Kennedy DP, Redcay E, Courchesne E. Failing to deactivate: resting functional abnormalities in autism. Proc Natl Acad Sci USA 103: 8275-8280

Department of Neurosciences, and Psychology, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 06/2006; 103(21):8275-80. DOI: 10.1073/pnas.0600674103
Source: PubMed


Several regions of the brain (including medial prefrontal cortex, rostral anterior cingulate, posterior cingulate, and precuneus) are known to have high metabolic activity during rest, which is suppressed during cognitively demanding tasks. With functional magnetic resonance imaging (fMRI), this suppression of activity is observed as "deactivations," which are thought to be indicative of an interruption of the mental activity that persists during rest. Thus, measuring deactivation provides a means by which rest-associated functional activity can be quantitatively examined. Applying this approach to autism, we found that the autism group failed to demonstrate this deactivation effect. Furthermore, there was a strong correlation between a clinical measure of social impairment and functional activity within the ventral medial prefrontal cortex. We speculate that the lack of deactivation in the autism group is indicative of abnormal internally directed processes at rest, which may be an important contribution to the social and emotional deficits of autism.

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    • "The informative role of the DMN in diagnostic classification was not surprising, given extensive evidence of DMN anomalies in ASD. These include fMRI findings indicating failure to enter the default mode in ASD (Kennedy et al., 2006; Murdaugh et al., 2012), as well as numerous fcMRI reports of atypical connectivity of the DMN (Assaf et al., 2010; Courchesne et al., 2005; Di Martino et al., 2013; Keown et al., 2013; Monk et al., 2009; Redcay et al., 2013; Uddin et al., 2013b; von dem Hagen et al., 2012; Washington et al., 2013; Zielinski et al., 2012). Functionally, the DMN is considered to relate to self-referential cognition, including domains of known impairment in ASD, such as theory of mind and affective decision making (Andrews-Hanna et al., 2010). "
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    ABSTRACT: Despite consensus on the neurological nature of autism spectrum disorders (ASD), brain biomarkers remain unknown and diagnosis continues to be based on behavioral criteria. Growing evidence suggests that brain abnormalities in ASD occur at the level of interconnected networks; however, previous attempts using functional connectivity data for diagnostic classification have reached only moderate accuracy. We selected 252 low-motion resting-state functional MRI (rs-fMRI) scans from the Autism Brain Imaging Data Exchange (ABIDE) including typically developing (TD) and ASD participants (n = 126 each), matched for age, non-verbal IQ, and head motion. A matrix of functional connectivities between 220 functionally defined regions of interest was used for diagnostic classification, implementing several machine learning tools. While support vector machines in combination with particle swarm optimization and recursive feature elimination performed modestly (with accuracies for validation datasets < 70%), diagnostic classification reached high accuracy of 91% with random forest (RF), a nonparametric ensemble learning method. Among the 100 most informative features (connectivities), for which this peak accuracy was achieved, participation of somatosensory, default mode, visual, and subcortical regions stood out. Whereas some of these findings were expected, given previous findings of default mode abnormalities and atypical visual functioning in ASD, the prominent role of somatosensory regions was remarkable. The finding of peak accuracy for 100 interregional functional connectivities further suggests that brain biomarkers of ASD may be regionally complex and distributed, rather than localized.
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    • "Several studies have repeatedly observed abnormal reactivity of insula in subjects with ASD in response to social and emotional signals (Uddin and Menon, 2009). Likewise, impaired deactivation and abnormal connectivity of the default mode network has been described in adults with ASD (Kennedy et al., 2006). We were able to demonstrate that male adults with ASD showed a modulation of these regions using a simple hand gesture task. "

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    • "DMN is characterized by a high default metabolism during rest (Gusnard et al. 2001) and needs to be switched off during cognitive demanding tasks (Greicius et al. 2003). Kennedy, Redcay, and Courchesne (2006) found that participants with autism, as compared to controls, do not "
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    ABSTRACT: In their commentary on EEG Biofeedback for Autism Spectrum Disorders (Kouijzer et al. 2013) Coben and Ricca (2014) offer explanations for the apparent lack of improvement following electroencephalography (EEG) biofeedback-training as compared to skin conductance (SC) biofeedback-training. The authors suggest that a different EEG-biofeedback regime using a bipolar montage directed at coherence might have been more successful. We have identified three issues in Coben and Ricca’s commentary that we think are important to discuss in the current reply.First, we disagree with the authors’ qualification that our study revealed no effects of EEG-biofeedback training. An important finding in our study was the improvement in the Trail Making Test in participants who succeeded to down regulate theta activation trough EEG-biofeedback. No such effect was found for the SC biofeedback group or in the group of participants who were not successful in down regulating theta power over time. In a study in ...
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