Anatomical dysconnectivity in bipolar disorder compared with schizophrenia: a selective review of structural network analyses using diffusion MRI
Abstract
Background The dysconnectivity hypothesis suggests that psychotic illnesses arise not from regionally specific focal pathophysiology, but rather from impaired neuroanatomical integration across networks of brain regions. Decreased white matter organization has been hypothesized to be a feature of psychotic illnesses in general, which is supported by meta-analyses of DTI studies in bipolar disorder and schizophrenia. Although many diffusion MRI studies investigate bipolar disorder and schizophrenia alone, relatively few studies directly compare structural features in these psychotic illnesses. Recently, the application of graph theory analyses to DTI data has supported the dysconnectivity hypothesis in bipolar disorder and schizophrenia, employing topological properties to assess neuroanatomical dysconnectivity. Methods This selective review evaluates white matter alterations using Diffusion Tensor Imaging (DTI) in bipolar disorder and schizophrenia, with a focus upon direct comparison DTI studies in both psychotic illnesses. We then expand in more detail on the development of network analyses and the application of these techniques in bipolar disorder and schizophrenia. Results Converging evidence indicates that frontal connectivity alterations are common to both disorders, with prominent fronto-temporal deficits identified in schizophrenia and inter-hemispheric and limbic alterations reported in bipolar disorder. Limitations In bipolar disorder, most connectome reports use c…
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Frontal disconnection is common to both bipolar disorder and schizophrenia.
“A review of dMRI findings in bipolar disorders and schizophrenia (O’Donoghue et al., 2017), concluded that frontal disconnection is common to both illnesses.”
From The cingulum bundle: Anatomy, function, and dysfunction (2018) · cites this paper as O’Donoghue et al., 2017
In bipolar disorders, abnormalities in interhemispheric and posterior limbic connectivity appeared more prominent, while schizophrenia was more linked with frontotemporal changes.
“In bipolar disorders, abnormalities in interhemispheric and posterior limbic connectivity appeared more prominent, while schizophrenia was more linked with frontotemporal changes (O’Donoghue et al., 2017).”
From The cingulum bundle: Anatomy, function, and dysfunction (2018) · cites this paper as O’Donoghue et al., 2017
Cites
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931 · see citing works
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,653 · see citing works
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173 · see citing works
Efficiency and Cost of Economical Brain Functional Networks
Achard, S., & Bullmore, E. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030017 · Cited by 2,553 · see citing works
White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI
Jones, D. K., Knösche, T. R., & Turner, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.081 · Cited by 2,479 · see citing works
Network hubs in the human brain
van den Heuvel, M. P., & Sporns, O. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.012 · Cited by 2,123 · see citing works
Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring
Stephan, K. E., Friston, K. J., & Frith, C. D. (2009) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn176 · Cited by 1,134 · see citing works
Belmaker, R. H. (2004) · New England Journal of Medicine · doi:10.1056/nejmra035354 · Cited by 473 · see citing works
McDonald, C., Bullmore, E. T., Sham, P. C., Chitnis, X., Wickham, H., Bramon, E., & Murray, R. M. (2004) · Archives of General Psychiatry · doi:10.1001/archpsyc.61.10.974 · Cited by 379 · see citing works
Self-citationPhillips, M. L., Ladouceur, C. D., & Drevets, W. C. (2008) · Molecular Psychiatry · doi:10.1038/mp.2008.82 · Cited by 366 · see citing works
Functional Dysconnectivity of Corticostriatal Circuitry as a Risk Phenotype for Psychosis
Fornito, A., Harrison, B. J., Goodby, E., Dean, A., Ooi, C., Nathan, P. J., Lennox, B. R., Jones, P. B., Suckling, J., & Bullmore, E. T. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.1976 · Cited by 279 · see citing works
Connectivity differences in brain networks
Zalesky, A., Cocchi, L., Fornito, A., Murray, M. M., & Bullmore, E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.068 · Cited by 260 · see citing works
A DTI-Derived Measure of Cortico-Cortical Connectivity
Zalesky, A., & Fornito, A. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2012113 · Cited by 141 · see citing works
Comparing connectomes across subjects and populations at different scales
Meskaldji, D. E., Fischi-Gomez, E., Griffa, A., Hagmann, P., Morgenthaler, S., & Thiran, J.-P. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.084 · Cited by 77 · see citing works
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van den Heuvel, M. P., & Sporns, O. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0177-6 · Cited by 462 · see citing works
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- Authors
- O’Donoghue, S., Holleran, L., Cannon, D. M., & McDonald, C.
- Affiliations
- Ollscoil na Gaillimhe – University of Galway (IE)
- Corresponding author
- O’Donoghue, Stefani
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2017-02
- Volume
- 209
- Pages
- 217-228
- ISSN
- 0165-0327 (ISSN-L)
- OpenAlex
- W2556948800
- Cited by
- 109
- References
- 14
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 7 · 2023: 8 · 2022: 11 · 2021: 31 · 2020: 10 · 2019: 16 · 2018: 11 · 2017: 9
- FWCI
- 1.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Affective Disorders (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Hardiman Research Scholarship, National University of Ireland
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- bipolar disorder, schizophrenia, white matter changes, diffusion tensor imaging, graph theory, brain network topology, fronto-temporal connectivity, limbic system, interhemispheric connectivity, cognitive impairment, mood disorders, deficit syndrome
- MeSH terms
- Bipolar Disorder, Brain, Humans, Nerve Net, Schizophrenia, Diffusion Tensor Imaging, Connectome
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