A method for detecting the time course of correlation between single-unit activity and EMG during a behavioral task.

The chance that a change in excitability of one neuron leads to a change in excitability of another is likely to vary within a single volitional act. This temporal variability in functional connectivity is impossible to assess with standard analytical procedures to accurately that measure the correlation between such elements. This reports describes a technique designed to overcome this limitation by expressing a correlation measure calculated repeatedly in short epochs throughout a behavioral trial. The activity of two elements, a motor cortical neuron and a shoulder muscle, that might take place during a drawing task was first simulated so that the correlation could be manipulated. Various correlation algorithms (standard cross-correlation, spike-triggered average, impulse-response function, impulse-response surface) were tested with these data. Spike trains from a monkey's motor cortex and rectified EMG from its posterior deltoid muscle were compared using the same techniques and shown to have a correlation that changed in a characteristic manner throughout a task that required the monkey to draw a sinusoid.