03:32.750 align:middle line:84% that there is information being conveyed 01:03:32.750 --> 01:03:35.890 align:middle line:84% by receptors that would probably be diagnostic of texture. 01:03:35.890 --> 01:03:38.150 align:middle line:84% And it would be really cool to actually try 01:03:38.150 --> 01:03:42.270 align:middle line:84% to build a model of tactile texture perception, 01:03:42.270 --> 01:03:43.990 align:middle line:84% kind of in the spirit of the ones that we 01:03:43.990 --> 01:03:46.550 align:middle line:90% have in these other domains. 01:03:46.550 --> 01:03:48.130 align:middle line:90% But that hasn't happened yet. 01:03:48.130 --> 01:03:51.310 align:middle line:84% So that'd be a cool thing for the future. 01:03:51.310 --> 01:03:55.980 align:middle line:84% So we got the mechanoreceptors in the skin. 01:03:55.980 --> 01:03:58.640 align:middle line:84% There's four main types that we talked about. 01:03:58.640 --> 01:04:01.640 align:middle line:84% But there's lots of other types of mechanoreceptors. 01:04:01.640 --> 01:04:04.200 align:middle line:84% Specifically within muscles, tendons, and joints, 01:04:04.200 --> 01:04:06.720 align:middle line:84% there are kinesthetic receptors that 01:04:06.720 --> 01:04:10.640 align:middle line:84% play an important role in our sense of where our limbs are 01:04:10.640 --> 01:04:12.380 align:middle line:84% and what kinds of movements are made. 01:04:12.380 --> 01:04:15.200 align:middle line:84% So that's part of what's called proprioception. 01:04:15.200 --> 01:04:19.000 align:middle line:84% There are receptors in muscle spindles 01:04:19.000 --> 01:04:20.780 align:middle line:84% that sense the tension in the muscle. 01:04:20.780 --> 01:04:22.155 align:middle line:84% We talked a little bit about that 01:04:22.155 --> 01:04:23.920 align:middle line:90% in the context of eye movements. 01:04:23.920 --> 01:04:25.640 align:middle line:84% So the receptors in tendons that signal 01:04:25.640 --> 01:04:28.220 align:middle line:84% the tension in the muscles that are attached to tendons, 01:04:28.220 --> 01:04:30.880 align:middle line:84% receptors in joints that react when a joint is 01:04:30.880 --> 01:04:34.007 align:middle line:84% bent at an extreme angle, all these are kind of things that 01:04:34.007 --> 01:04:35.840 align:middle line:84% help you control your body and make sure you 01:04:35.840 --> 01:04:40.280 align:middle line:84% don't break things if you don't have to. 01:04:40.280 --> 01:04:42.480 align:middle line:84% So here's just a picture showing some 01:04:42.480 --> 01:04:45.960 align:middle line:84% of the complexity of muscle fibers and the sensors 01:04:45.960 --> 01:04:49.280 align:middle line:90% that you have in there. 01:04:49.280 --> 01:04:53.000 align:middle line:84% So there are some interesting kind of neurological patient 01:04:53.000 --> 01:04:54.920 align:middle line:84% cases that illustrate some of the importance 01:04:54.920 --> 01:04:56.700 align:middle line:90% of these kinesthetic receptors. 01:04:56.700 --> 01:05:01.880 align:middle line:84% So there's a famous patient called Ian Waterman, who 01:05:01.880 --> 01:05:05.040 align:middle line:84% got this kind of virus that caused 01:05:05.040 --> 01:05:09.000 align:middle line:84% the cutaneous nerves connecting his kinesthetic receptors 01:05:09.000 --> 01:05:11.640 align:middle line:90% to the brain to be destroyed. 01:05:11.640 --> 01:05:17.160 align:middle line:84% So this guy was not getting any input from proprioception. 01:05:17.160 --> 01:05:20.360 align:middle line:84% So he lacked kinesthetic senses, became dependent on vision 01:05:20.360 --> 01:05:21.780 align:middle line:90% to tell his limb position. 01:05:21.780 --> 01:05:26.200 align:middle line:84% So it's a very strange way to be. 01:05:26.200 --> 01:05:26.700 align:middle line:90% All right. 01:05:26.700 --> 01:05:28.158 align:middle line:84% So those are kinesthetic receptors. 01:05:28.158 --> 01:05:29.500 align:middle line:90% There's also thermoreceptors. 