Journal of Neuropsychology最新文献

Psychometric properties of Tommy's Quest (TQ), a novel serious game to evaluate Theory of Mind (ToM) and the pen-and-paper Faux Pas Test (FPT) were assessed. Results from 67 cognitively unimpaired individuals indicated that TQ had adequate construct validity, internal consistency and test-retest reliability. Participants performed worse on TQ compared to the FPT, suggesting greater sensitivity to subtle deficits. These findings support serious games like TQ as a promising tool for ToM assessment, highlighting the need for clinical validation.

Objective: Immersive virtual reality (VR) enhances ecological validity and facilitates intuitive and ergonomic hand interactions for performing neuropsychological assessments. However, its comparability to traditional computerized methods remains unclear. This study investigates the convergent validity, user experience and usability of VR-based versus PC-based assessments of short-term and working memory, as well as psychomotor skills, while also examining how demographic and IT-related skills influence performance in both modalities.

Methods: Sixty-six participants performed the Digit Span Task (DST), Corsi Block Task (CBT) and Deary-Liewald Reaction Time Task (DLRTT) in both VR- and PC-based formats. Participants' experience in using computers and smartphones, and playing videogames, was considered. User experience and system usability of the formats were also evaluated.

Results: While performance on DST was similar across modalities, PC assessments enabled better performance on CBT and faster reaction times in DLRTT. Significant correlations between VR and PC versions supported convergent validity. Regression analyses revealed that performance on PC versions was influenced by computing and gaming experience, whereas performance on VR versions was largely independent of these factors, except for gaming experience predicting performance on CBT backward recall. Moreover, VR assessments received higher ratings for user experience and usability than PC-based assessments.

Conclusion: Immersive VR assessments provide an engaging alternative to traditional computerized methods, with minimal reliance on prior IT experience and demographic factors. This resilience to individual differences suggests that VR may offer a more equitable and accessible platform for automated cognitive assessment. Future research should explore the long-term reliability of VR-based assessments.

Reports of patients with impaired verbal short-term memory are central to the debate of whether there are independent short-term stores or whether immediate repetition is supported by activated long-term memory. Patients with selective impairments of verbal short-term memory support models with independent buffers. However, it has been argued that these patients were too rare to provide reliable data. Second, it has been suggested that these patients might suffer from subtle impairments of word perception, comprehension or production which previous studies had failed to notice. Ten neurological patients were assessed. Nine participants had impaired immediate spans for digits, letters and words whilst having unimpaired word perception, comprehension and production. Another patient exhibited better preserved immediate repetition despite severely impaired word perception, comprehension and production. This double dissociation provides unequivocal evidence for the functional independence of short- and long-term memory. The size of the present group of STM participants, the largest to date, makes it impossible to ignore data from neuropsychological patients.

Cognitive assessment and analysis of plasma biomarkers are lower-cost options for the early assessment of Alzheimer's disease (AD). In this study, we examined whether serial position markers in the Rey's AVLT were sensitive to plasma AD biomarkers in cognitively unimpaired older individuals. Participants (n = 327; mean age = 70.4, SD = 10.4) were free of dementia (MMSE = 24+) at baseline and recruited as part of the Memory Evaluation Research Initiative (MERI; Nathan Kline Institute, NY, USA). Data included plasma p-tau231, Aβ40 and Aβ42, AVLT scores and demographics. Bayesian linear and logistic regression analyses were carried out with plasma biomarkers as outcomes (including the Aβ42/40 ratio); memory scores, including traditional metrics and serial position scores, were predictors; and age, years of education, APOE ε4-status and reported gender were control variables. Results indicated that plasma p-tau231 was associated primarily with delayed primacy recall (first four words): the more primacy words were recalled, the lower the plasma p-tau231 levels were. This study confirms that serial position analysis of word-list recall data, and particularly delayed primacy, is a valuable tool for the identification of in vivo AD-related pathology in cognitively unimpaired individuals.

Dementia constitutes one of the most widespread neurological disorders, representing an important health concern due to its increasing prevalence. Among the various types of dementia, Alzheimer's disease (AD) is the most common in the elderly, characterized by episodic memory impairment and also a decline in executive functions. Mild cognitive impairment (MCI) is considered a transitional stage between normal ageing and dementia, often described as a pre-dementia state. Distinguishing between these states is of paramount importance for the detection and appropriate care of patients. Functional Assessment Battery (FAB) is a screening tool for assessing executive function. In this study, 36 healthy individuals (HC), 31 single-domain amnestic mild cognitive impairment (aMCI) patients, and 29 Alzheimer's disease (AD) patients were assessed using FAB to determine its reliability, validity, and discriminative validity in a Spanish sample. Results indicated a good internal consistency of FAB in the AD sample (α = .71), but not in the aMCI group (α = .49). Significant differences between HC and both aMCI and AD groups were observed in the total scores of FAB. The FAB also showed good accuracy in distinguishing between HC and patients (AUC = 0.85), with an estimated optimal cut-off point of 16.5. However, its ability to distinguish between aMCI and AD individuals was lower (AUC = 0.68). More studies are necessary to corroborate our results using larger samples.

