{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T10:05:34Z","timestamp":1777284334393,"version":"3.51.4"},"reference-count":77,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T00:00:00Z","timestamp":1670198400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T00:00:00Z","timestamp":1670198400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neuroinform"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1007\/s12021-022-09614-2","type":"journal-article","created":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T15:07:28Z","timestamp":1670252848000},"page":"443-455","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Co-alteration Network Architecture of Major Depressive Disorder: A Multi-modal Neuroimaging Assessment of Large-scale Disease Effects"],"prefix":"10.1007","volume":"21","author":[{"given":"Jodie P.","family":"Gray","sequence":"first","affiliation":[]},{"given":"Jordi","family":"Manuello","sequence":"additional","affiliation":[]},{"given":"Aaron F.","family":"Alexander-Bloch","sequence":"additional","affiliation":[]},{"given":"Cassandra","family":"Leonardo","sequence":"additional","affiliation":[]},{"given":"Crystal","family":"Franklin","sequence":"additional","affiliation":[]},{"given":"Ki Sueng","family":"Choi","sequence":"additional","affiliation":[]},{"given":"Franco","family":"Cauda","sequence":"additional","affiliation":[]},{"given":"Tommaso","family":"Costa","sequence":"additional","affiliation":[]},{"given":"John","family":"Blangero","sequence":"additional","affiliation":[]},{"given":"David C.","family":"Glahn","sequence":"additional","affiliation":[]},{"given":"Helen S.","family":"Mayberg","sequence":"additional","affiliation":[]},{"given":"Peter T.","family":"Fox","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,5]]},"reference":[{"key":"9614_CR1","doi-asserted-by":"publisher","first-page":"147","DOI":"10.3389\/fnsys.2010.00147","volume":"4","author":"A Alexander-Bloch","year":"2010","unstructured":"Alexander-Bloch, A., Gogtay, N., Meunier, D., et al. (2010). Disrupted modularity and local connectivity of brain functional networks in childhood-onset schizophrenia. Frontiers in Systems Neuroscience, 4, 147. https:\/\/doi.org\/10.3389\/fnsys.2010.00147","journal-title":"Frontiers in Systems Neuroscience"},{"issue":"4","key":"9614_CR2","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1016\/j.neuroimage.2011.11.035","volume":"59","author":"A Alexander-Bloch","year":"2012","unstructured":"Alexander-Bloch, A., Lambiotte, R., Roberts, B., et al. (2012). The discovery of population differences in network community structure: New methods and applications to brain functional networks in schizophrenia. NeuroImage, 59(4), 388\u20133900. https:\/\/doi.org\/10.1016\/j.neuroimage.2011.11.035","journal-title":"NeuroImage"},{"issue":"6","key":"9614_CR3","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1002\/ana.410100602","volume":"10","author":"SH Appel","year":"1981","unstructured":"Appel, S. H. (1981). A unifying hypothesis for the cause of amyotrophic lateral sclerosis, parkinsonism, and alzheimer disease. Annals of Neurology, 10(6), 499\u2013505. https:\/\/doi.org\/10.1002\/ana.410100602","journal-title":"Annals of Neurology"},{"issue":"3","key":"9614_CR4","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.neurad.2015.02.006","volume":"42","author":"SA Baltruschat","year":"2015","unstructured":"Baltruschat, S. A., Ventura-Campos, N., Cruz-G\u00f3mez, A. J., et al. (2015). Gray matter atrophy is associated with functional connectivity reorganization during the Paced Auditory Serial Addition Test (PASAT) execution in multiple sclerosis (MS). Journal of Neuroradiology, 42(3), 141\u2013149. https:\/\/doi.org\/10.1016\/j.neurad.2015.02.006","journal-title":"Journal of Neuroradiology"},{"key":"9614_CR5","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/j.nicl.2014.08.002","volume":"7","author":"DS Barron","year":"2014","unstructured":"Barron, D. S., Fox, P. T., Pardoe, H., et al. (2015). Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy. Neuroimage Clinical, 7, 273\u2013280. https:\/\/doi.org\/10.1016\/j.nicl.2014.08.002","journal-title":"Neuroimage Clinical"},{"issue":"6","key":"9614_CR6","doi-asserted-by":"publisher","first-page":"e50","DOI":"10.1111\/epi.12637","volume":"55","author":"DS Barron","year":"2014","unstructured":"Barron, D. S., Tandon, N., Lancaster, J. L., et al. (2014). Thalamic structural connectivity in medial temporal lobe epilepsy. Epilepsia, 55(6), e50-55. https:\/\/doi.org\/10.1111\/epi.12637","journal-title":"Epilepsia"},{"key":"9614_CR7","doi-asserted-by":"publisher","first-page":"352","DOI":"10.1038\/nn.4502","volume":"20","author":"DS Bassett","year":"2017","unstructured":"Bassett, D. S., & Sporns, O. (2017). Network neuroscience. Nature Neuroscience, 20, 352\u2013362. https:\/\/doi.org\/10.1038\/nn.4502","journal-title":"Nature Neuroscience"},{"key":"9614_CR8","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1038\/s41380-019-0385-5","volume":"24","author":"L Beijers","year":"2019","unstructured":"Beijers, L., Wardenaar, K. J., van Loo, H. M., & Schoevers, R. A. (2019). Dara-driven biological subtypes of depression: Systematic review of biological approaches to depression subtyping. Molecular Psychiatry, 24, 888\u2013900. https:\/\/doi.org\/10.1038\/s41380-019-0385-5","journal-title":"Molecular Psychiatry"},{"key":"9614_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.07.003","volume":"202","author":"RF Betzel","year":"2019","unstructured":"Betzel, R. F., Bertolero, M. A., Gordon, E. M., et al. (2019). The community structure of functional brain networks exhibits scale-specific patterns of variability across individuals and time. NeuroImage, 202, 115990. https:\/\/doi.org\/10.1016\/j.neuroimage.2019.07.003","journal-title":"NeuroImage"},{"key":"9614_CR10","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1016\/j.nicl.2018.02.036","volume":"18","author":"H Botha","year":"2018","unstructured":"Botha, H., Utianski, R. L., Whitwell, J. L., et al. (2018). Disrupted functional connectivity in primary progressive apraxia of speech. Neuroimage Clinical, 18, 617\u2013629. https:\/\/doi.org\/10.1016\/j.nicl.2018.02.036","journal-title":"Neuroimage Clinical"},{"issue":"1\u20133","key":"9614_CR11","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.jad.2006.10.028","volume":"101","author":"JD Bremner","year":"2007","unstructured":"Bremner, J. D., Vythilingam, M., Vermetten, E., et al. (2007). Effects of antidepressant treatment on neural correlates of emotional and neutral declarative verbal memory in depression. Journal of Affective Disorders, 101(1\u20133), 99\u2013111. https:\/\/doi.org\/10.1016\/j.jad.2006.10.028","journal-title":"Journal of Affective Disorders"},{"issue":"5","key":"9614_CR12","doi-asserted-by":"publisher","first-page":"1898","DOI":"10.1002\/hbm.23952","volume":"39","author":"F Cauda","year":"2018","unstructured":"Cauda, F., Nani, A., Costa, T., et al. (2018a). The morphometric co-atrophy networking of schizophrenia, autistic and obsessive spectrum disorders. Human Brain Mapping, 39(5), 1898\u20131928. https:\/\/doi.org\/10.1002\/hbm.23952","journal-title":"Human Brain Mapping"},{"issue":"11","key":"9614_CR13","doi-asserted-by":"publisher","first-page":"3211","DOI":"10.1093\/brain\/awy252","volume":"141","author":"F Cauda","year":"2018","unstructured":"Cauda, F., Nani, A., Manuello, J., et al. (2018b). Brain structural alterations are distributed following functional, anatomic, and genetic connectivity. Brain, 141(11), 3211\u20133232. https:\/\/doi.org\/10.1093\/brain\/awy252","journal-title":"Brain"},{"key":"9614_CR14","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.neuroimage.2018.09.036","volume":"184","author":"F Cauda","year":"2019","unstructured":"Cauda, F., Nani, A., Manuello, J., et al. (2019). The alteration landscape of the cerebral cortex. NeuroImage, 184, 359\u2013371. https:\/\/doi.org\/10.1016\/j.neuroimage.2018.09.036","journal-title":"NeuroImage"},{"issue":"1","key":"9614_CR15","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1148\/radiol.2021203414","volume":"299","author":"FL Chiang","year":"2021","unstructured":"Chiang, F. L., Feng, M., Romero, R. S., et al. (2021). Disruption of the Atrophy-based Functional Network in Multiple Sclerosis is Associated with Clinical Disability: Validation of a Meta-Analytic Model in Resting-State Functional MRI. Radiology, 299(1), 159\u2013166. https:\/\/doi.org\/10.1148\/radiol.2021203414","journal-title":"Radiology"},{"issue":"10","key":"9614_CR16","doi-asserted-by":"publisher","first-page":"816","DOI":"10.1016\/j.crad.2019.07.005","volume":"74","author":"FL