The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Temporal lobe and “default” hemodynamic brain modes discriminate between schizophrenia and bipolar disorder
Open accessAbstract
Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically‐based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or “spatial modes” exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task‐correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder. Hum Brain Mapp 2008. © 2007 Wiley‐Liss, Inc.
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A default mode of brain function
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.676 · Cited by 12,190
An Information-Maximization Approach to Blind Separation and Blind Deconvolution
Bell, A. J., & Sejnowski, T. J. (1995) · Neural Computation · doi:10.1162/neco.1995.7.6.1129 · Cited by 8,986
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Investigations into resting-state connectivity using independent component analysis
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1634 · Cited by 3,398
A method for making group inferences from functional MRI data using independent component analysis
Calhoun, V. D., Adali, T., Pearlson, G. D., & Pekar, J. J. (2001) · Human Brain Mapping · doi:10.1002/hbm.1048 · Cited by 2,994
Self-citationA Parametric Manipulation of Factors Affecting Task-induced Deactivation in Functional Neuroimaging
McKiernan, K. A., Kaufman, J. N., Kucera-Thompson, J., & Binder, J. R. (2003) · Journal of Cognitive Neuroscience · doi:10.1162/089892903321593117 · Cited by 1,080
Greicius, M. D., & Menon, V. (2004) · Journal of Cognitive Neuroscience · doi:10.1162/0898929042568532 · Cited by 684
Toward constructing an endophenotype strategy for bipolar disorders
Hasler, G., Drevets, W. C., Gould, T. D., Gottesman, I. I., & Manji, H. K. (2006) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.11.006 · Cited by 423
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Default Mode Network Activity and Connectivity in Psychopathology
Whitfield-Gabrieli, S., & Ford, J. M. (2012) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032511-143049 · Cited by 1,465
Whitfield-Gabrieli, S., Thermenos, H. W., Milanovic, S., Tsuang, M. T., Faraone, S. V., McCarley, R. W., Shenton, M. E., Green, A. I., Nieto-Castanon, A., LaViolette, P., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0809141106 · Cited by 1,435
A Baseline for the Multivariate Comparison of Resting-State Networks
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., et al. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00002 · Cited by 1,293
Self-citationBuilding better biomarkers: brain models in translational neuroimaging
Woo, C.-W., Chang, L. J., Lindquist, M. A., & Wager, T. D. (2017) · Nature Neuroscience · doi:10.1038/nn.4478 · Cited by 1,056
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls
Arbabshirani, M. R., Plis, S., Sui, J., & Calhoun, V. D. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.079 · Cited by 912
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Metadata
- Authors
- Calhoun, V. D., Maciejewski, P. K., Pearlson, G. D., & Kiehl, K. A.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2007-09-25
- Volume
- 29
- Issue
- 11
- Pages
- 1265-1275
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2040709265
- Cited by
- 346
- References
- 8
- FWCI
- 9.44
- Type
- journal article
- Language
- en
- Open access
- green
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