How the central nervous system of vertebrates handles the staggering number of mechanical variables involved in even the simplest movement is one of the central problems in motor control. The experiments described in this proposal derive from the investigations conducted in intact frogs, spinalized frogs, rats and cats and are based on the hypothesis that the Central nervous System (CNS) constructs movements from a limited repertoire of motor primitives. Specifically, our goal is to investigate the way in which the CNS controls the monkey's hand movements and the variety of complex motor behaviors of the hand makes the hand an ideal model system for testing the validity of the modularity hypothesis. 1). In the monkey, we will investigate whether the muscles controlling hand and finger movements are constrained to act as units. To this end, we will use a computational analysis to identify these units. The analysis will allow us to extract a small set of muscle synergies from the large range of muscle activations generated during the movements of the hand and fingers. We will then investigate whether the flexible combinations of these synergies can account for the large number of different motor patterns produced by the animal. 2). With the aid of a specially designed glove (cyberglove) we will record the angular position and motion of the hand and individual fingers of the monkey. The kinematic data obtained with the help of the glove will make it possible to correlate the distinct hand shape typical of a variety of grips with combinations with synergies extracted during hand and finger movements. 3). Our third goal is to investigate whether the hand motor areas of the frontal lobe (especially M1) are related to the muscle synergies we have extracted with our computational procedure. To this end we will utilize three complementary approaches: A) partial inactivation (muscimol) of areas within the M1 hand region. B). Micro-stimulation and NMDA iontophoresis of small regions of M1. C). Recording the activity of antidromically identified cortico-spinal neurons and interneurons from selected areas of M1. These areas will be selected according to the results obtained with the technique of muscimol inactivation and/or microstimulation. The question here is whether or not the discharge of cortico-spinal cells represents the amplitude and time coefficients of the muscle synergies we have extracted.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Program Projects (P01)
Project #
5P01NS044393-04
Application #
7560603
Study Section
Special Emphasis Panel (ZNS1)
Project Start
Project End
Budget Start
2006-06-01
Budget End
2007-05-31
Support Year
4
Fiscal Year
2006
Total Cost
$185,008
Indirect Cost
Name
Northwestern University at Chicago
Department
Type
DUNS #
005436803
City
Chicago
State
IL
Country
United States
Zip Code
60611
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
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
Ramkumar, Pavan; Acuna, Daniel E; Berniker, Max et al. (2016) Chunking as the result of an efficiency computation trade-off. Nat Commun 7:12176
Acuna, Daniel E; Berniker, Max; Fernandes, Hugo L et al. (2015) Using psychophysics to ask if the brain samples or maximizes. J Vis 15:
Cieslak, Matthew; Ingham, Roger J; Ingham, Janis C et al. (2015) Anomalous white matter morphology in adults who stutter. J Speech Lang Hear Res 58:268-77
Smith, J David; Zakrzewski, Alexandria C; Johnston, Jennifer J R et al. (2015) Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta). J Exp Psychol Anim Learn Cogn 41:322-35
Cantwell, George; Crossley, Matthew J; Ashby, F Gregory (2015) Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory. Psychon Bull Rev 22:1598-613
Pasquereau, Benjamin; Turner, Robert S (2015) Dopamine neurons encode errors in predicting movement trigger occurrence. J Neurophysiol 113:1110-23
Lee, Taraz G; Grafton, Scott T (2015) Out of control: diminished prefrontal activity coincides with impaired motor performance due to choking under pressure. Neuroimage 105:145-55

Showing the most recent 10 out of 114 publications