Chiang","year":"2019","unstructured":"Chiang, F. L., Wang, Q., Yu, F. F., et al. (2019). Localised grey matter atrophy in multiple sclerosis is network-based: A coordinate-based meta-analysis. Clinical Radiology, 74(10), 816\u2013819. https:\/\/doi.org\/10.1016\/j.crad.2019.07.005","journal-title":"Clinical Radiology"},{"issue":"8","key":"9614_CR17","doi-asserted-by":"publisher","first-page":"2382","DOI":"10.1093\/brain\/awu132","volume":"137","author":"NA Crossley","year":"2014","unstructured":"Crossley, N. A., Mechelli, A., Scott, J., et al. (2014). The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain, 137(8), 2382\u20132395. https:\/\/doi.org\/10.1093\/brain\/awu132","journal-title":"Brain"},{"issue":"Pt 9","key":"9614_CR18","doi-asserted-by":"publisher","first-page":"2375","DOI":"10.1093\/brain\/awm184","volume":"130","author":"G Douaud","year":"2007","unstructured":"Douaud, G., Smith, S., Jenkinson, M., et al. (2007). Anatomically related grey and white matter abnormalities in adolescent-onset schizophrenia. Brain, 130(Pt 9), 2375\u20132386. https:\/\/doi.org\/10.1093\/brain\/awm184","journal-title":"Brain"},{"key":"9614_CR19","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s00429-008-0189-x","volume":"213","author":"WC Drevets","year":"2008","unstructured":"Drevets, W. C., Price, J. L., & Furey, M. L. (2008). Brain structural and functional abnormalities in mood disorders: Implications for neurocircuitry models of depression. Brain Structure and Function, 213, 93\u2013118. https:\/\/doi.org\/10.1007\/s00429-008-0189-x","journal-title":"Brain Structure and Function"},{"key":"9614_CR20","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1038\/386824a0","volume":"386","author":"WC Drevets","year":"1997","unstructured":"Drevets, W. C., Price, J. L., Simpson, J. R., Jr., et al. (1997). Subgenual prefrontal cortex abnormalities in mood disorders. Nature, 386, 824\u2013827. https:\/\/doi.org\/10.1038\/386824a0","journal-title":"Nature"},{"key":"9614_CR21","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1186\/1745-6215-13-106","volume":"13","author":"BW Dunlop","year":"2012","unstructured":"Dunlop, B. W., Binder, E. B., Cubells, J. F., et al. (2012). Predictors of remission in depression to individual and combined treatments (PReDICT): Study protocol for a randomized controlled trial. Trials, 13, 106. https:\/\/doi.org\/10.1186\/1745-6215-13-106","journal-title":"Trials"},{"issue":"3","key":"9614_CR22","doi-asserted-by":"publisher","first-page":"2349","DOI":"10.1016\/j.neuroimage.2011.09.017","volume":"59","author":"SB Eickhoff","year":"2012","unstructured":"Eickhoff, S. B., Bzdok, D., Laird, A. R., et al. (2012). Activation likelihood estimation meta-analysis revisited. NeuroImage, 59(3), 2349\u20132361. https:\/\/doi.org\/10.1016\/j.neuroimage.2011.09.017","journal-title":"NeuroImage"},{"issue":"4","key":"9614_CR23","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1038\/nrn789","volume":"3","author":"PT Fox","year":"2002","unstructured":"Fox, P. T., & Lancaster, J. L. (2002). Opinion: Mapping context and content: The BrainMap model. Nature Reviews Neuroscience, 3(4), 319\u2013321. https:\/\/doi.org\/10.1038\/nrn789","journal-title":"Nature Reviews Neuroscience"},{"key":"9614_CR24","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1038\/s41593-018-0221-2","volume":"21","author":"H Fu","year":"2018","unstructured":"Fu, H., Hardy, J., & Duff, K. E. (2018). Selective Neuronal Vulnerability in Neurodegenerative Diseases: From Stressor Thresholds to Degeneration. Nature Neuroscience, 21, 1350\u20131358. https:\/\/doi.org\/10.1038\/s41593-018-0221-2","journal-title":"Nature Neuroscience"},{"key":"9614_CR25","unstructured":"Glerean, E. (2014). BRAMILA Matlab tools [Computer scripts]. Retrieved from https:\/\/users.aalto.fi\/~eglerean\/bramila.html"},{"key":"9614_CR26","unstructured":"GingerALE [Software edition 3.0]. (2019). Retrieved from http:\/\/brainmap.org\/ale\/"},{"issue":"7","key":"9614_CR27","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1016\/j.tins.2010.04.003","volume":"33","author":"M Goedert","year":"2010","unstructured":"Goedert, M., Clavaguera, F., & Tolnay, M. (2010). The propagation of prion-like protein inclusions in neurodegenerative diseases. Trends in Neurosciences, 33(7), 317\u2013325. https:\/\/doi.org\/10.1016\/j.tins.2010.04.003","journal-title":"Trends