Poster No:
568
Submission Type:
Late-Breaking Abstract Submission
Authors:
CHANG Zhao1
Institutions:
1Hong Kong Baptist University, Hong Kong, Hong Kong
First Author:
CHANG Zhao
Hong Kong Baptist University
Hong Kong, Hong Kong
Introduction:
Recent neuroimaging studies have examined how intrinsic brain network organization relates to psychiatric symptoms across schizophrenia (SZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD). Using resting-state functional MRI and advanced analytical methods-including nested-spectral partitioning and hierarchical degree metrics
Methods:
Nested-spectral partitioning and hierarchical degree metrics are both advanced concepts in graph theory and network analysis. They aim to provide more nuanced ways of understanding and grouping nodes in a graph, thereby revealing underlying structures, communities, or clusters. While they share a common goal of elucidating hidden patterns in complex networks, they do so from complementary standpoints. Nested-spectral partitioning leverages the power of spectral graph theory-particularly the properties of eigenvalues and eigenvectors of special matrices-to recursively refine partitions into more granular subgroups. On the other hand, hierarchical degree metrics focus on analyzing node connectivity patterns, layer by layer, to capture how degrees of influence or centrality evolve from one level of the graph to another.
Results:
we investigated network alterations specific to each disorder, as well as those shared across disorders.Key findings revealed that SZ and BD share significantly elevated functional network segregation compared to healthy controls, reflecting diminished integration across brain systems, particularly within limbic networks. In contrast, adult ADHD demonstrated minimal differences in these network metrics. Furthermore, distinct connectivity patterns were associated with specific symptom domains within each disorder: positive and negative symptoms in SZ exhibited opposing effects on network connectivity, while in BD, anxiety symptoms uniquely correlated with disruptions in network balance.Advanced network metrics substantially outperformed traditional analytical methods in predicting symptom severity and differentiating among disorders. Biological analyses further revealed that all three disorders exhibited network abnormalities involving dopaminergic systems, although each disorder displayed distinct gene expression signatures. Specifically, SZ and BD network changes were linked to genes involved in cellular localization and social behaviors, whereas ADHD-specific alterations correlated primarily with genes related to energy production pathways.These results highlight that psychiatric disorders do not uniformly impact neural organization; rather, each disorder-and individual symptom domains within each disorder-produces distinct patterns in the brain's functional connectome
Conclusions:
Our findings underscore the potential of network-based biomarkers for enhancing diagnostic precision and developing personalized interventions tailored to specific neurobiological profiles underlying psychiatric symptoms.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Keywords:
FUNCTIONAL MRI
Other - nested-spectral partitioning method
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Yes
Please indicate which methods were used in your research:
Functional MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
AFNI
FSL
Free Surfer
Provide references using APA citation style.
Chang, Z., Wang, X., Wu, Y., Lin, P., & Wang, R. (2023). Segregation, integration and balance in resting‐state brain functional networks associated with bipolar disorder symptoms. Human Brain Mapping, 44(2), 599-611.
Wang, X., Chang, Z., & Wang, R. (2023). Opposite effects of positive and negative symptoms on resting-state brain networks in schizophrenia. Communications Biology, 6(1), 279.
Wu, D., Chang, Z., Wang, Y., Jiang, Z., Wang, R., & Wu, Y. (2025). High-order network degree revealed shared and distinct features among adult schizophrenia, bipolar disorder and ADHD. Neuroscience, 568, 154-165.
No