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Exploratory structural equation modeling of resting-state fMRI: applicability of group models to individual subjects.

ABSTRACT: The extension of group-level connectivity methods to individual subjects remains a hurdle for statistical analyses of neuroimaging data. Previous group analyses of positron emission tomography data in clinically depressed patients, for example, have shown that resting-state connectivity prior to therapy predicts how patients eventually respond to pharmacological and cognitive-behavioral therapy. Such applications would be considerably more informative for clinical decision making if these connectivity methods could be extended into the individual subject domain. To test such an extension, 46 treatment-naïve depressed patients were enrolled in an fMRI study to model baseline resting-state functional connectivity. Resting-state fMRI scans were acquired and submitted to exploratory structural equation modeling (SEM) to derive the optimal group connectivity model. Jackknife and split sample tests confirm that group model was highly reproducible, and path weights were consistent across the best five group models. When this model was applied to data from individual subjects, 85% of patients fit the group model. Histogram analysis of individual subjects' paths indicate that some paths are better representative of group membership. These results suggest that exploratory SEM is a viable technique for neuroimaging connectivity analyses of individual subjects' resting-state fMRI data.

SUBMITTER: James GA

PROVIDER: S-EPMC2653594 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

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Exploratory structural equation modeling of resting-state fMRI: applicability of group models to individual subjects.

James G Andrew GA Kelley Mary E ME Craddock R Cameron RC Holtzheimer Paul E PE Dunlop Boadie W BW Nemeroff Charles B CB Mayberg Helen S HS Hu Xiaoping P XP

NeuroImage 20090107 3

The extension of group-level connectivity methods to individual subjects remains a hurdle for statistical analyses of neuroimaging data. Previous group analyses of positron emission tomography data in clinically depressed patients, for example, have shown that resting-state connectivity prior to therapy predicts how patients eventually respond to pharmacological and cognitive-behavioral therapy. Such applications would be considerably more informative for clinical decision making if these connec ...[more]

PMID: 19162206

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Project description:PurposeQuality of life (QOL) is an important clinical outcome for patients with schizophrenia, and recent studies have focused on subjective QOL. We evaluated the causal relationship between psychosocial aspect of subjective QOL, symptoms, cognitive functions, and salience network (SN) dysfunction in schizophrenia using structural equation modeling (SEM).Patients and methodsWe performed a cross-sectional study of 21 patients with symptomatically stabilized schizophrenia and 21 age-, sex-, and education level-matched healthy controls who underwent resting-state functional magnetic resonance imaging. We evaluated SN dysfunction in schizophrenia using independent component analysis (ICA). We rated participant psychopathology using the Positive and Negative Syndrome Scale (PANSS), the Brief Assessment of Cognition in Schizophrenia (BACS), and the Calgary Depression Scale for Schizophrenia (CDSS). We rated psychosocial aspect of subjective QOL using the Schizophrenia Quality of Life Scale (SQLS) psychosocial subscale. We applied SEM to examine the relationships between SN dysfunction, PANSS positive and negative scores, CDSS total scores, BACS composite scores, and SQLS psychosocial subscale scores.ResultsIn second-level analysis after group ICA, patient group had significant lower right pallidum functional connectivity (FC) within the SN than the controls did (Montreal Neurological Institute [MNI] [x y z] = [22 -2 -6]) (p = 0.027, family-wise error [FWE] corrected). In SEM, we obtained a good fit for an SEM model in which SN dysfunction causes depressed mood, which in turn determines psychosocial aspect of subjective QOL (chi-squared p = 0.9, root mean square error of approximation (RMSEA) < 0.001, comparative fit index [CFI] = 1.00, and standardized root mean square residual [SRMR]= 0.020).ConclusionWe found a continuous process by which SN dysfunction causes depressed moods that determine psychosocial aspect of subjective QOL in schizophrenia. This is the first report that offers a unified explanation of functional neuroimaging, symptoms, and outcomes. Future studies combining neuroimaging techniques and clinical assessments would elucidate schizophrenia's pathogenesis.

Dataset Information

Exploratory structural equation modeling of resting-state fMRI: applicability of group models to individual subjects.

Publications

Exploratory structural equation modeling of resting-state fMRI: applicability of group models to individual subjects.

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