A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity

Elife. 2018 Dec 10:7:e38844. doi: 10.7554/eLife.38844.

Abstract

Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual's predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases.

Keywords: biomarkers; functional connectivity; human; neuroscience; prediction model; rs-fMRI; working memory.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / diagnostic imaging
  • Brain / physiopathology*
  • Brain Mapping
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Memory Disorders / diagnostic imaging
  • Memory Disorders / physiopathology
  • Memory, Short-Term / physiology*
  • Mental Disorders / physiopathology*
  • Models, Neurological*
  • Nerve Net / diagnostic imaging
  • Nerve Net / physiopathology*
  • Neuropsychological Tests
  • Prognosis
  • Psychomotor Performance / physiology
  • Young Adult