The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Differential brain network activity across mood states in bipolar disorder
Open accessAbstract
Background This study aimed to identify how the activity of large-scale brain networks differs between mood states in bipolar disorder. The authors measured spontaneous brain activity in subjects with bipolar disorder in mania and euthymia and compared these states to a healthy comparison population. Methods 23 subjects with bipolar disorder type I in a manic episode, 24 euthymic bipolar I subjects, and 23 matched healthy comparison (HC) subjects underwent resting state fMRI scans. Using an existing parcellation of the whole brain, we measured functional connectivity between brain regions and identified significant differences between groups. Results In unbiased whole-brain analyses, functional connectivity between parietal, occipital, and frontal nodes within the dorsal attention network (DAN) were significantly greater in mania than euthymia or HC subjects. In the default mode network (DMN), connectivity between dorsal frontal nodes and the rest of the DMN differentiated both mood state and diagnosis. Limitations The bipolar groups were separate cohorts rather than subjects imaged longitudinally across mood states. Conclusions Bipolar mood states are associated with highly significant alterations in connectivity in two large-scale brain networks. These same networks also differentiate bipolar mania and euthymia from a HC population. State related changes in DAN and DMN connectivity suggest a circuit based pathology underlying cognitive dysfunction as well as activity/reactivity in bipolar mania. Altered activities in neural networks may be biomarkers of bipolar disorder diagnosis and mood state that are accessible to neuromodulation and are promising novel targets for scientific investigation and possible clinical intervention.
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“Therefore, previous studies using features from other domains were conducted on relatively small sample sets, prone to over-fitting and lack of validation in large-scale populations with synthetic heterogeneity14,33–35,57,58.”
From Optimizing multi-domain hematologic biomarkers and clinical features for the differential diagnosis of unipolar depression and bipolar depression (2023) · cites this paper as [34]
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Metadata
- Authors
- Brady Jr., R. O., Tandon, N., Masters, G. A., Margolis, A., Cohen, B. M., Keshavan, M., & Öngür, D.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Harvard University (US)
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 207
- Pages
- 367-376
- ISSN
- 0165-0327 (ISSN-L)
- PMC
- PMC5107137
- OpenAlex
- W2528865389
- Cited by
- 115
- References
- 36
- Citations by year
- 2025: 13 · 2024: 8 · 2023: 10 · 2022: 3 · 2021: 35 · 2020: 9 · 2019: 25 · 2018: 8 · 2017: 4
- FWCI
- 7.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Affective Disorders (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (K23MH100623, R01MH094594, R01MH078113)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- bipolar disorder, mood states, mania, euthymia, large-scale brain networks, functional connectivity, resting-state fMRI, dorsal attention network, default mode network, neural markers, neuromodulation targets, cognitive impairment
- MeSH terms
- Adult, Affect, Attention, Bipolar Disorder, Brain, Brain Mapping, Cyclothymic Disorder, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Rest, Case-Control Studies, Young Adult
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