Figure 6.

Double population scenario: learning in the output populations with minimal (τ_rec, A) model. (A) Mean firing rate of the output populations, black line for ℘^out₁ and gray line for ℘^out₂. Shaded area represents standard deviation and horizontal dotted gray lines show the two target firing rates (30 Hz for ℘^out₁, 5 Hz for ℘^out₂). (B) Symmetry measure applied on the connectivity of the output population. Color legend as in (B). Connectivity evolves differently in the two populations, leading to a bidirectional motif in ℘^out₁ and to a unidirectional motif in ℘^out₂. (C) Mean value of recovery time constant τ_rec. Black line: ℘^out₁ ∪ ℘^out₂ → ℘^out₁. Gray line: ℘^out₁ ∪ ℘^out₂ → ℘^out₂. We observe that the two populations develop different type of synapses, facilitating for ℘^out₁ and depressing for ℘^out₂. (D) Corresponding histograms of the recovery time constant at the end of the simulation. Light gray: ℘^out₂ → ℘^out₂, medium gray: ℘^out₁ → ℘^out₂, dark gray: ℘^out₁ → ℘^out₁, black: ℘^out₂ → ℘^out₁. The panels show that the achievement of the tasks and the differentiation of the synapses is still possible with this minimal model.