Extended Data Fig. 9: Development of the recurrent connectivity structure for different balancing parameters. | Nature Neuroscience

Extended Data Fig. 9: Development of the recurrent connectivity structure for different balancing parameters.

From: Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks

Extended Data Fig. 9

a, Sum of input excitatory connections onto each excitatory neuron of the network, ordered from the strongest to the weakest connection sum. b, Sum of output excitatory connections per excitatory neuron, following the same order from panel a. c, Sum of input inhibitory connections onto each excitatory neuron of the network, following the same order from panel a. d, Total excitatory (red) and inhibitory (blue) currents onto a given excitatory neuron of the recurrent network during the learning period. e, Firing-rate of two excitatory neurons in the recurrent network at different time bins (of size 1 second). f, Average membrane potential (calculated in a 1-second time bin) of the two neurons from panel b. Each row shows plots of simulations with a different balancing term, α (Eq. (2)). Panels a-c in the middle row (α = 1.2) are the same as in Fig. 7f–h.

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