01:05:29.500 --> 01:05:30.958 align:middle line:84% So these are sensory receptors that 01:05:30.958 --> 01:05:33.900 align:middle line:84% signal information about changes in skin temperature. 01:05:33.900 --> 01:05:36.220 align:middle line:84% So there's two main populations of thermoreceptors. 01:05:36.220 --> 01:05:38.240 align:middle line:84% There are those that are sensitive to warmth 01:05:38.240 --> 01:05:40.280 align:middle line:84% and those that are sensitive to cold. 01:05:40.280 --> 01:05:42.080 align:middle line:84% So your body is constantly regulating 01:05:42.080 --> 01:05:43.800 align:middle line:90% its internal temperature. 01:05:43.800 --> 01:05:46.200 align:middle line:84% And thermoreceptors respond when you make contact 01:05:46.200 --> 01:05:51.320 align:middle line:84% with an object that is warmer or colder than your skin. 01:05:51.320 --> 01:05:55.960 align:middle line:84% So this is a picture that shows thermoreceptive fields 01:05:55.960 --> 01:05:58.240 align:middle line:84% for these two types of fibers-- the cold fibers 01:05:58.240 --> 01:05:59.180 align:middle line:90% and the warmth fibers. 01:05:59.180 --> 01:06:04.820 align:middle line:84% So skin temperature is normally kept between 30 and 36 degrees 01:06:04.820 --> 01:06:05.400 align:middle line:90% Celsius. 01:06:05.400 --> 01:06:08.680 align:middle line:84% So it's regulated pretty tightly. 01:06:08.680 --> 01:06:12.240 align:middle line:84% And the cold fibers start to respond 01:06:12.240 --> 01:06:13.720 align:middle line:84% if you encounter something that's 01:06:13.720 --> 01:06:15.902 align:middle line:84% significantly colder than your skin temperature. 01:06:15.902 --> 01:06:18.360 align:middle line:84% The warm fibers respond when you encounter something that's 01:06:18.360 --> 01:06:20.680 align:middle line:84% significantly warmer than the skin temperature, 01:06:20.680 --> 01:06:24.080 align:middle line:84% telling you when the skin gets heated 01:06:24.080 --> 01:06:26.040 align:middle line:90% or cooled out of normal range. 01:06:26.040 --> 01:06:29.600 align:middle line:84% So that, of course, is part of material perception. 01:06:29.600 --> 01:06:31.920 align:middle line:84% It's also, again, a safety mechanism 01:06:31.920 --> 01:06:37.240 align:middle line:84% so that you don't burn yourself or freeze yourself, so forth. 01:06:37.240 --> 01:06:39.360 align:middle line:90% There's also nociceptors. 01:06:39.360 --> 01:06:42.860 align:middle line:84% So these are receptors that signal pain. 01:06:42.860 --> 01:06:46.280 align:middle line:84% So they transmit information about noxious stimulation 01:06:46.280 --> 01:06:48.120 align:middle line:90% that could damage your skin. 01:06:48.120 --> 01:06:52.120 align:middle line:84% So the key thing to note here is that there are two main groups 01:06:52.120 --> 01:06:53.940 align:middle line:90% of these nociceptors. 01:06:53.940 --> 01:06:57.680 align:middle line:84% So they have two different names-- 01:06:57.680 --> 01:06:59.700 align:middle line:90% A delta fibers and C fibers. 01:06:59.700 --> 01:07:02.720 align:middle line:84% But so the key thing to know about them is that one of them 01:07:02.720 --> 01:07:06.840 align:middle line:84% is myelinated, and the other one is unmyelinated. 01:07:06.840 --> 01:07:09.640 align:middle line:84% They both transmit information about pain and temperature. 01:07:09.640 --> 01:07:12.880 align:middle line:84% And so the consequence of that-- so what does myelin do? 01:07:12.880 --> 01:07:13.900 align:middle line:90% Anybody remember? 01:07:13.900 --> 01:07:17.080 align:middle line:90% 01:07:17.080 --> 01:07:17.980 align:middle line:90% Yeah. 01:07:17.980 --> 01:07:20.360 align:middle line:84% AUDIENCE: It insulates the signal of axons 01:07:20.360 --> 01:07:22.340 align:middle line:84% to make it travel a further distance. 01:07:22.340 --> 01:07:24.760 align:middle line:84% JOSH MCDERMOTT: Yeah, it also makes things faster. 01:07:24.760 --> 01:07:27.620 align:middle line:84% So myelinated fibers carry signals faster. 