Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina
Fig 8
Contrast-dependent filter changes in a model with spike-timing dynamics.
(A) Layout of the model. The stimulus feeds into a linear-nonlinear model, resulting in a firing rate, from which spikes are obtained by a Poisson process. Individual spikes are then shifted in time (as indicated by the red arrows), with the size of the shift depending on the activation level, which is given by the firing rate. (B) STAs obtained from model simulations for low and high contrast. (C) Eigenvalue spectrum obtained by STC analysis for high and low contrast, with the two most significant eigenvalues marked by green and light blue. (D) Scatter plot of spike-triggered stimuli for high-contrast stimulation of the model, projected onto k1 and k2. For clarity, only 0.2% of all analyzed spikes are shown in this plot. The inset shows the features k1 (green) and k2 (light blue), corresponding to the eigenvalues of the same color shown in (C). (E) Same as (D), but for low-contrast stimulation. (F) STA fits with features obtained from high-contrast STC analysis. Fit of high-contrast STA (i) and low-contrast STA (ii) as well as corresponding coefficients of determination (iii) and weights obtained for the two features (iv). (G) Same as (F), using the low-contrast-derived features.