Fig. 1.
Local and global network setup. A: a local population consists of externally driven, recurrently coupled 800 excitatory and 200 inhibitory neurons. Recurrent synapses in the inhibitory subpopulation, instantiated with coupling probability plocii, generate a γ-rhythm. This rhythm is imposed onto the excitatory subpopulation via connections from the inhibitory to the excitatory subpopulation with probability plocie. B: such a local population generates a stable γ-population-rhythm, as seen in the exemplary time courses of activity of the inhibitory (gray) and excitatory (black) subpopulation (top). Inhibitory neurons fire at markedly higher rates than their excitatory counterparts, as shown in the mean firing rate histogram (bottom). C: 4 local populations are interconnected to form the 2-layered global setup. The 1st layer populations A and B are driven by Poissonian spike trains representing 2 different stimuli SA and SB. Both 1st layer populations project to both 2nd layer populations C and D, whereas A and C, respectively B and D, are connected with the same coupling probability pAC = pBD. The strength of cross talk between A and D, respectively B and C, is regulated by the mixing parameter μ, i.e., pAD = pBC = μ·pAC with μ [0,1]. The value of μ determines the relative preference of SA and SB to C and D, i.e., if 0 < μ < 1, SB (SA) will be a nonpreferred stimulus for C (D). Intralayer lateral interactions differ between the 2 layers and depend on connection probabilities pABei, pCDie, and pCDii. In the 2nd layer, populations C and D are assumed to act as similar computational units due to the partly overlapping receptive fields, thus the lateral connectivity is the same as within local populations (see A) at lower strength (pCDie < plocie and pCDii < plocii). Attention is introduced as an additional input to 1 1st layer population (here A). All coupling probabilities and model parameters can be found in Table 1. D: simplified layout diagram of the full setup depicted in C used in Fig. 2.