Summary: Researchers reveal that reduced dynamic brain flexibility, or “flattened” network dynamics, not only distinguishes psychiatric patients from healthy controls, but tracks individual symptom fingerprints far more accurately than standard clinical diagnostic labels. This work provides compelling support for personalized, biology-informed frameworks in clinical neuroscience.
Key Facts
- Flattened Network Dynamics: Individuals with psychiatric conditions showed marked reductions in functional network flexibility, meaning their brain networks were less capable of shifting between distinct reconfigurations across varying cognitive demands.
- Symptom Fingerprints vs. Diagnostic Labels: Reconfiguration patterns in brain network dynamics correlated significantly more strongly with personalized “symptom fingerprints”, multidimensional behavioral, cognitive, and clinical profiles, than with traditional categorical diagnoses (e.g., depression vs. anxiety).
- Transdiagnostic Cohort Structure: The investigation evaluated 219 individuals across 11 different diagnostic categories, supporting the NIMH Research Domain Criteria (RDoC) effort to map mental health on a spectrum of biological and behavioral traits.
- Six Cognitive State Maps: By acquiring fMRI during resting state and multiple active tasks, the team mapped how brain networks dynamically reconfigure in real time across differing mental states rather than relying on static resting snapshots.
- Personalized Biomarkers: The findings establish time-varying network dynamics as a viable neurobiological biomarker for distinguishing clinical populations and developing targeted, individual-level interventions.
Source: Rutgers University
Individuals with psychiatric conditions show reduced flexibility in their brain network dynamics, according to a new Rutgers study.
The human brain is organized into networks that can adaptively shift and reorganize to meet ever-changing cognitive and emotional demands. This flexible reconfiguration of brain networks over time supports our ability to regulate our thoughts and behavior.
Disruptions in the brain’s dynamic processes are thought to play an important role in psychiatric illness. However, it remains unclear how differences in brain network dynamics relate to the wide range of symptoms seen across mental health conditions.
The study, published in Nature Communications, was led by Carrisa Cocuzza, a postdoctoral fellow, and Avram Holmes, an associate professor of psychiatry at Robert Wood Johnson Medical School and core faculty member of the Center for Advanced Human Brain Imaging Research within the Rutgers Brain Health Institute.
The researchers used a large, transdiagnostic dataset of 219 people that included individuals with 11 psychiatric diagnoses, alongside extensive behavioral, cognitive and clinical assessments.
Participants underwent magnetic resonance imaging scans both at rest and while performing tasks, allowing the researchers to examine how brain connectivity patterns changed across six cognitive states.
Using these data, team members characterized how brain networks reconfigure over time and identified individual “symptom fingerprints” by grouping behavioral and clinical measures into personalized profiles.
The researchers found individuals with psychiatric conditions showed reduced flexibility in their brain network dynamics.
“Their brain networks were less able to shift between different configurations across cognitive states compared to healthy individuals,” Cocuzza said.
These flattened dynamics were useful for distinguishing between patients and healthy participants as well as for identifying specific diagnostic categories.
“This work addresses a central challenge in clinical neuroscience, linking changes in brain function to the diverse symptoms experienced across psychiatric disorders,” Holmes said
Critically, patterns of brain network dynamics were more strongly related to individuals’ symptom fingerprints than to traditional diagnostic labels, suggesting that dynamic features of brain function may provide a more precise way of understanding mental illness, capturing how symptoms manifest in each individual rather than simply whether a diagnosis is present.
“The findings indicate that impairments in time-varying brain processes may underlie differences in cognitive and behavioral functioning across individuals,” Holmes added. “By showing that brain network dynamics track symptom variation across diagnostic boundaries, the study supports a shift toward more personalized, biology-informed models of mental health.”
Future research will build on these findings to further explore how brain network dynamics change over time and with intervention, to develop more precise, individualized approaches for assessing and supporting mental health.
Key Questions Answered:
A: Healthy brains continually alter their communication pathways depending on whether a person is resting, solving a problem, or managing emotions. Reduced flexibility, or “flattened” network dynamics, means the brain’s functional networks remain overly rigid or stuck in similar configurations regardless of changing cognitive states and environmental demands.
A: Traditional diagnoses often group patients by broad clinical labels that contain vast individual differences. A symptom fingerprint combines detailed behavioral, cognitive, and clinical measurements into a personalized profile. The Rutgers study showed that brain network dynamics align much closer to these individualized symptom profiles than to categorical diagnostic names.
A: By establishing that dynamic brain flexibility tracks symptom variation across diagnostic lines, this research supports a shift toward precision psychiatry. Future therapies and neuromodulation treatments can be tailored to target specific network dynamics and monitor how interventions restore neural flexibility at the individual level.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- Journal paper reviewed in full.
- Additional context added by our staff.
About this psychopharmacology and eating disorder research news
Author: Tongyue Zhang
Source: Rutgers
Contact: Tongyue Zhang – Rutgers
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease” by Carrisa V. Cocuzza, Sidhant Chopra, Ashlea Segal, Loïc Labache, Rowena Chin, Kaley Joss & Avram J. Holmes. Nature Communications
DOI:10.1038/s41467-026-75585-6
Abstract
Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease
The network organization of the human brain dynamically reconfigures in response to changing environmental demands, an adaptive process that may be disrupted in a symptom-relevant manner across psychiatric illnesses.
Here, in a transdiagnostic sample of participants with (n = 134) and without (n = 85) psychiatric diagnoses, functional connectomes from intrinsic (resting-state) and task-evoked fMRI were decomposed to identify constraints on brain network dynamics across six cognitive states.
Hierarchical clustering of 110 clinical, behavioral, and cognitive measures identified participant-specific symptom profiles, revealing four core dimensions of functioning: internalizing, externalizing, cognitive, and social/reward.
Brain network dynamics were flattened across cognitive states in individuals with psychiatric illness and could be used to accurately separate dimensional symptom profiles more robustly than both case/control status and primary diagnostic grouping. A key role of inhibitory cognitive control and frontoparietal network interactions was uncovered through systematic model comparison.
We provide evidence that brain network dynamics can accurately differentiate the extent that psychiatrically-relevant dimensions of functioning are exhibited across health and disease.
