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Exploring memory function in earthquake trauma survivors with resting-state fMRI and machine learning.

Yuchen Li1, Hongru Zhu1,2,3, Zhengjia Ren1,4

  • 1Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.

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Resting-state fMRI and machine learning reveal brain mechanisms linking spatial memory deficits to PTSD in earthquake survivors. These neuroimaging techniques may help identify memory impairments in trauma survivors.

Keywords:
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Area of Science:

  • Neuroimaging and neurophysiology
  • Psychiatric disorders
  • Cognitive neuroscience

Background:

  • Traumatic events like earthquakes can lead to memory dysfunction in survivors.
  • Resting-state functional magnetic resonance imaging (rs-fMRI) and machine learning (ML) show potential for assessing individual psychiatric conditions.
  • This study investigates the relationship between rs-fMRI data and memory function in trauma survivors.

Purpose of the Study:

  • To explore the association between resting-state brain activity and memory function in earthquake trauma survivors.
  • To apply machine learning techniques to neuroimaging data for understanding memory impairments.
  • To investigate the neurophysiological basis of memory deficits in the context of trauma.

Main Methods:

  • Eighty-nine Wenchuan earthquake survivors underwent rs-fMRI scans.
  • Participants were assessed for PTSD using the Clinician-Administered PTSD Scale (CAPS) and for memory function using the Wechsler Memory Scale-IV (WMS-IV).
  • Multiple kernel learning (MKL) was used to predict memory scores, and support vector machine (SVM) was employed for PTSD classification.

Main Results:

  • Spatial addition (working memory) showed a negative correlation with total CAPS scores (r=-0.22, P=0.04).
  • Simple MKL accurately predicted spatial addition scores (correlation=0.28, P=0.03), highlighting the left middle frontal gyrus and left precuneus.
  • SVM classification for PTSD diagnosis did not achieve statistical significance.

Conclusions:

  • Brain activity in the left middle frontal gyrus and left precuneus, measured by rs-fMRI, may underlie visual working memory deficits associated with PTSD.
  • Machine learning offers a promising approach for identifying the neural mechanisms of memory impairment in trauma survivors.