Eye Movement Patterns Can Distinguish Schizophrenia From the Major Affective Disorders and Healthy Control Subjects

Abstract

Background and hypothesis No objective tests are currently available to help diagnosis of major psychiatric disorders. This study evaluates the potential of eye movement behavior patterns to predict schizophrenia subjects compared to those with major affective disorders and control groups. Study Design Eye movements were recorded from a training set of UK subjects with schizophrenia (SCZ; n=120), bipolar affective disorder (BPAD; n=141), major depressive disorder (MDD; n=136) and healthy controls (CON; n=142), and from a hold-out set of 133 individuals with proportional group sizes. A German cohort of SCZ (n=60) and a Scottish cohort of CON subjects (n=184) acted as a second semi-independent test set. All patients met DSMIV and ICD10 criteria for SCZ, BPAD and MDD. Data from 98 eye movement features were extracted. We employed a gradient boosted(GB) decision tree multiclass classifier to develop a predictive model. We calculated the area under the curve (AUC) as the primary performance metric. Study results Estimates of AUC in one-versus-all comparisons were: SCZ (0.85), BPAD (0.78), MDD (0.76) and CON (0.85). Estimates on part-external validation were SCZ (0.89) and CON (0.65). In all cases, there was good specificity but only moderate sensitivity. The best individual discriminators included free viewing, fixation duration and smooth pursuit tasks. The findings appear robust to potential confounders such as age, sex, medication or mental state at the time of testing. Conclusions Eye movement patterns can discriminate schizophrenia from major mood disorders and control subjects with around 80% predictive accuracy.

Tablet-Based Cognitive and Eye Movement Measures as Accessible Tools for Schizophrenia Assessment: Multisite Usability Study

“…The AUC for scanpath length was 0.81, while the AUCs for cognitive function measures ranged between 0.85 and 0.90. These results were similar to the findings of previous studies using desktop-based eye movement measurements, which reported AUCs ranging between 0.77 and 0.89 [20,21,24], and previous studies using paper-based cognitive functioning measurements, which reported AUCs ranging between 0.88 and 0.90 [35,36]. Okazaki et al found that pairing certain cognitive function measures with eye movement measures led to improved performance and robustness in distinguishing patients with schizophrenia from healthy individuals, with an average increase in the AUC of 0.10 compared with eye movement measures alone and 0.05 compared with cognitive function measures alone [29].…”

“…This finding is in line with that in previous attempts to establish diagnostic markers for differentiating between patients with schizophrenia and those without schizophrenia using eye movement characteristics [37,38]. However, previous studies indicated mixed results of both cognitive function [39][40][41] and eye movement [21,38,42]. Conducting future studies on transdiagnostic characteristics of multiple modalities is increasingly important.…”

“…These analyses have been replicated in numerous samples [20][21][22][23]. In addition, these characteristics have been shown to be present from prodromal stages in patients with schizophrenia [24].…”

“…In addition, these characteristics have been shown to be present from prodromal stages in patients with schizophrenia [24]. However, findings regarding the specificity of these characteristics are still inconsistent [21,25].…”

Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis

“…Very recently St Clair and colleagues 46 applied a multiclass machine-learning model to differentiate patients with schizophrenia, bipolar affective disorder, major depression disorder, and healthy controls on the basis of 98 eye movement symptoms (including several SPEM variables). The model was tested in two validation sets achieving balanced accuracies for schizophrenia patients of 73% and 75%.…”