Figure 5
Reciprocity as a function of \(\tau\), FR and the type of transition graph. (a) Transition graph for solving the s-task with \(\tau = 7\). Blue and red lines represent transitions gated by \(s_{1}\) and \(s_{2}\), respectively. (b) Random transition graph. Nodes (network states) may receive different number of incoming connections. There are 24 nodes that are gated by both stimuli. (c) Reciprocity for T + F networks, with \(f_{r} = 1\), as a function of \(\tau\) and target FR. Reciprocity changes from slightly negative to slightly positive as \(\tau\) increases. For \(\tau = 7\), reciprocity is maximized around target FR = 0.5 spikes/time step and decreases for lower and higher values of target FR. (d) F networks with \(f_{r} = 1\) shows increasing positive reciprocity as \(\tau\) increases, maximized at target FR = 0.5 spikes/time step. (e) When the number of neurons is higher (\(f_{r} = 4\)), T + F networks show positive reciprocity that is minimal around target FR = 0.5, and increases towards higher and lower target FR, reaching the highest reciprocity values among all networks screened. (f) Reciprocity of F networks turns increasingly negative as \(\tau\) increases, reaching the lowest reciprocity among all networks screened, around target FR = 0.5 spikes/time step. For all panels, 30 networks were constructed for each \(\tau\) and target FR combination. Normalized means (mean/SD) are shown. Positive and negative reciprocity values were mapped separately to colours red and blue, respectively. Red tones go from 0 reciprocity (white) to maximal positive reciprocity (pure red). Blue tones go from 0 reciprocity (white) to maximal (in absolute value) negative reciprocity (pure blue). All random graphs were constructed with \(f_{bc} = 0.5\). Graphs were plotted with the Force-directed layout.