in Neurosciences"},{"key":"9614_CR28","doi-asserted-by":"publisher","first-page":"2356","DOI":"10.1093\/brain\/awu159","volume":"137","author":"R Gonz\u00e1lez-Redondo","year":"2014","unstructured":"Gonz\u00e1lez-Redondo, R., Garc\u00eda-Garc\u00eda, D., Clavero, P., et al. (2014). Grey matter hypometabolism and atrophy in Parkinson\u2019s disease with cognitive impairment: A two-step process. Brain, 137, 2356\u20132367. https:\/\/doi.org\/10.1093\/brain\/awu159","journal-title":"Brain"},{"issue":"1 Pt 1","key":"9614_CR29","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1006\/nimg.2001.0786","volume":"14","author":"CD Good","year":"2001","unstructured":"Good, C. D., Johnsrude, I. S., Ashburner, J., et al. (2001). A voxel-based morphometric study of ageing in 465 normal adult human brains. NeuroImage, 14(1 Pt 1), 21\u201336. https:\/\/doi.org\/10.1006\/nimg.2001.0786","journal-title":"NeuroImage"},{"issue":"4","key":"9614_CR30","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1001\/jamapsychiatry.2014.2206","volume":"72","author":"M Goodkind","year":"2015","unstructured":"Goodkind, M., Eickhoff, S. B., Oathes, et al. (2015). Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry., 72(4), 305\u2013315. https:\/\/doi.org\/10.1001\/jamapsychiatry.2014.2206","journal-title":"JAMA Psychiatry."},{"key":"9614_CR31","unstructured":"Gray, J.P., et al. (2020) ANIMA Database. Study data available at: https:\/\/anima.fz-juelich.de\/studies\/Gray_MMD_MA_2020"},{"key":"9614_CR32","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1176\/appi.ajp.2019.19050560","volume":"177","author":"JP Gray","year":"2020","unstructured":"Gray, J. P., M\u00fcller, V. I., Eickhoff, S., et al. (2020). Multimodal Abnormalities of Brain Structure and Function in Major Depressive Disorder: A Meta-Analysis of Neuroimaging Studies. American Journal of Psychiatry, 177, 422\u2013434. https:\/\/doi.org\/10.1176\/appi.ajp.2019.19050560","journal-title":"American Journal of Psychiatry"},{"issue":"11","key":"9614_CR33","doi-asserted-by":"publisher","first-page":"993","DOI":"10.1038\/mp.2008.57","volume":"13","author":"JP Hamilton","year":"2008","unstructured":"Hamilton, J. P., Siemer, M., & Gotlib, I. H. (2008). Amygdala volume in Major Depressive Disorder: A meta-analysis of magnetic resonance imaging studies. Molecular Psychiatry, 13(11), 993\u20131000. https:\/\/doi.org\/10.1038\/mp.2008.57","journal-title":"Molecular Psychiatry"},{"key":"9614_CR34","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/S1474-4422(09)70299-6","volume":"9","author":"CR Jack Jr","year":"2010","unstructured":"Jack, C. R., Jr., Knopman, D. S., Jagust, W. J., et al. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer\u2019s pathological cascade. The Lancet Neurology, 9, 119\u2013128. https:\/\/doi.org\/10.1016\/S1474-4422(09)70299-6","journal-title":"The Lancet Neurology"},{"key":"9614_CR35","unstructured":"Jeub, L.G.S., Bazzi, M., Jutla, I.S., et al. (2011\u20132019). A generalized Louvain method for community detection implemented in MATLAB. Retrieved from https:\/\/github.com\/GenLouvain\/GenLouvain"},{"issue":"11","key":"9614_CR36","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1016\/j.biopsych.2005.05.019","volume":"58","author":"PA Keedwell","year":"2005","unstructured":"Keedwell, P. A., Andrew, C., Williams, S. C., et al. (2005). The Neural Correlates of Anhedonia in Major Depressive Disorder. Biological Psychiatry, 58(11), 843\u2013853. https:\/\/doi.org\/10.1016\/j.biopsych.2005.05.019","journal-title":"Biological Psychiatry"},{"issue":"2","key":"9614_CR37","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.pscychresns.2007.12.020","volume":"164","author":"JM Kim","year":"2008","unstructured":"Kim, J. M., Hamilton, J. P., & Gotlib, I. H. (2008). Reduced Caudate Gray Matter Volume in Women with Major Depressive Disorder. Psychiatry Research: Neuroimaging, 164(2), 114\u2013122. https:\/\/doi.org\/10.1016\/j.pscychresns.2007.12.020","journal-title":"Psychiatry Research: Neuroimaging"},{"key":"9614_CR38","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.nicl.2018.01.002","volume":"18","author":"E Kotkowski","year":"2018","unstructured":"Kotkowski, E., Price, L. R., Fox, P. M., et al. (2018). The hippocampal network model: A transdiagnostic metaconnectomic approach. Neuroimage