Graph theory identifies altered prefrontal microcircuit organization in Shank3 mice, a mouse Model of autism.

Authors

Rongsong Liu, Yan Zhang, Mallory Lai, Viyaleta Davydzenka, Casey Moffitt, Nathaniel England, Giovanni Barbera, Rong Chen, Da-Ting Lin, Yun Li

Published in

Cell reports. Volume 45. Issue 8. Pages 117852. Aug 14, 2026. Epub Aug 14, 2026.

Abstract

Graph theory provides unique tools to assess complex networks. It has been previously used with functional magnetic resonance imaging (fMRI) datasets to quantify macroscopic-scale connections among different brain regions, readily capturing brain network changes in subjects with Alzheimer's disease. Here, we apply graph theory to miniscope calcium imaging data recorded from the prefrontal cortex of freely behaving wild-type (WT) and Shank3^fx mice (a mouse model of autism) during social behavior tasks to compare microscopic-scale functional connections among individual neurons. We demonstrate that Shank3^fx mice display reduced population-level neural activity and a less-integrated and rigid prefrontal microcircuit. Furthermore, we employ machine learning to predict genotypes and behavioral differences between WT and Shank3^fx mice using graph-theoretic metrics extracted from prefrontal microcircuits. Our results indicate strong links between altered prefrontal microcircuits and social behavior deficits in the Shank3^fx mice, highlighting prefrontal microcircuitry as a potential diagnostic and therapeutic target for autism.

PMID:
42599799
Bibliographic data and abstract were imported from PubMed on 15 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.