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bioRxiv · 10.1101/2025.06.17.660119

Column-Like Subnetwork Reconstruction in Motor Cortex from Graph-Based 3D High-Density Two-Photon Calcium Imaging

Aymard, P.·Boffi, J. C.·Asari, H.·Prevedel, R.·Holcman, D.
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Abstract

How precise 3D interactions among cortical neurons underlie layer-specific computations remains elusive. We developed a graph-framework to infer functional connectivity from fast volumetric two-photon Ca2+ imaging in the awake mouse primary motor cortex. By converting deconvolved traces into binary spike trains, removing population bursts, and applying an adaptive, layer-specific statistical threshold, we reconstructed a directed, weighted network of [~]1,000 neurons. Decomposition into strongly connected components revealed [~]10-cell subnetworks, predominantly in layer II/III but often bridging to layer Va. Across six 20-min recordings, we found that (1) layer II/III dominates connectivity, (2) feedback (Va[->]II/III) links are more numerous and stronger than the feed-forward (II/III[->]Va) ones, and (3) information flows in [≤] 6 synapses. We uncovered seven geometrical and dynamical motifs--ranging from compact columns to elongated diagonals--each with characteristic event sizes and durations. These findings reveal diverse, column-like microcircuits in M1 with a net ascending flow, suggesting that such subnetworks form elemental processing modules for motor control.

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Aymard, P., Boffi, J. C., Asari, H., Prevedel, R., Holcman, D.. 2025-06-17. Column-Like Subnetwork Reconstruction in Motor Cortex from Graph-Based 3D High-Density Two-Photon Calcium Imaging. https://doi.org/10.1101/2025.06.17.660119

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