V1 multiplexing from an intracellular point of view

Gáspár M.E., Polack P-O., Golshani P., Lengyel M., and Orban G. (2019) Representational untangling by the firing rate nonlinearity in V1 simple cells. eLife. 8(e43625):1-30.

 

An important computational goal of the visual system is ‘representational untangling’ (RU): representing increasingly complex features of visual scenes in an easily decodable format. RU is typically assumed to be achieved in high-level visual cortices via several stages of cortical processing. Here we show, using a canonical population coding model, that RU of low-level orientation information is already performed at the first cortical stage of visual processing, but not before that, by a fundamental cellular-level property: the thresholded firing rate nonlinearity of simple cells in the primary visual cortex (V1). We identified specific, experimentally measurable parameters that determined the optimal firing threshold for RU and found that the thresholds of V1 simple cells extracted from in vivo recordings in awake behaving mice were near optimal. These results suggest that information re-formatting, rather than maximisation, may already be a relevant computational goal for the early visual system.

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Caption

(A) Intracellularly recorded ‘generator’ membrane potential trace of a V1 simple cell (black) with spikes clipped off. Orange vertical lines show spike times, orange horizontal line shows estimated firing threshold (uth). Red marks show response baseline (uDC), signal variance (uAC), and noise magnitude (σ) estimated from the generator potential responses to multiple cycles of the moving grating stimulus. (B) Illustration of estimating the FRNL from electrophysiological data. The firing rate of a cell as a function of the membrane potential (top panel, black line, gray shaded area shows s.e.m.) is obtained as the normalised ratio of the probability distributions of the generator potential at spike times and at all times (bottom panel, orange and gray histograms, respectively). A threshold-power-law function was fitted to the firing rate function and the threshold linear fit was used to estimate the firing threshold (vertical orange line). Threshold-power-law fits with different levels of the FRNL exponent (red traces, κ1=1, κ2=2) were largely consistent with the firing rate estimated from the data.

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