Applied Neuropsychology-Adult最新文献

Objective: The study presented focuses on the creation of a machine learning (ML) model that uses electrophysiological (EEG) data to identify kids with attention deficit hyperactivity disorder (ADHD) from healthy controls. The EEG signals are acquired during cognitive tasks to distinguish children with ADHD from their counterparts.

Methodology: The EEG data recorded in cognitive exercises was filtered using low pass Bessel filter and notch filters to remove artifacts, by the data set owners. To identify unique EEG patterns, we used many well-known classifiers, including Naïve Bayes (NB), Random Forest, Decision Tree (DT), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost and Linear Discriminant Analysis (LDA), to identify distinct EEG patterns. Input features comprised EEG data from nineteen channels, individually and in combination.

Findings: Study indicates that EEG-based categorization can differentiate between individuals with ADHD and healthy individuals with accuracy of 84%. The RF classifier achieved a maximum accuracy of 0.84 when particular region combinations were used. Evaluation of classification performance utilizing hemisphere-specific EEG data yielded promising outcomes, particularly in the right hemisphere channels.

Novelty: The study goes beyond traditional methodologies by investigating the effect of regional data on categorization results. The contributions of various brain regions to these classifications are being extensively researched. Understanding the role of different brain regions in ADHD can lead to better diagnosis and treatment options for individuals with ADHD. The study of categorization ability, utilizing EEG data specific to each hemisphere, particularly channels in the right hemisphere region, provides further granularity to the findings.

The integration of virtual, mixed, and augmented reality technologies in cognitive neuroscience and neuropsychology represents a transformative frontier. In this Commentary, we conducted a meta-analysis of studies that explored the impact of Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR) on cognitive neuroscience and neuropsychology. Our review highlights the versatile applications of VR, ranging from spatial cognition assessments to rehabilitation for Traumatic Brain Injury. We found that MR and AR offer innovative avenues for cognitive training, particularly in memory-related disorders. The applications extend to addressing social cognition disorders and serving as therapeutic interventions for mental health issues. Collaborative efforts between neuroscientists and technology developers are crucial, with reinforcement learning and neuroimaging studies enhancing the potential for improved outcomes. Ethical considerations, including informed consent, privacy, and accessibility, demand careful attention. Our review identified common aspects of the meta-analysis, including the potential of VR technologies in cognitive neuroscience and neuropsychology, the use of MR and AR in memory research, and the role of VR in neurorehabilitation and therapy.

Memory impairment imposes a great burden on stroke patients and can be divided into Objective Memory Problems (OMPs) and Subjective Memory Complaints (SMCs). Studies have shown that these do not always co-occur. Possibly, the gap between SMCs and OMPs can be bridged when using a more ecologically valid memory test and considering the impact of other common stroke symptoms such as sensory hypersensitivity (SHS) and fatigue. In the present study, we applied Virtual Reality (VR) to create a sensory-rich environment with real-life stimuli. Memory performance was tested with the 15-Verbal Word Learning Test (VLT). Furthermore, we assessed SMCs (Everyday Memory Questionnaire), and the levels of SHS (Multi-Modal Evaluation of Sensory Sensitivity) and fatigue in the previous month. 31 chronic stroke patients and 32 healthy controls participated. The results showed that participants' memory performance decreased in a sensory-rich compared to a neutral environment. This decrease did not significantly differ between the groups. Interestingly, fatigue and SHS are related to the level of SMC in stroke patients but no such evidence was found in healthy controls. Last, for stroke patients, we found a significant negative correlation between SMCs and memory performance in a sensory-rich environment, but not in a neutral environment. In conclusion, our study implicates that in stroke patients, fatigue and SHS are related to SMCs and that using a sensory-rich VR environment might be a more ecologically valid way to objectify SMCs. However, interpretative caution is warranted due to the absence of sex and age-matched controls and potential selection bias.

