Putative Brain Networks Underlying Repetitive Negative Thinking and Comorbid Internalizing Problems in Autism
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Many high-functioning individuals with autism spectrum disorder (ASD) also experience depression and anxiety, yet little is known about mechanisms underlying this comorbidity. Repetitive negative thinking (RNT) about self-referential information is a transdiagnostic cognitive vulnerability factor that may account for the relationship between these two classes of symptoms. We propose a model where negative self-referential processing and cognitive inflexibility interact to increase risk for RNT, leading to internalizing problems in ASD. Examination of interactions within and between two well-characterized large-scale brain networks, the default mode network and the salience network, may provide insights into neurobiological mechanisms underlying RNT in ASD. We summarize previous literature supporting this model, emphasizing moving toward understanding RNT as a factor accounting for the high rates of internalizing problems in ASD. Future research avenues include understanding heterogeneity in clinical presentation and treating cognitive flexibility and RNT to reduce comorbid internalizing problems in ASD.
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Worry and rumination may reflect the same underlying construct of repetitive negative thinking, which is likely a product of inflexible thinking and difficulty engaging L-FPN executive control systems for emotion regulation.
“Worry and rumination may reflect the same underlying construct of repetitive negative thinking, which is likely a product of inflexible thinking and difficulty engaging the L-FPN executive control systems in the service of emotion regulation90.”
From Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations (2021) · cites this paper as [90]
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“Several recent studies support this model, identifying independent links between negative self-views, cognitive flexibility, and increased rates of anxiety and depression in children, adolescents, and adults with ASD (Boulter, Freeston, South, & Rodgers, 2013; Hollocks et al., 2014; Wallace et al., 2016; Williamson, C…”
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“Due to the heterogeneity of interests of individuals with ASD, the content of negative thoughts may differ within and across individuals with the disorder (Lam & Aman, 2007; Mazefsky et al., 2012).”
BackgroundThe post-event processing questionnaire in a clinical sample with social phobia
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Worry and Rumination in Anorexia Nervosa
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Cognitive inflexibility and frontal–cortical activation in pediatric obsessive–compulsive disorder
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Does resting-state connectivity reflect depressive rumination? A tale of two analyses
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An fMRI investigation of responses to peer rejection in adolescents with autism spectrum disorders
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Validity of the Autism Spectrum Disorder-Comorbid for Children (ASD-CC)
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Default Mode Hypoconnectivity Underlies a Sex-Related Autism Spectrum
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The Modifier Model of Autism and Social Development in Higher Functioning Children
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Repetitive Negative Thinking: A Transdiagnostic Correlate of Affective Disorders
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State sadness reduces neural sensitivity to nonrewards versus rewards
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Self-generated thoughts and depression: from daydreaming to depressive symptoms
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Ruminative brooding is associated with salience network coherence in early pubertal youth
Ordaz, S. J., LeMoult, J., Colich, N. L., Prasad, G., Pollak, M., Popolizio, M., Price, A., Greicius, M. D., & Gotlib, I. H. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw133 · Cited by 40 · see citing works
Burrows, C. A., Usher, L. V., Mundy, P. C., & Henderson, H. A. (2016) · Autism Research · doi:10.1002/aur.1727 · Cited by 39 · see citing works
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- Arditte KA Shaw AM Timpano KT Repetitive negative thinking: A transdiagnostic correlate of depression and anxiety Journal of Social and Clinical Psychology 2016 35 3 181 201
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Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations
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Self-citationCan't get it off my brain: Meta-analysis of neuroimaging studies on perseverative cognition.
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Self-citationSelective Mutism and Its Relations to Social Anxiety Disorder and Autism Spectrum Disorder
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Insula-Retrosplenial Cortex Overconnectivity Increases Internalizing via Reduced Insight in Autism
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Atypical frontoamygdala functional connectivity in youth with autism
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Whole-Brain Functional Dynamics Track Depressive Symptom Severity
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Negative interpretation bias connects to real-world daily affect: A multistudy approach.
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A Computational Network Control Theory Analysis of Depression Symptoms
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Anxiety Sensitivity Domains are Differently Affected by Social and Non-social Autistic Traits
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- Authors
- Burrows, C. A., Timpano, K. R., & Uddin, L. Q.
- Affiliations
- University of Miami (US)
- Corresponding author
- Burrows, Catherine A.
- Venue
- Clinical Psychological Science
- Publisher
- SAGE Publications
- Published
- 2017-04-26
- Volume
- 5
- Issue
- 3
- Pages
- 522-536
- ISSN
- 2167-7026 (ISSN-L)
- 2167-7034
- PMC
- PMC5461967
- OpenAlex
- W2609527921
- Cited by
- 43
- References
- 130
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 5 · 2023: 8 · 2022: 3 · 2021: 6 · 2020: 3 · 2019: 3 · 2018: 7
- FWCI
- 2.04
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NARSAD
- International Society for Autism Research
- National Institute of Mental Health (K01MH092288, R01MH107549)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- autism spectrum disorder, repetitive negative thinking, internalizing problems, depression, anxiety, comorbidities, self-referential processing, cognitive flexibility, default mode network, salience network, large-scale brain networks
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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