title: Limbic-frontal circuitry in major depression: a path modeling metanalysis.
abstract: This paper reports the results of an across lab metanalysis of effective connectivity in major depression (MDD). Using FDG PET data and Structural Equation Modeling, a formal depression model was created to explicitly test current theories of limbic-cortical dysfunction in MDD and to characterize at the path level potential sources of baseline variability reported in this patient population. A 7-region model consisting of lateral prefrontal cortex (latF9), anterior thalamus (aTh), anterior cingulate (Cg24), subgenual cingulate (Cg25), orbital frontal cortex (OF11), hippocampus (Hc), and medial frontal cortex (mF10) was tested in scans of 119 depressed patients and 42 healthy control subjects acquired during three separate studies at two different institutions. A single model, based on previous theory and supported by anatomical connectivity literature, was stable for the three groups of depressed patients. Within the context of this model, path differences among groups as a function of treatment response characteristics were also identified. First, limbic-cortical connections (latF9-Cg25-OF11-Hc) differentiated drug treatment responders from nonresponders. Second, nonresponders showed additional abnormalities in limbic-subcortical pathways (aTh-Cg24-Cg25-OF11-Hc). Lastly, more limited limbic-cortical (Hc-latF9) and cortical-cortical (OF11-mF10) path differences differentiated responders to cognitive behavioral therapy (CBT) from responders to pharmacotherapy. We conclude that the creation of such models is a first step toward full characterization of the depression phenotype at the neural systems level, with implications for the future development of brain-based algorithms to determine optimal treatment selection for individual patients.
authors.affiliation: Rotman Research Institute, Baycrest Centre for Geriatric Care, 3560 Bathurst Street, Toronto, Ontario, Canada M6A 2E1.
authors.forename: D A
authors.initials: DA
authors.lastname: Seminowicz
authors.forename: H S
authors.initials: HS
authors.lastname: Mayberg
authors.forename: A R
authors.initials: AR
authors.lastname: McIntosh
authors.forename: K
authors.initials: K
authors.lastname: Goldapple
authors.forename: S
authors.initials: S
authors.lastname: Kennedy
authors.forename: Z
authors.initials: Z
authors.lastname: Segal
authors.forename: S
authors.initials: S
authors.lastname: Rafi-Tari
mesh_terms: D000465:Algorithms; D018687:Antidepressive Agents, Second-Generation / Q000627:therapeutic use; D003865:Major Depressive Disorder / Q000000981:diagnostic imaging / Q000188:drug therapy / Q000473:pathology*; D004351:Drug Resistance; D004565:Electroconvulsive Therapy; D019788:Fluorodeoxyglucose F18; D005625:Frontal Lobe / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008032:Limbic System / Q000473:pathology*; D008959:Models, Neurological; D009415:Nerve Net / Q000473:pathology*; D017374:Paroxetine / Q000627:therapeutic use; D019275:Radiopharmaceuticals; D014055:Tomography, Emission-Computed
chemical_list: D018687:Antidepressive Agents, Second-Generation; D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18; D017374:Paroxetine