The long-term goal of this research is to elucidate the dynamic brain mechanisms underlying spatio-temporally integrated motor and cognitive tasks using magetoencephalography (MEG). The tasks are designed to test hypotheses regarding temporal integration of information as the tasks are being carried out in space. We will focus on praxis, namely complex, purposeful motor actions, such as copying figures from visual templates and finding exist routes in mazes. These tasks are commonly used in clinical neurology underlying these tasks require planning across, and unfold within, space and time, and therefore, exemplify the theme of this program project research application. Data will be acquired using a state-of-the-art whole-head MEG instrument with 248 axial gradiometers. The hypotheses will be tested (a) that specific praxis tasks involve cooperative interactions of specific brain areas, especially in the parietal and frontal cortex, (b) that there is a partial overlap among the dynamic patterns of this activation across tasks, and (c) that this overlap corresponds to the common functional core shared by these tasks. The dynamic processing aspects of the core as well as signal analysis of individual MEG channels and their relations. A 64-processor Linux cluster will be used for these analyses. The results to be obtained will provide novel insights into how the brain deals with dynamic spatiotemporal processes and carries out purposeful eupractic motor actions. It is expected that these insights will lead, in turn, to the generation of specific hypotheses concerning altered neural mechanisms underlying constructional apraxia.
| 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
