Digital cognitive assessments as low-burden markers for predicting future cognitive decline and tau accumulation across the Alzheimer's spectrum.

BACKGROUND: Digital cognitive assessments, particularly those that can be done at home, present as low-burden biomarkers for participants and patients alike, but their effectiveness in the diagnosis of Alzheimer's disease (AD) or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk of cognitive decline. METHODS: We analyzed >500 Alzheimer's Disease Neuroimaging Initiative participants who underwent a brief digital cognitive assessment and amyloid beta (Aß)/tau positron emission tomography scans, examining their ability to distinguish cognitive status and predict cognitive decline. RESULTS: Performance on the digital cognitive assessment was superior to both cortical Aß and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation. DISCUSSION: Digital assessments are effective at identifying at-risk individuals, supporting their utility as low-burden tools for early AD detection and monitoring. HIGHLIGHTS: Performance on digital cognitive assessments predicts progression to mild cognitive impairment at a higher proficiency compared to amyloid beta and tau. Deficits in mnemonic discrimination are indicative of future cognitive decline. Impaired mnemonic discrimination predicts future entorhinal and inferior temporal tau.

Stakeholder-informed pragmatic trial protocol of the TabCAT-BHA for the detection of cognitive impairment in primary care.

BACKGROUND: Cognitive impairment and dementia are frequently under-recognized. Health system strategies anchored in primary care are essential to address gaps in timely, comprehensive diagnosis. The goal of this paper is to describe the adaptation of a tablet-based brain health assessment (TabCAT-BHA) intervention and the study protocol to test its effectiveness in improving the detection of cognitive impairment, including dementia. METHODS: This mixed-methods, pragmatic, cluster randomized, hybrid effectiveness-implementation trial is being conducted in two 18-month waves with 26 Kaiser Permanente Southern California primary care clinics, with 13 serving as intervention clinics and 13 as usual care clinics. Patients 65 years and older with memory concerns (n ~ 180,000) receiving care at the 26 clinics will be included in the analyses. Primary care clinics are provided the following practice supports as part of the TabCAT-BHA intervention: brief education and training on neurocognitive disorders and study workflows; digital tools to assess cognitive function and support clinician decision making and documentation; and registered nurse support during the work-up and post-diagnosis periods for primary care providers, patients, and families. The intervention was adapted based on engagement with multiple levels of clinical and operational leaders in the healthcare system. Effectiveness outcomes include rates of cognitive impairment diagnosis in primary care and rates of completed standardized cognitive assessments and specialist referrals with incident diagnoses. Implementation outcomes include acceptability-appropriateness-feasibility, adoption, and fidelity. RESULTS: We identified seven themes organized by system-, provider-, and patient-level domains that were used to adapt the TabCAT-BHA intervention. Accordingly, changes were made to the provider education, diagnostic work-up, and post-diagnostic support. Results will be reported in fall of 2027. CONCLUSIONS: Our engagement with multiple primary and specialty care clinical and operational leaders to adapt the TabCAT-BHA intervention to these primary care clinics has informed the protocol to evaluate the intervention's effectiveness for improving the detection of cognitive impairment, including dementia, in an integrated healthcare system. TRIAL REGISTATION: Clinicaltrials.gov: NCT06090578 (registered 10/24/23).

Cardiology and Neurophysiological Stimulation of Internet Gaming Disorders: A Systematic Review.