In Japan, the diagnostic criteria for the higher brain dysfunction (HBD) emerged in 2005 in response to social needs for support for the patients and their families. The issue of cognitive dysfunction after brain trauma is not unique to Japan. The purpose of this study was to reveal the current status of family members of HBD patients from their perspective, focusing on the changes before and after the establishment of diagnostic criteria in Japan. We conducted a questionnaire survey for family members supporting the HBD patients. The questionnaire included the causative condition, explanation on HBD by health professionals, and problems/difficulties they encountered. This research involved family members of 278 HBD cases (males = 211, age 49 years). The major underlying cause was head injury (n = 139). Compared to patients diagnosed pre-2005, a significantly larger proportion of family members after 2005 received information on the condition during the acute phase (within one month) (p < 0.001), including that from physicians (p < 0.001). Nearly half of the families cited a lack of awareness of HBD among the professionals as a problem. In Japan, awareness of HBD in the society is gradually increasing especially after the current diagnostic criteria were implemented, and there has been a steady increase over time in early diagnosis. Yet, there still remain those not appropriately diagnosed. To salvage those patients and the families left behind, we are suggesting several recommendations to further augment clinical practice and the healthcare systems in Japan.

Parkinson's disease is the second most common neurodegenerative disease, but therapeutic options such as neuromodulation continue to show variable effects, making clinical management of the disease difficult. This systematic review with meta-analysis and meta-regression aimed to analyze the isolated effect of cortical modulation with transcranial direct current stimulation (tDCS) compared to sham stimulation on cognitive changes in people with Parkinson's disease. The databases used were: Web of Science, Scopus, PsycINFO, PubMed, and Cochrane. The results showed that tDCS can influence the improvement of cognition in PD (Inverse Variance:0.24 [95% Confidence Interval: 0.09 to -0.40], p < 0.00). The meta-analysis showed that active tDCS can influence cognitive function by improving aspects related to memory (Inverse Variance:0.34 [95% Confidence Interval: 0.07 to 0.61], p < 0.01) and reducing reaction time in cognitive tasks (Inverse Variance:0.42 [95% Confidence Interval: 0.07 to 0.76], p < 0.02). Innovative meta-regression analyses showed that variables such as age (Q = 2.54, df = 1, p < 0.11), education level (Q = 2.62, df = 1, p < 0.10), disease duration (Q = 0.01, df = 1, p < 0.92), and Unified PD Rating Scale stage (Q = 0.01, df = 1, p < 0.92) did not influence the results. Thus, tDCS may be a therapeutic option for cognitive changes in people with PD, and we suggest further studies to identify protocols that can be replicated.

Motor assessment has emerged as complementary evidence for the detection of late life cognitive disorders. Clinicians lack inexpensive, accurate, and portable tools for this purpose. To fill this void, the current study piloted measures from the Mizzou Point-of-care Assessment System a multimodal sensor platform. We examined the ability of these motor function measures to distinguish neurocognitive status and assessed their associations with cognitive performance. Data came from 42 older adults, including 16 with mild cognitive impairment (MCI). Participants performed dual task gait, pairing walking with serial subtraction by sevens, along with aa neuropsychological test battery. T-tests revealed that individuals with MCI demonstrated slower stride times (d = .55) and shorter stride lengths (d = .98) compared to healthy older adults. Results from hierarchical regression showed that stride time and stride length predicted cognitive performance across several domains, after controlling for cognitive status and demographics. Cognitive status moderated this relationship for global cognition and attention, wherein gait measures were significantly related to these outcomes for the cognitively normal group, but not the MCI group. Evidence from the current study provided preliminary support that MPASS measures demonstrate expected associations with cognitive performance and can distinguish amongst those with and without cognitive impairment.

Objectives: This study examined the role of caregivers' perception of cognitive impairment in burden of family caregivers in Alzheimer's disease (AD). We hypothesized that the evaluation of cognitive impairment by family caregivers plays a pivotal role in burden.

Methods: The study included 110 dyads (person with AD and their caregiver) recruited from a Memory Unit in France. The cognitive impairment and depressive symptoms of person with AD were evaluated by a geriatrician using the Mini Mental State Examination (MMSE) and the Geriatric Depression Scale (GDS-15). Caregivers provided self-reports on the perception of cognitive impairment (IQCODE) of the care recipient, the caregiving burden (ZBI), depressive symptoms (GDS-15), and self-esteem (RSE). Descriptive analyses, comparison of different caregiver burden groups, and multinomial logistic regression analyses to understand correlates of caregiver burden were conducted with SPSS^®, version 20.

