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Bayesian Mapping of the Striatal Microcircuit Reveals Robust Asymmetries in the Probabilities and Distances of Connections

Cinotti, François; Humphries, Mark D.

Bayesian Mapping of the Striatal Microcircuit Reveals Robust Asymmetries in the Probabilities and Distances of Connections Thumbnail


Authors

François Cinotti

MARK HUMPHRIES Mark.Humphries@nottingham.ac.uk
Professor of Computational Neuroscience



Abstract

The striatum’s complex microcircuit is made by connections within and between its D1- and D2-receptor expressing projection neurons and at least five species of interneuron. Precise knowledge of this circuit is likely essential to understanding striatum’s functional roles and its dysfunction in a wide range of movement and cognitive disorders. We introduce here a Bayesian approach to mapping neuron connectivity using intracellular recording data, which lets us simultaneously evaluate the probability of connection between neuron types, the strength of evidence for it, and its dependence on distance. Using it to synthesise a complete map of the mouse striatum, we find strong evidence for two asymmetries: a selective asymmetry of projection neuron connections, with D2 neurons connecting twice as densely to other projection neurons than do D1 neurons, but neither subtype preferentially connecting to another; and a length-scale asymmetry, with interneuron connection probabilities remaining non-negligible at more than twice the distance of projection neuron connections. We further show our Bayesian approach can evaluate evidence for wiring changes, using data from the developing striatum and a mouse model of Huntington’s disease. By quantifying the uncertainty in our knowledge of the microcircuit, our approach reveals a wide range of potential striatal wiring diagrams consistent with current data.

Citation

Cinotti, F., & Humphries, M. D. (2022). Bayesian Mapping of the Striatal Microcircuit Reveals Robust Asymmetries in the Probabilities and Distances of Connections. Journal of Neuroscience, 42(8), 1417-1435. https://doi.org/10.1523/JNEUROSCI.1487-21.2021

Journal Article Type Article
Acceptance Date Nov 27, 2021
Online Publication Date Dec 10, 2021
Publication Date Feb 23, 2022
Deposit Date Jan 18, 2022
Publicly Available Date Jan 21, 2022
Journal The Journal of neuroscience : the official journal of the Society for Neuroscience
Electronic ISSN 1529-2401
Publisher Society for Neuroscience
Peer Reviewed Peer Reviewed
Volume 42
Issue 8
Pages 1417-1435
DOI https://doi.org/10.1523/JNEUROSCI.1487-21.2021
Public URL https://nottingham-repository.worktribe.com/output/7276658
Publisher URL https://www.jneurosci.org/content/early/2021/12/09/JNEUROSCI.1487-21.2021/tab-article-info

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