EEG predicts the attention level of elderly measured by RBANS

Purpose - This study aims to investigate the correlation between neural indexes of attention and behavioral indexes of attention and detect the most informative period of brain activity in which the strongest correlation with attentive performance (behavioral index) exists. Finally, to further validate the findings, this paper aims at the prediction of different levels of attention function based on the attention score obtained from repeatable battery for the assessment of neurophysiological status (RBANS). Design/methodology/approach - The present paper analyzes electroencephalogram (EEG) signals recorded by a single prefrontal channel from 105 elderly subjects while they were responding to Stroop color test which is an attention-demanded task. Beside Stroop test, subjects also performed RBANS which provides their level of functionality in different domains including attention. After data acquisition (EEG during Stroop test and RBANS attention score), the authors extract the spectral features of EEG as neural indexes of attention and subjects’ reaction time in response to Stroop test as behavioral index of attention. Then, they explore the correlation between these post-cue frequency band oscillations of EEG with elderly response time (RT). Next, the authors exploit these findings to classify RBANS attention score. Findings - The observations of this study suggest that there is significant negative correlation between alpha gamma ratio (AGR) and RT (p < 0.0001), theta beta ratio (TBR) is positively correlated with subjects’ RT (p < 0.0001), these correlations are stronger in a 500ms period right after triggering the cue (question onset in Stroop test), and 4) TBR and AGR can be effectively used to predict RBANS attention score. Research limitations/implications - Because of the experiment design, the pre-cue EEG of the next trail was very much overlapped with the post-cue EEG of the current trail. Therefore, the authors could analyze only post-cue EEG. In future study, it would be interesting to investigate the predictability of subject’s future performance from pre-cue EEG and mental preparation. Practical implications - This study provides an insight into the research on detection of human attention level from EEG instead of conventional neurophysiological tests. It has also potential to be used in implementation of feasible and efficient EEG-based brain computer interface training systems for elderly. Originality/value - To the best of the authors’ knowledge, this study is among very few attempts for early prediction of cognitive decline in the domain of attention from brain activity (EEG) instead of conventional tests which are prone to human errors

Early detection of mild cognitive impairment with in-home sensors to monitor behavior patterns in community-dwelling senior citizens in Singapore: Cross-sectional feasibility study

Singapore Management University; National Medical Research Council’s Healthcare Research Scholarshi

Bipolar disorder, brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and brain morphology

10.1371/journal.pone.0038469PLoS ONE77

A brain-computer interface based cognitive training system for healthy elderly: A randomized control pilot study for usability and preliminary efficacy

10.1371/journal.pone.0079419PLoS ONE811-POLN

A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder

10.1371/journal.pone.0046692PLoS ONE710

The Generalizability of Older Adult Self-Report (OASR) Syndromes of Psychopathology Across 20 Societies

OBJECTIVES: As the world population ages, psychiatrists will increasingly need instruments for measuring constructs of psychopathology that are generalizable to diverse elders. The study tested whether syndromes of co-occurring problems derived from self-ratings of psychopathology by US elders would fit self-ratings by elders in 19 other societies. METHODS/DESIGN: The Older Adult Self-Report (OASR) was completed by 12,826 60- to 102-year-olds in 19 societies from North and South America, Asia, and Eastern, Northern, Southern, and Western Europe, plus the US. Individual and multi-group confirmatory factor analyses (CFAs) tested the fit of the 7-syndrome OASR model, consisting of the Anxious/Depressed, Worries, Somatic Complaints, Functional Impairment, Memory/Cognition Problems, Thought Problems, and Irritable/Disinhibited syndromes. RESULTS: In individual CFAs, the primary model fit index showed good fit for all societies, while the secondary model fit indices showed acceptable to good fit. The items loaded strongly on their respective factors, with a median item loading of .63 across the 20 societies; and 98.7% of the loadings were statistically significant. In multi-group CFAs, 98% of items demonstrated approximate or full metric invariance. Fifteen percent of items demonstrated approximate or full scalar invariance and another 59% demonstrated scalar invariance across more than half of societies. CONCLUSIONS: The findings supported the generalizability of OASR syndromes across societies. The seven syndromes offer empirically-based clinical constructs that are relevant for elders of different backgrounds. They can be used to assess diverse elders, and as a taxonomic framework to facilitate communication, services, research and training in geriatric psychiatry. This article is protected by copyright. All rights reserved

Levels of serum brain-derived neurotropic factor in individuals at ultra-high risk for psychosis—findings from the longitudinal youth at risk study (LYRIKS)

Background:Identifying biomarkers to enrich prognostication and risk predictions in individuals at high risk of developing psychosis will enable stratified early intervention efforts. Brain-derived neurotrophic factor has been widely studied in schizophrenia and in first-episode psychosis with promising results. The aim of this study was to examine the levels of serum brain-derived neurotrophic factor between healthy controls and individuals with ultra-high risk of psychosis.Methods:A sample of 106 healthy controls and 105 ultra-high risk of psychosis individuals from the Longitudinal Youth at Risk Study was included in this study. Ultra-high risk of psychosis status was determined using the Comprehensive Assessment of At-Risk Mental State at recruitment. Calgary Depression Scale for Schizophrenia was used to assess the severity of depression. All participants were followed up for 2 years, and ultra-high risk of psychosis remitters were defined by ultra-high risk of psychosis individuals who no longer fulfilled Comprehensive Assessment of At-Risk Mental State criteria at the end of the study period. Levels of brain-derived neurotrophic factor were measured in the serum by enzyme-linked immunosorbent assay method.Results:The ultra-high risk of psychosis group had significantly higher baseline levels of serum brain-derived neurotrophic factor compared with the control group (3.7 vs 3.3 ng/mL, P=.018). However, baseline levels of serum brain-derived neurotrophic factor did not predict the development of psychosis (OR=0.64, CI=0.40–1.02) or remission (OR=0.83, CI=0.60–1.15) from ultra-high risk of psychosis status.Conclusion:Findings from our study did not support a role for serum brain-derived neurotrophic factor in predicting outcomes in ultra-high risk of psychosis individuals. However, the finding of higher levels of serum brain-derived neurotrophic factor in ultra-high risk of psychosis individuals deserves further study.NMRC (Natl Medical Research Council, S’pore)MOH (Min. of Health, S’pore)Published versio