01:07:27.620 --> 01:07:35.200 align:middle line:84% And many of you have probably had the experience 01:07:35.200 --> 01:07:37.300 align:middle line:90% of something painful. 01:07:37.300 --> 01:07:40.860 align:middle line:84% So imagine you're walking around barefoot early in the morning. 01:07:40.860 --> 01:07:44.720 align:middle line:84% You haven't had your cup of coffee, and you step on a LEGO-- 01:07:44.720 --> 01:07:47.890 align:middle line:84% something that happens to me fairly routinely. 01:07:47.890 --> 01:07:50.410 align:middle line:84% There will be two distinct stages to that experience 01:07:50.410 --> 01:07:51.550 align:middle line:90% of stepping on a LEGO. 01:07:51.550 --> 01:07:54.970 align:middle line:84% You get this kind of quick, sharp pain followed 01:07:54.970 --> 01:07:57.570 align:middle line:90% by a throbbing sensation. 01:07:57.570 --> 01:08:00.330 align:middle line:84% And that's believed to actually correspond 01:08:00.330 --> 01:08:01.830 align:middle line:90% to these two classes of fibers. 01:08:01.830 --> 01:08:03.890 align:middle line:84% There's a very quick signal that's 01:08:03.890 --> 01:08:07.810 align:middle line:84% supposed to tell you to get your foot off the LEGO. 01:08:07.810 --> 01:08:09.130 align:middle line:90% So that's fast. 01:08:09.130 --> 01:08:11.570 align:middle line:84% And then this unmyelinated signal, 01:08:11.570 --> 01:08:18.930 align:middle line:84% that is, I guess, probably just telling you, is my foot damaged? 01:08:18.930 --> 01:08:20.609 align:middle line:84% Do I need to be careful for a while? 01:08:20.609 --> 01:08:23.073 align:middle line:84% And that one doesn't need to be as fast. 01:08:23.073 --> 01:08:24.990 align:middle line:84% The difference is speed is due to myelination. 01:08:24.990 --> 01:08:27.010 align:middle line:90% So that's the key concept there. 01:08:27.010 --> 01:08:29.990 align:middle line:84% Two classes of these pain receptor fibers. 01:08:29.990 --> 01:08:32.529 align:middle line:90% 01:08:32.529 --> 01:08:35.850 align:middle line:84% So again, there are these crazy cases 01:08:35.850 --> 01:08:39.770 align:middle line:84% of individuals that are born with insensitivity 01:08:39.770 --> 01:08:41.229 align:middle line:90% to some aspects of this. 01:08:41.229 --> 01:08:46.970 align:middle line:84% So a famous patient was born with insensitivity to pain. 01:08:46.970 --> 01:08:49.130 align:middle line:84% And this had major consequences for her life. 01:08:49.130 --> 01:08:53.170 align:middle line:84% She didn't sneeze or cough or gag or blink reflexively, 01:08:53.170 --> 01:08:55.550 align:middle line:84% suffered injuries, burning herself on radiators, 01:08:55.550 --> 01:08:59.569 align:middle line:84% biting her tongue when chewing food because these receptors are 01:08:59.569 --> 01:09:02.090 align:middle line:84% sending you signals to not do certain things. 01:09:02.090 --> 01:09:05.010 align:middle line:84% And this particular individual is from a long time ago, 01:09:05.010 --> 01:09:06.729 align:middle line:84% but died very young from infections 01:09:06.729 --> 01:09:08.810 align:middle line:84% that possibly might have been prevented if she 01:09:08.810 --> 01:09:10.689 align:middle line:90% had been able to sense pain. 01:09:10.689 --> 01:09:14.689 align:middle line:84% So you've got this massive array of different types of receptors. 01:09:14.689 --> 01:09:16.330 align:middle line:90% Where do they end up? 01:09:16.330 --> 01:09:21.290 align:middle line:84% So they project ultimately to somatosensory cortex. 01:09:21.290 --> 01:09:24.130 align:middle line:84% So touch sensations are represented somatotopically 01:09:24.130 --> 01:09:25.069 align:middle line:90% in the brain. 01:09:25.069 --> 01:09:27.810 align:middle line:90% So this is another key concept. 01:09:27.810 --> 01:09:28.910 align:middle line:90% And I should emphasize. 01:09:28.910 --> 01:09:33.109 align:middle line:84% So this is an idea that's been in all the textbooks forever. 