Classification of Mild Cognitive Impairment Using Functional Near-Infrared Spectroscopy-Derived Biomarkers With Convolutional Neural Networks.

OBJECTIVE: To date, early detection of mild cognitive impairment (MCI) has mainly depended on paper-based neuropsychological assessments. Recently, biomarkers for MCI detection have gained a lot of attention because of the low sensitivity of neuropsychological assessments. This study proposed the functional near-infrared spectroscopy (fNIRS)-derived data with convolutional neural networks (CNNs) to identify MCI. METHODS: Eighty-two subjects with MCI and 148 healthy controls (HC) performed the 2-back task, and their oxygenated hemoglobin (HbO2) changes in the prefrontal cortex (PFC) were recorded during the task. The CNN model based on fNIRS-derived spatial features with HbO2 slope within time windows was trained to classify MCI. Thereafter, the 5-fold cross-validation approach was used to evaluate the performance of the CNN model. RESULTS: Significant differences in averaged HbO2 values between MCI and HC groups were found, and the CNN model could better discriminate MCI with over 89.57% accuracy than the Korean version of the Montreal Cognitive Assessment (MoCA) (89.57%). Specifically, the CNN model based on HbO2 slope within the time window of 20-60 seconds from the left PFC (96.09%) achieved the highest accuracy. CONCLUSION: These findings suggest that the fNIRS-derived spatial features with CNNs could be a promising way for early detection of MCI as a surrogate for a conventional screening tool and demonstrate the superiority of the fNIRS-derived spatial features with CNNs to the MoCA.

Performance of ChatGPT on the National Korean Occupational Therapy Licensing Examination.

Background: ChatGPT is an artificial intelligence-based large language model (LLM). ChatGPT has been widely applied in medicine, but its application in occupational therapy has been lacking. Objective: This study examined the accuracy of ChatGPT on the National Korean Occupational Therapy Licensing Examination (NKOTLE) and investigated its potential for application in the field of occupational therapy. Methods: ChatGPT 3.5 was used during the five years of the NKOTLE with Korean prompts. Multiple choice questions were entered manually by three dependent encoders, and scored according to the number of correct answers. Results: During the most recent five years, ChatGPT did not achieve a passing score of 60% accuracy and exhibited interrater agreement of 0.6 or higher. Conclusion: ChatGPT could not pass the NKOTLE but demonstrated a high level of agreement between raters. Even though the potential of ChatGPT to pass the NKOTLE is currently inadequate, it performed very close to the passing level even with only Korean prompts.

Non-equivalence of sub-tasks of the Rey-Osterrieth Complex Figure Test with convolutional neural networks to discriminate mild cognitive impairment.

BACKGROUND: The Rey-Osterrieth Complex Figure Test (RCFT) is a tool to evaluate cognitive function. Despite its usefulness, its scoring criteria are as complicated as its figure, leading to a low reliability. Therefore, this study aimed to determine the feasibility of using the convolutional neural network (CNN) model based on the RCFT as a screening tool for mild cognitive impairment (MCI) and investigate the non-equivalence of sub-tasks of the RCFT. METHODS: A total of 354 RCFT images (copy and recall conditions) were obtained from 103 healthy controls (HCs) and 74 patients with amnestic MCI (a-MCI). The CNN model was trained to predict MCI based on the RCFT-copy and RCFT-recall images. To evaluate the CNN model's performance, accuracy, sensitivity, specificity, and F1-score were measured. To compare discriminative power, the area under the curve (AUC) was calculated by the receiver operating characteristic (ROC) curve analysis. RESULTS: The CNN model based on the RCFT-recall was the most accurate in discriminating a-MCI (accuracy: RCFT-copy = 0.846, RCFT-recall = 0.872, MoCA-K = 0.818). Furthermore, the CNN model based on the RCFT could better discriminate MCI than the MoCA-K (AUC: RCFT-copy = 0.851, RCFT-recall = 0.88, MoCA-K = 0.848). The CNN model based on the RCFT-recall was superior to the RCFT-copy. CONCLUSION: These findings suggest the feasibility of using the CNN model based on the RCFT as a surrogate for a conventional screening tool for a-MCI and demonstrate the superiority of the CNN model based on the RCFT-recall to the RCFT-copy.

