This brain graph maps connections between brain regions, formed by white matter pathways that carry signals across the brain. It highlights the connections that differ in bipolar disorder, particularly in networks involved in emotion regulation, reward processing, attention, and self-reflection.
Photo Credit: Stevens INI
Scientific Frontline: Extended "At a Glance" Summary: Bipolar Disorder and Brain Network Connectivity
The Core Concept: Researchers have mapped subtle but widespread differences in the brain’s white matter communication pathways among individuals with bipolar disorder. These structural variations correlate with illness severity, treatment exposure, and specific clinical features like episode frequency and age of onset.
Key Distinction/Mechanism: Rather than focusing solely on isolated brain regions or gray matter, this study utilizes graph theory and diffusion MRI to analyze the brain as an interconnected transportation system. In bipolar disorder, this network is less densely connected and less efficient, relying more heavily on key "hub" regions with information taking longer, less direct routes.
Major Frameworks/Components:
- Diffusion MRI: An advanced imaging technique used to map the structural neural pathways (white matter) that facilitate communication between brain regions.
- Graph Theory: A mathematical approach that models the brain as nodes (regions) and routes (connections) to estimate the efficiency of information exchange.
- Fronto-Limbic Circuits: Pathways critical for emotion regulation, which showed altered connectivity based on manic episode frequency and age of onset.
- Basal Ganglia Pathways: Circuits involved in motivation and reward processing, which also demonstrated network alterations.
- Default Mode and Salience Networks: Systems crucial for internal thought and prioritizing relevant information, which were significantly impacted.
Branch of Science: Neurobiology, Psychiatry, Computational Neuroscience.
Future Application: The framework established by this global, cross-sectional mapping paves the way for longitudinal studies to track patients over time. Ultimately, these biologically grounded markers could allow clinicians to predict illness trajectories, tailor personalized medical interventions, and separate the neurobiological effects of bipolar disorder from the secondary effects of prescribed medications.
Why It Matters: Bipolar disorder arises from complex brain circuits rather than isolated regions. By proving that large-scale brain network analysis can be successfully harmonized across international sites, this research provides a vital, system-wide understanding of the disorder, moving the field closer to precision medicine and biologically informed psychiatric care.
The largest diffusion MRI network analysis of bipolar disorder to date reveals subtle but widespread differences in brain communication pathways involved in emotion, reward, and cognitive control.
New research from the Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI) at the Keck School of Medicine of USC has discovered subtle but widespread differences in the brain’s communication networks in people with bipolar disorder, offering new insight into how illness severity and treatment may relate to brain wiring.
Published in Biological Psychiatry, the study was led by Leila Nabulsi, PhD, a senior research associate at the Stevens INI, together with Dara M. Cannon, PhD, professor at the University of Galway, Ireland. The team analyzed brain scans from 449 people with bipolar disorder and 510 healthy controls across 16 international research sites through the ENIGMA Bipolar Disorder Working Group. This work was made possible by ENIGMA, an international consortium founded and led in part by Paul M. Thompson, PhD, associate director of the Stevens INI. ENIGMA brings together researchers worldwide to pool their brain imaging and clinical data, allowing them to detect subtle patterns that would be difficult to identify in smaller studies.
Mapping the Brain’s Communication System Using diffusion MRI, an advanced imaging technique that maps the brain’s neural pathways, the researchers examined how different regions of the brain are structurally connected. White matter acts as the brain’s communication infrastructure, allowing different regions to send signals to one another. In bipolar disorder, where patients have episodes of depression and mania or hypomania, changes in these communication pathways lead to disruptions in mood, emotion regulation, reward processing, and cognitive control.
“Bipolar disorder is defined by changes in mood and behavior, but those symptoms arise from complex brain circuits that do not operate in isolation,” said Leila Nabulsi, PhD, the study’s first author. “While previous studies identified changes in individual brain regions, we still know less about how these regions are connected as part of larger networks. By viewing the brain as an interconnected system, we can now see how differences in communication pathways relate to the circuits that regulate mood and to features of the illness.”
Previous large-scale MRI studies from the ENIGMA Consortium found that people with bipolar disorder tend to have differences in gray matter, the tissue that contains most neuronal cell bodies. Less is known about how white matter pathways are organized into large-scale brain networks, and how the efficiency of those networks relates to illness severity and treatment. To address this, the research team used diffusion MRI and a network analysis approach known as graph theory. In simple terms, this approach models the brain like a transportation system: brain regions are treated as “nodes,” and the connections between them as “routes.” Researchers can then estimate how efficiently information may move across the network.
Subtle but Widespread Network Differences The study found that people with bipolar disorder showed subtle but consistent differences in how brain networks are organized. Compared with psychiatrically healthy controls, participants with bipolar disorder had less densely connected networks, lower efficiency in how information is exchanged, and longer routes for communication between brain regions. Their brain networks relied more on highly connected “hub” regions, key points that help coordinate communication across the brain. This pattern may reflect the brain’s attempt to adapt to these network changes, with information flowing less directly and relying more on a limited set of pathways.
The most pronounced differences were seen in networks involved in emotion regulation, reward processing, attention, and self-reflection—functional systems known to be affected in bipolar disorder. These included frontolimbic circuits, which help regulate emotion; basal ganglia pathways involved in motivation and reward; and regions within the brain’s default mode and salience networks, which are important for internal thought and prioritizing relevant information.