01:09:33.109 --> 01:09:35.689 align:middle line:84% This has very recently kind of been challenged-- 01:09:35.689 --> 01:09:38.529 align:middle line:84% this idea that there is a full kind 01:09:38.529 --> 01:09:41.210 align:middle line:84% of map of the body that's laid out in somatosensory cortex 01:09:41.210 --> 01:09:43.689 align:middle line:84% and is kind of currently under debate. 01:09:43.689 --> 01:09:46.662 align:middle line:84% So it may well be that in another year or two, 01:09:46.662 --> 01:09:47.870 align:middle line:90% the story is going to change. 01:09:47.870 --> 01:09:49.350 align:middle line:90% But this is the classical story. 01:09:49.350 --> 01:09:52.729 align:middle line:84% And so the classical idea is that there 01:09:52.729 --> 01:09:55.330 align:middle line:84% is a somatotopic map in somatosensory cortex 01:09:55.330 --> 01:09:58.510 align:middle line:84% that's analogous to retinotopic mapping that's found in vision, 01:09:58.510 --> 01:10:01.250 align:middle line:84% where adjacent areas on the skin connect 01:10:01.250 --> 01:10:04.530 align:middle line:90% to adjacent areas in the brain. 01:10:04.530 --> 01:10:06.573 align:middle line:84% And people will often refer to homunculus. 01:10:06.573 --> 01:10:08.490 align:middle line:84% It's like a map-like representation of regions 01:10:08.490 --> 01:10:11.130 align:middle line:90% of the body in the brain. 01:10:11.130 --> 01:10:13.450 align:middle line:84% And somatosensory cortex typically 01:10:13.450 --> 01:10:15.050 align:middle line:90% is divided into two regions-- 01:10:15.050 --> 01:10:16.190 align:middle line:90% S1 and S2. 01:10:16.190 --> 01:10:18.128 align:middle line:84% S1 is primary somatosensory cortex, 01:10:18.128 --> 01:10:20.170 align:middle line:84% kind of gets direct projections from the thalamus 01:10:20.170 --> 01:10:21.810 align:middle line:90% or most of them. 01:10:21.810 --> 01:10:26.330 align:middle line:84% And then, whereas S2 doesn't, or to a lesser extent. 01:10:26.330 --> 01:10:29.490 align:middle line:90% 01:10:29.490 --> 01:10:32.570 align:middle line:84% So if you're interested in old-school neuroanatomy, 01:10:32.570 --> 01:10:37.810 align:middle line:84% S1 includes Brodmann areas 1, 2, 3a, and 3b. 01:10:37.810 --> 01:10:39.750 align:middle line:90% S2 is within the lateral sulcus. 01:10:39.750 --> 01:10:43.210 align:middle line:84% So remember, the central sulcus is this big sulcus here 01:10:43.210 --> 01:10:46.430 align:middle line:84% that divides the frontal lobe and the parietal lobe. 01:10:46.430 --> 01:10:49.150 align:middle line:84% And on one side of that is motor cortex. 01:10:49.150 --> 01:10:53.050 align:middle line:84% On the other side of that is somatosensory cortex. 01:10:53.050 --> 01:10:56.610 align:middle line:84% So what this is showing is the regions 01:10:56.610 --> 01:10:59.450 align:middle line:84% of the body that are represented in different places 01:10:59.450 --> 01:11:01.530 align:middle line:90% within somatosensory cortex. 01:11:01.530 --> 01:11:05.330 align:middle line:84% And superimposed on this are the classical divisions 01:11:05.330 --> 01:11:08.932 align:middle line:90% of Brodmann areas 1, 2, and 3. 01:11:08.932 --> 01:11:10.890 align:middle line:84% And what you're supposed to take away from this 01:11:10.890 --> 01:11:13.850 align:middle line:84% is that kind of adjacent places on the body 01:11:13.850 --> 01:11:16.310 align:middle line:90% are adjacent on the cortex. 01:11:16.310 --> 01:11:18.997 align:middle line:84% And so the kind of classic picture that it's so classic, 01:11:18.997 --> 01:11:20.830 align:middle line:84% many of you have already probably seen this. 01:11:20.830 --> 01:11:22.413 align:middle line:84% How many of you have seen this before? 01:11:22.413 --> 01:11:24.630 align:middle line:84% Yeah, this is shown in every introductory class. 