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Sundermann B, Olde lütke Beverborg M, Pfleiderer B.2014. Meta-analysis of resting-state fMRI in depression: generating spatial hypotheses for potential clinical applications. PeerJ PrePrints2:e412v1https://doi.org/10.7287/peerj.preprints.412v1
Information derived from functional magnetic resonance imaging (fMRI) during wakeful rest has been introduced as a candidate diagnostic biomarker in unipolar major depressive disorder (MDD). Multiple reports of resting state fMRI in MDD describe group effects. Such prior knowledge can be adopted to pre-select potentially discriminating features, for example for diagnostic classification models with the aim to improve diagnostic accuracy. Purpose of this analysis was to consolidate spatial information about alterations of spontaneous brain activity in MDD to serve such feature selection and as a secondary aim to improve understanding of disease mechanisms. 32 studies were included in final analyses. Coordinates extracted from the original reports were assigned to two categories based on directionality of findings. Meta-analyses were calculated using the non-additive activation likelihood estimation approach with coordinates organized by subject group to account for non-independent samples. Results were compared with established resting state networks (RSNs) and spatial representations of recently introduced temporally independent functional modes (TFMs) of spontaneous brain activity. Converging evidence revealed a distributed pattern of brain regions with increased or decreased spontaneous activity in MDD. The most distinct finding was hyperactivity/ hyperconnectivity presumably reflecting the interaction of cortical midline structures (posterior default mode network components associated with self-referential processing and the subgenual anterior cingulate cortex) with lateral frontal areas related to externally-directed cognition. One particular TFM seems to better comprehend the findings than classical RSNs. Alterations that can be captured by resting state fMRI show considerable overlap with those identifiable with other neuroimaging modalities though differing in some aspects.
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Sundermann B, Olde lütke Beverborg M and Pfleiderer B (2014) Toward literature-based feature selection for diagnostic classification: a meta-analysis of resting-state fMRI in depression. Front. Hum. Neurosci. 8:692. doi: 10.3389/fnhum.2014.00692