This PPG proposal describes a collaborative effort by five distinguished motor systems groups at five prominent institutions. We will probe the brain's remarkable capacity for the Integration of Motor Programs Across Space and Time. Dr. Scott Grafton, at Dartmouth College, will characterize the neural substrates for the on-line adjustment of errors, for adaptation to persistent perturbations and for skill learning in humans, using functional MRI and transcranial magnetic stimulation. Dr. Emilio Bizzi, at MIT, will develop a new perspective on how the motor cortex solves the problem of transforming a planned hand movement into the intricate set of motor commands needed to carry out this task. Dr. Peter Strick, at the University of Pittsburgh, will characterize how sequences of movements are merged together and adjusted on-line to create skilled actions, using microelectrode recording in non-human primates and 2DG labeling of activity in the motor areas. Dr. James Houk, at Northwestern University, will characterize the regulatory actions of subcortical loops through the basal ganglia and cerebellum in each of the above tasks, using paired microelectrode recordings from subcortical neurons and the cortical neurons to which they project. Dr. Andy Barto, at the University of Massachusetts at Amherst, will explore computation models of each of the motor tasks. Core A support for videoconferencing and administration will facilitate strategic collaborations between the investigators at different institutions, and a Collaborative Core B will fund collaborations between two or more of the PIs to facilitate our ability to compare neurophysiologic data spanning a broad range of both spatial and temporal resolution. The support of these interrelated projects should yield results beyond those achievable if each project were pursued separately, and can be expected to significantly advance our knowledge about how motor programs are integrated across space and time.
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 |
Showing the most recent 10 out of 114 publications