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

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

VStore: Feasibility and acceptability of a novel virtual reality functional cognition task

Virtual reality (VR) is becoming an increasingly popular tool in neuroscience and mental health research. In recent years, efforts have been made to virtualise neuropsychological testing with the intent to increase the ecological validity of cognitive assessments. However, there are some limitations in the current literature—feasibility and acceptability data are often not reported or available and sample sizes have generally been small. In this study, we describe the development and establish the feasibility and acceptability of use of a novel functional cognition VR shopping task, VStore, in three separate samples with data from a total of 210 participants. Two samples include healthy volunteers between the ages of 20 and 79 and there is one clinical cohort of patients with psychosis. Main VStore outcomes were: 1) verbal recall of 12 grocery items, 2) time to collect items, 3) time to select items on a self-checkout machine, 4) time to make the payment, 5) time to order hot drink, and 6) total time. Feasibility and acceptability were assessed by the completion rate across the three studies. VR induced adverse effects were assessed preand post-VStore administration to establish tolerability. Finally, as an exploratory objective, VStore’s ability to differentiate between younger and older age groups, and between patients and matched healthy controls was examined as preliminary indication of its potential utility. The overall completion rate across the studies was exceptionally high (99.95%), and VStore did not induce any adverse effects. Additionally, there was a clear difference in VStore performance metrics between both the patients and controls and between younger and older age groups, suggesting potential clinical utility of this VR assessment. These findings demonstrate that VStore is a promising neuropsychological tool that is well-tolerated and feasible to administer to both healthy and clinical populations. We discuss the implications for future research involving neuropsychological testing based on our experience and the contemporary literature

A novel virtual reality assessment of functional cognition: Validation study

Background: Cognitive deficits are present in several neuropsychiatric disorders, including Alzheimer disease, schizophrenia, and depression. Assessments used to measure cognition in these disorders are time-consuming, burdensome, and have low ecological validity. To address these limitations, we developed a novel virtual reality shopping task—VStore. Objective: This study aims to establish the construct validity of VStore in relation to the established computerized cognitive battery, Cogstate, and explore its sensitivity to age-related cognitive decline. Methods: A total of 142 healthy volunteers aged 20-79 years participated in the study. The main VStore outcomes included verbal recall of 12 grocery items, time to collect items, time to select items on a self-checkout machine, time to make the payment, time to order coffee, and total completion time. Construct validity was examined through a series of backward elimination regression models to establish which Cogstate tasks, measuring attention, processing speed, verbal and visual learning, working memory, executive function, and paired associate learning, in addition to age and technological familiarity, best predicted VStore performance. In addition, 2 ridge regression and 2 logistic regression models supplemented with receiver operating characteristic curves were built, with VStore outcomes in the first model and Cogstate outcomes in the second model entered as predictors of age and age cohorts, respectively. Results: Overall VStore performance, as indexed by the total time spent completing the task, was best explained by Cogstate tasks measuring attention, working memory, paired associate learning, and age and technological familiarity, accounting for 47% of the variance. In addition, with λ=5.16, the ridge regression model selected 5 parameters for VStore when predicting age (mean squared error 185.80, SE 19.34), and with λ=9.49 for Cogstate, the model selected all 8 tasks (mean squared error 226.80, SE 23.48). Finally, VStore was found to be highly sensitive (87%) and specific (91.7%) to age cohorts, with 94.6% of the area under the receiver operating characteristic curve. Conclusions: Our findings suggest that VStore is a promising assessment that engages standard cognitive domains and is sensitive to age-related cognitive decline

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

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

VStore: Feasibility and acceptability of a novel virtual reality functional cognition task

Virtual reality (VR) is becoming an increasingly popular tool in neuroscience and mental health research. In recent years, efforts have been made to virtualise neuropsychological testing with the intent to increase the ecological validity of cognitive assessments. However, there are some limitations in the current literature—feasibility and acceptability data are often not reported or available and sample sizes have generally been small. In this study, we describe the development and establish the feasibility and acceptability of use of a novel functional cognition VR shopping task, VStore, in three separate samples with data from a total of 210 participants. Two samples include healthy volunteers between the ages of 20 and 79 and there is one clinical cohort of patients with psychosis. Main VStore outcomes were: 1) verbal recall of 12 grocery items, 2) time to collect items, 3) time to select items on a self-checkout machine, 4) time to make the payment, 5) time to order hot drink, and 6) total time. Feasibility and acceptability were assessed by the completion rate across the three studies. VR induced adverse effects were assessed pre- and post-VStore administration to establish tolerability. Finally, as an exploratory objective, VStore’s ability to differentiate between younger and older age groups, and between patients and matched healthy controls was examined as preliminary indication of its potential utility. The overall completion rate across the studies was exceptionally high (99.95%), and VStore did not induce any adverse effects. Additionally, there was a clear difference in VStore performance metrics between both the patients and controls and between younger and older age groups, suggesting potential clinical utility of this VR assessment. These findings demonstrate that VStore is a promising neuropsychological tool that is well-tolerated and feasible to administer to both healthy and clinical populations. We discuss the implications for future research involving neuropsychological testing based on our experience and the contemporary literature

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

Correction: Well-being, problematic alcohol consumption and acute subjective drug effects in past-year ayahuasca users: A large, international, self-selecting online survey (Scientific Reports DOI: 10.1038/s41598-017-14700-6)

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