Leveraging heterogeneity for neural computation with fading memory in layer 2/3 cortical microcircuits
Fig 7
Temporal tuning and linear memory capacity.
(a): distributions of intrinsic timescales (τint) in the quiet (Q, bottom) and active (A, top) states, for each of the different conditions. (b) Optimal stimulus resolution (Δt) that allows each circuit to perfectly track its input signal (see also red star markers in (a) and S4 Fig). (c): Fading memory functions for the different heterogeneity conditions, determined as the ability to reconstruct the input signal at different delays (k). Colours as in panel (d) below. (d): Total memory capacity, corresponding to the area under the curves in (c). Apart from the main conditions depicted in (c), pair-wise combinations among conditions are depicted in between. (e) Effects of synaptic heterogeneity on memory capacity, in conditions where the weight distributions are fixed, but re-shuffled such that the strongest weights are assigned to the connections among the input population (Shuffled1), from the input population to all excitatory neurons (Shuffled2), or from the input population to all neurons (Shuffled3). Results depicted in (b), (d) and (e) were gathered from 10 simulations per condition.