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A neural mechanism underlying predictive visual motion processing in patients with schizophrenia.

Authors :
Scheliga, Sebastian
Schwank, Rosalie
Scholle, Ruben
Habel, Ute
Kellermann, Thilo
Source :
Psychiatry Research. Dec2022, Vol. 318, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• We investigated neural correlates of visual motion (VM) processing in psychosis. • fMRI was recorded during three VM conditions with decreasing predictability. • For patients, activity of temporo-parietal junction (TPJ) was reduced during VM. • Patients had increased TPJ connections to frontal areas but not to sensory regions. • We discussed these correlates of VM in light of a potential marker for psychosis. Psychotic symptoms may be traced back to sensory sensitivity. Thereby, visual motion (VM) processing particularly has been suggested to be impaired in schizophrenia (SCZ). In healthy brains, VM underlies predictive processing within hierarchically structured systems. However, less is known about predictive VM processing in SCZ. Therefore, we performed fMRI during a VM paradigm with three conditions of varying predictability, i.e., Predictable-, Random-, and Arbitrary motion. The study sample comprised 17 SCZ patients and 23 healthy controls. We calculated general linear model (GLM) analysis to assess group differences in VM processing across motion conditions. Here, we identified significantly lower activity in right temporoparietal junction (TPJ) for SCZ patients. Therefore, right TPJ was set as seed for connectivity analyses. For patients, across conditions we identified increased connections to higher regions, namely medial prefrontal cortex, or paracingulate gyrus. Healthy subjects activated sensory regions as area V5, or superior parietal lobule. Reduced TPJ activity may reflect both a failure in the bottom-up flow of visual information and a decrease of signal processing as consequence of increased top-down input from frontal areas. In sum, these altered neural patterns provide a framework for future studies focusing on predictive VM processing to identify potential biomarkers of psychosis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01651781
Volume :
318
Database :
Academic Search Index
Journal :
Psychiatry Research
Publication Type :
Academic Journal
Accession number :
160437550
Full Text :
https://doi.org/10.1016/j.psychres.2022.114934