BACKGROUND: Internet Gaming Disorder (IGD) is recognized as a mental health condition associated with excessive video gaming, leading to functional impairments. The inclusion of IGD in the DSM-5 has underscored the importance of comprehensively understanding its physiological and psychological effects. OBJECTIVE: This systematic review aims to analyze and synthesize existing literature on the cardiophysiological and neurophysiological activities of individuals diagnosed with IGD, with a focus on identifying patterns, trends, and implications for clinical practice and future research. METHODS: A systematic search was conducted in PubMed and Scopus databases to identify relevant studies published up to 2023. The search strategy included terms related to IGD, cardiophysiology, neurophysiology, and relevant measurement techniques. Inclusion criteria encompassed peer-reviewed research articles and clinical trials examining cardiophysiological (e.g., heart rate variability, blood pressure) and neurophysiological (e.g., brain imaging, electroencephalography) parameters in individuals with IGD. Exclusion criteria were applied to ensure methodological rigor and relevance to the research question. RESULTS: The initial search yielded 1320 papers related to IGD, of which twenty studies met the eligibility criteria and were included in the review. Data extraction and synthesis focused on key cardiophysiological and neurophysiological outcomes observed in individuals with IGD compared to healthy controls. Findings revealed decreased Heart Rate Variability (HRV), increased sympathetic activity, and executive control deficits in IGD individuals based on Electrocardiogram (ECG) recordings and cognitive assessments. Neuroimaging studies demonstrated heightened brain activation in the lateral and prefrontal cortex, altered reward processing, and impulse control mechanisms among IGD subjects. Gender-specific differences were noted, with males exhibiting distinct thalamic activation striatum and decreased Regional Homogeneity (ReHo) in the right Posterior Cingulate (rPCC) compared to females. DISCUSSION: The synthesized evidence indicates a complex interplay between excessive gaming and cardiophysiological/neurophysiological changes, highlighting the need for multidimensional assessments in diagnosing and managing IGD. Implications for clinical practice include early detection using ECG, EEG, and advanced neuroimaging techniques, as well as personalized interventions tailored to individual characteristics and gender-specific differences. CONCLUSION: This systematic review provides a comprehensive overview of the cardiophysiological and neurophysiological activities associated with Internet Gaming Disorder. The findings underscore the need for further research to elucidate underlying mechanisms, develop standardized diagnostic protocols, and optimize targeted interventions for individuals with IGD.

Metacognitive accuracy differences in Parkinson's disease and REM sleep behavioral disorder relative to healthy controls.

Background: Metacognition is the ability to monitor and self-assess cognitive performance. It can be impaired in neurodegenerative diseases, with implications for daily function, and the ability of patients to reliably report their symptoms to health professionals. However, metacognition has not been systematically assessed in early-mid stage Parkinson's disease (PD) and REM sleep behavioral disorder (RBD), a prodrome of PD. Objectives: This study aimed to evaluate metacognitive accuracy and self-confidence in PD and RBD patients across various cognitive tasks. Methods: We conducted detailed computerized cognitive assessments with 19 cognitive tasks within an established PD and RBD cohort. Participants self-rated their performance post-task. Metacognitive accuracy was calculated by comparing these ratings against objective performance and further analyzed against clinical and mental health factors. Results: PD and RBD patients' metacognitive accuracy aligned with control subjects. However, they exhibited lower confidence across cognitive domains, reflecting their reduced cognitive performance. A notable inverse correlation was observed between their confidence and MDS-UPDRS I and II scales and HADS anxiety and depression scores. Conclusion: Our findings indicate that patients with early to mid-stage PD and RBD are generally aware of their cognitive status, differing from other neurological disorders. The inverse relationship between patient confidence and symptoms of depression, anxiety, and daily life challenges underscores the impact of emotional and functional difficulties on their self-perception of cognitive abilities. This insight could be significant for understanding how these conditions affect mental health, aiding clinicians in developing more effective patient care strategies.

Occupational Therapy Practitioners' Perceptions on Addressing Cognition in Acute Care: A National Survey.

This study aimed to identify commonly used standardized cognitive screens and functional performance assessments among occupational therapy practitioners at level 1 trauma centers in the USA. A survey completed by 269 occupational therapy practitioners revealed the most common cognitive screens and the association between cognitive tool training and standardized cognitive tool implementation. Implications for practice are discussed with suggestions for improving occupational therapy practice.

Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11.2 deletion syndrome.

BACKGROUND: Neurocognitive functioning is an integral phenotype of 22q11.2 deletion syndrome relating to severity of psychopathology and outcomes. A neurocognitive battery that could be administered remotely to assess multiple cognitive domains would be especially beneficial to research on rare genetic variants, where in-person assessment can be unavailable or burdensome. The current study compares in-person and remote assessments of the Penn computerised neurocognitive battery (CNB). METHODS: Participants (mean age = 17.82, SD = 6.94 years; 48% female) completed the CNB either in-person at a laboratory (n = 222) or remotely (n = 162). RESULTS: Results show that accuracy of CNB performance was equivalent across the two testing locations, while slight differences in speed were detected in 3 of the 11 tasks. CONCLUSIONS: These findings suggest that the CNB can be used in remote settings to assess multiple neurocognitive domains.

A psychometric evaluation of the NIH Toolbox fluid cognition tests adapted for Swahili and Dholuo languages in Kenyan children and adolescents.

OBJECTIVE: Our objective was to evaluate the psychometric properties of the culturally adapted NIH Toolbox African Languages® when used in Swahili and Dholuo-speaking children in western Kenya. METHOD: Swahili-speaking participants were recruited from Eldoret and Dholuo-speaking participants from Ajigo; all were <14 years of age and enrolled in primary school. Participants completed a demographics questionnaire and five fluid cognition tests of the NIH Toolbox® African Languages program, including Flanker, Dimensional Change Card Sort (DCCS), Picture Sequence Memory, Pattern Comparison, and List Sorting tests. Statistical analyses examined aspects of reliability, including internal consistency (in both languages) and test-retest reliability (in Dholuo only). RESULTS: Participants included 479 children (n = 239, Swahili-speaking; n = 240, Dholuo-speaking). Generally, the tests had acceptable psychometric properties for research use within Swahili- and Dholuo-speaking populations (mean age = 10.5; SD = 2.3). Issues related to shape identification and accuracy over speed limited the utility of DCCS for many participants, with approximately 25% of children unable to match based on shape. These cultural differences affected outcomes of reliability testing among the Dholuo-speaking cohort, where accuracy improved across all five tests, including speed. CONCLUSIONS: There is preliminary evidence that the NIH Toolbox ® African Languages potentially offers a valid assessment of development and performance using tests of fluid cognition in Swahili and Dholuo among research settings. With piloting underway across other diverse settings, future research should gather additional evidence on the clinical utility and acceptability of these tests, specifically through the establishment of norming data among Kenyan regions and evaluating these psychometric properties.

VR for Cognition and Memory.

This chapter will provide a review of research into human cognition through the lens of VR-based paradigms for studying memory. Emphasis is placed on why VR increases the ecological validity of memory research and the implications of such enhancements.

Computerized cognitive testing in patients with Parkinson's disease: an Indian perspective.

Aim: This study investigates perspectives on computer-based assessments among elderly individuals with Parkinson's disease (PD) in India for more efficient usability of digital assessments for this population. Materials & methods: Content analysis was conducted on 30 participants diagnosed with PD, who were interviewed for their preferences and perspectives on integrating technology in healthcare assessments. Results: Elderly individuals with PD in India favored paper-pencil assessments over computer-based alternatives due to limited technological familiarity, resistance to change, lack of trust in healthcare technology and PD-related motor challenges. Conclusion: Elderly patients with Parkinson's in India indicated their discomfort with computer-based based cognitive assessment. Addressing barriers toward digital assessments in India is crucial for their successful implementation in healthcare.

Early Identification of Cognitive Impairment: Utility of the Mini-Cog in Non-Clinical Settings.

While we currently cannot cure Alzheimer's disease or change the course of the disease, there are advantages to early detection. Routine, evidence based, brief cognitive screens offer destigmatized opportunities for diagnosis and improve the possibility of early identification of cognitive impairment. This community-based participatory research project evaluated the use of the Mini-Cog™ instrument to detect cognitive impairment in vulnerable community-dwelling older adults when administered by trained social services providers. Over 9 months, a case manager screened 69 clients ages 65 to 94 (mean 74.67) who met inclusion criteria for the pilot; 84.1% were female, 53.6% were Black, 26% were living with undetected cognitive impairment. Although participants agreed to Mini-Cog™ screening, two-thirds with Mini-Cog™ scores indicating cognitive impairment refused referrals for further evaluation. Future interventions should reduce stigma by educating the public about dementia and engaging members of racial and cultural communities in outreach.

Invited Commentary: Algorithmic Dementia Classification-Promises and Challenges.

Dementia is a complex, progressive syndrome characterized by cognitive decline and disability. Gold-standard dementia diagnosis requires several hours of cognitive and clinical assessment and review by a panel of clinicians and is infeasible in large population-based cohort studies. Alternatively, algorithmic dementia classification methods, which use models that take into account measures of cognition and functional limitations or cognitive and functional-limitation score cutoffs, have been developed to predict dementia status for participants in large studies. Developing accurate dementia classification algorithms is crucial for high-quality studies of the distribution and determinants of dementia. The accompanying article by Nichols et al. (Am J Epidemiol. 2023;192(4):520-534) assesses differences in associations of measures of cognition and functional limitations with prevalent dementia versus incident dementia and discusses implications for algorithmic dementia classification in research studies. This work highlights important opportunities for tailoring measures of cognition and functional limitations to study goals by selecting optimal measures and developing and validating algorithms specific to study needs. Combining efficient, high-quality assessments of cognition and functional limitations with innovative study designs will facilitate collection of higher-quality measurements in larger samples and support future development of accurate dementia classifications, ultimately leading to more impactful epidemiologic studies.

