Neural responses are typically characterized by computing the mean firing rate, but response variability can exist across trials. Many studies have examined the effect of a stimulus on the mean response, but few have examined the effect on response variability. We measured neural variability in 13 extracellularly recorded datasets and one intracellularly recorded dataset from seven areas spanning the four cortical lobes in monkeys and cats. In every case, stimulus onset caused a decline in neural variability. This occurred even when the stimulus produced little change in mean firing rate. The variability decline was observed in membrane potential recordings, in the spiking of individual neurons and in correlated spiking variability measured with implanted 96-electrode arrays. The variability decline was observed for all stimuli tested, regardless of whether the animal was awake, behaving or anaesthetized. This widespread variability decline suggests a rather general property of cortex, that its state is stabilized by an input.
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This work was supported by a Helen Hay Whitney postdoctoral fellowship (M.M.C.), Burroughs Welcome Fund Career Awards in the Biomedical Sciences (M.M.C. and K.V.S.), Gatsby Charitable Foundation (M.S. and B.M.Y.), US National Institutes of Health (NIH), National Institute of Neurological Disorders and Stroke Collaborative Research in Computational Neuroscience grant R01-NS054283 (K.V.S. and M.S.), the Michael Flynn Stanford Graduate Fellowship (J.P.C.), the Howard Hughes Medical Institute and NIH grant EY05603 (W.T.N., L.P.S., M.R.C. and G.S.C.), a Howard Hughes Medical Institute predoctoral fellowship (M.R.C.), NIH grant EY014924 (T.M. and K.M.A.), Sloan Foundation (T.M. and K.V.S.), Pew Charitable Trust (T.M.), NIH EY015958 and EY018894 (M.A.S.), NIH EY02017 and EY04440 (J.A.M.), NIH EY016774 (A.K.), NIH 1 EY13138-01 (D.C.B., A.M.C., P.H. and B.B.S.), NIH EY019288 (N.J.P.), the Pew Charitable Trust (N.J.P.), EY04726 (D.F.), US National Defense Science and Engineering Graduate Fellowships (B.M.Y. and G.S.), National Science Foundation Graduate Research Fellowships (B.M.Y. and G.S.), the Christopher and Dana Reeve Foundation (K.V.S. and S.I.R.), and the awards from Stanford Center for Integrated Systems, National Science Foundation Center for Neuromorphic Systems Engineering at Caltech, Office of Naval Research, NIH Director's Pioneer Award 1DP1OD006409 and Whitaker Foundation (K.V.S.).
A movie version of Figure 7a. Data are from PMd, and show the decline in across-trial variance after the onset of the stimulus (a reach target). The movie spans 750 ms, beginning 400 ms before stimulus onset and ending 350 ms after. The movie ends before the go cue is given. Each black dot shows the state of PMd on one trial. Fifteen randomly-chosen trials are shown. Dots turn blue for a brief moment at the time of stimulus onset. Note the subsequent drop in the variance of the dot locations (i.e., a drop in firing-rate variance). This feature of the response is at least as clear as the change in mean dot location (i.e., the change in mean firing rates). G20040123 dataset.
As in Supplementary Video 1, but more time is shown and the trajectory of the RT-outlier trial is now included (red). The movie spans ∼1500 ms. This time-span differs slightly across trials, as they have different go-cue and movement-onset times. At the time of the go cue, each dot turns green and further progress is halted. Progress resumes once all trials have passed the time of their respective go cues. This re-aligns the data to the go cue, much as is commonly done in PSTH's. Traces end at movement onset.
As in Supplementary Video 1, but for the G20040122 PMd dataset (that shown in Figure 7c).
As in Supplementary Video 2, but for the G20040122 PMd dataset (that shown in Figure 7c).
About this article
Biological Cybernetics (2018)