Citation

Caruana N, Inkley C, El Zein M. Schizophr. Res. Cogn. 2020; 21: e100181.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.scog.2020.100181

PMID

unavailable

Abstract

The successful integration of eye gaze direction and emotion cues from faces is important not only for co-ordinated interactions, but also for the detection of social signals alerting us to threat posed by a conspecific, or elsewhere in our immediate environment. It is now well-established that people with schizophrenia experience aberrant eye gaze and facial emotion processing. These social-cognitive differences might contribute to the maintenance of socially-themed delusions which are characterised by the hyper-attribution of threatening intentions to others. However, no study has directly examined whether the mechanisms which govern the integration of eye gaze and emotion information diverge in schizophrenia, and more importantly, whether this reflects a fundamental 'bottom-up' perceptual deficit or a 'top-down' cognitive bias. Fifteen outpatients diagnosed with schizophrenia and 21 healthy age- and IQ-matched controls performed an emotion categorisation task (anger/fear) on morphed facial expressions of anger or fear, displaying either direct or averted gaze.

RESULTS in both controls and patients replicated the previous finding that combinations of anger with direct gaze, and fear with averted gaze - which signal a relevant threat to the observer - benefited from more accurate emotion recognition than alternate gaze-emotion combinations. Bayesian model selection revealed that for patients this effect was mediated by a shift in decision bias towards emotions which signal self-relevant threat, rather than a change in sensitivity as observed in controls. These results critically highlight a different cognitive mechanism governing gaze and face-cued emotion integration in schizophrenia, which has a top-down influence on the evaluation of perceptual input.

Language: en

Keywords

Social perception; Schizophrenia; Emotion; Computational modelling; Face processing; Gaze