Your browser doesn't support javascript.
loading
Multi-voxel pattern analysis of amygdala functional connectivity at rest predicts variability in posttraumatic stress severity.
Fitzgerald, Jacklynn M; Belleau, Emily L; Miskovich, Tara A; Pedersen, Walker S; Larson, Christine L.
Afiliación
  • Fitzgerald JM; Department of Psychology, Marquette University, Milwaukee, WI, USA.
  • Belleau EL; Department of Psychiatry, McLean Hospital, Belmont, MA, USA.
  • Miskovich TA; Harvard Medical School, Boston, MA, USA.
  • Pedersen WS; VA Northern California Healthcare System, Vallejo, CA, USA.
  • Larson CL; Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA.
Brain Behav ; 10(8): e01707, 2020 08.
Article en En | MEDLINE | ID: mdl-32525273
INTRODUCTION: Resting state functional magnetic resonance imaging (rsfMRI) studies demonstrate that individuals with posttraumatic stress disorder (PTSD) exhibit atypical functional connectivity (FC) between the amygdala, involved in the generation of emotion, and regions responsible for emotional appraisal (e.g., insula, orbitofrontal cortex [OFC]) and regulation (prefrontal cortex [PFC], anterior cingulate cortex). Consequently, atypical amygdala FC within an emotional processing and regulation network may be a defining feature of PTSD, although altered FC does not seem constrained to one brain region. Instead, altered amygdala FC involves a large, distributed brain network in those with PTSD. The present study used a machine-learning data-driven approach, multi-voxel pattern analysis (MVPA), to predict PTSD severity based on whole-brain patterns of amygdala FC. METHODS: Trauma-exposed adults (N = 90) completed the PTSD Checklist-Civilian Version to assess symptoms and a 5-min rsfMRI. Whole-brain FC values to bilateral amygdala were extracted and used in a relevance vector regression analysis with a leave-one-out approach for cross-validation with permutation testing (1,000) to obtain significance values. RESULTS: Results demonstrated that amygdala FC predicted PCL-C scores with statistically significant accuracy (r = .46, p = .001; mean sum of squares = 130.46, p = .001; R2  = 0.21, p = .001). Prediction was based on whole-brain amygdala FC, although regions that informed prediction (top 10%) included the OFC, amygdala, and dorsolateral PFC. CONCLUSION: Findings demonstrate the utility of MVPA based on amygdala FC to predict individual severity of PTSD symptoms and that amygdala FC within a fear acquisition and regulation network contributed to accurate prediction.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Descanso / Trastornos por Estrés Postraumático / Amígdala del Cerebelo / Vías Nerviosas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Brain Behav Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Descanso / Trastornos por Estrés Postraumático / Amígdala del Cerebelo / Vías Nerviosas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Brain Behav Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos