TY - JOUR
T1 - Failure to segregate emotional processing from cognitive and sensorimotor processing in major depression
AU - Epstein, Jane
AU - Perez, David Lewis
AU - Ervin, Kate
AU - Pan, Hong
AU - Kocsis, James Howard
AU - Butler, Tracy
AU - Stern, Emily
AU - Silbersweig, David Alan
PY - 2011/9/30
Y1 - 2011/9/30
N2 - Most functional neuroimaging studies of major depressive disorder (MDD) employ univariate methods of statistical analysis to localize abnormalities of neural activity. Less has been done to investigate functional relations between these regions, or with regions not usually implicated in depression. Examination of intraneuronal and interneural network relations is important for the advancement of emerging network models for MDD. Principal component analysis (PCA), a multivariate statistical method, was used to examine differences in functional connectivity between 10 unmedicated patients with MDD and 12 healthy subjects engaged in a positive word viewing task. In healthy subjects, principal component (PC) 1 (33% variance) revealed functional connectivity of task-specific sensory, linguistic, and motor regions, along with functional anticorrelations in the default mode network; PC2 (10% variance) displayed functional connectivity of areas involved in emotional processing. This segregation of functions did not occur in the depressed group, where regions involved in emotional functions appeared in PC1 (34% variance) co-varying with those involved in linguistic, motor, and default mode network processing. The lack of segregation of emotional processing from cognitive and sensorimotor functions may represent a systems level neural substrate for a core phenomenon of depression: the interconnection of affective disturbance with experience, cognition, and behavior.
AB - Most functional neuroimaging studies of major depressive disorder (MDD) employ univariate methods of statistical analysis to localize abnormalities of neural activity. Less has been done to investigate functional relations between these regions, or with regions not usually implicated in depression. Examination of intraneuronal and interneural network relations is important for the advancement of emerging network models for MDD. Principal component analysis (PCA), a multivariate statistical method, was used to examine differences in functional connectivity between 10 unmedicated patients with MDD and 12 healthy subjects engaged in a positive word viewing task. In healthy subjects, principal component (PC) 1 (33% variance) revealed functional connectivity of task-specific sensory, linguistic, and motor regions, along with functional anticorrelations in the default mode network; PC2 (10% variance) displayed functional connectivity of areas involved in emotional processing. This segregation of functions did not occur in the depressed group, where regions involved in emotional functions appeared in PC1 (34% variance) co-varying with those involved in linguistic, motor, and default mode network processing. The lack of segregation of emotional processing from cognitive and sensorimotor functions may represent a systems level neural substrate for a core phenomenon of depression: the interconnection of affective disturbance with experience, cognition, and behavior.
KW - Default mode network
KW - FMRI
KW - Functional connectivity
KW - Neuroimaging
KW - Principal component analysis
KW - Ventral striatum
UR - http://www.scopus.com/inward/record.url?scp=80051681138&partnerID=8YFLogxK
U2 - 10.1016/j.pscychresns.2011.01.012
DO - 10.1016/j.pscychresns.2011.01.012
M3 - Article
C2 - 21764265
AN - SCOPUS:80051681138
SN - 0925-4927
VL - 193
SP - 144
EP - 150
JO - Psychiatry Research - Neuroimaging
JF - Psychiatry Research - Neuroimaging
IS - 3
ER -