Predicting clinical responses in major depression using intrinsic functional connectivity

NeuroReport

Volumn 26, Issue 12, 2015, Pages 675-680

  Qin, Jian ^a   Shen, Hui ^a   Zeng, Ling Li ^a   Jiang, Weixiong ^b   Liu, Li ^c   Hu, Dewen ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^b HUNAN FIRST NORMAL UNIVERSITY   (China)

^c CHINA MEDICAL UNIVERSITY   (China)

Author keywords

functional connectivity magnetic resonance imaging; major depressive disorder; medication status; multivariate pattern analysis; resting state

Indexed keywords

SEROTONIN NORADRENALIN REUPTAKE INHIBITOR; SEROTONIN UPTAKE INHIBITOR;

ADULT; ARTICLE; BASAL GANGLION; BRAIN FUNCTION; CEREBELLUM; CLASSIFIER; CLINICAL ARTICLE; CONNECTOME; CONTROLLED STUDY; DISEASE COURSE; DISEASE SEVERITY; EMOTION; FEMALE; FOLLOW UP; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; FUSIFORM GYRUS; HUMAN; INFERIOR TEMPORAL GYRUS; INSULA; MAJOR DEPRESSION; MALE; MENTAL PATIENT; MULTIVARIATE ANALYSIS; MULTIVARIATE PATTERN ANALYSIS; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; PARIETAL CORTEX; POSTERIOR CINGULATE; POSTERIOR INSULA; PRECUNEUS; PREDICTION; PRIMARY MOTOR CORTEX; PRIORITY JOURNAL; RESTING STATE FUNCTIONAL CONNECTIVITY NUCLEAR MAGNETIC RESONANCE IMAGING; STRUCTURED INTERVIEW; SUPPLEMENTARY MOTOR AREA; SUPPORT VECTOR MACHINE; TEMPORAL CORTEX; THALAMUS; TREATMENT DURATION; TREATMENT RESPONSE; BRAIN; BRAIN MAPPING; DEPRESSIVE DISORDER, MAJOR; METABOLISM; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PREDICTIVE VALUE; PROCEDURES; PSYCHOLOGY; TREATMENT OUTCOME; YOUNG ADULT;

ADULT; BRAIN; BRAIN MAPPING; DEPRESSIVE DISORDER, MAJOR; FEMALE; FOLLOW-UP STUDIES; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; NERVE NET; PREDICTIVE VALUE OF TESTS; TREATMENT OUTCOME; YOUNG ADULT;

EID: 84937686418     PISSN: 09594965     EISSN: 1473558X     Source Type: Journal    
DOI: 10.1097/WNR.0000000000000407     Document Type: Article

References (28)

1. Zeng LL, Shen H, Liu L, Hu D. Unsupervised classification of major depression using functional connectivity MRI. Hum Brain Mapp 2014; 35: 1630-1641
2. Drevets WC, Price JL, Furey ML. Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Struct Funct 2008; 213: 93-118
3. Craddock RC, Holtzheimer PE 3rd, Hu XP, Mayberg HS. Disease state prediction from resting state functional connectivity. Magn Reson Med 2009; 62: 1619-1628
4. Zeng LL, Shen H, Liu L, Wang L, Li B, Fang P, et al. Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain 2012; 135 (Pt 5): 1498-1507
5. Delaveau P, Jabourian M, Lemogne C, Guionnet S, Bergouignan L, Fossati P. Brain effects of antidepressants in major depression: a meta-Analysis of emotional processing studies. J Affect Disord 2011; 130: 66-74
6. Anand A, Li Y, Wang Y, Wu J, Gao S, Bukhari L, et al. Antidepressant effect on connectivity of the mood-regulating circuit: an FMRI study. Neuropsychopharmacology 2005; 30: 1334-1344
7. APA. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC: American Psychiatric Press; 2000
8. First MB, Spitzer RL, Gibbon M. Structured Clinical Interview for DSM-IV Axis 1 Disorder-Patient Edition (SCID-I/P). New York: State Psychiatric Institute; 1995
9. Fox MD, Zhang D, Snyder AZ, Raichle ME. The global signal and observed anticorrelated resting state brain networks. J Neurophysiol 2009; 101: 3270-3283
10. Dosenbach NU, Nardos B, Cohen AL, Fair DA, Power JD, Church JA, et al. Prediction of individual brain maturity using fMRI. Science 2010; 329: 1358-1361
11. Biostatistical Analysis. Upper Saddle River, New Jersey: Prentice Hall; 1996 1996 Upper Saddle River New Jersey Prentice Hall Zar JH
12. Guyon I, Elisseeff A. An introduction to variable and feature selection. J Mach Learn Res 2003; 3: 1157-1182
13. Mwangi B, Ebmeier KP, Matthews K, Steele JD. Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder. Brain 2012; 135 (Pt 5): 1508-1521
14. Mackiewicz A, Ratajczak W. Principal components analysis. Comput Geosci 1993; 19: 303-342
15. Vapnik V. The natures of statistical learning theory. New York: Springer-Verlag; 1995
16. Drucker H, Burges CJ, Kaufman L, Smola A, Vapnik V. Support vector regression machines. Adv Neural Inform Proc Syst 1997; 9: 155-161
17. Lehmann EL, Casella G. Theory of point estimation, 2nd ed. New York: Springer; 1998
18. Oquendo M, Baca-Garcia E, Artes-Rodriguez A, Perez-Cruz F, Galfalvy H, Blasco-Fontecilla H, et al. Machine learning and data mining: strategies for hypothesis generation. Mol Psychiatry 2012; 17: 956-959
19. Pereira F, Mitchell T, Botvinick M. Machine learning classifiers and fMRI: a tutorial overview. Neuroimage 2009; 45: S199
20. Costafreda SG, Chu C, Ashburner J, Fu CH. Prognostic and diagnostic potential of the structural neuroanatomy of depression. PloS one 2009; 4: e6353
21. Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007; 62: 429-437
22. Fossati P, Hevenor SJ, Graham SJ, Grady C, Keightley ML, Craik F, et al. In search of the emotional self: an fMRI study using positive and negative emotional words. Am J Psychiatry 2003; 160: 1938-1945
23. Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci USA 2010; 107: 11020-11025
24. Northoff G. Psychopathology and pathophysiology of the self in depression -neuropsychiatric hypothesis. J Affect Disord 2007; 104: 1-14
25. McCabe C, Mishor Z. Antidepressant medications reduce subcorticalcortical resting-state functional connectivity in healthy volunteers. Neuroimage 2011; 57: 1317-1323
26. Li B, Liu L, Friston KJ, Shen H, Wang L, Zeng L-L, et al. A treatment-resistant default mode subnetwork in major depression. Biol Psychiatry 2013; 74: 48-54
27. Lemogne CMH, Bergouignan L, Volle E, Delaveau P, Lehericy S. Selfreferential processing and the prefrontal cortex over the course of depression: a pilot study. J Affect Disord 2010; 124: 196-201
28. Farb NA AA, Bloch RT, Segal ZV. Mood-linked responses in medial prefrontal cortex predict relapse in patients with recurrent unipolar depression. Biol Psychiatry 2011; 70: 366-372