Spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Krishna Choudhary; Sven Berberich; Thomas T G Hahn; James M McFarland; Mayank R Mehta

doi:10.1038/s41467-024-47617-6

Spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Nat Commun. 2024 May 8;15(1):3542. doi: 10.1038/s41467-024-47617-6.

Authors

Krishna Choudhary^{1

2}, Sven Berberich^{3

4}, Thomas T G Hahn⁵, James M McFarland⁶, Mayank R Mehta^{7

8

9

10}

Affiliations

¹ Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, CA, USA.
² HRL Laboratories, Malibu, CA, USA.
³ Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
⁴ Department of Psychiatry and Psychotherapy, University Medical Center, Johannes Gutenberg University, Mainz, Germany.
⁵ Zentralinstitut fur Seelische Gesundheit, Mannheim, Germany.
⁶ Department of Physics, Brown University, Providence, RI, USA.
⁷ Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, CA, USA. mayankmehta@ucla.edu.
⁸ W. M. Keck Center for Neurophysics, University of California, Los Angeles, CA, USA. mayankmehta@ucla.edu.
⁹ Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, USA. mayankmehta@ucla.edu.
¹⁰ Departments of Neurology and Neurobiology, University of California, Los Angeles, Los Angeles, CA, USA. mayankmehta@ucla.edu.

Abstract

Understanding the functional connectivity between brain regions and its emergent dynamics is a central challenge. Here we present a theory-experiment hybrid approach involving iteration between a minimal computational model and in vivo electrophysiological measurements. Our model not only predicted spontaneous persistent activity (SPA) during Up-Down-State oscillations, but also inactivity (SPI), which has never been reported. These were confirmed in vivo in the membrane potential of neurons, especially from layer 3 of the medial and lateral entorhinal cortices. The data was then used to constrain two free parameters, yielding a unique, experimentally determined model for each neuron. Analytic and computational analysis of the model generated a dozen quantitative predictions about network dynamics, which were all confirmed in vivo to high accuracy. Our technique predicted functional connectivity; e. g. the recurrent excitation is stronger in the medial than lateral entorhinal cortex. This too was confirmed with connectomics data. This technique uncovers how differential cortico-entorhinal dialogue generates SPA and SPI, which could form an energetically efficient working-memory substrate and influence the consolidation of memories during sleep. More broadly, our procedure can reveal the functional connectivity of large networks and a theory of their emergent dynamics.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Computer Simulation
Connectome
Entorhinal Cortex* / physiology
Male
Membrane Potentials / physiology
Mice
Models, Neurological*
Nerve Net / physiology
Neural Pathways / physiology
Neurons* / physiology

Abstract

Publication types

MeSH terms

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