Researchers detect early brain changes linked to future psychosis

By Published On: 9 December 2025
Researchers detect early brain changes linked to future psychosis

Researchers mapped brain network differences in people at high risk of psychosis, offering clues to how the illness begins.

The study used neuroimaging (detailed brain scans) to spot early, network-level changes in more than 3,000 people at varying levels of risk.

Those at clinical high risk, meaning people with early warning signs of psychosis, had less efficiently organised brain networks than healthy individuals.

The research was conducted by teams from the National University of Singapore and the Institute of Mental Health, Singapore, using data from 31 global sites.

Dr Siwei Liu isfirst author of the paper.

The researcher said: “Treating the brain as a complex network has allowed us to capture subtle but meaningful differences in communication pathways.

“These findings highlight the potential of brain imaging to detect early alterations and how early changes in network structure may contribute to the onset of psychotic symptoms.”

Using graph theory-based network analysis, a method that treats the brain as a network of nodes (regions) and edges (connections), the team mapped structural communication.

The study found that differences in frontal and temporal brain areas were linked to whether an individual developed psychosis later in life and how severe their symptoms were.

The researchers plan to explore brain network patterns further with the goal of identifying biomarkers that could support early detection and targeted interventio

Associate professor Juan Helen Zhou, corresponding author, said: “This study underscores that psychosis is not a sudden event but a progressive process reflected in the brain’s communication networks.

“Individuals at high clinical risk already show distinctive patterns of reduced integration and local efficiency.

“Understanding these patterns gives us an opportunity to identify at-risk individuals earlier and with greater precision. Ultimately, integrating such imaging-based insights into clinical assessment could improve prognosis and allow for timely and preventive therapies.”

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