01:11:24.630 --> 01:11:30.192 align:middle line:84% So you end up with this map of the body that's laid out. 01:11:30.192 --> 01:11:31.650 align:middle line:84% Now the other thing that you'll see 01:11:31.650 --> 01:11:35.930 align:middle line:84% is that the amount of cortical real estate that 01:11:35.930 --> 01:11:40.060 align:middle line:84% is devoted to a body part is not proportional to the size 01:11:40.060 --> 01:11:41.080 align:middle line:90% of the body part. 01:11:41.080 --> 01:11:45.620 align:middle line:84% What is this kind of loosely analogous to that we've studied 01:11:45.620 --> 01:11:47.280 align:middle line:90% in another sensory system? 01:11:47.280 --> 01:11:52.780 align:middle line:90% 01:11:52.780 --> 01:11:53.540 align:middle line:90% Yeah. 01:11:53.540 --> 01:11:55.820 align:middle line:84% AUDIENCE: Like the vision system [INAUDIBLE]. 01:11:55.820 --> 01:11:56.695 align:middle line:90% JOSH MCDERMOTT: Yeah. 01:11:56.695 --> 01:11:59.240 align:middle line:84% So we talked about cortical magnification in vision 01:11:59.240 --> 01:12:05.300 align:middle line:84% where there's much more area in the cortex representing 01:12:05.300 --> 01:12:07.408 align:middle line:84% the fovea than representing the periphery. 01:12:07.408 --> 01:12:08.200 align:middle line:90% It's the same idea. 01:12:08.200 --> 01:12:10.300 align:middle line:84% And so again, in the fovea in the vision, 01:12:10.300 --> 01:12:12.360 align:middle line:84% there's lots and lots of receptors. 01:12:12.360 --> 01:12:13.860 align:middle line:84% They have to be packed together very 01:12:13.860 --> 01:12:17.420 align:middle line:84% densely because there's an image that is formed on the fovea. 01:12:17.420 --> 01:12:19.380 align:middle line:84% Similarly, in your fingertips or your lips, 01:12:19.380 --> 01:12:20.540 align:middle line:84% there's lots and lots of receptors 01:12:20.540 --> 01:12:23.040 align:middle line:84% that have to be packed very densely because they're supposed 01:12:23.040 --> 01:12:24.620 align:middle line:90% to be detecting stuff there. 01:12:24.620 --> 01:12:27.580 align:middle line:84% But then once you get to the cortex, kind of things 01:12:27.580 --> 01:12:30.220 align:middle line:84% spread out, and the density of the cells is equal. 01:12:30.220 --> 01:12:32.020 align:middle line:84% And you devote much more area to things 01:12:32.020 --> 01:12:35.600 align:middle line:84% like the face or the fingers than to the arm, 01:12:35.600 --> 01:12:37.660 align:middle line:90% for instance, or the back. 01:12:37.660 --> 01:12:42.580 align:middle line:84% And so a lot of what we know about this originally 01:12:42.580 --> 01:12:45.620 align:middle line:84% derived from experiments by neurosurgeons 01:12:45.620 --> 01:12:47.980 align:middle line:84% who were stimulating with electrodes 01:12:47.980 --> 01:12:51.420 align:middle line:90% in these different regions. 01:12:51.420 --> 01:12:54.158 align:middle line:84% This would be done with epilepsy patients who they'd potentially 01:12:54.158 --> 01:12:55.200 align:middle line:90% be performing surgery on. 01:12:55.200 --> 01:12:57.482 align:middle line:84% So they'd have an electrode in somatosensory cortex, 01:12:57.482 --> 01:12:58.940 align:middle line:84% and they'd inject a little current. 01:12:58.940 --> 01:13:01.140 align:middle line:84% And people would say they felt tickled. 01:13:01.140 --> 01:13:02.860 align:middle line:84% And so they'd move the electrode around, 01:13:02.860 --> 01:13:05.980 align:middle line:84% and like the location of the tickle would move around. 01:13:05.980 --> 01:13:08.640 align:middle line:84% And this led to this idea of a map. 01:13:08.640 --> 01:13:12.180 align:middle line:84% As I said, this has recently kind of been challenged. 01:13:12.180 --> 01:13:14.640 align:middle line:84% And we'll see where this kind of ends up. 01:13:14.640 --> 01:13:17.860 align:middle line:90% 01:13:17.860 --> 01:13:20.380 align:middle line:84% Supposedly, you got this map of the body 01:13:20.380 --> 01:13:23.000 align:middle line:84% that exhibits something kind of like cortical magnification. 01:13:23.000 --> 01:13:26.220 align:middle line:84% One of the other things that you see in somatosensory cortex 01:13:26.220 --> 01:13:27.740 align:middle line:90% is orientation tuning. 01:13:27.740 --> 01:13:30.540 align:middle line:84% So this is very much analogous to the orientation 01:13:30.540 --> 01:13:32.380 align:middle line:84% tuning that you see in visual cortex. 01:13:32.380 --> 01:13:35.120 align:middle line:84% So this is a receptive field that would be measured. 01:13:35.120 --> 01:13:37.260 align:middle line:84% The way that this is measured is with a device 01:13:37.260 --> 01:13:38.280 align:middle line:90% that looks like this. 01:13:38.280 --> 01:13:41.100 align:middle line:84% So you've got all these little pins. 01:13:41.100 --> 01:13:45.220 align:middle line:84% And so you can press the pins up or down. 01:13:45.220 --> 01:13:48.040 align:middle line:84% That will provide localized mechanical stimulation. 01:13:48.040 --> 01:13:50.620 align:middle line:84% So the animal's got its fingertip on this thing. 01:13:50.620 --> 01:13:52.500 align:middle line:84% You can generate different kinds of stimuli 01:13:52.500 --> 01:13:55.040 align:middle line:84% and derive the receptive field in different ways. 01:13:55.040 --> 01:13:57.760 align:middle line:84% And this is an oriented receptive field that you see. 01:13:57.760 --> 01:14:01.300 align:middle line:90% 01:14:01.300 --> 01:14:04.600 align:middle line:84% So this is showing how this would work. 01:14:04.600 --> 01:14:07.160 align:middle line:84% So you'd present like a little embossed line segment. 01:14:07.160 --> 01:14:09.420 align:middle line:84% And you can vary the orientation. 01:14:09.420 --> 01:14:11.513 align:middle line:84% And you can see here that there are orientations 01:14:11.513 --> 01:14:12.680 align:middle line:90% that give you big responses. 01:14:12.680 --> 01:14:16.740 align:middle line:84% And then as you rotate it off, the response gets less. 01:14:16.740 --> 01:14:18.220 align:middle line:84% The orientation tuning is present 01:14:18.220 --> 01:14:21.940 align:middle line:84% if you just press a thing into the skin versus scanning it 01:14:21.940 --> 01:14:27.140 align:middle line:84% over the skin, and it's independent of the pressure 01:14:27.140 --> 01:14:33.000 align:middle line:84% by which the line segment is pressed into the skin. 01:14:33.000 --> 01:14:35.660 align:middle line:90% 01:14:35.660 --> 01:14:38.260 align:middle line:84% Two last things, and then we will call it quits. 01:14:38.260 --> 01:14:42.440 align:middle line:84% So one kind of other interesting analog with other systems-- 01:14:42.440 --> 01:14:44.242 align:middle line:84% we just talked about visual search 01:14:44.242 --> 01:14:45.700 align:middle line:84% where you have an array of elements 01:14:45.700 --> 01:14:48.840 align:middle line:84% and you have to detect something that's different. 01:14:48.840 --> 01:14:50.940 align:middle line:84% You can also perform haptic search 01:14:50.940 --> 01:14:52.940 align:middle line:84% where there will be elements that are presented 01:14:52.940 --> 01:14:54.500 align:middle line:90% to the different fingertips. 01:14:54.500 --> 01:14:57.082 align:middle line:84% So you have to represent the-- recognize 01:14:57.082 --> 01:14:58.540 align:middle line:84% the presence of material properties 01:14:58.540 --> 01:15:00.660 align:middle line:84% that are presented haptically to the fingers 01:15:00.660 --> 01:15:02.120 align:middle line:90% with this kind of device. 01:15:02.120 --> 01:15:05.460 align:middle line:84% The question is whether some properties kind of pop out. 01:15:05.460 --> 01:15:09.340 align:middle line:84% So you could present a rough texture or a smooth texture. 01:15:09.340 --> 01:15:12.260 align:middle line:84% So remember, we analyze visual search results 01:15:12.260 --> 01:15:16.600 align:middle line:84% by plotting reaction time versus the number of elements. 