The readings listed below are the foundation of this course. Where available, journal article abstracts from PubMed (an online database providing access to citations from biomedical literature) are included.
Spinal Cord and Reflexes
Bizzi, E., M . C. Tresch, P. Saltiel, and A. d’Avella. “New Perspectives on Spinal Motor Systems.” Nature Reviews/Neuroscience 1 (2000): 101-108.
PubMed abstract: The production and control of complex motor functions are usually attributed to central brain structures such as cortex, basal ganglia and cerebellum. In traditional schemes the spinal cord is assigned a subservient function during the production of movement, playing a predominantly passive role by relaying the commands dictated to it by supraspinal systems. This review challenges this idea by presenting evidence that the spinal motor system is an active participant in several aspects of the production of movement, contributing to functions normally ascribed to ‘higher’ brain regions.
Kandel, Schwartz, and Jessell. Principles of Neural Science. 4th ed. McGraw Hill, chap. 34, 36 and 37.
Motor Cortex and Premotor Cortex
Assigned Reading:
Kandel, E., et al. Principles of Neuroscience. 2002, chap. 38, 42 and 43.
Papers for Discussion:
Graziano, M. S., C. S. Taylor, and T. Moore. “Complex Movements Evoked by Microstimulation of Precentral Cortex.” Neuron 34 (2002): 841-851.
PubMed abstract: Electrical microstimulation was used to study primary motor and premotor cortex in monkeys. Each stimulation train was 500 ms in duration, approximating the time scale of normal reaching and grasping movements and the time scale of the neuronal activity that normally accompanies movement. This stimulation on a behaviorally relevant time scale evoked coordinated, complex postures that involved many joints. For example, stimulation of one site caused the mouth to open and also caused the hand to shape into a grip posture and move to the mouth. Stimulation of this site always drove the joints toward this final posture, regardless of the direction of movement required to reach the posture. Stimulation of other cortical sites evoked different postures. Postures that involved the arm were arranged across cortex to form a map of hand positions around the body. This stimulation-evoked map encompassed both primary motor and the adjacent premotor cortex. We suggest that these regions fit together into a single map of the workspace around the body.
Graziano, M. S., C. S. Taylor, T. Moore and D. F. Cooke. “The Cortical Control of Movement Revisited.” Neuron 36 (2002): 349-362.
PubMed abstract: Recently, we found that electrical stimulation of motor cortex caused monkeys to make coordinated, complex movements. These evoked movements were arranged across the cortex in a map of spatial locations to which the hand moved. We suggest that some of the subdivisions previously described within primary motor and premotor cortex may represent different types of actions that monkeys tend to make in different regions of space. According to this view, primary and premotor cortex may fit together into a larger map of manual space.
Wessberg, J., et al. “Real-Time Prediction of Hand Trajectory by Ensembles of Cortical Neurons in Primates.” Nature 408 (2000): 361-365.
PubMed abstract: Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.
Somatosensory
Kandel, E., et al. Principles of Neuroscience. 2002, chap. 21, 22, and 23.
Oculomotor System
The Neural Control of Visually Guided Eye Movements. Pp. 3-46.
Schiller, Peter H., Edward J. Tehovnik. “Look and see: How the Brain Moves Your Eyes About.” Prog. Brain Res. 134 (2001).
PubMed abstract: Two major cortical streams are involved in the generation of visually guided saccadic eye movements: the anterior and the posterior. The anterior stream from the frontal and medial eye fields has direct access to brainstem oculomotor centers. The posterior stream from the occipital cortices reaches brainstem oculomotor centers through the superior colliculus. The parietal cortex interconnects with both streams. Our findings suggest that the posterior stream plays an unique role in the execution of rapid, short-latency eye movements called ’express saccades’. Both the anterior and posterior streams play a role in the selection of targets to which saccades are to be generated, but do so in different ways. Areas V1, V2 and LIP contribute to decisions involved in where to look as well as where not to look. In addition, area LIP is involved in decisions about how long to maintain fixation prior to the execution of a saccade. Area V4 does not appear to be directly involved in eye-movement generation. In the anterior stream, the frontal eye fields, and to a lesser extent the medial eye fields, are involved in the correct execution of saccades subsequent to decisions made about where to look and where not to look.
Simpson, J. “The Accessory Optic System.” Ann Rev Neurosci (1984). Tehovnik, Edward J., Marc A. Sommer, I-Han Chou, Warren M. Slocum, and Peter H. Schiller “Eye Fields in the Frontal Lobes of Primates.” Brain Res Reviews 32 (2000): 413-448.
