# Graph Theory Identifies Autistic Patterns in the Prefrontal Circuit of 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

PMC · DOI: 10.21203/rs.3.rs-8725198/v1 · Research Square · 2026-02-03

## TL;DR

This study uses graph theory to identify differences in prefrontal brain circuits in a mouse model of autism, linking these changes to social behavior deficits.

## Contribution

The study applies graph theory to microscopic neural networks in an autism mouse model, revealing prefrontal microcircuit alterations linked to social behavior.

## Key findings

- Shank3fx mice showed reduced neural activity and less-integrated prefrontal microcircuits during social behavior.
- Graph-theoretic metrics from prefrontal microcircuits predicted genotype and social behavior differences.
- Altered prefrontal microcircuits are strongly linked to social behavior deficits in the autism mouse model.

## Abstract

As a well-developed branch of mathematics, graph theory provides unique tools to quantifiably assess various properties of complex networks. Applied to brain circuits, network-level analyses can illustrate disruptions to brain organization that yield both mechanistic and diagnostic insights. Previously, graph theory has been used with functional magnetic resonance imaging datasets to quantify connections among different brain regions, readily capturing the macroscopic-scaled differences in brain networks between healthy and Alzheimer’s subjects. Here, we applied graph theory on the microscopic scale, using miniscope-based calcium imaging from the freely behaving wild type (WT) and Shank3fx mice (a mouse model of autism), and compared functional connections among individual neurons in the prefrontal microcircuits during social behavior. We demonstrated that Shank3fx mice displayed reduced neural activity, less-integrated network, and fewer network changes in the prefrontal microcircuits between the presence and absence of social targets. Furthermore, we employed machine learning to test whether graph-theoretic metrics extracted from the prefrontal microcircuits could be predictive of genotype and genotype-associated social behavior difference between Shank3fx and WT mice. Our results indicate a strong link between altered prefrontal microcircuits and social behavior deficits in an autism mouse model, highlighting prefrontal microcircuitry as a potential diagnostic and therapeutic target for autism.

## Linked entities

- **Genes:** SHANK3 (SH3 and multiple ankyrin repeat domains 3) [NCBI Gene 85358]
- **Diseases:** autism (MONDO:0005260)
- **Species:** Mus musculus (taxon 10090)

## Full-text entities

- **Genes:** Shank3 (SH3 and multiple ankyrin repeat domains 3) [NCBI Gene 58234] {aka Spank-2, proSAP2}
- **Diseases:** Autism (MESH:D001321), Alzheimer's (MESH:D000544)
- **Chemicals:** calcium (MESH:D002118)
- **Species:** Mus musculus (house mouse, species) [taxon 10090]

## Full text

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## Figures

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## References

50 references — full list in the complete paper: https://tomesphere.com/paper/PMC12889843/full.md

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Source: https://tomesphere.com/paper/PMC12889843