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Journal of Neuroscience, Vol 8, 2938-2947, Copyright © 1988 by Society for Neuroscience
Primate motor cortex and free arm movements to visual targets in three- dimensional space. III. Positional gradients and population coding of movement direction from various movement origins
RE Kettner, AB Schwartz and AP Georgopoulos
Philip Bard Laboratories of Neurophysiology, Department of Neuroscience, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21205.
In one experiment, we studied the relations between the frequency of
discharge of 274 single cells in the arm area of the motor cortex of the
monkey and the actively maintained position of the hand in space. We found
that the frequency of discharge of 63.9% of the cells studied was a
multilinear function of the position of the hand in space according to the
following equation (multiple linear regression): d = f + fxsx + fysy +
fzsz, where d is the discharge rate of a single cell, f, fx, fy, fz are
regression coefficients, and sx, sy, sz are the coordinates of the position
of the hand. The equation above defines a positional gradient which implies
that the frequency of cell discharge will increase at a maximum rate when
the position of the hand changes along a certain direction; we call this
direction of orientation of the positional gradient, and the rate of change
in discharge rate along this orientation, the magnitude of the gradient.
The orientations of the positional gradients were distributed throughout
three-dimensional (3-D) space and their magnitudes differed among different
cells. In a different experiment, we studied the changes in activity of 289
cells in the arm area of the motor cortex when the monkeys made equal-
amplitude movements that started from different points in space, were in
the same direction, and traveled along parallel trajectories in 3-D space.
Four pairs of such movement directions (i.e., a total of 8 movement
directions) were studied for every cell, and the changes in cell activity
associated with movements within each pair were compared. We found that
these changes in cell activity did not differ statistically for 68.4% of
the movement pairs studied but did differ for the remaining 31.6%. The data
from the whole population of cells studied in this experiment were analyzed
using the population vector analysis described in the preceding paper
(Georgopoulos et al., 1988). Thus, 8 population vectors were calculated, 1
for each of the 8 movement directions studied. We found that the direction
of the population vector was close to the direction of the corresponding
movement. These results indicate that the population vector provides unique
information concerning the direction of the movement even when the point of
origin of the movement varies in 3-D space.
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