Unveiling Neurocognitive Disparities in Encoding and Retrieval between Paper and Digital Tablet-Based Learning.

The widespread use of mobile devices and laptops has replaced traditional paper-based learning and the question of how the brain efficiency of digital tablet-based learning differs from that of paper-based learning remains unclear. The purpose of this study was to investigate the difference in brain efficiency for learning between paper-based and digital tablet-based learning by measuring activity in the prefrontal cortex (PFC) using functional near-infrared spectroscopy. Thirty-two subjects were randomly assigned to the paper-based learning or the digital tablet-based learning group. Subjects in each group performed a memory task that required memorizing a three-minute novel (encoding phase) on a paper or digital tablet, followed by a test in which they answered four multiple-choice questions based on the novel's content. To compare both groups, behavioral performance on the test (retrieval phase) and activity in the PFC were measured. As a result, no significant difference in behavioral performance between both groups was observed (p > 0.05). However, the paper-based learning group showed significantly lower activity in the PFC in the encoding phase than the digital tablet-based learning group (p < 0.05) but not in the retrieval phase. The current study demonstrated that brain efficiency in encoding is higher in subjects with paper-based learning than those with digital tablet-based learning. This finding has important implications for education, particularly in terms of the pros and cons of electronic document-based learning.

Effects of Personalized Cognitive Training Using Mental Workload Monitoring on Executive Function in Older Adults With Mild Cognitive Impairment.

Although a variety of cognitive training has been performed, its optimally personalized delivery is still unknown. This study established the mental workload classification model using a convolutional neural network based on functional near-infrared spectroscopy-derived data. The dorsolateral prefrontal cortex (DLPFC) while thirty individuals with mild cognitive impairment (MCI) performed spatial working memory testing was found to be a considerable indicator to classify 3 levels of mental workload with an accuracy of over 86%. In the next step, forty subjects with MCI were randomly allocated into the experimental group (EG) that received cognitive training with mental workload-based difficulty adjustment or the control group (CG) that received conventional cognitive training. To compare both groups, the Trail Making Test Part B (TMT-B) and hemodynamic responses in the DLPFC during the TMT-B were measured. After the 16 training sessions, the EG subjects achieved a greater improvement in the TMT-B than the CG subjects (p < 0.05). Also, the EG subject showed a significantly lower DLPFC activity during the TMT-B than the CG subject (p < 0.05). In sum, the EG subjects better performed executive function with lower energy from the DLPFC. These findings imply that the importance of mental workload monitoring to provide personalized cognitive training.

Mental workload classification using convolutional neural networks based on fNIRS-derived prefrontal activity.

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is a tool to assess brain activity during cognitive testing. Despite its usefulness, its feasibility in assessing mental workload remains unclear. This study was to investigate the potential use of convolutional neural networks (CNNs) based on functional near-infrared spectroscopy (fNIRS)-derived signals to classify mental workload in individuals with mild cognitive impairment. METHODS: Spatial images by constructing a statistical activation map from the prefrontal activity of 120 subjects with MCI performing three difficulty levels of the N-back task (0, 1, and 2-back) were used for CNNs. The CNNs were evaluated using a 5 and 10-fold cross-validation method. RESULTS: As the difficulty level of the N-back task increased, the accuracy decreased and prefrontal activity increased. In addition, there was a significant difference in the accuracy and prefrontal activity across the three levels (p's < 0.05). The accuracy of the CNNs based on fNIRS-derived spatial images evaluated by 5 and 10-fold cross-validation in classifying the difficulty levels ranged from 0.83 to 0.96. CONCLUSION: fNIRS could also be a promising tool for measuring mental workload in older adults with MCI despite their cognitive decline. In addition, this study demonstrated the feasibility of the classification performance of the CNNs based on fNIRS-derived signals from the prefrontal cortex.

Feasibility of Virtual Shopping Budget-Management Training on Executive Functions in Healthy Young Adults: A Pilot Study.