Clinical, 18, 115\u2013129. https:\/\/doi.org\/10.1016\/j.nicl.2018.01.002","journal-title":"Neuroimage Clinical"},{"issue":"7","key":"9614_CR39","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1001\/archpsyc.1992.01820070047007","volume":"49","author":"K Krishnan","year":"1992","unstructured":"Krishnan, K., McDonald, W. M., Escalona, P. R., et al. (1992). Magnetic Resonance Imaging of the Caudate Nuclei in Depression. Archives of General Psychiatry, 49(7), 533\u2013557. https:\/\/doi.org\/10.1001\/archpsyc.1992.01820070047007","journal-title":"Archives of General Psychiatry"},{"issue":"1","key":"9614_CR40","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1385\/ni:3:1:065","volume":"3","author":"AR Laird","year":"2005","unstructured":"Laird, A. R., Lancaster, J. L., & Fox, P. T. (2005). BrainMap: The social evolution of a functional neuroimaging database. Neuroinformatics, 3(1), 65\u201378. https:\/\/doi.org\/10.1385\/ni:3:1:065","journal-title":"Neuroinformatics"},{"key":"9614_CR41","doi-asserted-by":"publisher","first-page":"23","DOI":"10.3389\/fninf.2012.00023","volume":"6","author":"JL Lancaster","year":"2012","unstructured":"Lancaster, J. L., Laird, A. R., Eickhoff, S. B., et al. (2012). Automated regional behavioral analysis for human brain images. Frontiers in Neuroinformatics, 6, 23. https:\/\/doi.org\/10.3389\/fninf.2012.00023","journal-title":"Frontiers in Neuroinformatics"},{"issue":"2","key":"9614_CR42","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1093\/schbul\/sbm158","volume":"34","author":"SM Lawrie","year":"2008","unstructured":"Lawrie, S. M., McIntosh, A. M., Hall, J., et al. (2008). Brain structure and function changes during the development of schizophrenia: The evidence from studies of subjects at increased genetic risk. Schizophrenia Bulletin, 34(2), 330\u2013340. https:\/\/doi.org\/10.1093\/schbul\/sbm158","journal-title":"Schizophrenia Bulletin"},{"key":"9614_CR43","doi-asserted-by":"publisher","first-page":"137","DOI":"10.3389\/fnagi.2016.00137","volume":"8","author":"K Li","year":"2016","unstructured":"Li, K., Laird, A. R., Price, L. R., et al. (2016). Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades. Front in Aging Neuroscience, 8, 137. https:\/\/doi.org\/10.3389\/fnagi.2016.00137","journal-title":"Front in Aging Neuroscience"},{"key":"9614_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2021.102583","volume":"30","author":"D Liloia","year":"2021","unstructured":"Liloia, D., Mancuso, L., Uddin, L. Q., et al. (2021). Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence. Neuroimage Clinical, 30, 102583. https:\/\/doi.org\/10.1016\/j.nicl.2021.102583","journal-title":"Neuroimage Clinical"},{"key":"9614_CR45","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1016\/j.nicl.2016.04.008","volume":"11","author":"Y Lu","year":"2016","unstructured":"Lu, Y., Liang, H., Han, D., et al. (2016). The volumetric and shape changes of the putamen and thalamus in first episode, untreated major depressive disorder. Neuroimage Clinical, 11, 658\u2013666. https:\/\/doi.org\/10.1016\/j.nicl.2016.04.008","journal-title":"Neuroimage Clinical"},{"key":"9614_CR46","doi-asserted-by":"publisher","first-page":"2299","DOI":"10.1016\/S0140-6736(18)31948-2","volume":"10161","author":"GS Malhi","year":"2018","unstructured":"Malhi, G. S., & Mann, J. J. (2018). Depression. The Lancet, 10161, 2299\u20132312. https:\/\/doi.org\/10.1016\/S0140-6736(18)31948-2","journal-title":"The Lancet"},{"key":"9614_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117220","volume":"222","author":"L Mancuso","year":"2020","unstructured":"Mancuso, L., Fornito, A., Costa, T., et al. (2020). A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders. NeuroImage, 222, 117220. