Poster No:
445
Submission Type:
Abstract Submission
Authors:
Josselin Houenou1
Institutions:
1Department of Psychiatry, University of Melbourne, Melbourne, Victoria
First Author:
Josselin Houenou
Department of Psychiatry, University of Melbourne
Melbourne, Victoria
Introduction:
Theoretical models of major psychiatric disorders are critically lacking the field. Therefore, most studies are observational and not mechanistic. Many neuroimaging studies have identified abnormal connectivity in limbic networks in bipolar disorder, either structural or functional. In parallel, neuronal, synaptic and circadian abnormalities are present in most patients suffering from BD. Our aim was thus to build an integrated, multi-scale, whole-brain model of bipolar disorder to reconcile the different lines of research.
Methods:
We will first review the relevant existing literature on bipolar disorder on different fields : 1) the "classical" connectomics (using fMRI, EEG and DTI) 2) the cellular synaptic literature, including the effect of lithium, its first line treatment 3) the circadian disturbances, from mice modeling to clinical sleep pattern changes 4) the observable manifestations of bipolar disorder, either clinical or dimensional. This allowed us to build a hypothesis driven whole-brain neural model of bipolar disorder. Using platforms dedicated to whole-brain modeling (EBrains www.ebrains.eu), we will test different models of bipolar disorders based on different parameters of the whole-brain networks.
Results:
Our literature review and tests using Ebrains led us to design a whole-brain model of bipolar disorder based on anatomical and functional connectivity changes. Neuronal hyperexcitability, white matter abnormalities, myelin changes, chronic hyperexcitability of the amygdala, lack of synchronisation and abnormal oscillations lie at the heart of our model. This model offers a framework for the efficacy of lithium and anticonvulsants. Finally, our model is specific to bipolar disorder (compared with schizophrenia and unipolar depression).
Conclusions:
In summary, stemming mostly from fMRI and DTI literature, we here provide a new whole-brain multi-scale model of bipolar disorder. Its predictions can be tested and the models refined and challenged, as a in a classical scientific approach.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Diffusion MRI Modeling and Analysis
fMRI Connectivity and Network Modeling
Keywords:
Affective Disorders
FUNCTIONAL MRI
Modeling
MRI
Psychiatric
Psychiatric Disorders
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
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.
Other
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?
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Not applicable
Were any animal research approved by the relevant IACUC or other animal research panel?
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Please indicate which methods were used in your research:
Computational modeling
Provide references using APA citation style.
Magioncalda, P. (2022). A unified model of the pathophysiology of bipolar disorder. Molecular Psychiatry, Jan;27(1):202-211.
Phillips, M.L. (2014) A critical appraisal of neuroimaging studies of bipolar disorder: toward a new conceptualization of underlying neural circuitry and a road map for future research. American Journal of Psychiatry, Aug;171(8):829-43.
Schirner, M. (2022) Brain simulation as a cloud service: The Virtual Brain on EBRAINS. Neuroimage, May 1;251:118973.
Wang, H.E. (2024) Virtual brain twins: from basic neuroscience to clinical use. National Science Review Feb 28;11(5):nwae079
No