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Neural noise and spatio-temporal patterns of movement-related activity
in the supplementary motor area
Bruno Averbeck
University of Rochester
We analyzed the variability and coding capacity of simultaneously
recorded pairs of neurons in the primate supplementary motor area
(SMA). The coding performance was analyzed to determine whether the
temporal precision of spike arrival times and the interactions within
and between neurons improve the prediction of the upcoming movement
direction. There were three main findings in the analyses. First,
analysis of neuronal variability showed that the variance of spike
counts was smaller than its mean in many SMA neurons, suggesting that
a Poisson process is not a good model for the neural responses we
recorded. Second, we found that the correlation in spike count
variability between pairs of neurons was concentrated at low
frequencies (10 Hz). Third, we tested multiple decoding models that
differed in the temporal resolution and the correlations in the spike
trains which were utilized for decoding. The results showed that in
about 68% of neuron pairs, the arrival times of spikes at a resolution
between 66 and 40 ms carried more information than spike counts in a
200 ms bin. In addition, in 24% of neuron pairs, inclusion of within-
or between-neuron correlations in spike trains significantly improved
decoding accuracy. These results suggest that in some SMA neurons
there is more information in the spatio-temporal pattern of activity
than there is in the rate code of independent neurons.