01:15:16.600 --> 01:15:18.860 align:middle line:84% Here it's the number of fingers as opposed 01:15:18.860 --> 01:15:21.820 align:middle line:84% to the number of line segments or whatever. 01:15:21.820 --> 01:15:23.900 align:middle line:84% And when you're searching for rough stimuli 01:15:23.900 --> 01:15:29.300 align:middle line:84% among smooth stimuli, you get pretty flat search results, 01:15:29.300 --> 01:15:31.510 align:middle line:90% indicating pop out. 01:15:31.510 --> 01:15:34.610 align:middle line:84% So rough among smooth pops out, hard among soft, 01:15:34.610 --> 01:15:38.575 align:middle line:84% cool among warm, edge surfaces among smooth surfaces. 01:15:38.575 --> 01:15:39.950 align:middle line:84% But unlike the visual system, you 01:15:39.950 --> 01:15:42.690 align:middle line:84% don't get pop-out for distinct orientations. 01:15:42.690 --> 01:15:45.430 align:middle line:84% So if you do horizontal lines among vertical lines, 01:15:45.430 --> 01:15:47.110 align:middle line:90% you don't get pop-out. 01:15:47.110 --> 01:15:50.070 align:middle line:84% So same kind of phenomena but the features that 01:15:50.070 --> 01:15:52.150 align:middle line:84% seem to be kind of fundamental may 01:15:52.150 --> 01:15:56.150 align:middle line:84% be very different across sensory systems. 01:15:56.150 --> 01:15:59.970 align:middle line:84% Finally, a really cool kind of application of touch is Braille. 01:15:59.970 --> 01:16:03.310 align:middle line:84% So this is how someone without sight would read. 01:16:03.310 --> 01:16:07.710 align:middle line:84% So Braille consists of these patterns of embossed dots. 01:16:07.710 --> 01:16:09.590 align:middle line:84% And you might wonder, well, what's 01:16:09.590 --> 01:16:10.930 align:middle line:90% the point of having these dots? 01:16:10.930 --> 01:16:13.950 align:middle line:84% Why not just actually emboss the actual letters? 01:16:13.950 --> 01:16:16.030 align:middle line:84% And what this is supposed to show 01:16:16.030 --> 01:16:18.430 align:middle line:84% is that at the kind of coarse spatial scales 01:16:18.430 --> 01:16:21.590 align:middle line:84% that the receptors in our fingertips are measuring things, 01:16:21.590 --> 01:16:23.110 align:middle line:84% those patterns of embossed dots are 01:16:23.110 --> 01:16:26.150 align:middle line:84% more discriminable than the actual letters would be. 01:16:26.150 --> 01:16:26.990 align:middle line:90% All right. 01:16:26.990 --> 01:16:30.550 align:middle line:84% So this is supposed to be what the pattern of stimulation 01:16:30.550 --> 01:16:32.990 align:middle line:84% would be for each of those different Braille letters 01:16:32.990 --> 01:16:34.968 align:middle line:84% and for each of the different actual letters. 01:16:34.968 --> 01:16:36.510 align:middle line:84% And the idea is that these things all 01:16:36.510 --> 01:16:40.683 align:middle line:84% look subtly different, and these all look the same. 01:16:40.683 --> 01:16:42.350 align:middle line:84% So Braille is an interesting application 01:16:42.350 --> 01:16:43.310 align:middle line:90% of the sense of touch. 01:16:43.310 --> 01:16:43.810 align:middle line:90% All right. 01:16:43.810 --> 01:16:45.370 align:middle line:84% That's all I got for you about the sense of touch. 01:16:45.370 --> 01:16:46.570 align:middle line:90% What questions do you have? 01:16:46.570 --> 01:16:50.630 align:middle line:90% 01:16:50.630 --> 01:16:53.030 align:middle line:84% Again, a lot of the action is at the receptor level. 01:16:53.030 --> 01:16:56.790 align:middle line:84% We don't have much in the way of understanding 01:16:56.790 --> 01:17:01.150 align:middle line:84% of higher-order aspects of perception. 01:17:01.150 --> 01:17:04.350 align:middle line:84% Hopefully, that's to come in the future. 01:17:04.350 --> 01:17:05.690 align:middle line:90% OK, have a great weekend. 01:17:05.690 --> 01:17:07.010 align:middle line:90% We got one more class to go. 01:17:07.010 --> 01:17:09.380 align:middle line:90% I will see you Tuesday. 01:17:09.380 --> 01:17:29.000 align:middle line:90%