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Mathematically, these distributions are described by the formula: P i) ≈ ci- γ where P i) is the frequency of nodes with exactly i connections or sets with exactly i members, γ is a parameter which typically assumes values between 1 and 3, and c is a normalization constant.
The third term, the double summation, represents the influence of other neurons on (v_{ij}), which occurs via the intrasegmental ((k = i)) and intersegmental ((k neq i)) connections.
For attractor dynamics to emerge the strength of E and I connections are set to depend on the relative locations of neurons in network space.
Interestingly, in addition we find that addition of I–I connections causes an overall increase in the frequency of gamma oscillations (see Figure 7D I).
To address it we have simulated networks with the suggested stochastic connectivity scaled and a fixed synaptic weight for each synapse whose value depends on gE and gI for E and I connections respectively.
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