Estimating random effects in a finite Markov chain with absorbing states: Application to cognitive data.

Finite Markov chains with absorbing states are popular tools for analyzing longitudinal data with categorical responses. The one step transition probabilities can be defined in terms of fixed and random effects but it is difficult to estimate these effects due to many unknown parameters. In this article we propose a three-step estimation method. In the first step the fixed effects are estimated by using a marginal likelihood function, in the second step the random effects are estimated after substituting the estimated fixed effects into a joint likelihood function defined as a h-likelihood, and in the third step the covariance matrix for the vector of random effects is estimated using the Hessian matrix for this likelihood function. An application involving an analysis of longitudinal cognitive data is used to illustrate the method.

Relationships of Motor Changes with Cognitive and Neuropsychiatric Features in FMR1 Male Carriers Affected with Fragile X-Associated Tremor/Ataxia Syndrome.

The premutation expansion of the Fragile X Messenger Ribonucleoprotein 1 (FMR1) gene on the X chromosome has been linked to a range of clinical and subclinical features. Nearly half of men with FMR1 premutation develop a neurodegenerative disorder; Fragile X-Associated Tremor/Ataxia Syndrome (FXTAS). In this syndrome, cognitive executive decline and psychiatric changes may co-occur with major motor features, and in this study, we explored the interrelationships between these three domains in a sample of adult males affected with FXTAS. A sample of 23 adult males aged between 48 and 80 years (mean = 62.3; SD = 8.8), carrying premutation expansions between 45 and 118 CGG repeats, and affected with FXTAS, were included in this study. We employed a battery of cognitive assessments, two standard motor rating scales, and two self-reported measures of psychiatric symptoms. When controlling for age and/or educational level, where appropriate, there were highly significant correlations between motor rating score for ICARS gait domain, and the scores representing global cognitive decline (ACE-III), processing speed (SDMT), immediate memory (Digit Span), and depression and anxiety scores derived from both SCL90 and DASS instruments. Remarkably, close relationships of UPDRS scores, representing the contribution of Parkinsonism to FXTAS phenotypes, were exclusive to psychiatric scores. Highly significant relationships between CGG repeat size and most scores for three phenotypic domains suggest a close tracking with genetic liability. These findings of relationships between a constellation of phenotypic domains in male PM carriers with FXTAS are reminiscent of other conditions associated with disruption to cerebro-cerebellar circuits.

Unsupervised mobile app-based cognitive testing in a population-based study of older adults born 1944.

Background: Mobile app-based tools have the potential to yield rapid, cost-effective, and sensitive measures for detecting dementia-related cognitive impairment in clinical and research settings. At the same time, there is a substantial need to validate these tools in real-life settings. The primary aim of this study was thus to evaluate the feasibility, validity, and reliability of mobile app-based tasks for assessing cognitive function in a population-based sample of older adults. Method: A total of 172 non-demented (Clinical Dementia Rating 0 and 0.5) older participants (aged 76-77) completed two mobile app-based memory tasks-the Mnemonic Discrimination Task for Objects and Scenes (MDT-OS) and the long-term (24 h) delayed Object-In-Room Recall Task (ORR-LDR). To determine the validity of the tasks for measuring relevant cognitive functions in this population, we assessed relationships with conventional cognitive tests. In addition, psychometric properties, including test-retest reliability, and the participants' self-rated experience with mobile app-based cognitive tasks were assessed. Result: MDT-OS and ORR-LDR were weakly-to-moderately correlated with the Preclinical Alzheimer's Cognitive Composite (PACC5) (r = 0.3-0.44, p < .001) and with several other measures of episodic memory, processing speed, and executive function. Test-retest reliability was poor-to-moderate for one single session but improved to moderate-to-good when using the average of two sessions. We observed no significant floor or ceiling effects nor effects of education or gender on task performance. Contextual factors such as distractions and screen size did not significantly affect task performance. Most participants deemed the tasks interesting, but many rated them as highly challenging. While several participants reported distractions during tasks, most could concentrate well. However, there were difficulties in completing delayed recall tasks on time in this unsupervised and remote setting. Conclusion: Our study proves the feasibility of mobile app-based cognitive assessments in a community sample of older adults, demonstrating its validity in relation to conventional cognitive measures and its reliability for repeated measurements over time. To further strengthen study adherence, future studies should implement additional measures to improve task completion on time.