PubMed abstract: Two eye fields have been identified in the frontal lobes of primates: one is situated dorsomedially within the frontal cortex and will be referred to as the eye field within the dorsomedial frontal cortex (DMFC); the other resides dorsolaterally within the frontal cortex and is commonly referred to as the frontal eye field (FEF). This review documents the similarities and differences between these eye fields. Although the DMFC and FEF are both active during the execution of saccadic and smooth pursuit eye movements, the FEF is more dedicated to these functions. Lesions of DMFC minimally affect the production of most types of saccadic eye movements and have no effect on the execution of smooth pursuit eye movements. In contrast, lesions of the FEF produce deficits in generating saccades to briefly presented targets, in the production of saccades to two or more sequentially presented targets, in the selection of simultaneously presented targets, and in the execution of smooth pursuit eye movements. For the most part, these deficits are prevalent in both monkeys and humans. Single-unit recording experiments have shown that the DMFC contains neurons that mediate both limb and eye movements, whereas the FEF seems to be involved in the execution of eye movements only. Imaging experiments conducted on humans have corroborated these findings. A feature that distinguishes the DMFC from the FEF is that the DMFC contains a somatotopic map with eyes represented rostrally and hindlimbs represented caudally; the FEF has no such topography. Furthermore, experiments have revealed that the DMFC tends to contain a craniotopic (i.e., head-centered) code for the execution of saccadic eye movements, whereas the FEF contains a retinotopic (i.e., eye-centered) code for the elicitation of saccades. Imaging and unit recording data suggest that the DMFC is more involved in the learning of new tasks than is the FEF. Also with continued training on behavioural tasks the responsivity of the DMFC tends to drop. Accordingly, the DMFC is more involved in learning operations whereas the FEF is more specialized for the execution of saccadic and smooth pursuit eye movements.
Basal Ganglia
Blazquez, P., N. Fujii, J. Kojima, and A. M. Graybiel. “A Network Representation of Response Probability in the Striatum.” Neuron 33 (2002): 973-982.
PubMed abstract: The striatum of the basal ganglia is considered a key structure in the learning circuitry of the brain. To analyze neural signals that underlie striatal plasticity, we recorded from an identifiable class of striatal interneurons as macaque monkeys underwent training in a range of conditioning and non-associative learning paradigms, and recorded eyeblink electromyographs as the measure of behavioral response. We found that the responses of these striatal interneurons were modifiable under all training conditions and that their population responses were tightly correlated with the probability that a given stimulus would evoke a behavioral response. Such a network signal, proportional to current response probability, could be crucial to the learning and decision functions of the basal ganglia.
Fiorillo, C. D., P. N. Tobler, and W. Schultz. “Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons.” Science 299 (2003): 1898-1902.
PubMed abstract: Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P = 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior.
Graybiel, A. M. and Y. Kubota. “Understanding Corticobasal Ganglia Networks As Part of a Habit Formation System.” In Mental and Behavioral Dysfunction in Movement Disorders, by Bédard, M. A. et al. Totawa, N.J: Humana, 2003.
Graziano, M. S., C. S. Taylor, and T. Moore. “Complex Movements Evoked by Microstimulation of Precentral Cortex.” Neuron 34 (2002): 841-851.
PubMed abstract: Electrical microstimulation was used to study primary motor and premotor cortex in monkeys. Each stimulation train was 500 ms in duration, approximating the time scale of normal reaching and grasping movements and the time scale of the neuronal activity that normally accompanies movement. This stimulation on a behaviorally relevant time scale evoked coordinated, complex postures that involved many joints. For example, stimulation of one site caused the mouth to open and also caused the hand to shape into a grip posture and move to the mouth. Stimulation of this site always drove the joints toward this final posture, regardless of the direction of movement required to reach the posture. Stimulation of other cortical sites evoked different postures. Postures that involved the arm were arranged across cortex to form a map of hand positions around the body. This stimulation-evoked map encompassed both primary motor and the adjacent premotor cortex. We suggest that these regions fit together into a single map of the workspace around the body.
Graziano, M. S., C. S. Taylor, T. Moore and D. F. Cooke. “The Cortical Control of Movement Revisited.” Neuron 36 (2002): 349-62.
PubMed abstract: Recently, we found that electrical stimulation of motor cortex caused monkeys to make coordinated, complex movements. These evoked movements were arranged across the cortex in a map of spatial locations to which the hand moved. We suggest that some of the subdivisions previously described within primary motor and premotor cortex may represent different types of actions that monkeys tend to make in different regions of space. According to this view, primary and premotor cortex may fit together into a larger map of manual space.
Kandel, E. et al. “The Basal Ganglia.” Chap. 43 in Principles of Neuroscience. 2002.
———. Principles of Neuroscience. 2002, chap. 38, 42 and 43.
Kawagaoe, R., Y. Takikawa, and O. Hikosaka. “Expectation of Reward Modulates Cognitive Signals in the Basal Ganglia.” Nat. Neurosci. 1 (1998): 411-416.
