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

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

The structure of neural networks provides the stage on which their activity unfolds. Models of cerebral cortex linking connectivity to dynamics have primarily 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, 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 specifically adjusted for every population. However, differentially varying the external current onto excitatory and inhibitory populations reveals that only the EM-based model robustly exhibits biologically 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 cortical microcircuits.

Authors 4

1. Anno Christopher Kurth corresponding Aachen

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   RWTH Aachen University, Aachen, Germany

2. Jasper Albers corresponding Aachen

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   RWTH Aachen University, Aachen, Germany

3. Markus Diesmann Aachen Department of Physics Faculty 1 Department of Psychiatry, Psychotherapy and Psychosomatics School of Medicine

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany

   Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany

4. Sacha Jennifer van Albada

   Forschungszentrum Jülich · University of Cologne

   Affiliation as printed

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   Institute of Zoology, University of Cologne, Cologne, Germany