To date, budget management in virtual shopping training has not been given much importance. The main objective of this study was to investigate the effects of virtual shopping budget-management training on executive functions and brain activation. Sixteen participants were randomly assigned to the experimental group that received virtual shopping budget-management training or the waitlist control group for a total of 16 sessions. To examine the effects of virtual shopping budget-management training on brain activation, HbO2 was measured in the prefrontal cortex via functional near-infrared spectroscopy (fNIRS) during the Trail Making Test Part B (TMT-B) and Stroop test. Mann-Whitney and Wilcoxon signed-rank tests were used to compare outcomes between and within the two groups. The virtual shopping budget-management training showed no significant difference in all outcomes between both groups (p > 0.05). No significant differences were observed in HbO2 levels during both TMT-B (p > 0.05) and the Stroop test (p > 0.05). However, in the pre-post comparisons, there was a significant difference in the TMT-B (p < 0.05) and Stroop test (p < 0.05) in the experimental group. In this study, although we did not find a distinct advantage in training, it confirmed its potential for clinical benefits in healthy young adults through training.

Cognotyping by What-Where-When Retrieval Reveals the Potential Role of Temporal Memory and Its Neural Correlates in Understanding Individual Differences across Aging and Alzheimer Disease.

Despite distinct neural representation of what, where, and when information, studies of individual differences in episodic memory have neglected to test the three components separately. Here, we used a componential episodic memory task to measure cognitive profiles across a wide age range and in Alzheimer disease (AD) and to examine the role of theta oscillations in explaining performance. In Experiment 1, we tested a group of 47 young adults (age 21-30 years, 21 women) while recording their scalp EEG. A separate behavioral experiment (Experiment 2) was performed in 42 older adults (age 66-85 years, 29 women) and in a group of 16 AD patients (age 80-90 years, 12 women). In Experiment 1, K-means clustering based on behavioral data resulted in three "cognotypes" whose memory profiles showed corresponding differences in their EEG markers: What and where memory depended on frontal theta power and when memory depended on theta modulation by temporal distance between retrieved items. In Experiment 2, healthy older adults showed three cognotypes similar to those found in younger adults; moreover, AD patients had an overlapping profile with one specific cognotype, characterized by marked difficulties in when memory. These findings highlight the utility of componential episodic memory tests and cognotyping in understanding individual strengths and vulnerabilities in age-related neurocognitive decline.

Does Cognitive-Physical Dual-Task Training Have Better Clinical Outcomes than Cognitive Single-Task Training Does? A Single-Blind, Randomized Controlled Trial.

PURPOSE: At present, there is a controversy regarding the effect of dual-task training on improving the cognitive function of people with mild cognitive impairment (MCI). This study was to develop and verify the effects of the cognitive-physical dual-task training program on the executive function of older adults with MCI. METHOD: Participants were randomly allocated to the experimental group (EG) receiving cognitive-physical dual-task training (n = 21) or the control group (CG) receiving cognitive single-task training (n = 21). RESULTS: After 16 sessions for 8 weeks, the Korean version of the Executive Function Performance Task (EFPT-K), the Frontal Assessment Battery (FAB), and Korean version of the Instrumental Activities of Daily Living (K-IADL) tests were implemented to assess people's executive function and instrumental activities during daily living. As the result, there were no significant differences in general characteristics between both groups (p > 0.05). After 16 sessions, the EG showed greater improvements in the EFPT-K (p < 0.05; η2 = 0.133), the FAB (p < 0.001; η2 = 0.305), and the K-IADL (p < 0.01; η2 = 0.221) compared to those of the CG. CONCLUSION: These results indicate that cognitive-physical dual-task training is clinically beneficial to improve the executive function and daily instrumental activities of older adults with MCI. Cognitive-physical dual-task training is a promising intervention for older adults with MCI.

Can the fNIRS-derived neural biomarker better discriminate mild cognitive impairment than a neuropsychological screening test?