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.117220","journal-title":"NeuroImage"},{"key":"9614_CR48","unstructured":"Mango [Software edition 4.1]. (2019). Retrieved from http:\/\/ric.uthscsa.edu\/mango\/"},{"key":"9614_CR49","doi-asserted-by":"publisher","first-page":"379","DOI":"10.3389\/fneur.2017.00739","volume":"8","author":"J Manuello","year":"2017","unstructured":"Manuello, J., Nani, A., Premi, E., et al. (2017). The Pathoconnectivity Profile of Alzheimer\u2019s Disease: A Morphometric Coalteration Network Analysis. Frontiers in Neurology, 8, 379. https:\/\/doi.org\/10.3389\/fneur.2017.00739","journal-title":"Frontiers in Neurology"},{"issue":"3","key":"9614_CR50","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1111\/j.1600-0447.2007.01033.x","volume":"116","author":"LB Marangell","year":"2007","unstructured":"Marangell, L. B., Martinez, M., Jurdi, R. A., et al. (2007). Neurostimulation therapies in depression: A review of new modalities. Acta Psychiatrica Scandinavica, 116(3), 174\u2013181. https:\/\/doi.org\/10.1111\/j.1600-0447.2007.01033.x","journal-title":"Acta Psychiatrica Scandinavica"},{"issue":"5","key":"9614_CR51","doi-asserted-by":"publisher","first-page":"651","DOI":"10.1016\/j.neuron.2005.02.014","volume":"45","author":"HS Mayberg","year":"2005","unstructured":"Mayberg, H. S., Lozano, A. M., Voon, V., et al. (2005). Deep Brain Stimulation for Treatment-Resistant Depression. Neuron, 45(5), 651\u2013660. https:\/\/doi.org\/10.1016\/j.neuron.2005.02.014","journal-title":"Neuron"},{"issue":"8","key":"9614_CR52","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1001\/jamapsychiatry.2013.143","volume":"70","author":"CL McGrath","year":"2013","unstructured":"McGrath, C. L., Kelley, M. E., Holtzheimer, P. E., et al. (2013). Toward a Neuroimaging Treatment Selection Biomarker for Major Depressive Disorder. JAMA Psychiatry, 70(8), 821\u2013829. https:\/\/doi.org\/10.1001\/jamapsychiatry.2013.143","journal-title":"JAMA Psychiatry"},{"issue":"1","key":"9614_CR53","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1001\/jamapsychiatry.2016.2783","volume":"74","author":"VI M\u00fcller","year":"2017","unstructured":"M\u00fcller, V. I., Cieslik, E. C., Serbanescu, I., et al. (2017). Altered Brain Activity in Unipolar Depression Revisited: Meta-analyses of Neuroimaging Studies. JAMA Psychiatry, 74(1), 47\u201355. https:\/\/doi.org\/10.1001\/jamapsychiatry.2016.2783","journal-title":"JAMA Psychiatry"},{"issue":"5","key":"9614_CR54","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1002\/ajmg.b.31196","volume":"156B","author":"RL Olvera","year":"2011","unstructured":"Olvera, R. L., Bearden, C. E., Velligan, D. I., et al. (2011). Common Genetic Influences on Depression, Alcohol and Substance Use Disorders in Mexican-American Families. American Journal of Medical Genetics Part b: Neuropsychiatric Genetics, 156B(5), 561\u2013568. https:\/\/doi.org\/10.1002\/ajmg.b.31196","journal-title":"American Journal of Medical Genetics Part b: Neuropsychiatric Genetics"},{"issue":"3","key":"9614_CR55","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1002\/hbm.20182","volume":"27","author":"RS Patel","year":"2006","unstructured":"Patel, R. S., Bowman, F. D., & Riling, J. K. (2006). A Bayesian approach to determining connectivity of the human brain. Human Brain Mapping, 27(3), 267\u2013276. https:\/\/doi.org\/10.1002\/hbm.20182","journal-title":"Human Brain Mapping"},{"key":"9614_CR56","doi-asserted-by":"publisher","unstructured":"Reid, A.T., Bzdok, D., Genon, S., et al: (2015). ANIMA: A data-sharing initiative for neuroimaging meta-analyses. Neuroimage, 124(B), 1245\u20131253. https:\/\/doi.org\/10.1016\/j.neuroimage.2015.07.060","DOI":"10.1016\/j.neuroimage.2015.07.060"},{"issue":"12","key":"9614_CR57","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.1016\/j.bpsc.2020.12.002","volume":"6","author":"AL Rodrigue","year":"2021","unstructured":"Rodrigue, A. L., Mastrovito, D., Esteban, O., et al. (2021). Searching for Imaging Biomarkers of Psychotic Dysconnectivity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(12), 1135\u20131144. https:\/\/doi.org\/10.1016\/j.bpsc.2020.12.002","journal-title":"Biological Psychiatry: Cognitive Neuroscience and Neuroimaging"},{"issue":"2","key":"9614_CR58","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1016\/j.jad.2011.08.001","volume":"140","author":"J Sacher","year":"2012","unstructured":"Sacher, J., Neumann, J., F\u00fcnfst\u00fcck, T., et al. (2012). Mapping the depressed brain: A meta-analysis of structural and functional alterations in major depressive disorder. Journal of Affective Disorders, 140(2), 142\u2013148. https:\/\/doi.org\/10.1016\/j.jad.2011.08.001","journal-title":"Journal of Affective Disorders"},{"key":"9614_CR59","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.neulet.2016.07.028","volume":"630","author":"C Sanchis-Segura","year":"2016","unstructured":"Sanchis-Segura, C., Cruz-G\u00f3mez, A. J., Belenguer, A., et