Area of Research

Cognitive/Systems Neuroscience

Specialization

Control and learning of limb movement kinematics and dynamics in humans, using psychophysics and neuroimaging; underlying neural processing in animals.

RESEARCH THEME

We investigate the neural mechanisms underlying the control of voluntary movements in normal human subjects and patients with motor disorders. In particular we study the execution of aimed movements and examine the implicit and explicit aspects of learning necessary for movement accuracy. In some experiments we analyze limb kinematics (i.e. spatial trajectories) and dynamics (i.e. torques acting at the joints) and the associated changes in regional cerebral blood flow using PET. Important goals are to determine how neural mechanisms break down the computational task of controlling the moving limb and the roles of sensory processing in motor learning. We have shown that visuospatial information about target location is transformed into vectorial coordinates centered at the hand. Implicit learning mechanisms adaptively adjust the gain and reference frame of this transformation based on visuospatial errors. Movement vectors are transformed into muscle commands coded in an intrinsic coordinate system and requires learning internal models of inertial dynamics. This form of implicit learning occurs and is consolidated in parallel using proprioceptive information alone and distinct working memory systems. Current experiments focus on identifying the neural substrates of these processes through neuroimaging and network analyses. These indicate that the right parietal cortex plays a critical in the learning of new spatial reference frames.

In separate PET experiments we examine explicit learning of motor sequences. This utilizes different brain networks, primarily in the left hemisphere (notably the dorsolateral prefrontal, premotor and cingulate cortices). Our work is now focused on the role of motor learning in movement disorders due to central nervous system lesions. In normal subjects, for example, we find that different brain networks subserve the acquisition and retrieval processes during motor sequence learning. In Parkinson's disease, however, these networks function in abnormal ways and thus new networks are recruited to achieve learning.

SELECTED PUBLICATIONS

Ghilardi MF, Moisello C, Silvestri G, Ghez C, Krakauer JW. (2008) Learning of a sequential motor skill comprises explicit and implicit components that consolidate differently. J Neurophysiol. 2008 Dec 10.
                                                                
Ghez C, Scheidt RA, and H. Heijink (2007) Different Learned Coordinate Frames for Planning Trajectories and Final Positions in Reaching. J Neurophysiol 98: 3614-3626

Scheidt RA and  Ghez C.(2007) Separate Adaptive Mechanisms for Controlling Trajectory and Final Position in Reaching. J Neurophysiol 98:3600-3613

Feigin A, Ghilardi MF, Huang C, Ma Y, Carbor M, Guttman M, Paulsen JS, Ghez CP, Eidelberg D. (2006) Preclinical Huntington's disease: Compensatory brain responses during learning. Ann Neurol 59(1):53-9

Habeck C, Krakauer JW, Ghez C, Sackeim HA, Eidelberg D, Stern Y, Moeller JR. (2005) A new approach to spatial covariance modeling of functional brain imaging data: ordinal trend analysis. Neural Comput, 17(7):1602-45.

Krakauer J, Ghez C, Ghilardi, MF. (2005) Adaptation to Visuomotor Transformations: Consolidation, Interference, and Forgetting. J. Neurosci, 25(2): 473-478.