Linear Encoding of Muscle Activity in Primary Motor Cortex and
Cerebellum
Ben Townsend, Liam Paninski, and
Roger Lemon
J.
Neurophysiology 96: 2578-2592, 2006.
The activity of neurons in primary motor cortex (M1) and cerebellum is
known to correlate with extrinsic movement parameters, including hand
position and velocity. Relatively few studies have addressed the
encoding of intrinsic parameters, such as muscle activity. Here we
applied a generalized regression analysis to describe the relationship
of neurons in M1 and cerebellar dentate nucleus to electromyographic
(EMG) activity from hand and forearm muscles, during performance of
precision grip by macaque monkeys. We showed that cells in both M1 and
dentate encode muscle activity in a linear fashion, and that EMG
signals provide predictions of neural discharge that are equally
accurate to those from kinematic information under these task
conditions. Neural activity in M1 was significantly more correlated
with both EMG and kinematic signals than was activity in dentate
nucleus. Furthermore, the analysis enabled us to look at the temporal
properties of muscle encoding. Cells were broadly tuned to muscle
activity as a function of the lag between spiking and EMG and there
was considerable heterogeneity in the optimal delay among individual
neurons. However, a single lag (40 ms) was generally sufficient to
provide good fits. Finally, incorporating spike history effects in our
model offered no advantage in predicting novel spike trains,
reinforcing the simple nature of the muscle encoding that we observed
here.
Reprint | Liam Paninski's research page