Feasibility of Digital Memory Assessments in an Unsupervised and Remote Study Setting.

Sensitive and frequent digital remote memory assessments via mobile devices hold the promise to facilitate the detection of cognitive impairment and decline. However, in order to be successful at scale, cognitive tests need to be applicable in unsupervised settings and confounding factors need to be understood. This study explored the feasibility of completely unsupervised digital cognitive assessments using three novel memory tasks in a Citizen Science project across Germany. To that end, the study aimed to identify factors associated with stronger participant retention, to examine test-retest reliability and the extent of practice effects, as well as to investigate the influence of uncontrolled settings such as time of day, delay between sessions or screen size on memory performance. A total of 1,407 adults (aged 18-89) participated in the study for up to 12 weeks, completing weekly memory tasks in addition to short questionnaires regarding sleep duration, subjective cognitive complaints as well as cold symptoms. Participation across memory tasks was pseudorandomized such that individuals were assigned to one of three memory paradigms resulting in three otherwise identical sub-studies. One hundred thirty-eight participants contributed to two of the three paradigms. Critically, for each memory task 12 independent parallel test sets were used to minimize effects of repeated testing. First, we observed a mean participant retention time of 44 days, or 4 active test sessions, and 77.5% compliance to the study protocol in an unsupervised setting with no contact between participants and study personnel, payment or feedback. We identified subject-level factors that contributed to higher retention times. Second, we found minor practice effects associated with repeated cognitive testing, and reveal evidence for acceptable-to-good retest reliability of mobile testing. Third, we show that memory performance assessed through repeated digital assessments was strongly associated with age in all paradigms, and individuals with subjectively reported cognitive decline presented lower mnemonic discrimination accuracy compared to non-complaining participants. Finally, we identified design-related factors that need to be incorporated in future studies such as the time delay between test sessions. Our results demonstrate the feasibility of fully unsupervised digital remote memory assessments and identify critical factors to account for in future studies.

Modeling Users' Cognitive Performance Using Digital Pen Features.

Digital pen features model characteristics of sketches and user behavior, and can be used for various supervised machine learning (ML) applications, such as multi-stroke sketch recognition and user modeling. In this work, we use a state-of-the-art set of more than 170 digital pen features, which we implement and make publicly available. The feature set is evaluated in the use case of analyzing paper-pencil-based neurocognitive assessments in the medical domain. Most cognitive assessments, for dementia screening for example, are conducted with a pen on normal paper. We record these tests with a digital pen as part of a new interactive cognitive assessment tool with automatic analysis of pen input. The physician can, first, observe the sketching process in real-time on a mobile tablet, e.g., in telemedicine settings or to follow Covid-19 distancing regulations. Second, the results of an automatic test analysis are presented to the physician in real-time, thereby reducing manual scoring effort and producing objective reports. As part of our evaluation we examine how accurately different feature-based, supervised ML models can automatically score cognitive tests, with and without semantic content analysis. A series of ML-based sketch recognition experiments is conducted, evaluating 10 modern off-the-shelf ML classifiers (i.e., SVMs, Deep Learning, etc.) on a sketch data set which we recorded with 40 subjects from a geriatrics daycare clinic. In addition, an automated ML approach (AutoML) is explored for fine-tuning and optimizing classification performance on the data set, achieving superior recognition accuracies. Using standard ML techniques our feature set outperforms all previous approaches on the cognitive tests considered, i.e., the Clock Drawing Test, the Rey-Osterrieth Complex Figure Test, and the Trail Making Test, by automatically scoring cognitive tests with up to 87.5% accuracy in a binary classification task.

Tracking the Progression and Influence of Beta-Amyloid Plaques Using Percolation Centrality and Collective Influence Algorithm: A Study Using PET Images.