“In people with bipolar disorder, the brain’s communication system may be less efficiently organized, with information taking less direct routes across the network,” Nabulsi said. “We found consistent effects across a large, international sample, and they may help explain clinical differences and treatment effects in patients.”
“Psychiatric disorders are biologically complex, and no single research site can capture the full picture on its own,” said Thompson. “By harmonizing data across research groups worldwide, ENIGMA gives us the statistical power to identify brain signatures of mental health conditions and discover new ways to resist them.”
Linking Brain Wiring to Illness History The study also related these brain network differences to clinical features of bipolar disorder. Individuals who had been ill longer showed broader reductions in how efficiently large-scale brain networks communicate, along with altered connectivity between the amygdala and hippocampus, regions that are central to emotions and memory. A later age of onset, by contrast, was linked to a different pattern: more pronounced changes in specific circuits connecting the cerebellum, thalamus, and frontolimbic pathways, which are also involved in emotion regulation. Individuals who had experienced psychosis showed more pronounced differences in brain network organization overall. People who experienced a greater number of manic episodes tended to have higher connectivity in certain frontolimbic pathways, which may reflect illness-related changes or the brain’s attempt to adapt to these network alterations.
Understanding Treatment in Context The study also examined how different types of medication relate to brain network organization—the first large-scale effort to assess treatment effects on white matter connectivity using network-based approaches. In addition to grouping medications by traditional nomenclature, the researchers analyzed them based on their underlying biological mechanisms to understand how different mechanisms of action may be linked to changes in brain connectivity.
Antidepressant use, particularly selective serotonin reuptake inhibitors (SSRIs), was linked to less efficient communication across the brain overall, and to specific changes in limbic circuits involved in emotion regulation. Anticonvulsant and antipsychotic use was also linked to changes in circuits related to emotion regulation and cognitive control.
“This study should not be interpreted as guidance for changing treatment,” Nabulsi said. “Medications are prescribed for a variety of clinical reasons, and people receiving certain treatments may also differ in illness history or symptom severity. We found that treatment exposure is an important factor to consider when studying the biology of bipolar disorder, so we can separate the effects of the illness from those of the medications. We hope this encourages future studies to take these factors into account.”
Toward More Personalized Care The researchers emphasize that these findings do not show that medications caused the observed brain differences. Because the study was cross-sectional, meaning participants were scanned at a single point in time, it cannot determine cause and effect. Future longitudinal studies that follow individuals over time are needed to clarify how treatment, illness progression, and brain network changes are related. Ongoing work within the ENIGMA Bipolar Disorder Working Group is now addressing these questions in large-scale datasets from patients assessed repeatedly over time.
The study also shows that large-scale brain network analysis can be successfully carried out across multiple international sites, despite differences in scanners, imaging protocols, and patient populations. This type of harmonized approach brings researchers closer to identifying reliable and biologically grounded markers to inform diagnosis, prognosis, and treatment.
“Bipolar disorder affects millions of people worldwide, yet treatment response is highly variable,” said Arthur W. Toga, PhD, director of the Stevens INI. “Studies like this help us move closer to understanding the brain circuits involved, which is an essential step toward more personalized and biologically informed approaches to care.”
By identifying how large-scale brain networks are linked to illness severity and treatment exposure, the study provides a framework to understand bipolar disorder at the level of brain systems rather than isolated regions. The research team hopes this work will lay the groundwork for future longitudinal studies that follow patients over time and determine whether these network patterns predict symptom course, treatment response, and risk for future episodes.
Toga said the work also highlights the value of combining brain imaging with careful clinical evaluation.
“The more precisely we can map the brain systems involved in bipolar disorder, the better positioned we are to develop tools that may eventually help clinicians predict illness trajectories and tailor interventions,” he said. “This is the kind of foundational science we do at the Stevens INI that moves the field toward more personalized health care.”
Resource material: Nabulsi discuss this study on The Biological Psychiatry Podcast
Published in journal: Biological Psychiatry
Authors: Leila Nabulsi, Melody J.Y. Kang, Neda Jahanshad, Genevieve McPhilemy, Fiona M. Martyn, Bartholomeus Haarman, Colm McDonald, Brian Hallahan, Stefani O’Donoghue, Dan J. Stein, Fleur M. Howells, Freda Scheffler, Henk S. Temmingh, David C. Glahn, Amanda Rodrigue, Edith Pomarol-Clotet, Eduard Vieta, Joaquim Radua, Raymond Salvador, Andriana Karuk, Erick J. Canales-Rodríguez, Josselin Houenou, Pauline Favre, Mircea Polosan, Arnaud Pouchon, Paolo Brambilla, Marcella Bellani, Philip B. Mitchell, Gloria Roberts, Udo Dannlowski, Tiana Borgers, Susanne Meinert, Kira Flinkenflügel, Jonathan Repple, Elisabeth J. Leehr, Dominik Grotegerd, Tim Hahn, Michèle Wessa, Mary L. Phillips, Lea Teutenberg, Tilo Kircher, Benjamin Straube, Olaf Steinstraeter, Frederike Stein, Florian Thomas-Odenthal, Nina Alexander, Paula L. Usemann, Andreas Jansen, Michael Berk, Orwa Dandash, Nadine Parker, Chao Suo, Sophia I. Thomopoulos, Paul M. Thompson, Ole A. Andreassen, Christopher R.K. Ching, and Dara M. Cannon for the ENIGMA Bipolar Disorder Working Group
Source/Credit: Keck School of Medicine of USC | Sidney Taiko Sheehan
Edited by: Scientific Frontline
Reference Number: ns070826_01
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