EPELI: a novel virtual reality task for the assessment of goal-directed behavior in real-life contexts

Working memory related functional connectivity in adult ADHD and its amenability to training: A randomized controlled trial

BACKGROUND

Working memory (WM) deficits are among the most prominent cognitive impairments in attention deficit hyperactivity disorder (ADHD). While functional connectivity is a prevailing approach in brain imaging of ADHD, alterations in WM-related functional brain networks and their malleability by cognitive training are not well known. We examined whole-brain functional connectivity differences between adults with and without ADHD during n-back WM tasks and rest at pretest, as well as the effects of WM training on functional and structural brain connectivity in the ADHD group.

METHODS

Forty-two adults with ADHD and 36 neurotypical controls performed visuospatial and verbal n-back tasks during functional magnetic resonance imaging (fMRI). In addition, seven-minute resting state fMRI data and diffusion-weighted MR images were collected from all participants. The adults with ADHD continued into a 5-week randomized controlled WM training trial (experimental group training on a dual n-back task, n = 21; active control group training on Bejeweled II video game, n = 21), followed by a posttraining MRI. Brain connectivity was examined with Network-Based Statistic.

RESULTS

At the pretest, adults with ADHD had decreased functional connectivity compared with the neurotypical controls during both n-back tasks in networks encompassing fronto-parietal, temporal, occipital, cerebellar, and subcortical brain regions. Furthermore, WM-related connectivity in widespread networks was associated with performance accuracy in a continuous performance test. Regarding resting state connectivity, no group differences or associations with task performance were observed. WM training did not modulate functional or structural connectivity compared with the active controls.

CONCLUSION

Our results indicate large-scale abnormalities in functional brain networks underlying deficits in verbal and visuospatial WM commonly faced in ADHD. Training-induced plasticity in these networks may be limited.

Naturalistic assessments in virtual reality and in real life help resolve the age-prospective memory paradox

Cognitive aging researchers have long reported "paradoxical" age differences in prospective memory (PM), with age deficits in laboratory settings and age benefits (or no deficits) in real-world settings. We propose a theoretical account that explains this "age-PM-paradox" as a consequence of both methodological factors and developmental changes in cognitive abilities and personality traits. To test this account, young  and older  adults   performed a series of naturalistic PM tasks in the lab and real world. Age-related PM deficits were observed in both lab-based tasks where demands were implemented using virtual reality and in-person role-playing. In contrast, older adults performed equal to or better than young adults on both real-world tasks, where demands were implemented in participants' daily lives. Consistent with our proposed account, an index of these "paradoxical" effects was partially predicted by age-related differences in working memory, vigilance, agreeableness, and neuroticism, whose predictive utility varied across task settings.

Enhancing Ecological Validity: Virtual Reality Assessment of Executive Functioning in Children and Adolescents with ADHD

BACKGROUND

SmartAction-VR uses virtual reality to simulate daily life tasks and assess cognitive performance based on the multi-errand paradigm. This study explored whether this new task could provide insights into the executive functioning of children and adolescents with ADHD in their everyday activities.

METHODS

A cross-sectional study was conducted between November 2021 and December 2022. It consisted of one session and was divided into two parts (cognitive tests; and SmartAction-VR). The sample comprised 76 children and adolescents with a median age (IQR) of 13 (11-14) years and an age range of 9-17 years. Of these participants, 60.50% (n = 46) were males. Out of this sample, 40 participants were in the ADHD group and 36 were in the neurotypical group. The following instruments were used: Waisman Activities of Daily Living Scale, Assessment of Sensory Processing and Executive Functioning, Pediatric Simulator Disease Questionnaire, Digit span subtest, Stroop test, NEPSY-II Subtest of Auditory Attention and Cognitive Flexibility, Trail Making Test, Zoo Map Test, and SmartAction-VR.

RESULTS

The ADHD group demonstrated lower accuracy (U = 406, p = 0.010), higher values for total errors (U = 292, p = 0.001), more commissions (U = 417, p = 0.003), new actions (U = 470, p = 0.014), and forgetting actions (U = 406, p = 0.010), as well as fewer perseverations compared to the neurotypical group (U = 540.5, p = 0.029). Additionally, participants who forgot more actions were found to have lower independence in daily life (r = -0.281, p = 0.024).

CONCLUSIONS

The correlations between the results of SmartAction-VR and activities of daily living, as well as cognitive tests, suggest that this new task could be useful for evaluating executive functioning in daily life.

Diagnosis of ADHD using virtual reality and artificial intelligence: an exploratory study of clinical applications

Introduction

Diagnosis of Attention Deficit/Hyperactivity Disorder (ADHD) is based on clinical evaluation of symptoms by a psychiatrist, referencing results of psychological tests. When diagnosing ADHD, the child's behavior and functionality in real-life situations are critical components. However, direct observation by a clinician is often not feasible in practice. Therefore, such information is typically gathered from primary caregivers or teachers, which can introduce subjective elements. To overcome these limitations, we developed AttnKare-D, an innovative digital diagnostic tool that could analyze children's behavioral data in Virtual Reality using Artificial Intelligence. The purpose of this study was to explore the utility and safety of AttnKare-D for clinical application.

Method

A total of 21 children aged between 6 and 12 years were recruited for this study. Among them, 15 were children diagnosed with ADHD, 5 were part of a normal control group, and 1 child was excluded due to withdrawal of consent. Psychological assessments, including K-WISC, Conners CPT, K-ARS, and K-CBCL, were conducted for participants and their primary caregivers. Diagnoses of ADHD were confirmed by child and adolescent psychiatrists based on comprehensive face-to-face evaluations and results of psychological assessments. Participants underwent VR diagnostic assessment by performing various cognitive and behavioral tasks in a VR environment. Collected data were analyzed using an AI model to assess ADHD diagnosis and the severity of symptoms.

Results

AttnKare-D demonstrated diagnostic performance with an AUC of 0.893 when compared to diagnoses made by child and adolescent psychiatrist, showing a sensitivity of 0.8 and a specificity of 1.0 at a cut-off score of 18.44. AttnKare-D scores showed a high correlation with K-ARS scores rated by parents and experts, although the correlation was relatively low for inattention scores.

Conclusion

Results of this study suggest that AttnKare-D can be a useful tool for diagnosing ADHD in children. This approach has potential to overcome limitations of current diagnostic methods, enhancing the accuracy and objectivity of ADHD diagnoses. This study lays the groundwork for further improvement and research on diagnostic tools integrating VR and AI technologies. For future clinical applications, it is necessary to conduct clinical trials involving a sufficient number of participants to ensure reliable use.