Automatic Detection of Cognitive Impairment with Virtual Reality.

Cognitive impairment features in neuropsychiatric conditions and when undiagnosed can have a severe impact on the affected individual's safety and ability to perform daily tasks. Virtual Reality (VR) systems are increasingly being explored for the recognition, diagnosis and treatment of cognitive impairment. In this paper, we describe novel VR-derived measures of cognitive performance and show their correspondence with clinically-validated cognitive performance measures. We use an immersive VR environment called VStore where participants complete a simulated supermarket shopping task. People with psychosis (k=26) and non-patient controls (k=128) participated in the study, spanning ages 20-79 years. The individuals were split into two cohorts, a homogeneous non-patient cohort (k=99 non-patient participants) and a heterogeneous cohort (k=26 patients, k=29 non-patient participants). Participants' spatio-temporal behaviour in VStore is used to extract four features, namely, route optimality score, proportional distance score, execution error score, and hesitation score using the Traveling Salesman Problem and explore-exploit decision mathematics. These extracted features are mapped to seven validated cognitive performance scores, via linear regression models. The most statistically important feature is found to be the hesitation score. When combined with the remaining extracted features, the multiple linear regression model resulted in statistically significant results with R2 = 0.369, F-Stat = 7.158, p(F-Stat) = 0.000128.

Alpha3/alpha2 power ratios relate to performance on a virtual reality shopping task in ageing adults.

Background: Aspects of cognitive function decline with age. This phenomenon is referred to as age-related cognitive decline (ARCD). Improving the understanding of these changes that occur as part of the ageing process can serve to enhance the detection of the more incapacitating neurodegenerative disorders such as Alzheimer's disease (AD). In this study, we employ novel methods to assess ARCD by exploring the utility of the alpha3/alpha2 electroencephalogram (EEG) power ratio - a marker of AD, and a novel virtual reality (VR) functional cognition task - VStore, in discriminating between young and ageing healthy adults. Materials and methods: Twenty young individuals aged 20-30, and 20 older adults aged 60-70 took part in the study. Participants underwent resting-state EEG and completed VStore and the Cogstate Computerised Cognitive Battery. The difference in alpha3/alpha2 power ratios between the age groups was tested using t-test. In addition, the discriminatory accuracy of VStore and Cogstate were compared using logistic regression and overlying receiver operating characteristic (ROC) curves. Youden's J statistic was used to establish the optimal threshold for sensitivity and specificity and model performance was evaluated with the DeLong's test. Finally, alpha3/alpha2 power ratios were correlated with VStote and Cogstate performance. Results: The difference in alpha3/alpha2 power ratios between age cohorts was not statistically significant. On the other hand, VStore discriminated between age groups with high sensitivity (94%) and specificity (95%) The Cogstate Pre-clinical Alzheimer's Battery achieved a sensitivity of 89% and specificity of 60%, and Cogstate Composite Score achieved a sensitivity of 83% and specificity of 85%. The differences between the discriminatory accuracy of VStore and Cogstate models were statistically significant. Finally, high alpha3/alpha2 power ratios correlated strongly with VStore (r = 0.73), the Cogstate Pre-clinical Alzheimer's Battery (r = -0.67), and Cogstate Composite Score (r = -0.76). Conclusion: While we did not find evidence that the alpha3/alpha2 power ratio is elevated in healthy ageing individuals compared to young individuals, we demonstrated that VStore can classify age cohorts with high accuracy, supporting its utility in the assessment of ARCD. In addition, we found preliminary evidence that elevated alpha3/alpha2 power ratio may be linked to lower cognitive performance.

In the eye of the beholder? Oxytocin effects on eye movements in schizophrenia.

BACKGROUND: Individuals with schizophrenia have difficulty in extracting salient information from faces. Eye-tracking studies have reported that these individuals demonstrate reduced exploratory viewing behaviour (i.e. reduced number of fixations and shorter scan paths) compared to healthy controls. Oxytocin has previously been demonstrated to exert pro-social effects and modulate eye gaze during face exploration. In this study, we tested whether oxytocin has an effect on visual attention in patients with schizophrenia. METHODS: Nineteen male participants with schizophrenia received intranasal oxytocin 40UI or placebo in a double-blind, placebo-controlled, crossover fashion during two visits separated by seven days. They engaged in a free-viewing eye-tracking task, exploring images of Caucasian men displaying angry, happy, and neutral emotional expressions; and control images of animate and inanimate stimuli. Eye-tracking parameters included: total number of fixations, mean duration of fixations, dispersion, and saccade amplitudes. RESULTS: We found a main effect of treatment, whereby oxytocin increased the total number of fixations, dispersion, and saccade amplitudes, while decreasing the duration of fixations compared to placebo. This effect, however, was non-specific to facial stimuli. When restricting the analysis to facial images only, we found the same effect. In addition, oxytocin modulated fixation rates in the eye and nasion regions. DISCUSSION: This is the first study to explore the effects of oxytocin on eye gaze in schizophrenia. Oxytocin had enhanced exploratory viewing behaviour in response to both facial and inanimate control stimuli. We suggest that the acute administration of intranasal oxytocin may have the potential to enhance visual attention in schizophrenia.