Graph theory reveals hyper-functionality in visual cortices of Seasonal Affective Disorder patients. (February 2015)

• Record Type: Journal Article
• Authors: Borchardt, Viola; Krause, Anna Linda; Starck, Tuomo; Nissilä, Juuso; Timonen, Markku; Kiviniemi, Vesa; Walter, Martin
• Is Part Of: World journal of biological psychiatry. Volume 16:Number 2(2015)
• Page Start: 123
• Page End: 134
• Publication Date: 2015-02
• Subjects: Biological psychiatry -- Periodicals; Biological Psychiatry -- Periodicals; 616.89
• DOI: 10.3109/15622975.2014.966144
• Languages: English
• ISSNs: 1562-2975

Abstract

<abstract> <title>Abstract</title> <p> <italic>Objectives.</italic> Seasonal affective disorder (SAD) is a subtype of recurrent unipolar or bipolar depressive disorder with a higher prevalence in winter than in summer. The biological underpinnings of SAD are so far poorly understood. Studies examining SAD have found disturbances between the molecular and connectivity scales. The aim of the study was to explore changes in functional connectivity typical for SAD. <italic>Methods.</italic> We investigated unmedicated, untreated SAD patients and healthy controls using resting-state functional magnetic resonance imaging (rs-fMRI) utilizing graph theory, a data driven and hypothesis free approach, to model functional networks of the brain. <italic>Results.</italic> Comparing whole brain network properties using graph theory we observed globally affected network topologies with increasing pathlength in SAD. Nodal changes, however, were highly restricted to bilateral inferior occipital cortex. Interestingly, we found a lateralization where hyper-connectedness was restricted to right inferior occipital cortex and hyper-efficiency was found in the left inferior occipital cortex. Furthermore, we found these nodes became more "hub like" in patients, suggesting a greater functional role. <italic>Conclusions.</italic> Our work stresses the importance of abnormal intrinsic processing during rest, primarily affecting visual areas and subsequently changing whole brain networks, and thus providing an important hint towards potential future therapeutic approaches.</p> </abstract>