Keck School of Medicine Wins $3.2 Million Grant

The National Institute of Mental Health is funding a massive brain study using artificial intelligence.

Updated on Oct. 26, 2026 in Autism

Keck School of Medicine Wins $3.2 Million Grant

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The National Institute of Mental Health awarded a $3.2 million grant to the Keck School of Medicine for a five-year study on psychiatric disorders. Researchers will use AI to analyze over 94,000 resting-state functional MRI scans from international participants.

Why it matters

This study aims to determine how various psychiatric disorders influence brain function and whether they align with three distinct families suggested by genetic data. By leveraging a massive global dataset, investigators hope to identify subtle markers of illness that have previously remained hidden.

The study will analyze 94,000 functional MRI scans collected from 257 sites across 27 countries. Participants in the dataset range from four to 95 years old.

The players

Keck School of Medicine

This institution is part of the University of Southern California and serves as the lead research site for this global mental health study.

National Institute of Mental Health

This federal agency is the primary funding body responsible for supporting research to improve the understanding of mental health and psychiatric disorders.

ENIGMA Consortium

This is an international alliance of scientists that works to understand brain structure and function using large-scale imaging data.

The details

The project will expand the existing ENIGMA Consortium by using a standardized pipeline across eight international research groups. Investigators plan to examine how various medications affect brain connectivity patterns while searching for potential links between different psychiatric conditions.

The $3.2 million grant award was announced on October 26, 2026.

The Big Picture

This project builds upon the established work of the ENIGMA Consortium by applying standardized AI pipelines to a vast array of global neuroimaging data. It marks a shift toward large-scale data synthesis to bridge gaps between clinical diagnoses and observable biological brain function.

This research may eventually lead to more accurate diagnostic tools or personalized treatment plans for people affected by various psychiatric conditions. By better understanding how medications impact brain connectivity, doctors could gain more precise data to guide long-term therapeutic decisions.

The takeaway

Large-scale collaborative research is increasingly necessary to decode the complexities of the human brain. Identifying biological markers for mental health conditions remains a priority that could fundamentally change how psychiatric disorders are categorized and treated in the future.