PubMed abstract: Action is controlled by both motivation and cognition. The basal ganglia may be the site where these kinds of information meet. Using a memory-guided saccade task with an asymmetric reward schedule, we show that visual and memory responses of caudate neurons are modulated by expectation of reward so profoundly that a neuron’s preferred direction often changed with the change in the rewarded direction. The subsequent saccade to the target was earlier and faster for the rewarded direction. Our results indicate that the caudate contributes to the determination of oculomotor outputs by connecting motivational values (for example, expectation of reward) to visual information.
Wessberg, J., et al. “Real-Time Prediction of Hand Trajectory by Ensembles of Cortical Neurons in Primates.” Nature 408 (2000): 361-365.
PubMed abstract: Signals derived from the rat motor cortex can be used for controlling one-dimensional movements of a robot arm. It remains unknown, however, whether real-time processing of cortical signals can be employed to reproduce, in a robotic device, the kind of complex arm movements used by primates to reach objects in space. Here we recorded the simultaneous activity of large populations of neurons, distributed in the premotor, primary motor and posterior parietal cortical areas, as non-human primates performed two distinct motor tasks. Accurate real-time predictions of one- and three-dimensional arm movement trajectories were obtained by applying both linear and nonlinear algorithms to cortical neuronal ensemble activity recorded from each animal. In addition, cortically derived signals were successfully used for real-time control of robotic devices, both locally and through the Internet. These results suggest that long-term control of complex prosthetic robot arm movements can be achieved by simple real-time transformations of neuronal population signals derived from multiple cortical areas in primates.
Wichmann, T. and M. R. DeLong. “Functional and Pathophysiological Models of the Basal Ganglia”. Curr. Opin. Neurobiol. 6 (1996): 751-758.
PubMed abstract: Because of new data, anatomical and functional models of the basal ganglia in normal and pathological conditions (e.g. Parkinson’s and Huntington’s diseases) have recently come under greater scrutiny. An update of these models is clearly timely, taking into consideration not only changes in neuronal discharge rates, but also changes in the patterning and synchronization of neuronal discharge, the role of extrastriatal dopamine, and expanded intrinsic and input/output connections of these nuclei.
Cortical Plasticity
Pons, T. P., P. E. Garraghty, D. P. Friedman, and M. Mishkin. “Physiological Evidence for Serial Processing in Somatosensory Cortex.” Science 237 (1987): 417-442.
PubMed abstract: Removal of the representation of a specific body part in the postcentral cortex of the macaque resulted in the somatic deactivation of the corresponding body part in the second somatosensory area. In contrast, removal of the entire second somatosensory area had no grossly detectable effect on the somatic responsivity of neurons in the postcentral cortex. This direct electrophysiological evidence for serial cortical processing in somesthesia is similar to that found earlier for vision and, taken together with recent anatomical evidence, suggests that there is a common cortical plan for the processing of sensory information in the various sensory modalities.
Pons, T. P., P. E. Garraghty, A. K. Ommaya, J. H. Kaas, E. Taub, and M. Mishkin. “Massive Cortical Reorganization After Sensory Deafferentation in Adult Macaques.” Science 252 (1991): 1857-1860.
PubMed abstract: After limited sensory deafferentations in adult primates, somatosensory cortical maps reorganize over a distance of 1 to 2 millimeters mediolaterally, that is, in the dimension along which different body parts are represented. This amount of reorganization was considered to be an upper limit imposed by the size of the projection zones of individual thalamocortical axons, which typically also extend a mediolateral distance of 1 to 2 millimeters. However, after extensive long-term deafferentations in adult primates, changes in cortical maps were found to be an order of magnitude greater than those previously described. These results show the need for a reevaluation of both the upper limit of cortical reorganization in adult primates and the mechanisms responsible for it.
Sur, M. “Somatosensory cortex. Maps of Time and Space.” Nature 378 (1995): 13-14.
Wang, X., M. M. Merzenich, K. Sameshima, and W. M. Jenkins. “Remodelling of Hand Representation in Adult Cortex Determined by Timing of Tactile Stimulation.” Nature 378 (1995): 71-75.
PubMed abstract: The primate somatosensory cortex, which processes tactile stimuli, contains a topographic representation of the signals it receives, but the way in which such maps are maintained is poorly understood. Previous studies of cortical plasticity indicated that changes in cortical representation during learning arise largely as a result of hebbian synaptic change mechanisms. Here we show, using owl monkeys trained to respond to specific stimulus sequence events, that serial application of stimuli to the fingers results in changes to the neuronal response specificity and maps of the hand surfaces in the true primary somatosensory cortical field (S1 area 3b). In this representational remodelling stimuli applied asynchronously to the fingers resulted in these fingers being integrated in their representation, whereas fingers to which stimuli were applied asynchronously were segregated in their representation. Ventroposterior thalamus response maps derived in these monkeys were not equivalently reorganized. This representational plasticity appears to be cortical in origin.