Both Alzheimer's (AD) and Parkinson's disease (PD) are often associated with memory dysfunction, but their pathophysiological underpinnings differ. The current research aimed to differentiate specific profiles of memory impairment due to AD versus PD. We used controlled learning and cued recall paradigm based on the Memory Binding Test (MBT) in 'clinically cognitively normal' controls (CN; n = 161), in patients with amnestic mild cognitive impairment due to AD (AD-aMCI; n = 50) and due to PD (PD-MCI; n = 22), and in PD with normal cognition (n = 18) as based on performance in the neuropsychological battery to prevent circularity in diagnostic decision-making. We applied analysis of covariance (ANCOVA) and Receiver Operating Characteristic (ROC) analysis to determine between-group differences and detection potential of the MBT. We found statistically large between-group differences with worse memory performance in paired cued recall conditions in AD-aMCI .050). The detection potential of MBT paired cued recall for differentiating memory impairment in AD-aMCI from CN yielded an AUC of 90% (95% CI, 85-96) and an AUC of 91% (95% CI, 81->99) between AD-aMCI and PD-MCI. Associative memory and binding impairment are most pronounced in AD-aMCI in comparison to PD-MCI and controls. Overall, the MBT is an efficient tool for the differential diagnosis of memory impairment due to the two most common neurodegenerative diseases.

Neuropsychology's place in diagnosing dementia is still up for debate. With the advent of disease-modifying therapies, the optimisation of diagnostic pathways is increasingly urgent, particularly in the early stages of Alzheimer's disease. Yet, biomarker-driven frameworks eclipse neuropsychological testing as an ancillary tool rather than recognising it as a core component of clinical assessment. Emerging evidence indicates that relying solely on biomarkers does not provide a dependable forecast for the onset or progression of dementia. This drawback underscores how important neuropsychology is. Nonetheless, the clinical adoption of neuropsychological tests for diagnostic purposes requires a paradigm shift towards a more rigorous methodology. Despite its recognised diagnostic potential, the current neuropsychological framework is constrained by thresholds derived from normative distributions rather than Clinimetrics. Many existing tests rely on arbitrary cut-offs that do not account for disease prevalence, personological variability, or real-world cognitive performance. This oversimplified approach reduces the sensitivity of neuropsychological assessments and limits their integration into clinical practice. The development of population-specific clinimetric studies that establish weighted cut-offs for sensitivity and specificity based on clinical aims is crucial to ensure clinically meaningful decision-making.

Artificial intelligence (AI) and machine learning (ML) algorithms are revolutionising the world, and they have the potential to revolutionise neuropsychology as well. A particularly fruitful field for this revolution is the cognitive assessment of neurodegenerative disorders, such as Alzheimer's disease, Parkinson's disease, Mild Cognitive Impairment and Primary Progressive Aphasia. This narrative review explores the impact of ML and AI in classifying these patients by using biomarkers or neuropsychological tests, using vast amounts of data and providing previously unattainable insights. Additionally, the article will evaluate the accuracies of several ML algorithms, such as support vector machines, random forest or convolutional neural networks. The article will also discuss the challenges related to ML like the risk of overfitting and the need for ML algorithms to execute a differential analysis among several pathologies-a capability that current research has yet to achieve fully. Furthermore, it proposes new directions to improve the clinical utility and accuracy of ML classification algorithms in neuropsychology, underlining the possibility for theoretical advancements based on the results of these classifications.

We investigated the course of recovery of emotion recognition impairments during the first year after mild stroke. Furthermore, we studied whether long-term emotion recognition impairments are related to behavioural problems and mood problems. Patient recruitment took place at the stroke unit of a general hospital. Fifty-eight mild ischaemic stroke patients underwent neuropsychological assessments of emotion recognition and overall cognition at 6-8 weeks and 1-year post-stroke. At follow-up, questionnaires were administered to identify behavioural problems and mood problems. Emotion recognition scores of patients were compared to scores of 109 healthy controls that were matched according to age, sex and educational level to identify impairments. Baseline patient emotion recognition scores were compared to the patient scores at follow-up to investigate recovery. In this group of mild stroke patients, emotion recognition was impaired compared with healthy controls, with no recovery over time. One year after stroke emotion recognition was impaired in 31% of the mild stroke participants. At 1-year post-stroke, impaired emotion recognition was associated with overall cognitive impairment and self-reported behavioural problems, but not with mood. Even in mild stroke, emotion recognition is on average impaired in the long term and related to behavioural problems. A substantial portion of mild stroke patients have impairments in emotion recognition both in the subacute phase as well as in the long term. Early assessment of emotion recognition is important to identify patients at risk of developing behavioural problems. Appropriate and early treatment might be necessary to prevent persisting problems.

Depressive symptoms (DS) after stroke are associated with marked negative consequences for rehabilitation. Identifying determinants of DS is needed to enable prediction and develop psychological interventions. A promising candidate may be self-concept and changes thereof, so-called self-discrepancy. Consulting recent self-concept models, we investigated the role of self-concept subdomains and their individual importance. Within a prospective longitudinal study, 120 stroke survivors were interviewed via telephone 3 years post-ictus to assess present and past self-concept, self-discrepancy, self-concept subdomains and DS. The association of self-concept measures and DS was investigated using an ANCOVA. Controlling for established determinants (age, sex, history of depression, functional independence, social support), multiple regression analyses were used to examine the independent influence of self-concept measures and the role of subdomains and importance-weightings. Self-discrepancy showed a significant interaction with DS (F (1, 118) = 32.69, p < .001, η² = .22). DS showed a stronger association with present (r = -.72) than with past self-concept (r = -.34) and self-discrepancy (r = -.47; all p < .001). Age, history of depression, social support and present self-concept were independent predictors of DS while functional independence was not (∆F (1, 113) = 48.04, p < .001). Importance-weighting of subdomains did not affect explained variance, though the number of self-concept subdomains showing significant association with DS increased. Findings propose appraisals of self-concept as independent predictors of DS after stroke. Considering individual importance of subdomains reveals their differential influence. The results suggest investigating the use of general self-concept for prediction and considering the individual relevance of subdomains in psychological interventions after stroke.