Neurons in primary motor cortex engaged during action observation

Abstract

Neurons in higher cortical areas appear to become active during action observation, either by mirroring observed actions (termed mirror neurons) or by eliciting mental rehearsal of observed motor acts. We report the existence of neurons in the primary motor cortex (M1), an area that is generally considered to initiate and guide movement performance, responding to viewed actions. Multielectrode recordings in monkeys performing or observing a well-learned step-tracking task showed that approximately half of the M1 neurons that were active when monkeys performed the task were also active when they observed the action being performed by a human. These 'view' neurons were spatially intermingled with 'do' neurons, which are active only during movement performance. Simultaneously recorded 'view' neurons comprised two groups: approximately 38% retained the same preferred direction (PD) and timing during performance and viewing, and the remainder (62%) changed their PDs and time lag during viewing as compared with performance. Nevertheless, population activity during viewing was sufficient to predict the direction and trajectory of viewed movements as action unfolded, although less accurately than during performance. 'View' neurons became less active and contained poorer representations of action when only subcomponents of the task were being viewed. M1 'view' neurons thus appear to reflect aspects of a learned movement when observed in others, and form part of a broadly engaged set of cortical areas routinely responding to learned behaviors. These findings suggest that viewing a learned action elicits replay of aspects of M1 activity needed to perform the observed action, and could additionally reflect processing related to understanding, learning or mentally rehearsing action.

Figure 1

Comparison of neural activity during performance and viewed action. Neurons in A, B show view task-related firing and directional tuning during action observation PD_(view)=4°±8° (bootstrap, p<0.001), PD_(view)=162°±6° (p<0.001). Left, perievent histograms of average firing across all trials aligned on the start of movement (time 0) showing do (black) and view (gray) task-related activity for example MI neurons in monkey A) CL, and B) LA. Histograms are placed at the respective target locations. Do and view task related firing for each of 8 directions, where a rightward movement is towards 0° (middle-right histogram), and an upward movement is towards 90° (top-center histogram). Center: circular plots showing directional tuning in do (black, above) and view (gray, below). Arrows plot observed peak firing for each direction. The firing rate scale is reported near the 90° line; the circular plot shows the best fit cosine function with (95% confidence limit) for the best fit model; the thick straight line marks the PD and the gray shadow indicates the 95% confidence interval. For (A) PD_(do)=342°±7° (bootstrap, p<0.001), (B) PD_(do)=135°±5° (p<0.001). Right, rasters showing firing rate for trials in each neuron's PD_(do) (up) and PD_(view) (down), aligned on the start of movement (0); the earlier triangles mark go cue; diamonds mark the end of movement. Note that firing in view task is reduced and more variable than in do task, but these neurons retain tuning and movement relationship across the two conditions.

Figure 2

Example of a MI neuron only active during movement (same format as Fig. 1): Note that this neuron is not modulated in the view condition (monkey LA).

Figure 3

Example of a view neuron with changed preferred direction between do and view conditions (same format as Fig. 1, monkey LA).

Figure 4

Prediction of movement direction from MI activity in view and do conditions. Each bar shows the predicted direction of movement based on the entire population (all, black), those that retain the same preferred direction (sPD; gray), and those that change their (dPD white) in view and do tasks for each of the three monkey (RN, CL, LA). The Bayesian classifier (BC) has relative values in the range [0, 1], where 1 = perfect classification. Groupings show the results of different classifier models. The do(do) model predicts movement from a classifier built from data in the do task using a new do task trial; the view(view) model predicts viewed direction from view related activity; do(view) predicts movement in do task from view related activity; view(do) predicts viewed direction using a model created from the do task activity. Horizontal line=chance level (12.5%).

Figure 5

MI activity for full and partial task conditions: A, B) histograms for a single neuron during (A) do task (black) compared to full view task (gray) (B) viewing only hand actions termed view device (black), or viewing only the screen, termed view screen (gray). View activity is markedly reduced and highly variable when only subcomponents of the task are present. The circular plots are the same format as Fig. 1. PD for each condition, marked with thick line: (A) do, sPD_(do)=54°±7°; full view, sPD_(view)=64°±8° (B); view device, PD_{(view device)}=356°±9°; view screen PD_{(view screen)}=49°±9°; (C) Number of tuned cells; (D) mean firing rate in full and partial task conditions¹. ¹ * =a significant difference in the firing rate during ‘do’ from that during the other three conditions, as well as view from do, view screen, view device (KW test, p<0.05).