Evidence map›Paper›PMID 32446241›Full record

ArticleNeuroImage. Clinical2020

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

Andrew A Nicholson, Sherain Harricharan, Maria Densmore, Richard W J Neufeld, Tomas Ros, Margaret C McKinnon, Paul A Frewen, Jean Théberge, Rakesh Jetly, David Pedlar and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NeuroImage. Clinical, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Article
  9. Functional brain imaging in posttraumatic stress disorder: a review.Journal of neural transmission (Vienna, Austria : 1996) · 2026
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  18. Adverse childhood experiences and post-traumatic stress impacts on brain connectivity and alcohol use in adolescence.Child neuropsychology : a journal on normal and abnormal development in childhood and adolescence · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Andrew A NicholsonDepartment of Cognition, Emotion and Methods in Psychology, University of Vienna, Austria; Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada. Electronic address: Dr.AndrewNicholson@gmail.com.
Sherain HarricharanDepartment of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
Maria DensmoreDepartment of Psychiatry, Western University, London, ON, Canada; Imaging Division, Lawson Health Research Institute, London, ON, Canada.
Richard W J NeufeldDepartment of Psychiatry, Western University, London, ON, Canada; Department of Psychology, Western University, London, ON, Canada; Department of Medical Imaging, Western University, London, ON, Canada.
Tomas RosDepartment of Neuroscience, University of Geneva, Switzerland.
Margaret C McKinnonDepartment of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program, St. Joseph's Healthcare, Hamilton, ON, Canada; Homewood Research Institute, Guelph, ON, Canada.
Paul A FrewenDepartment of Psychiatry, Western University, London, ON, Canada; Department of Neuroscience, Western University, London, ON, Canada.
Jean ThébergeDepartment of Psychiatry, Western University, London, ON, Canada; Department of Medical Imaging, Western University, London, ON, Canada; Imaging Division, Lawson Health Research Institute, London, ON, Canada; Department of Diagnostic Imaging, St. Joseph's Health Care, London, ON, Canada.
Rakesh JetlyCanadian Forces, Health Services, Ottawa, Ontario, Canada.
David PedlarCanadian Institute for Military and Veteran Health Research (CIMVHR), Canada.
Ruth A LaniusDepartment of Psychiatry, Western University, London, ON, Canada; Department of Neuroscience, Western University, London, ON, Canada; Imaging Division, Lawson Health Research Institute, London, ON, Canada.

Funding

CIHR
6 · The paper itself

Abstract

Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of the current study was to a) compare ICN functional connectivity between PTSD, dissociative subtype PTSD (PTSD+DS) and healthy individuals; and b) to examine the use of multivariate machine learning algorithms in classifying PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. Our neuroimaging dataset consisted of resting-state fMRI scans from 186 participants [PTSD (n = 81); PTSD + DS (n = 49); and healthy controls (n = 56)]. We performed group-level independent component analyses to evaluate functional connectivity differences within each ICN. Multiclass Gaussian Process Classification algorithms within PRoNTo software were then used to predict the diagnosis of PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. When comparing the functional connectivity of ICNs between PTSD, PTSD+DS and healthy controls, we found differential patterns of connectivity to brain regions involved in emotion regulation, in addition to limbic structures and areas involved in self-referential processing, interoception, bodily self-consciousness, and depersonalization/derealization. Machine learning algorithms were able to predict with high accuracy the classification of PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. Our results suggest that alterations within intrinsic connectivity networks may underlie unique psychopathology and symptom presentation among PTSD subtypes. Furthermore, the current findings substantiate the use of machine learning algorithms for classifying subtypes of PTSD illness based on ICNs.

Indexed as

Machine LearningAdultAmygdalaBrainBrain MappingDissociative DisordersEmotionsFemaleHumansMaleMiddle AgedNerve NetNeural PathwaysStress Disorders, Post-Traumatic

Identifiers

PMID32446241
PMCPMC7240193

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.