This proposal is a collaborative effort by a team of five motor systems groups at five institutions seeking to probe the mechanisms that underlie the brain's capacity for learning a new motor skill. The common thread for all groups is to focus on changes that occur within the primary motor cortex as a new skill is acquired. Changes in motor cortex will be characterized in relationship to critical input areas including premotor and parietal cortex and the role of subcortical circuits in learning will also be modeled. Both immediate and long-lasting changes of motor cortex representation will be investigated using a synthesis of molecular, cellular, systems and computational level of analysis. Project 1: Dr. Peter Strick (at the University of Pittsburgh) will combine flavoprotein optical imaging and single unit recording in monkey to characterize changes of activity in premotor and motor cortex as animals learn sequential behavior. Flavoprotein imaging allows for long-term cortical mapping over at least two years time, making it possible to look at dynamic alterations of cortical neuronal activity throughout the training period. Project 2: Dr. Scott Grafton (at University of California, Santa Barbara) will use functional MRI and transcranial magnetic stimulation in humans to study the neural substrates for off-line consolidation of three types of newly acquired motor skills: sequencing, visuomotor and dynamic adaptation. The tasks are similar to those in the other projects allowing for translation between monkey and human studies. Project 3: Dr. Emilio Bizzi (at MIT) will collaborate with experts in nanotechnology and conducting polymers at MIT to develop a new type of electrode based on fine wires of conducting polymers. With this he will perform chronic recordings of primary motor neurons in primates learning to move in novel dynamics. Project 4: Dr. James Houk (at Northwestern University) and Dr. Andrew Barto (at the University of Massachusetts at Amherst) will develop computational models of learning that are integral to the other projects of this PPG. These models will be used to explore critical behavioral and representational issues. Core A: Support for program administration and videoconferencing to achieve PPG integration. In addition, the core will support 3 satellite conferences on motor learning and mechanisms of cortical reorganization that are relevant for translational research. These interrelated projects, focusing on single anatomical substrate and common set of learning behaviors, should provide an integration of methodologies across multiple levels of analysis that are far beyond those achievable if each project were pursued separately. The collaborative effort can be expected to significantly advance our knowledge about mechanisms that support motor cortex plasticity.

Public Health Relevance

The proposed work is central to the problem of understanding the mechansims where practice leads to to reorganization of the hunnan motor system in the face of aging, neurodeneration, stroke or brain injury. Understanding these mechansims has an impact on the design of therapies directed at preserving function, developing compensator movements and ultimately, developing novel motor capacity.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Program Projects (P01)
Project #
5P01NS044393-10
Application #
8529621
Study Section
National Institute of Neurological Disorders and Stroke Initial Review Group (NSD)
Program Officer
Chen, Daofen
Project Start
2002-09-01
Project End
2014-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
10
Fiscal Year
2013
Total Cost
$1,089,219
Indirect Cost
$173,600
Name
University of California Santa Barbara
Department
Neurosciences
Type
Organized Research Units
DUNS #
094878394
City
Santa Barbara
State
CA
Country
United States
Zip Code
93106
Kahn, Ari E; Mattar, Marcelo G; Vettel, Jean M et al. (2017) Structural Pathways Supporting Swift Acquisition of New Visuomotor Skills. Cereb Cortex 27:173-184
Ramkumar, Pavan; Acuna, Daniel E; Berniker, Max et al. (2016) Chunking as the result of an efficiency computation trade-off. Nat Commun 7:12176
Ohbayashi, Machiko; Picard, Nathalie; Strick, Peter L (2016) Inactivation of the Dorsal Premotor Area Disrupts Internally Generated, But Not Visually Guided, Sequential Movements. J Neurosci 36:1971-6
Crossley, Matthew J; Horvitz, Jon C; Balsam, Peter D et al. (2016) Expanding the role of striatal cholinergic interneurons and the midbrain dopamine system in appetitive instrumental conditioning. J Neurophysiol 115:240-54
Helie, Sebastien; Roeder, Jessica L; Vucovich, Lauren et al. (2015) A neurocomputational model of automatic sequence production. J Cogn Neurosci 27:1412-26
Bassett, Danielle S; Yang, Muzhi; Wymbs, Nicholas F et al. (2015) Learning-induced autonomy of sensorimotor systems. Nat Neurosci 18:744-51
Smith, J David; Zakrzewski, Alexandria C; Herberger, Eric R et al. (2015) The time course of explicit and implicit categorization. Atten Percept Psychophys 77:2476-90
Glaser, Joshua I; Zamft, Bradley M; Church, George M et al. (2015) Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization. PLoS One 10:e0131593
Overduin, Simon A; d'Avella, Andrea; Roh, Jinsook et al. (2015) Representation of Muscle Synergies in the Primate Brain. J Neurosci 35:12615-24
Wymbs, Nicholas F; Grafton, Scott T (2015) The Human Motor System Supports Sequence-Specific Representations over Multiple Training-Dependent Timescales. Cereb Cortex 25:4213-25

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