Background: The study of brain networks, particularly the spread of disease, is made easier thanks to the network theory. The aberrant accumulation of beta-amyloid plaques and tau protein tangles in Alzheimer's disease causes disruption in brain networks. The evaluation scores, such as the mini-mental state examination (MMSE) and neuropsychiatric inventory questionnaire, which provide a clinical diagnosis, are affected by this build-up. Purpose: The percolation of beta-amyloid/tau tangles and their impact on cognitive tests are still unspecified. Methods: Percolation centrality could be used to investigate beta-amyloid migration as a characteristic of positron emission tomography (PET)-image-based networks. The PET-image-based network was built utilizing a public database containing 551 scans published by the Alzheimer's Disease Neuroimaging Initiative. Each image in the Julich atlas has 121 zones of interest, which are network nodes. Furthermore, the influential nodes for each scan are computed using the collective influence algorithm. Results: For five nodal metrics, analysis of variance (ANOVA; P < .05) reveals the region of interest (ROI) in gray matter (GM) Broca's area for Pittsburgh compound B (PiB) tracer type. The GM hippocampus area is significant for three nodal metrics in the case of florbetapir (AV45). Pairwise variance analysis of the clinical groups reveals five to twelve statistically significant ROIs for AV45 and PiB, respectively, that can distinguish between pairs of clinical situations. Based on multivariate linear regression, the MMSE is a trustworthy evaluation tool. Conclusion: Percolation values suggest that around 50 of the memory, visual-spatial skills, and language ROIs are critical to the percolation of beta-amyloids within the brain network when compared to the other extensively used nodal metrics. The anatomical areas rank higher with the advancement of the disease, according to the collective influence algorithm.

Reduced rank multinomial logistic regression in Markov chains with application to cognitive data.

Finite Markov chains are useful tools for studying transitions among health states; these chains can be complex consisting of a mix of transient and absorbing states. The transition probabilities, which are often affected by covariates, can be difficult to estimate due to the presence of many covariates and/or a subset of transitions that are rarely observed. The purpose of this article is to show how to estimate the effect of a subset of covariates of interest after adjusting for the presence of multiple other covariates by applying multidimensional dimension reduction to the latter. The case in which transitions within each row of the one-step transition probability matrix are estimated by multinomial logistic regression is discussed in detail. Dimension reduction for the adjustment covariates involves estimating the effect of the covariates by a product of matrices iteratively; at each iteration one matrix in the product is fixed while the second is estimated using either standard software or nonlinear estimation, depending on which of the matrices in the product is fixed. The algorithm is illustrated by an application where the effect of at least one Apolipoprotein-E (APOE) gene ϵ4 allele on transition probability is estimated in a Markov Chain that includes adjustment for eight covariates and focuses on transitions from normal cognition to several forms of mild cognitive impairment, with possible absorption into dementia. Data were drawn from annual cognitive assessments of 649 participants enrolled in the BRAiNS cohort at the University of Kentucky's Alzheimer's Disease Research Center.

Population measures of subjective cognitive decline: A means of advancing public health policy to address cognitive health.

Subjective cognitive decline (SCD) is receiving increasing attention as studies have suggested that SCD status is associated with risk of future cognitive decline and dementia. Population-based measures of SCD can be extremely useful to the public health community, health-care providers, researchers, and policymakers. A large population-based SCD measure now exists through the state-based Behavioral Risk Factor Surveillance System (BRFSS). All 50 states have included the cognitive decline module, which asks about SCD, to their BRFSS survey one or more times. Population measures of SCD can aid researchers in designing clinical studies by better estimating the populations that may be at risk for more severe cognitive decline based on their SCD status to ensure that the optimal groups are targeted. Population-level estimates of SCD can also help to inform health-care providers' decisions about initiating cognitive assessments, managing other conditions among those with memory problems, and identifying the needs of caregivers.

Using a serious game to measure executive functioning: Response inhibition ability.

In previous research, we developed a serious target acquisition game (with moles as targets) for assessing cognitive speed. Tong, Chignell, Tierney, and Lee demonstrated that performance on the game may be a useful screening tool for risk of delirium onset. In this study, we validate a version of the game where there are not only targets (moles) that should be hit but also distractors (butterflies, or moles with hats) that should not be hit. We hypothesized that performance on the game should be a measure of response inhibition ability, which has been implicated as a factor in many types of psychopathology. We carried out an experiment (with 30 healthy participants) to test whether the serious game does in fact measure response inhibition by comparing game performance with a standard response inhibition task (the Go/No-Go discrimination task). Our results show that, with the distractors, the game does in fact assess response inhibition ability. We discuss the implications of this work for assessing executive functions in the elderly, and for evaluating recovery in neuro-rehabilitation, and declining ability to perform activities of daily living.