ArticleHuman brain mapping2025
Higher-Order Triadic Interactions: Insights Into the Multiscale Network Organization in Schizophrenia.
Article in Human brain mapping, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Comparative Mapping of Functional and Structural Homologies in the Pig and Human Brain.bioRxiv : the preprint server for biology · 2026Article
- Astrocyte-mediated higher-order control of synaptic plasticity.Communications biology · 2026Article
- Microstructural Disruption of the Forceps Minor in Schizophrenia: A Potential Clinical Imaging Biomarker Using Translational DTI.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Complex biological systems, like the brain, exhibit intricate multiway and multiscale interactions that drive emergent behaviors. In psychiatry, neural processes extend beyond pairwise connectivity, involving higher-order interactions critical for understanding mental disorders. Conventional brain network studies focus on pairwise links, offering insights into basic connectivity but failing to capture the complexity of neural dysfunction in psychiatric conditions. This study seeks to address this gap by utilizing a matrix-based entropy functional for estimating total correlation, which serves as a mathematical framework for capturing multivariate information. We apply this framework to fMRI-ICA-derived multiscale brain networks, enabling the investigation of multivariate interaction patterns within the human brain across multiple scales. Additionally, this approach holds significant promise for psychiatric research on schizophrenia, offering a novel framework for investigating higher-order triadic brain network interactions associated with the disorder. By examining both triple interactions and the latent factors underlying the triadic relationships among intrinsic brain connectivity networks through tensor decomposition, our study presents a novel approach to understanding changes in higher-order brain networks in schizophrenia. This framework not only advances our understanding of complex brain functions but also opens new avenues for investigating the pathophysiology of schizophrenia, potentially informing more targeted diagnostic and therapeutic strategies. Moreover, this method for analyzing multiway interactions is applicable across signal analysis domains. In this study, we apply this approach to neural signals in schizophrenia, demonstrating its ability to reveal complex multiway interaction patterns and provide new insights into brain connectivity beyond traditional pairwise analyses in the context of brain disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.