Reduced functional connectivity within and between ‘social’ resting state networks in autism spectrum conditions

doi:10.1093/scan/nss053 SCAN (2013) 8, 694 ^701 Reduced functional connectivity within and between social resting state networks in autism spectrum conditions Elisabeth A. H. von dem Hagen,1 Raliza S. Stoyanova,1 Simon Baron-Cohen,2 and Andrew J. Calder1 1 MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, UK and 2Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK Individuals with Autism Spectrum Conditions (ASC) have difficulties in social interaction and communication, which is reflected in hypoactivation of brain regions engaged in social processing, such as medial prefrontal cortex (mPFC), amygdala and insula. Resting state studies in ASC have identified reduced connectivity of the default mode network (DMN), which includes mPFC, suggesting that other resting state networks incorporating social brain regions may also be abnormal. Using Seed-based Connectivity and Group Independent Component Analysis (ICA) approaches, we looked at resting functional connectivity in ASC between specific social brain regions, as well as within and between whole networks incorporating these regions. We found reduced functional connectivity within the DMN in individuals with ASC, using both ICA and seed-based approaches. Two further networks identified by ICA, the salience network, incorporating the insula and a medial temporal lobe network, incorporating the amygdala, showed reduced inter-network connectivity. This was underlined by reduced seed-based connectivity between the insula and amygdala. The results demonstrate significantly reduced functional connectivity within and between resting state networks incorporating social brain regions. This reduced connectivity may result in difficulties in communication and integration of information across these networks, which could contribute to the impaired processing of social signals in ASC. Keywords: autism; resting state; fMRI INTRODUCTION Individuals with Autism Spectrum Conditions (ASC) are characterised by their difficulties in social interaction and communication, unusually repetitive patterns of behaviour, and extremely narrow interests. Their difficulties in social interaction and communication include abnormal eye contact, difficulties in maintaining a conversation, difficulties in reading emotions, gestures, and mental states and difficulties with the pragmatics of language (Baron-Cohen, 1995; Frith, 2001). Previous studies that have examined the neurobiological basis of social impairments in ASC have found reduced activity across several brain regions during a range of social tasks. A recent meta-analysis by Di Martino et al. (2009) identified these regions of hypoactivation during social tasks as comprising medial prefrontal cortex (mPFC), amygdala, insular cortex, angular gyrus/temporoparietal junction (TPJ) and posterior cingulate cortex (PCC). While some of these regions, such as mPFC, TPJ and the amygdala, have been studied extensively in ASC, others like the insula and PCC have only more recently been associated with ASC (Silani et al., 2008; Di Martino et al., 2009). Amygdala hypoactivation has been related to atypical emotional processing in individuals with ASC (Baron-Cohen et al., 1999; Ashwin et al., 2007), while a number of studies have identified reduced activation in mPFC and TPJ during theory-of-mind, social attention and gaze perception tasks (Castelli et al., 2002; Pelphrey et al., 2005). Although the role of PCC in ASC remains elusive and understudied, hypoactivation of the insula, which plays a key role in interoceptive processing and monitoring bodily states of arousal (Craig, 2002), has been linked to reduced emotional awareness of Received 30 November 2011; Accepted 18 April 2012 Advance Access publication 3 May 2012 We would like to thank the participants for volunteering their time, Sally Wheelwright and Michael Lombardo for help with participant recruitment, and the radiographers at the MRC Cognition & Brain Sciences Unit. Supported by the UK Medical Research Council (MC_US_A060_0017 to AJC and a program grant to SBC). Correspondence should be addressed to Elisabeth A. H. von dem Hagen, Medical Research Council, Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB1 3UF, UK. E-mail: the self and others in both typical controls and ASC (Silani et al., 2008). Interestingly, the areas of mPFC and TPJ implicated in ASC show remarkable overlap with the default mode network, one of the key ‘resting state’ brain networks comprising regions whose activity is highly correlated at rest (Shulman et al., 1997; Raichle et al., 2001; Buckner et al., 2008). As the brain regions subserving the default mode network (mPFC, PCC, angular gyrus/TPJ) display abnormal activation in ASC during specific cognitive tasks, some studies have considered whether abnormalities are also apparent in the intrinsic activity or connectivity of these regions at rest. A key advantage of the resting state over task-based measures is the absence of confounds associated with underlying differences in task performance, or differences in the way in which the task is executed. Resting state studies of ASC identified reduced functional connectivity or reduced activity at rest within regions of the default mode network (Cherkassky et al., 2006; Kennedy et al., 2006; Kennedy and Courchesne, 2008b; Monk et al., 2009; Assaf et al., 2010), with the most consistent finding involving reduced activation of, or connectivity with, mPFC. Although the most widely studied resting state network, the default mode is only one of many networks that show consistent, highly correlated activity at rest. Methodological advances, such as the application of independent component analyses (ICA) to resting state data, have enabled the identification of dozens of functionally relevant resting state networks (Beckmann et al., 2005; Damoiseaux et al., 2006; Smith et al., 2009; Allen et al., 2011). The presence of these networks is highly reliable across individuals, and connectivity within and between these networks has been shown to differ in certain neuropsychiatric conditions (Greicius et al., 2004; Jafri et al., 2008), as well as within the healthy ageing population (Damoiseaux et al., 2008; Allen et al., 2011). Importantly, it is becoming increasingly clear that these ‘resting’ networks also reflect ‘functional’ networks, i.e. sets of brain regions that are engaged during specific cognitive or mental processes (Smith et al., 2009). Furthermore, behavioural measures relating to the function a ß The Author(s) 2012. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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