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Connecting Connectomes to Physiology

Alexander Borst and Christian Leibold
Journal of Neuroscience 17 May 2023, 43 (20) 3599-3610; DOI: https://doi.org/10.1523/JNEUROSCI.2208-22.2023
Alexander Borst
1Max-Planck Institute for Biological Intelligence, Department Circuits-Computation-Models, Martinsried, Germany
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Christian Leibold
2Fakultät für Biologie & Bernstein Center Freiburg, Albert-Ludwigs-Universität Freiburg, D-79104, Freiburg, Germany
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Abstract

With the advent of volumetric EM techniques, large connectomic datasets are being created, providing neuroscience researchers with knowledge about the full connectivity of neural circuits under study. This allows for numerical simulation of detailed, biophysical models of each neuron participating in the circuit. However, these models typically include a large number of parameters, and insight into which of these are essential for circuit function is not readily obtained. Here, we review two mathematical strategies for gaining insight into connectomics data: linear dynamical systems analysis and matrix reordering techniques. Such analytical treatment can allow us to make predictions about time constants of information processing and functional subunits in large networks.

SIGNIFICANCE STATEMENT This viewpoint provides a concise overview on how to extract important insights from Connectomics data by mathematical methods. First, it explains how new dynamics and new time constants can evolve, simply through connectivity between neurons. These new time-constants can be far longer than the intrinsic membrane time-constants of the individual neurons. Second, it summarizes how structural motifs in the circuit can be discovered. Specifically, there are tools to decide whether or not a circuit is strictly feed-forward or whether feed-back connections exist. Only by reordering connectivity matrices can such motifs be made visible.

  • connectomics
  • network dynamics
  • neural circuits

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The Journal of Neuroscience: 43 (20)
Journal of Neuroscience
Vol. 43, Issue 20
17 May 2023
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Connecting Connectomes to Physiology
Alexander Borst, Christian Leibold
Journal of Neuroscience 17 May 2023, 43 (20) 3599-3610; DOI: 10.1523/JNEUROSCI.2208-22.2023

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Connecting Connectomes to Physiology
Alexander Borst, Christian Leibold
Journal of Neuroscience 17 May 2023, 43 (20) 3599-3610; DOI: 10.1523/JNEUROSCI.2208-22.2023
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Keywords

  • connectomics
  • network dynamics
  • neural circuits

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