Computational protocol: Diverse coupling of neurons to populations in sensory cortex

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Protocol publication

[…] Spikes were detected and visually verified using the programs NDmanager and Neuroscope. Spike sorting involved an automated stage, performed using KlustaKwik, and a manual verification stage for which Klusters or KlustaViewa were used. Detailed analysis of coupling to population rate and LFP was performed only for units with isolation distance > 20 (see refs. ,). Units were selected and sorted blind to measures of population coupling and all other cellular parameters.Population rate (e.g. in ) was computed by accumulating all the detected spikes (both well-isolated units and multi-unit activity) with 1 ms resolution, and smoothing the resulting vector with a Gaussian of half-width 12 ms. The population rate used to compute the stPR for any individual unit did not include the spikes of that unit. The baseline level of each stPR (which reflects the mean population rate) was subtracted.For stLFP computations, raw extracellular signals were first digitally band-pass filtered offline between 0.1 and 200 Hz to isolate the local field potential. For units recorded on a particular shank, the LFP was taken from an adjacent shank (200 μm away), to avoid contaminating the stLFP by the spike waveform itself. The size of stLFP was taken as the ordinate value of the negative peak of the crosscorrelation in a 1 s interval around 0 lag. stLFPs were normalized similarly to stPRs (see below).The size of the stPR was quantified as the value of the spike-triggered population rate at 0 time lag. Thus, the population coupling of unit i is given by: ci=1∣∣fi∣∣∫fi(t)∑j≠i(fj(t)−μj)dt Here, f represents the smoothed firing rate of a neuron (Gaussian kernel of half width 12∕√2 ms), μ is its mean firing rate, and ||f|| represents its norm (i.e., the number of spikes fired). To compare the sizes of stPRs across recordings, they were normalized by the median size of the stPR of the shuffled data in each recording (see next paragraph).Spike shuffling was performed according to the previously described raster marginals model. In more detail, the recording was first divided into non-overlapping 1 ms bins. A binary matrix was then constructed with one column for each time bin and one row for each isolated unit as well as additional rows for the multiunit spiking on each shank. Each matrix element contained a 1 if the corresponding unit spiked in the corresponding time bin. To shuffle, random 2-by-2 submatrices were repeatedly chosen with each row and column of the submatrix containing a 0 and 1; the positions of 0s and 1s were then exchanged in the submatrix, which leaves the summed values of each row and column identical. As we have discussed previously, such a shuffling procedure produces in the limit a uniform sample from a distribution subject to the constraints on the mean firing rate and population rate distribution of the original data.To characterise the responses of individual cells to drifting grating stimuli, the response for each orientation was averaged across trials, contrasts and spatial frequencies, and the orientation with the highest value was taken as preferred. The spatial frequency which evoked the highest response along the preferred orientation was taken as the preferred spatial frequency. The orientation selectivity index (OSI) was computed as (Rpref−Rortho)/(Rpref+Rortho), where Rpref and Rortho are the responses in the preferred and orthogonal orientations. f1/f0 was taken as the ratio between the power of the average response around 2 Hz (which was the temporal frequency of the drifting grating stimuli) and the mean increase in the firing rate above the spontaneous level.In primate area V4, we measured the firing rate changes during saccade preparation for isolated single neurons. Spikes were counted during the interval between 0.5s after cue onset and the end of the post-cue period (i.e., start of the blank period), and were converted to firing rates for each trial based on the duration of that period. We compared firing rates from trials for which the cue indicated a saccade into the RF would be required and trials for which the cue indicated a saccade to an orthogonal location outside the RF would be required. Only spikes from correctly performed trials were considered for this analysis. Peak stPR size was measured identically to rodent electrophysiological recordings, and was computed from the continuous recording of the entire experimental session. […]

Pipeline specifications

Software tools NDManager, NeuroScope, Klusters
Application Clinical electrophysiology
Organisms Mus musculus, Macaca mulatta