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Functional network dysfunction in anxiety and anxiety disorders
Open accessAbstract
A recent paradigm shift in systems neuroscience is the division of the human brain into functional networks. Functional networks are collections of brain regions with strongly correlated activity both at rest and during cognitive tasks, and each network is believed to implement a different aspect of cognition. We propose here that anxiety disorders and high trait anxiety are associated with a particular pattern of functional network dysfunction: increased functioning of the cingulo-opercular and ventral attention networks as well as decreased functioning of the fronto-parietal and default mode networks. This functional network model can be used to differentiate the pathology of anxiety disorders from other psychiatric illnesses such as major depression and provides targets for novel treatment strategies.
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In the citing paper
“Both, goal-directed stimulus processing [46] and the function of the dorsal attention network [47] have been found to be impaired in highly anxious individuals.”
From They are laughing at me: Cerebral mediation of cognitive biases in social anxiety (2014) · cites this paper as [47]
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Experimental — accuracy not yet measuredIn the citing paper
“Specific treatments can then be targeted to individual patients based on their personalized pattern of brain network dysfunction.112”
From Precision clinical trials: a framework for getting to precision medicine for neurobehavioural disorders (2021) · cites this paper as [112]
In the citing paper
“Anxiety and ABs may emerge from an imbalance between threat salience evaluation and cognitive control processes, described at both cognitive and neural network levels [115,118-121].”
From Anxiety and Threat-Related Attention: Cognitive-Motivational Framework and Treatment (2018) · cites this paper as [119]
In the citing paper
“Sylvester et al. (2012) propose that anxiety-related dysfunction in each of the four networks should be evident on tasks using neutral stimuli (i.e., it is not specific to processing threat information).”
From Anxiety and attention to threat: cognitive mechanisms and treatment with attention bias modification (2016) · cites this paper as Sylvester et al., 2012
In the citing paper
“Furthermore, Sylvester et al. (2012) propose that both high trait anxiety and anxiety disorders are associated with individual differences in dysfunction in four brain networks: ventral attention, frontoparietal, cingulo-opercular and default mode network; which results in increased bottom-up stimulus-driven attention, reduced topdown attention control, increased error sensitivity, and poor”
From Anxiety and attention to threat: cognitive mechanisms and treatment with attention bias modification (2016) · cites this paper as Sylvester et al., 2012
In the citing paper
“The same may apply to other functions, such as cognitive flexibility, or bottom-up spatial orienting (Eysenck et al., 2007;Sylvester et al., 2012).”
From Anxiety and attention to threat: cognitive mechanisms and treatment with attention bias modification (2016) · cites this paper as Sylvester et al., 2012
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Metadata
- Authors
- Sylvester, C. M., Corbetta, M., Raichle, M. E., Rodebaugh, T. L., Schlaggar, B. L., Sheline, Y. I., Zorumski, C. F., & Lenze, E. J.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Sylvester, C.M.
- ORCID
- Venue
- Trends in Neurosciences
- Publisher
- Elsevier BV
- Published
- 2012-09
- Volume
- 35
- Issue
- 9
- Pages
- 527-535
- ISSN
- 0166-2236 (ISSN-L)
- PMC
- PMC3432139
- OpenAlex
- W2068673705
- Cited by
- 579
- References
- 110
- Citations by year
- 2026: 48 · 2025: 43 · 2024: 52 · 2023: 58 · 2022: 36 · 2021: 55 · 2020: 43 · 2019: 38 · 2018: 46 · 2017: 35 · 2016: 46 · 2015: 25 · 2014: 33 · 2013: 16 · 2012: 2
- FWCI
- 1.92
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Trends in Neurosciences (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Funders
- National Institutes of Health (5r01mh077791-07)
- U.S. Public Health Service (K24 65421)
- National Institute on Alcohol Abuse and Alcoholism (R01AA017413, AA017413)
- National Institute of Mental Health (R21MH090308, MH07791, R01MH096482, MH090308, R01-MH-077791, K24MH079510)
- National Institute of Neurological Disorders and Stroke (P50NS006833, NS 06833)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD061117, 5R01HD61117-6)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- functional brain networks, anxiety disorders, trait anxiety, cingulo-opercular network, ventral attention network, frontoparietal network, default mode network, network dysfunction, major depressive disorder, treatment goals
- MeSH terms
- Anxiety, Anxiety Disorders, Brain, Brain Diseases, Humans, Models, Neurological, Nerve Net
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
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