The goal of this project is to understand how ensembles of interacting neurons in multiple motor cortical areas coordinate proximal and distal components in reaching and reach-to-grasp behavior. Psychophysical research has determined that reaching and prehensile movements are characterized by distinct coordination patterns among the arm, wrist, and fingers and has postulated the existence of coordination mechanisms that temporally couple these segments of the upper limb. However, the neural substrate underlying these temporal coordination patterns is unknown. We have recently discovered the existence of travelling wave activity as recorded from local field potential (LFP) recordings in non-human primates that propagates horizontally across primary motor (MI), dorsal premotor (PMd), and ventral premotor (PMv) cortices. These propagating waves are mediated by oscillatory activity in the beta frequency range (i.e. 15-40 Hz) and propagate primarily along a rostro-caudal axis in MI and PMv and a medio-lateral axis in PMd. Given the gradient in proximal and distal movement representations along these axes in these areas, our working hypothesis is that these waves reflect the coordination of proximal and distal components of the upper limb during reaching and prehension. In particular, rostral MI, caudal PMv, and medial PMd are associated with proximal limb segments of the shoulder and elbow and caudal, rostral, and lateral regions of MI, PMv, and PMd, respectively are associated with distal limb segments of the wrist and fingers. Therefore, the proximal-to-distal sequencing of the upper arm that characterizes many behaviors including the accelerative phase of reach-to-grasp is signaled by wave propagation in the rostral-to-caudal direction in MI, caudal-to-rostral direction in PMv, and medial-to-lateral direction in PMd. In contrast, distal-to-proximal coordination patterns should be associated with wave propagation in the opposite direction. We will 1) determine whether properties of these propagating waves correlate with distinct coordination patterns of the shoulder, elbow, wrist, and fingers during reach and reach- to-grasp behaviors;2) establish a link between these wave properties and behavior via behavioral constraints and perturbations 3) determine whether multiple single unit activity reflects spatio-temporal patterns consistent with the LFP waves recorded on the same electrode arrays. To accomplish this, high-density electrode arrays will be chronically implanted in MI, PMv, and PMd from which 100s of single units and local field potentials will be simultaneously recorded while monkeys reach for and grasp objects of different sizes, shapes, and orientations in different three-dimensional locations. A digital optical tracking system using a set of ten infrared cameras will monitor the kinematics of the arm and hand during reach-to-grasp behavior and EMG signals will measure activity from arm, wrist, and extrinsic finger muscles. A set of classical and novel computational methods will be employed to characterize the dynamics of wave activity measured using LFPs and multiple single units.

Public Health Relevance

Coordinated reaching and grasping is a ubiquitous feature of human behavior that traces its evolutionary roots to primate foraging for food in arboreal environments and has allowed for the development of more complex actions including tool use. The proposed project will enhance our understanding of the cortical basis of these coordinated behaviors which may lead to more effective rehabilitative treatments for motor disabled patients with cortical damage due to stroke or injury. This work also has direct relevance towards the development of a neuro-motor prosthesis by which spinal cord-damaged or ALS patients may be able to control and temporally coordinate reach and grasp components of artificial devices by activating ensembles of motor cortical neurons.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Sensorimotor Integration Study Section (SMI)
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Chen, Daofen
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University of Chicago
Schools of Medicine
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Dickey, Adam S; Amit, Yali; Hatsopoulos, Nicholas G (2013) Heterogeneous neural coding of corrective movements in motor cortex. Front Neural Circuits 7:51
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Wu, Wei; Kulkarni, Jayant E; Hatsopoulos, Nicholas G et al. (2009) Neural decoding of hand motion using a linear state-space model with hidden states. IEEE Trans Neural Syst Rehabil Eng 17:370-8

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