al. (2016). Increased regional gray matter atrophy and enhanced functional connectivity in male multiple sclerosis patients. Neuroscience Letters, 630, 154\u2013157. https:\/\/doi.org\/10.1016\/j.neulet.2016.07.028","journal-title":"Neuroscience Letters"},{"issue":"1","key":"9614_CR60","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.neuron.2009.03.024","volume":"62","author":"WW Seeley","year":"2009","unstructured":"Seeley, W. W., Crawford, R. K., Zhou, J., et al. (2009). Neurodegenerative diseases target large-scale human brain networks. Neuron, 62(1), 42\u201352. https:\/\/doi.org\/10.1016\/j.neuron.2009.03.024","journal-title":"Neuron"},{"issue":"11","key":"9614_CR61","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1101\/gr.1239303","volume":"13","author":"P Shannon","year":"2003","unstructured":"Shannon, P., Markiel, A., Ozier, O., et al. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 2498\u20132504. https:\/\/doi.org\/10.1101\/gr.1239303","journal-title":"Genome Research"},{"issue":"31","key":"9614_CR62","doi-asserted-by":"publisher","first-page":"13040","DOI":"10.1073\/pnas.0905267106","volume":"106","author":"SM Smith","year":"2009","unstructured":"Smith, S. M., Fox, P. T., Miller, K. L., et al. (2009). Correspondence of the brain\u2019s functional architecture during activation and rest. PNAS, 106(31), 13040\u201313045. https:\/\/doi.org\/10.1073\/pnas.0905267106","journal-title":"PNAS"},{"key":"9614_CR63","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","volume":"23","author":"SM Smith","year":"2004","unstructured":"Smith, S. M., Jenkinson, M., Woolrich, M. W., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23, S208-219. https:\/\/doi.org\/10.1016\/j.neuroimage.2004.07.051","journal-title":"NeuroImage"},{"issue":"2","key":"9614_CR64","doi-asserted-by":"publisher","first-page":"875","DOI":"10.1016\/j.neuroimage.2010.08.063","volume":"54","author":"SM Smith","year":"2011","unstructured":"Smith, S. M., Miller, K. L., Salimi-Khorshidi, G., et al. (2011). Network modelling methods for FMRI. NeuroImage, 54(2), 875\u2013891. https:\/\/doi.org\/10.1016\/j.neuroimage.2010.08.063","journal-title":"NeuroImage"},{"issue":"2","key":"9614_CR65","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1162\/netn_e_00052","volume":"2","author":"O Sporns","year":"2018","unstructured":"Sporns, O., & Bassett, D. S. (2018). Editorial: New Trends in Connectomics. Network Neuroscience, 2(2), 125\u2013127. https:\/\/doi.org\/10.1162\/netn_e_00052","journal-title":"Network Neuroscience"},{"issue":"4","key":"9614_CR66","doi-asserted-by":"publisher","first-page":"1846","DOI":"10.1002\/hbm.23486","volume":"38","author":"E Sprooten","year":"2017","unstructured":"Sprooten, E., Rasgon, A., Goodman, M., et al. (2017). Addressing reverse inference in psychiatric neuroimaging: Meta-analyses of task-related brain activation in common mental disorders. Human Brain Mapping, 38(4), 1846\u20131864. https:\/\/doi.org\/10.1002\/hbm.23486","journal-title":"Human Brain Mapping"},{"key":"9614_CR67","doi-asserted-by":"publisher","first-page":"765","DOI":"10.1006\/nimg.2002.1131","volume":"16","author":"PE Turkeltaub","year":"2002","unstructured":"Turkeltaub, P. E., Eden, G. F., Jones, K. M., et al. (2002). Meta-analysis of the Functional Neuroanatomy of Single-Word Reading: Method and Validation. NeuroImage, 16, 765\u2013780. https:\/\/doi.org\/10.1006\/nimg.2002.1131","journal-title":"NeuroImage"},{"issue":"8","key":"9614_CR68","doi-asserted-by":"publisher","first-page":"3308","DOI":"10.1002\/hbm.24078","volume":"39","author":"T Vanasse","year":"2018","unstructured":"Vanasse, T., Fox, P. M., Barron, D. S., et al. (2018). BrainMap VBM: An Environment for Structural Meta-analysis. Human Brain Mapping, 39(8), 3308\u20133325. https:\/\/doi.org\/10.1002\/hbm.24078","journal-title":"Human Brain Mapping"},{"key":"9614_CR69","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1038\/s42003-021-01832-9","volume":"4","author":"TJ Vanasse","year":"2021","unstructured":"Vanasse, T. J., Fox, P. T., Fox, P. M., et al. (2021). Brain pathology recapitulates physiology: A network meta-analysis. Communications Biology, 4, 301. https:\/\/doi.org\/10.1038\/s42003-021-01832-9","journal-title":"Communications