Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Affective Brain Signal Variability Separates Social Anxiety Disorder Patients From Healthy Individuals
Stockholm University, Faculty of Social Sciences, Department of Psychology, Clinical psychology.
Stockholm University, Faculty of Social Sciences, Department of Psychology.
Show others and affiliations
2018 (English)In: Biological Psychiatry, ISSN 0006-3223, E-ISSN 1873-2402, Vol. 83, no 9, p. S249-S250Article in journal, Meeting abstract (Other academic) Published
Abstract [en]

Background: Amygdala hyper-responsiveness to negative socio-affective stimuli have typically been demonstrated in patients with social anxiety disorder (SAD). Relative to conventional methods, there is emerging evidence that brain signal variability could be a better predictor of behavior than mean neural response.

Methods: We recruited 46 patients with SAD (mean age 31, 63% females) and 40 matched healthy controls (HC) to undergo 3 Tesla functional magnetic resonance imaging (fMRI) at 2 time-points, totaling 172 MRIsessions. Blood-oxygen level-dependent (BOLD-fMRI) was performed while viewing happy and fearful faces in blocks of 80 seconds. BOLD-fMRI data was reviewed by manually classifying signal from noise. Variability was calculated as each voxel’s standard deviation on signal across scanning-time. Multivariate partial least squares (PLS) estimated patterns of variability that separates patient from controls.

Results: PLS found one significant latent variable with cross-block covariance on 64%, permutated (x 1000) P<0.001, bootstrapped 95% confidence intervals on each condition, demonstrating less signal variability to happy faces in patients, relative to controls. This pattern of response was spatially located in several regions across the whole-brain, with large clusters appearing in bilateral amygdala, medial prefrontal cortex and posterior cingulate cortex/precuneus.

Conclusions: We found that neural response variability to positive socio-affective stimuli accurately separated patients from controls. It is likely that less signal variability highlights a deficit in effective emotion processing. We add to the growing literature on healthy individuals suggesting that task-specific brain signal variability contains useful information. The brain signal variability approach opens new avenues to evaluate and better understand brain function in common psychopathology.

Place, publisher, year, edition, pages
2018. Vol. 83, no 9, p. S249-S250
Keywords [en]
social anxiety disorder, BOLD fMRI, variability
National Category
Psychology
Research subject
Psychology
Identifiers
URN: urn:nbn:se:su:diva-160600DOI: 10.1016/j.biopsych.2018.02.644OAI: oai:DiVA.org:su-160600DiVA, id: diva2:1251838
Conference
The 73rd Annual Meeting of the Society of Biological Psychiatry, New York, US, May 10-12, 2018
Available from: 2018-09-28 Created: 2018-09-28 Last updated: 2018-09-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Månsson, KristofferManzouri, AmirhossainFischer, Håkan
By organisation
Clinical psychologyDepartment of PsychologyBiological psychology
In the same journal
Biological Psychiatry
Psychology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 162 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf