Parietal-Prefrontal Feedforward Connectivity in Association With Schizophrenia Genetic Risk and Delusions

Am J Psychiatry. 2020 Dec 1;177(12):1151-1158. doi: 10.1176/appi.ajp.2020.19111176. Epub 2020 May 27.

Abstract

Objective: Conceptualizations of delusion formation implicate deficits in feedforward information updating across the posterior to prefrontal cortices, resulting in dysfunctional integration of new information about contexts in working memory and, ultimately, failure to update overfamiliar prior beliefs. The authors used functional MRI and machine learning models to address individual variability in feedforward parietal-prefrontal information updating in patients with schizophrenia. They examined relationships between feedforward connectivity, and delusional thinking and polygenic risk for schizophrenia.

Methods: The authors studied 66 schizophrenia patients and 143 healthy control subjects during performance of context updating in working memory. Dynamic causal models of effective connectivity were focused on regions of the prefrontal and parietal cortex potentially implicated in delusion processes. The effect of polygenic risk for schizophrenia on connectivity was examined in healthy individuals. The authors then leveraged support vector regression models to define optimal normalized target connectivity tailored for each patient and tested the extent to which deviation from this target could predict individual variation in severity of delusions.

Results: In schizophrenia patients, updating and manipulating context information was disproportionately less accurate than was working memory maintenance, with an interaction of task accuracy by diagnosis. Patients with delusions also tended to have relatively reduced parietal-prefrontal feedforward effective connectivity during context updating in working memory manipulation. The same connectivity was adversely influenced by polygenic risk for schizophrenia in healthy subjects. Individual patients' deviation from predicted "normal" feedforward connectivity based on the support vector regression models correlated with severity of delusions.

Conclusions: These computationally derived observations support a role for feedforward parietal-prefrontal information processing deficits in delusional psychopathology and in genetic risk for schizophrenia.

Keywords: Computational Psychiatry; Delusions; Schizophrenia Spectrum and Other Psychotic Disorders.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, N.I.H., Intramural

MeSH terms

  • Adolescent
  • Adult
  • Case-Control Studies
  • Delusions / physiopathology*
  • Female
  • Humans
  • Individuality
  • Machine Learning
  • Magnetic Resonance Imaging
  • Male
  • Memory, Short-Term / physiology
  • Middle Aged
  • Multifactorial Inheritance / genetics
  • Neural Pathways / physiopathology
  • Parietal Lobe / physiopathology*
  • Prefrontal Cortex / physiopathology*
  • Schizophrenia / physiopathology*
  • Young Adult