Biology"},{"issue":"11","key":"9614_CR70","doi-asserted-by":"publisher","first-page":"1128","DOI":"10.1001\/archgenpsychiatry.2010.144","volume":"67","author":"TA Victor","year":"2010","unstructured":"Victor, T. A., Furey, M. L., Fromm, S. J., et al. (2010). Relationship Between Amygdala Responses to Masked Faces and Mood State and Treatment in Major Depressive Disorder. Archives of General Psychiatry, 67(11), 1128\u20131138. https:\/\/doi.org\/10.1001\/archgenpsychiatry.2010.144","journal-title":"Archives of General Psychiatry"},{"key":"9614_CR71","doi-asserted-by":"publisher","first-page":"10401","DOI":"10.1038\/s41598-017-08944-5","volume":"7","author":"W Wang","year":"2017","unstructured":"Wang, W., Zhao, Y., Hu, X., et al. (2017). Conjoint and dissociated structural and functional abnormalities in first-episode drug-naive patients with major depressive disorder: A multimodal meta-analysis. Scientific Reports, 7, 10401. https:\/\/doi.org\/10.1038\/s41598-017-08944-5","journal-title":"Scientific Reports"},{"issue":"10","key":"9614_CR72","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/j.tins.2013.06.007","volume":"36","author":"JD Warren","year":"2013","unstructured":"Warren, J. D., Rohrer, J. D., Schott, J. M., et al. (2013). Molecular nexopathies: A new paradigm of neurodegenerative disease. Trends in Neurosciences, 36(10), 561\u2013569. https:\/\/doi.org\/10.1016\/j.tins.2013.06.007","journal-title":"Trends in Neurosciences"},{"issue":"6684","key":"9614_CR73","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1038\/30918","volume":"393","author":"D Watts","year":"1998","unstructured":"Watts, D., & Strogatz, S. (1998). Collective dynamics of \u2018small-world\u2019 networks. Nature, 393(6684), 440\u2013442. https:\/\/doi.org\/10.1038\/30918","journal-title":"Nature"},{"key":"9614_CR74","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2022.1780","author":"NR Winter","year":"2022","unstructured":"Winter, N. R., Leenings, R., Ernsting, J., et al. (2022). Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder Across Neuroimaging Modalities. JAMA Psychiatry, Online Edition. https:\/\/doi.org\/10.1001\/jamapsychiatry.2022.1780","journal-title":"JAMA Psychiatry, Online Edition."},{"key":"9614_CR75","unstructured":"World Health Organization. (2021). Depression and Other Common Mental Disorders: Global Health Estimates. License: CC BY-NC-SA 3.0 IGO. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/depression"},{"issue":"3","key":"9614_CR76","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1152\/jn.00338.2011","volume":"106","author":"BTT Yeo","year":"2011","unstructured":"Yeo, B. T. T., Krienen, F. M., Sepulcre, J., et al. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106(3), 1125\u20131165. https:\/\/doi.org\/10.1152\/jn.00338.2011","journal-title":"Journal of Neurophysiology"},{"issue":"6","key":"9614_CR77","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1016\/j.neuron.2012.03.004","volume":"73","author":"J Zhou","year":"2012","unstructured":"Zhou, J., Gennatas, E. D., Kramer, J. H., et al. (2012). Predicting Regional Neurodegeneration from the Healthy Brain Functional Connectome. Neuron, 73(6), 1216\u20131227. https:\/\/doi.org\/10.1016\/j.neuron.2012.03.004","journal-title":"Neuron"}],"container-title":["Neuroinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12021-022-09614-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12021-022-09614-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12021-022-09614-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T04:16:32Z","timestamp":1681186592000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12021-022-09614-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,5]]},"references-count":77,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["9614"],"URL":"https:\/\/doi.org\/10.1007\/s12021-022-09614-2","relation":{},"ISSN":["1539-2791","1559-0089"],"issn-type":[{"value":"1539-2791","type":"print"},{"value":"1559-0089","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,5]]},"assertion":[{"value":"6 November 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 December 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to Participate"}},{"value":"All authors report no financial or non-financial interests related directly or indirectly to this submission.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}}]}}