Introduction: Early detection of mild cognitive impairment (MCI), a pre-clinical stage of Alzheimer's disease (AD), has been highlighted as it could be beneficial to prevent progression to AD. Although prior studies on MCI screening have been conducted, the optimized detection way remain unclear yet. Recently, the potential of biomarker for MCI has gained a lot of attention due to a relatively low discriminant power of clinical screening tools. Methods: This study evaluated biomarkers for screening MCI by performing a verbal digit span task (VDST) using functional near-infrared spectroscopy (fNIRS) to measure signals from the prefrontal cortex (PFC) from a group of 84 healthy controls and 52 subjects with MCI. The concentration changes of oxy-hemoglobin (HbO) were explored during the task in subject groups. Results: Findings revealed that significant reductions in HbO concentration were observed in the PFC in the MCI group. Specially, the mean of HbO (mHbO) in the left PFC showed the highest discriminant power for MCI, which was higher than that of the Korean version of montreal cognitive assessment (MoCA-K) widely used as a screening tool for MCI. Furthermore, the mHbO in the PFC during the VDST was identified to be significantly correlated to the MoCA-K scores. Discussion: These findings shed new light on the feasibility and superiority of fNIRS-derived neural biomarker for screening MCI.

Ecological Effects of VR-Based Cognitive Training on ADL and IADL in MCI and AD patients: A Systematic Review and Meta-Analysis.

Declines in activities of daily living (ADL) and instrumental activities of daily living (IADL) performances due to cognitive impairments hinder mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients' independent and safe daily lives. In order to prevent and treat this, several cognitive interventions have been implemented, but their ecological validity was not ensured due to that their contents are far from real life. Virtual reality (VR) can resemble real life with immersive stimuli, but there have been few studies confirming its ecological effects on ADL and IADL. Therefore, this study conducted a meta-analysis of VR-based cognitive training to investigate its ecological effects on ADL and IADL in MCI and AD patients. From February 2012 to February 2022, a search was conducted for articles published in PubMed, Cochrane, Science Direct, and Web of Science. Quality assessment was assessed by the PEDro scale, and the Cochrane Collaboration tool was used to assess risk of bias. Publication bias was assessed by Egger's regression. Five studies that met inclusion criteria were included in this study. The VR-based cognitive training showed significant effects on ADL and IADL in both MCI and AD patients. When comparing effects in each group, both MCI and AD patients showed significant effects on ADL and IADL, but MCI patients showed lower effects on ADL and IADL than AD patients. The results indicated that VR-based cognitive training would be beneficial to improve ADL and IADL in MCI and AD patients, suggesting that VR-based cognitive training is ecologically valid.

Effects of Virtual Reality-Based Graded Exposure Therapy on PTSD Symptoms: A Systematic Review and Meta-Analysis.

Previous studies reported that virtual reality (VR)-based exposure therapy (VRET) was a clinically beneficial intervention for specific phobias. However, among VRET, VR-based graded exposure therapy (VR-GET) is little known about its efficacy on posttraumatic stress disorder (PTSD) symptoms. Therefore, this meta-analysis investigated the effects of VR-GET for PTSD symptoms. A literature search yielded seven randomized controlled trials. The differences between conditions regarding the primary outcome of PTSD symptoms in the effect size of the individual study were calculated using Hedges' g. The findings showed VR-GET showed a significantly larger effect size for PTSD symptoms (g = 1.100, p = 0.001), compared to controls. However, no significant difference between conventional VRET and controls was found for PTSD symptoms (g = -0.279, p = 0.970). These findings indicated the superiority of VR-GET for PTSD symptoms compared to controls, supporting the importance of immersive PTSD treatments. Nevertheless, the results need to be interpreted with caution due to the substantial number of military service personnel studies. Future trials, considering individually tailored scenarios in virtual environments to cover a wider range of trauma types, are required to investigate its evidence on treating PTSD.

Effects of Personalized Cognitive Training with the Machine Learning Algorithm on Neural Efficiency in Healthy Younger Adults.