Results: The findings show that the caregivers are on average 60 years old and the majority are women. They care for persons with AD, who are on average 82 years old and most of whom are women. Our results show that the duration of caregiving, depression of the caregiver, and caregivers' perception of cognitive impairment contribute significantly to burden of caregiver.

Discussion: This study shows that it is necessary to adopt the caregiver-centered approach to support the dyad. The role of the caregivers' perception of cognitive impairment in AD should be developed when supporting caregivers in suffering.

Previous studies indicate that the effect of prism adaptation training (PAT) on unilateral neglect may depend on clinical characteristics. In this explorative work, we re-analyzed data from a previously conducted randomized controlled trial (N = 23) to investigate whether age, etiology, severity of motor impairments, and visual field deficits affect the efficacy of PAT. Additionally, we reviewed PAT studies that reported lesion maps and distinguished responders from non-responders. We transferred these maps into a common standard brain and added data from 12 patients from our study. We found patients suffering from subarachnoid bleeding appeared to show stronger functional recovery than those with intracranial hemorrhage or cortical infarction. Furthermore, patients with visual field deficits and those with more severe contralateral motor impairments had larger after-effect sizes but did not differ in treatment effects. In addition, patients with parietal lesions showed reduced recovery, whereas patients with lesions in the basal ganglia recovered better. We conclude that PAT (in its current form) is effective when fronto-subcortical areas are involved but it may not be the best choice when parietal regions are affected. Overall, the present work adds to the understanding on the effects of clinical characteristics on PAT.

Frontotemporal dementia (FTD) is an early-onset neurodegenerative disorder with a heterogeneous clinical presentation. Verbal fluency is regularly used as a sensitive measure of language ability, semantic memory, and executive functioning, but qualitative changes in verbal fluency in FTD are currently overlooked. This retrospective study examined qualitative, linguistic features of verbal fluency in 137 patients with behavioral variant (bv)FTD (n = 50), or primary progressive aphasia (PPA) [25 non-fluent variant (nfvPPA), 27 semantic variant (svPPA), and 34 logopenic variant (lvPPA)] and 25 control participants. Between-group differences in clustering, switching, lexical frequency (LF), age of acquisition (AoA), neighborhood density (ND), and word length (WL) were examined in the category and letter fluency with analysis of variance adjusted for age, sex, and the total number of words. Associations with other cognitive functions were explored with linear regression analysis. The results showed that the verbal fluency performance of patients with svPPA could be distinguished from controls and other patient groups by fewer and smaller clusters, more switches, higher LF, and lower AoA (all p < 0.05). Patients with lvPPA specifically produced words with higher ND than the other patient groups (p < 0.05). Patients with bvFTD produced longer words than the PPA groups (p < 0.05). Clustering, switching, LF, AoA, and ND-but not WL-were differentially predicted by measures of language, memory, and executive functioning (range standardized regression coefficient 0.25-0.41). In addition to the total number of words, qualitative linguistic features differ between subtypes of FTD. These features provide additional information on lexical processing and semantic memory that may aid the differential diagnosis of FTD.

This study evaluated the measurement invariance of a neuropsychological battery across rural and urban older adults from Costa Rica. Rural and urban older adults (N = 295) from the Epidemiology and Development of Alzheimer's Disease (EDAD) study in Costa Rica were assessed. The baseline factor model for the EDAD neuropsychological measures was identified with nine neuropsychological measures and three cognitive constructs: Verbal Memory, Spatial Reasoning, and Cognitive Flexibility. Measurement and structural invariance were established, and, then, group comparisons of the latent cognitive factors were conducted to explore regional disparities. The findings showed that most of the neuropsychological tests in EDAD can be directly compared across the groups, allowing for cognitive constructs comparisons. The rural sample showed a disadvantage in the Spatial Reasoning and Cognitive Flexibility abilities. When age and education were included in the models, differences between the regions disappeared. Having more years of education was associated with higher cognitive abilities, with a larger effect for the rural group. Norms for Costa Rican older adults should consider age and education adjustments. This study contributes to the growing area of measurement invariance in neuropsychological assessment as it highlights the importance of examining the comparability of assessment measures across different cultural groups.