Important features of the kinetics and kinematics of human object grasping and manipulation have been characterized, providing significant insight into how the Central Nervous System controls the hand. However, the underlying neural mechanisms that regulate the activity of multiple hand muscles are not yet well understood. This gap in our understanding of hand control has significant clinical implications for rehabilitation of hand function following neurological injury such as stroke. In our previous work we focused on correlated neural input to hand muscles to quantify the neural bases of force coordination during object grasping. We found that correlated neural input is distributed in a muscle-pair specific fashion, i.e., the neural coupling between certain muscle pairs is stronger than that between other muscle pairs. However, within this distribution, the strength of neural coupling of given muscle pairs could be modulated to task conditions. Yet, these results were obtained from a relatively small number of muscles and limited range of task conditions (grip type and object center of mass).
The aim of the present study is to determine the neural mechanisms underlying a crucial aspect of hand control: the modulation of digit force direction. To attain this objective we will quantify the modulation of (a) EMG amplitude and (b) correlated neural input (coherence) of all muscles of the thumb, index and middle fingers as a function of digit force direction. Our working hypotheses are that (1) a force-direction dependent modulation of coherence between two muscles will occur as the relative force contribution of a given muscle to the modulation of fingertip force direction changes and (2) coherence modulation will occur within an invariant distribution of correlated neural input among hand muscle pairs. These hypotheses will be tested through one-digit force production tasks and multi-digit grasping tasks (Aim#1 and #2, respectively). The outcomes of our experiments will establish how motor commands controlling groups of hand muscles are modulated as a function of force direction and task constraints. Our data are expected to improve our understanding of the control of prehension, specifically the principles underlying fundamental mechanisms of synergistic control of hand muscles for object grasping and manipulation. Relevance to public health: We believe that this knowledge will be beneficial to rehabilitation and restoration of hand function as well as to the field of neuroprosthetics.
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