To date, neural efficiency, an ability to economically utilize mental resources, has not been investigated after cognitive training. The purpose of this study was to provide customized cognitive training and confirm its effect on neural efficiency by investigating prefrontal cortex (PFC) activity using functional near-infrared spectroscopy (fNIRS). Before training, a prediction algorithm based on the PFC activity with logistic regression was used to predict the customized difficulty level with 86% accuracy by collecting data when subjects performed four kinds of cognitive tasks. In the next step, the intervention study was designed using one pre-posttest group. Thirteen healthy adults participated in the virtual reality (VR)-based spatial cognitive training, which was conducted four times a week for 30 min for three weeks with customized difficulty levels for each session. To measure its effect, the trail-making test (TMT) and hemodynamic responses were measured for executive function and PFC activity. During the training, VR-based spatial cognitive performance was improved, and hemodynamic values were gradually increased as the training sessions progressed. In addition, after the training, the performance on the trail-making task (TMT) demonstrated a statistically significant improvement, and there was a statistically significant decrease in the PFC activity. The improved performance on the TMT coupled with the decreased PFC activity could be regarded as training-induced neural efficiency. These results suggested that personalized cognitive training could be effective in improving executive function and neural efficiency.

Efficacy of Neuro-Feedback Training for PTSD Symptoms: A Systematic Review and Meta-Analysis.

If the negative emotions experienced in life become trauma, they affect daily life. Neuro-feedback technology has recently been introduced as a treatment, but many different neuro-feedback protocols and methods exits. This study conducted a meta-analysis of neuro-feedback training for post-traumatic stress disorder (PTSD) symptoms to evaluate the effects of functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG)-based neuro-feedback training. A search of PubMed, the Cochrane Library, Web of Science, Science Direct, and ClinicalTrials.gov was conducted from January 2011 to December 2021. The studies' quality was assessed using the Cochrane risk of bias tool and publication bias was assessed by Egger's regression test. Seven studies that met the inclusion criteria were used for the systematic review and meta-analysis. EEG was more effective than fMRI for PTSD symptoms, and the effect on PTSD symptoms was higher than on anxiety and depression. There was no difference in the effectiveness of the training sessions. Our findings showed that EEG-based neuro-feedback training was more helpful for training PTSD symptoms. Additionally, the methods were also shown to be valid for evaluating clinical PTSD diagnoses. Further research is needed to establish a gold standard protocol for the EEG-based neuro-feedback training (EEG-NFT) method for PTSD symptoms.

Can the Virtual Reality-Based Spatial Memory Test Better Discriminate Mild Cognitive Impairment than Neuropsychological Assessment?

Neuropsychological screening tools for mild cognitive impairment (MCI) have been widely used. However, to date, their sensitivity and specificity still remain unsatisfied. This study aims to investigate whether spatial memory can discriminate MCI better than neuropsychological screening tools. A total of 56 healthy older adults and 36 older adults with MCI participated in this study; they performed a spatial cognitive task based on virtual reality (SCT-VR), the Korean version of the Montreal Cognitive Assessment (MoCA-K), and the Wechsler Adult Intelligence Scale-Revised Block Design Test (WAIS-BDT). The discriminant power was compared between the SCT-VR and the MoCA-K, and the reliability and validity of the SCT-VR were analyzed. The spatial memory, assessed by the SCT-VR, showed better sensitivity and specificity (sensitivity: 0.944; specificity: 0.964) than the MoCA-K (sensitivity: 0.857; specificity: 0.746). The test-retest reliability of the SCT-VR was relatively high (ICCs: 0.982, p < 0.001) and the concurrent validity of the SCT-VR with the MoCA-K (r = −0.587, p < 0.001) and the WAIS-BDT (r = −0.594, p < 0.001) was statistically significant. These findings shed light on the importance of spatial memory as a behavioral marker of MCI. The ecologically validated spatial memory tasks based on VR need to be investigated by neuroscientific studies in the future.

Is Dual-Task Training Clinically Beneficial to Improve Balance and Executive Function in Community-Dwelling Older Adults with a History of Falls?

