Fig 4. Membrane and threshold time constants influence temporal selectivity similarly.

(A-B) For rate encoding, the firing rate of the model neurons was limited by τ_m (A) and τ_θ (B), if either of them were too small. Short τ_m prevent integration, while short τ_θ lead to a threshold that quickly follows the input. (C-D) The limitation in firing rate by τ_m (C) and τ_θ (D) translates to a limitation of represented stimulus information. Only for short values of τ_m and τ_θ the lowpass shape gives way for a bandpass shape, which is a consequence of the decoding bin size chosen here (2ms): for small σ and low τ_m/τ_θ the responses to different stimuli will tend to fall in a small number of bins. (E) We extract the average σ that maximized MI for a combination of τ_m and τ_θ. The resulting dependence is monotonically in τ_m and τ_θ, consistent with a change in the σ edge of the lowpass relationship (Fig 3A). (F-G) For pattern encoding, the firing rate is limited analogously by τ_m (F) and τ_θ (G). (H-I) The value of σ that leads to highest MI shifts with both τ_m (H) and τ_θ (I), indicating a match between the membrane dynamics and the temporal scale of input patterns that can effectively be encoded. Larger σ values generate temporal patterns that are more distinguishable but the spikes are more dispersed in time,and both τ_m and τ_θ set the temporal limit in which the spikes can be integrated. (J) The best MI is achieved at different average σ across the range of τ_m and τ_θ, monotonically increasing for both parameters.