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Record W3128155298 · doi:10.1080/20008198.2020.1866410

Restoring large scale brain networks in the aftermath of trauma: implications for neuroscientifically-informed treatments

2021· article· en· W3128155298 on OpenAlexaff
Ruth A. Lanius, Paul Frewen, A. N. Nicholson, Margaret C. McKinnon

Bibliographic record

VenueEuropean journal of psychotraumatology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcMaster UniversityWestern University
Fundersnot available
KeywordsDefault mode networkSalience (neuroscience)Psychological interventionPsychologyPsychopathologyNeuroimagingPsychiatryFunctional magnetic resonance imagingNeuroscience

Abstract

fetched live from OpenAlex

Background: Several intrinsic networks in the brain, including the default mode network, the salience network, and the central executive network, have shown to be critical to higher cognitive functioning. Importantly, these networks have been demonstrated to be compromised in psychopathology, including posttraumatic stress disorder (PTSD) (Akiki, Averill, & Abdallah, 2017 Akiki, T. J., Averill, C. L., & Abdallah, C. G. (2017). A network-based neurobiological model of PTSD: Evidence from structural and functional neuroimaging studies. Current Psychiatry Reports, 19(11), 1.[Crossref], [Web of Science ®] , [Google Scholar]; Lanius, Frewen, Tursich, Jetly, & McKinnon, 2015 Lanius, R. A., Frewen, P. A., Tursich, M., Jetly, R., & McKinnon, M. C. (2015). Restoring large-scale brain networks in PTSD and related disorders: A proposal for neuroscientifically-informed treatment interventions. European Journal of Psychotraumatology, 6(1), 27313.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]; Lanius, Terpou, & McKinnon, 2020 Lanius, R. A., Terpou, B. A., & McKinnon, M. C. (2020). The sense of self in the aftermath of trauma: Lessons from the default mode network in posttraumatic stress disorder. European Journal of Psychotraumatology, 11(1), 1807703. https://doi.org10.1080/20008198.2020.1807703[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]; Szeszko & Yehuda, 2020 Szeszko, P. R., & Yehuda, R. (2019). Magnetic resonance imaging predictors of psychotherapy treatment response in post-traumatic stress disorder: A role for the salience network. Psychiatry Research, 277, 52–1.[Crossref], [Web of Science ®] , [Google Scholar]).Objective: 1) To outline the major large-scale networks of the human brain and their impaired functioning in PTSD; 2) to describe neuroscientifically-informed interventions targeting directly the abnormalities observed in these brain networks in PTSD.Methods: Literature relevant to this topic will be reviewed.Results: Increasing evidence for impaired functioning of the default mode network, the salience network, the central executive network, and the dorsal/ventral attention networks in PTSD has been described. Each network has been proposed to be associated with specific clinical symptoms observed in PTSD, including an altered sense of self (default mode network), increased or decreased or arousal/interoception (salience network), cognitive dysfunction (central executive network; attentional networks). Specific neuroscientifically-informed treatments designed to restore each of these brain networks and the related clinical symptomatology will be discussed.Conclusions: Neuroscientifically-informed treatments will be critical to future research and personalized medicine agendas aimed at targeting specific PTSD symptomatology and restoring functioning in the aftermath of this often devastating disorder.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.335
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2021
Admission routes1
Has abstractyes

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