Interactions among groups of neurons in primary motor cortex (MI) may convey information about motor behavior. We investigated the information carried by interactions in MI of macaque monkeys using a novel multielectrode array to record simultaneously from 12-16 neurons during an arm-reaching task. Pairs of simultaneously recorded cells revealed significant correlations in their trial-to-trial firing rate variation when estimated over broad (600 msec) time intervals. This covariation was only weakly related to the preferred directions of the individual MI neurons estimated from the firing rate and did not vary significantly with interelectrode distance. Most significantly, in a portion of cell pairs, correlation strength varied with the direction of the arm movement. We evaluated to what extent correlated activity provided additional information about movement direction beyond that available in single neuron firing rate. A multivariate statistical model successfully classified direction from single trials of neural data. However, classification was consistently better when correlations were incorporated into the model as compared to one in which neurons were treated as independent encoders. Information-theoretic analysis demonstrated that interactions caused by correlated activity carry additional information about movement direction beyond that based on the firing rates of independently acting neurons. These results also show that cortical representations incorporating higher order features of population activity would be richer than codes based solely on firing rate, if such information can exploited by the nervous system.

All models of self-motion from optical flow assume the instantaneous velocity field as input. We tested this assumption for human observers using random-dot displays that simulated translational and circular paths of movement by manipulating the lifetime and displacement of individual dots. For translational movement, observers were equally accurate in judging direction of heading from a "velocity field" with a two-frame dot life and a "direction field" in which the magnitudes of displacement were randomized while the radial pattern of directions was preserved, but at chance with a "speed field" in which the directions were randomized, preserving only magnitude. Accuracy declined with increasing noise in vector directions, but remained below 2.6 degrees with a 90 degrees noise envelope. Thus, the visual system uses the radial morphology of vector directions to determine translational heading and can tolerate large amounts of noise in this pattern. For circular movement, observers were equally accurate with a 2-frame "velocity field", 3-frame "acceleration" displays, and 2-frame and 3-frame "direction fields", consistent with the use of the pattern of vector directions to locate the center of rotation. The results indicate that successive independent velocity fields are sufficient for perception of translational and circular heading.

Classically, it has been hypothesized that reach-to-grasp movements arise from two discrete parietofrontal cortical networks. As part of these networks, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. Recent studies have shown that such a strict delineation of function along anatomical boundaries is unlikely, partly because reaching to different locations can alter distal hand kinematics and grasping different objects can affect kinematics of the proximal arm. Here, we used chronically implanted multielectrode arrays to record unit-spiking activity in both PMd and PMv simultaneously while rhesus macaques engaged in a reach-to-grasp task. Generalized linear models were used to predict the spiking activity of cells in both areas as a function of different kinematic parameters, as well as spike history. To account for the influence of reaching on hand kinematics and vice versa, we applied demixed principal components analysis to define kinematics synergies that maximized variance across either different object locations or grip types. We found that single cells in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that this classical division of reach and grasp in PMd and PMv, respectively, does not accurately reflect the encoding preferences of cells in those areas.