Machine learning applied to fMRI patterns of brain activation in response to mutilation pictures predicts PTSD symptoms.

ABSTRACT:

Background

The present study aimed to apply multivariate pattern recognition methods to predict posttraumatic stress symptoms from whole-brain activation patterns during two contexts where the aversiveness of unpleasant pictures was manipulated by the presence or absence of safety cues.

Methods

Trauma-exposed participants were presented with neutral and mutilation pictures during functional magnetic resonance imaging (fMRI) collection. Before the presentation of pictures, a text informed the subjects that the pictures were fictitious ("safe context") or real-life scenes ("real context"). We trained machine learning regression models (Gaussian process regression (GPR)) to predict PTSD symptoms in real and safe contexts.

Results

The GPR model could predict PTSD symptoms

SUBMITTER: Portugal LCL 

PROVIDER: S-EPMC10552290 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature