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.

The temporal dynamics of sleep disturbance and psychopathology in psychosis: a digital sampling study.

BACKGROUND: Sleep disruption is a common precursor to deterioration and relapse in people living with psychotic disorders. Understanding the temporal relationship between sleep and psychopathology is important for identifying and developing interventions which target key variables that contribute to relapse. METHODS: We used a purpose-built digital platform to sample self-reported sleep and psychopathology variables over 1 year, in 36 individuals with schizophrenia. Once-daily measures of sleep duration and sleep quality, and fluctuations in psychopathology (positive and negative affect, cognition and psychotic symptoms) were captured. We examined the temporal relationship between these variables using the Differential Time-Varying Effect (DTVEM) hybrid exploratory-confirmatory model. RESULTS: Poorer sleep quality and shorter sleep duration maximally predicted deterioration in psychosis symptoms over the subsequent 1-8 and 1-12 days, respectively. These relationships were also mediated by negative affect and cognitive symptoms. Psychopathology variables also predicted sleep quality, but not sleep duration, and the effect sizes were smaller and of shorter lag duration. CONCLUSIONS: Reduced sleep duration and poorer sleep quality anticipate the exacerbation of psychotic symptoms by approximately 1-2 weeks, and negative affect and cognitive symptoms mediate this relationship. We also observed a reciprocal relationship that was of shorter duration and smaller magnitude. Sleep disturbance may play a causal role in symptom exacerbation and relapse, and represents an important and tractable target for intervention. It warrants greater attention as an early warning sign of deterioration, and low-burden, user-friendly digital tools may play a role in its early detection.

Correction to: Skating on thin ice: pragmatic prescribing for medication refractory schizophrenia.

After publication of the original article [1], the authors have notified us that there was an oversight on acknowledging funding received for the study. They would like to mention that Professor Sukhi Shergill was funded by an ERC Consolidator Award.

Parsing the Roles of the Frontal Lobes and Basal Ganglia in Task Control Using Multivoxel Pattern Analysis.

Cognitive control has traditionally been associated with pFC based on observations of deficits in patients with frontal lesions. However, evidence from patients with Parkinson disease indicates that subcortical regions also contribute to control under certain conditions. We scanned 17 healthy volunteers while they performed a task-switching paradigm that previously dissociated performance deficits arising from frontal lesions in comparison with Parkinson disease, as a function of the abstraction of the rules that are switched. From a multivoxel pattern analysis by Gaussian Process Classification, we then estimated the forward (generative) model to infer regional patterns of activity that predict Switch/Repeat behavior between rule conditions. At 1000 permutations, Switch/Repeat classification accuracy for concrete rules was significant in the BG, but at chance in the frontal lobe. The inverse pattern was obtained for abstract rules, whereby the conditions were successfully discriminated in the frontal lobe but not in the BG. This double dissociation highlights the difference between cortical and subcortical contributions to cognitive control and demonstrates the utility of multivariate approaches in investigations of functions that rely on distributed and overlapping neural substrates.

Realising stratified psychiatry using multidimensional signatures and trajectories.

BACKGROUND: Stratified or personalised medicine targets treatments for groups of individuals with a disorder based on individual heterogeneity and shared factors that influence the likelihood of response. Psychiatry has traditionally defined diagnoses by constellations of co-occurring signs and symptoms that are assigned a categorical label (e.g. schizophrenia). Trial methodology in psychiatry has evaluated interventions targeted at these categorical entities, with diagnoses being equated to disorders. Recent insights into both the nosology and neurobiology of psychiatric disorder reveal that traditional categorical diagnoses cannot be equated with disorders. We argue that current quantitative methodology (1) inherits these categorical assumptions, (2) allows only for the discovery of average treatment response, (3) relies on composite outcome measures and (4) sacrifices valuable predictive information for stratified and personalised treatment in psychiatry. METHODS AND FINDINGS: To achieve a truly 'stratified psychiatry' we propose and then operationalise two necessary steps: first, a formal multi-dimensional representation of disorder definition and clinical state, and second, the similar redefinition of outcomes as multidimensional constructs that can expose within- and between-patient differences in response. We use the categorical diagnosis of schizophrenia-conceptualised as a label for heterogeneous disorders-as a means of introducing operational definitions of stratified psychiatry using principles from multivariate analysis. We demonstrate this framework by application to the Clinical Antipsychotic Trials of Intervention Effectiveness dataset, showing heterogeneity in both patient clinical states and their trajectories after treatment that are lost in the traditional categorical approach with composite outcomes. We then systematically review a decade of registered clinical trials for cognitive deficits in schizophrenia highlighting existing assumptions of categorical diagnoses and aggregate outcomes while identifying a small number of trials that could be reanalysed using our proposal. CONCLUSION: We describe quantitative methods for the development of a multi-dimensional model of clinical state, disorders and trajectories which practically realises stratified psychiatry. We highlight the potential for recovering existing trial data, the implications for stratified psychiatry in trial design and clinical treatment and finally, describe different kinds of probabilistic reasoning tools necessary to implement stratification.

Skating on thin ice: pragmatic prescribing for medication refractory schizophrenia.

BACKGROUND: Clozapine is the treatment of choice for medication refractory psychosis, but it does not benefit half of those put on it. There are numerous studies of potential post-clozapine strategies, but little data to guide the order of such treatment in this common clinical challenge. We describe a naturalistic observational study in 153 patients treated by a specialist psychosis service to identify optimal pharmacotherapy practice, based on outcomes. METHODS: Medication and clinical data, based on the OPCRIT tool, were examined on admission and discharge from the national psychosis service. The primary outcome measure was the percentage change in mental state examination symptoms between admission and discharge and the association with medication on discharge. Exploratory analyses evaluated the specificity of individual medication effects on symptom clusters. RESULTS: There were fewer drugs prescribed at discharge relative to admission, suggesting an optimisation of medication, and a doubling of the number of patients treated with clozapine. Treatment with clozapine on discharge was associated with maximal decrease in symptoms from admission. In the group of patients that did not respond to clozapine monotherapy, the most effective drug combinations were clozapine augmentation with 1) sodium valproate, 2) lithium, 3) amisulpride, and 4) quetiapine. There was no support for a dose-response relationship for any drug combination. CONCLUSIONS: Clozapine monotherapy is clearly the optimal medication in medication refractory schizophrenia and it is possible to maximise its use. In patients unresponsive to clozapine monotherapy, augmentation with sodium valproate, lithium, amisulpride and quetiapine, in that order, is a reasonable treatment algorithm. Reducing the number of ineffective drugs is possible without a detrimental effect on symptoms. Exploratory data indicated that clozapine was beneficial across a range of symptoms domains, whereas olanzapine was beneficial specifically for hallucinations and lamotrigine for comorbid affective symptoms.

Trust versus paranoia: abnormal response to social reward in psychotic illness.

Psychosis is characterized by an elementary lack of trust in others. Trust is an inherently rewarding aspect of successful social interactions and can be examined using neuroeconomic paradigms. This study was aimed at investigating the underlying neural basis of diminished trust in psychosis. Functional magnetic resonance imaging data were acquired from 20 patients with psychosis and 20 healthy control subjects during two multiple-round trust games; one with a cooperative and the other with a deceptive counterpart. An a priori region of interest analysis of the right caudate nucleus, right temporo-parietal junction and medial prefrontal cortex was performed focusing on the repayment phase of the games. For regions with group differences, correlations were calculated between the haemodynamic signal change, behavioural outcomes and patients' symptoms. Patients demonstrated reduced levels of baseline trust, indicated by smaller initial investments. For the caudate nucleus, there was a significant game × group interaction, with controls showing stronger activation for the cooperative game than patients, and no differences for the deceptive game. The temporo-parietal junction was significantly more activated in control subjects than in patients during cooperative and deceptive repayments. There were no significant group differences for the medial prefrontal cortex. Patients' reduced activation within the caudate nucleus correlated negatively with paranoia scores. The temporo-parietal junction signal was positively correlated with positive symptom scores during deceptive repayments. Reduced sensitivity to social reward may explain the basic loss of trust in psychosis, mediated by aberrant activation of the caudate nucleus and the temporo-parietal junction.