Purpose: To date, the effects of dual-task training on balance underlying cognitive function remain unclear. Therefore, this study was to verify the effects of cognitive−physical dual-task training on balance and executive function in community-dwelling older adults with a history of falls. Method: Fifty-eight participants were randomly allocated to the experimental group (EG) receiving cognitive−physical dual-task training (n = 29) or to the control group (CG) receiving functional balance training (n = 29). After 12 sessions for 6 weeks, the One Leg Standing Test (OLST), the Timed UP and Go (TUG), and part B of the Trail-Making Test (TMT-B) were implemented to examine static and dynamic balance and executive function. Results: After the 12 sessions, the EG showed a greater improvement in the OLST (p < 0.001; η2 = 0.332), the TUG (p < 0.001; η2 = 0.375), and the TMT-B (p < 0.001; η2 = 0.224) compared to the CG. Conclusion: These results indicate that dual-task training is clinically beneficial to improving static and dynamic balance as well as executive function in older adults with a history of falls. These findings shed new light on a clinical implication that executive function should be considered in balance training for older adults.

Does the virtual shopping training improve executive function and instrumental activities of daily living of patients with mild cognitive impairment?

To date, ecological validity of virtual shopping training for patients with mild cognitive impairment (MCI) has not been confirmed yet. Main objective of this study was to investigate effects of virtual shopping training on executive function and instrumental activities of daily living (IADL) in patients with MCI. 32 patients with MCI were randomly assigned to the experimental group that received virtual shopping training or the waitlist control group for a total of 16 sessions. To examine effects of virtual shopping training on executive function and IADL, Korean version of the Executive Function Performance Test (EFPT-K) and Korean Instrumental Activities of Daily living (K-IADL) were conducted. After the 16 sessions, the experimental group showed greater improvement in the EFPT-K (p < 0.001) and the K-IADL (p < 0.001) compared to the control group. These results suggest that virtual shopping training might be clinically beneficial to enhance executive function and IADL in patients with MCI.

Effects of acute moderate-intensity aerobic exercise on executive function and prefrontal cortex activity in community-dwelling older adults: A single-blind, randomized controlled trial.

AIM: To date, there is a controversy regarding the effects of acute aerobic exercise of moderate intensity on executive function and prefrontal cortex activity in community-dwelling older adults. This study aimed to investigate the effects of acute aerobic exercise of moderate intensity in healthy older adults. METHODS: Fifty-six healthy older adults were randomly assigned to the experimental group (EG) that performed moderate-intensity aerobic exercise or the wait-list control group (CG) for a total of 15 sessions. To compare the two groups, the Stroop Color-Word Task (SCWT) and the Trail-Making Test Part B (TMT-B) were implemented for executive function and prefrontal cortex activity during executive function testing. RESULTS: After the intervention, the EG achieved a significant improvement in the SCWT (P < 0.001; η2  = 0.196) and the TMT-B (P < 0.001; η2  = 0.245) compared with the CG. In addition, the EG showed a lower HbO2 concentration in the prefrontal cortex than the CG during the SCWT (P < 0.05; η2  = 0.076) and the TMT-B (P < 0.05; η2  = 0.090). CONCLUSIONS: These findings shed new light on the clinical effectiveness of acute moderate-intensity aerobic exercise on executive function and prefrontal cortex activity in healthy older adults. Geriatr Gerontol Int 2022; 22: 227-232.

Effects of virtual reality-based spatial cognitive training on hippocampal function of older adults with mild cognitive impairment.

BACKGROUND: To date, there is a controversy on effects of cognitive intervention to maintain or improve hippocampal function for older adults with mild cognitive impairment (MCI). OBJECTIVE: The main objective of this study was to exam effects of virtual reality-based spatial cognitive training (VR-SCT) using VR on hippocampal function of older adults with MCI. METHOD: Fifty-six older adults with MCI were randomly allocated to the experimental group (EG) that received the VR-SCT or the waitlist control group (CG) for a total of 24 sessions. To investigate effects of the VR-SCT on spatial cognition and episodic memory, the Weschsler Adult Intelligence Scale-Revised Block Design Test (WAIS-BDT) and the Seoul Verbal Learning Test (SVLT) were used. RESULTS: During the sessions, the training performances gradually increased (p < .001). After the intervention, the EG showed significant greater improvements in the WAIS-BDT (p < .001, η2 = .667) and recall of the SVLT (p < .05, η2 =.094) compared to the CG but in recognition of the SVLT (p > .05, η2 =.001). CONCLUSION: These results suggest that the VR-SCT might be clinically beneficial to enhance spatial cognition and episodic memory of older adults with MCI.