Cell-type specific projection patterns promote balanced activity in cortical microcircuits

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Abstract

Brain structure provides the stage on which activity unfolds. Models linking connectivity to dynamics have relied on probabilistic estimates of connectivity derived from paired electrophysiological recordings or single-neuron morphologies obtained by light microscopy (LM) studies. Only recently have electron microscopy (EM) data sets been processed and made available for volumes of cortex on the cubic millimeter scale, thereby exposing the actual connectivity of neurons. Here, we construct a population-based, layer-resolved connectivity map from EM data, taking into account the spatial scale of local cortical connectivity. We compare the obtained connectivity with a map based on an established LM data set. Simulating spiking neural networks constrained by the derived microcircuit architectures shows that both models allow for biologically plausible ongoing activity when synaptic currents caused by neurons outside the network model are adjusted for every population independently. However, differentially varying the external current onto excitatory and inhibitory populations uncovers that only the EM-based model robustly shows plausible dynamics. Our work confirms the long-standing hypothesis that a preference of excitatory neurons for inhibitory targets, not present in the LM-based model, promotes balanced activity in the cortical microcircuit.

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