# A network analysis of facial and vocal emotion recognition deficits in schizophrenia

## TL;DR

This study shows that people with schizophrenia have significant trouble recognizing facial and vocal emotions, which are closely linked to cognitive impairments.

## Contribution

The study introduces a network analysis approach to demonstrate strong links between cognitive and emotion recognition deficits in schizophrenia.

## Key findings

- Schizophrenia patients showed significantly lower accuracy in facial and vocal emotion recognition compared to healthy controls.
- Network analysis revealed strong correlations between cognitive performance (MCCB) and emotion recognition abilities.
- Multimodal assessments combining cognitive and emotion recognition tests improved diagnostic accuracy for schizophrenia.

## Abstract

Facial and vocal emotion recognition deficits are common in individuals with schizophrenia.

In this observational, single-center study, 106 patients with schizophrenia (SCZ) and 118 age- and sex-matched healthy controls underwent cognitive and emotional function assessments. The Temporal Experience of Pleasure Scale (TEPS), Personal and Social Performance Scale, Positive and Negative Symptom Scale, and Brief Negative Symptom Scale were used to evaluate psychotic symptoms in the SCZ group. Participants were assessed using the MATRICS Consensus Cognitive Battery (MCCB), the Positive and Negative Syndrome Scale, and emotion recognition tests involving 42 facial and 42 vocal emotional tasks.

The SCZ group had significant impairments in facial and vocal emotion recognition, with lower accuracy across all emotional categories. Mean scores in the SCZ group were significantly lower than those in the control group (facial, 23.55 ± 7.10 vs. 31.86 ± 5.16; vocal, 18.64 ± 9.48 vs. 29.42 ± 5.01, respectively; p<0.001). Emotion recognition deficits and demographic or clinical characteristics were not significantly correlated. Network analysis revealed strong intercorrelations among different cognitive domains, linking MCCB performance to emotion recognition abilities (r>0.9; p<0.001). Integration of tests of cognitive function (MCCB, area under the curve [AUC]=91.90%, p<0.01), emotion recognition abilities (facial, AUC=82.56%; vocal, AUC=82.82%; p<0.01), and TEPS (AUC=91.13%, p<0.01) proved useful for distinguishing patients with schizophrenia from healthy individuals.

These findings underscore the importance of emotion recognition impairments in schizophrenia and their strong association with cognitive deficits. Future interventions should focus on targeted cognitive and affective training strategies. Incorporating multimodal assessments into clinical evaluations may enhance diagnostic accuracy.