While early-life adverse experiences have been linked to late-life cognitive decline, few studies have explored war exposure. Paradoxically, one study even indicated a late-life cognitive advantage of early-childhood war exposure. In the present study, we explored these associations.

We examined older adults exposed to World War II (1940–1944; n = 1179) and the subsequent Civil war (1946–1949; n = 962) in Greece during early and middle childhood with a comprehensive neuropsychological assessment and for ApoE-ε allele status, including demographic information and medical history.

Higher cognitive performance in language tasks predicted middle childhood, relative to early childhood, WWII-exposure group membership (B = .316, p = .038, OR:1.372, 95%CI:1.018–1.849), primarily for men, while higher attention/speed (B = .818, p = .002, OR:2.265, 95%CI:1.337–3.838) and total cognitive score (B = .536, p = .040, OR:1.709, 95%CI:1.026–2.849) were predictors of belonging to the middle-childhood group, only in men. Individuals who did not meet criteria for Mild Cognitive Impairment (MCI)/dementia were more likely to belong to the middle-childhood war-exposure group. Similarly, for the Civil war, higher cognitive scores and reduced likelihood to meet criteria for MCI/dementia were predictors of middle, relative to early childhood war exposure group membership (visuospatial score: B = .544, p = .001, OR:1.723, 95%CI:1.246–2.381, MMSE: B = .134, p = .020, OR:1.143, 95%CI:1.021–1.297), primarily for women. Results remained consistent when adjusting for multimorbidity, sex, education, current age, depression, and anxiety.

The present findings suggest that better cognitive performance and lower likelihood of MCI or dementia were associated with being exposed to significant hardships, such as war, during middle childhood, regardless of potentially confounding factors. Further studies are needed to shed light on this relationship.

Mild cognitive impairment (MCI) involves measurable cognitive decline that does not yet significantly disrupt daily functioning but may signal increased risk of dementia. Reliable prediction of dementia conversion in MCI is essential for early intervention and optimized clinical trial design. This study aimed to evaluate the predictive performance of various machine learning (ML) classification algorithms using clinical and neuropsychological data.

Data were drawn from the Gothenburg MCI Study and included 347 patients from a memory clinic, of whom 84 (24%) converted to dementia within two to six years. We applied 11 ML classification algorithms (logistic regression, linear discriminant analysis, naïve Bayes, k-nearest neighbors, LASSO, ridge regression, elastic net, decision tree, random forest, gradient boosting, and support vector machine (SVM)) to predict dementia conversion based on 54 clinical predictors (e.g., cerebrospinal fluid biomarkers, neuropsychological test scores, comorbidities, and demographics). In a second step, we included delta scores reflecting change in neuropsychological test performance from baseline to follow-up.

Without delta scores, LASSO, ridge, elastic net, random forest, and SVM performed best, achieving accuracy ≥0.87, kappa = 0.64, and AUC-ROC ≥0.90. These models demonstrated high specificity (0.94) but moderate sensitivity (0.68). Including delta scores improved performance, with ridge and elastic net achieving accuracy = 0.90, kappa = 0.73 and 0.72, AUC-ROC = 0.94, specificity = 0.96, and sensitivity = 0.73. The elastic net model yielded a positive predictive value of 0.85 and a negative predictive value of 0.92.

ML models incorporating clinical and cognitive change data can accurately predict dementia conversion in MCI, supporting their utility in clinical decision-making.

Evaluating pauses in natural speech is a promising strategy for improving reliability, validity, and efficiency in assessing cognitive functions in people with mild cognitive impairment (MCI) and Alzheimer’s dementia (AD).

We conducted a quantitative meta-analysis of studies employing automated pause analysis. We included measures of speaking rate for comparison.

We identified 13 studies evaluating pause measures and 8 studies of speaking rate in people with MCI (n’s = 276 & 109, respectively) and AD (n’s = 170 & 81, respectively) and healthy aged controls (n’s = 492 & 231, respectively). Studies evaluated speech across various tasks, including standard neuropsychological, reading, and free/conversational tasks. People with AD and MCI showed longer pauses than controls at approximately 1.20 and 0.62 standard deviations, respectively, though there was substantial heterogeneity across studies. A more modest effect, of 0.66 and 0.27 SDs, was observed between these groups in speech rate. The largest effects were observed for standardized memory tasks.

Of the many ways that speech can be objectified, pauses appear particularly important for understanding cognition in AD. Pause analysis has the benefit of being face valid, interpretable in ratio format as a reaction time, tied to known socio-cognitive functions, and relatively easy to measure, compute, and interpret. Automation of speech analysis can greatly expand the assessment of AD and potentially improve early identification of one of the most devastating and costly diseases affecting humans.

Spatial neglect is a heterogeneous post-stroke disorder with subtypes differing in reference frames, processing stages, and spatial domains. While egocentric peri-personal neglect recovery has been studied, recovery trajectories of allocentric peri-personal visuospatial and personal neglect remain unclear. This study investigated recovery time courses of egocentric and allocentric peri-personal visuospatial and personal neglect during the first 12 weeks post-stroke; whether initial severity predicts recovery and defines distinct patient clusters; and how subtypes interrelate over time.

Forty-one first-ever stroke patients were evaluated at weeks 3, 5, 8, and 12 post-stroke using the Broken Hearts Test, Line Bisection Test, Visuospatial Search Time Test, and Fluff Test. Recovery was analyzed using linear mixed models, clustering with Gaussian finite mixture models, and interrelationships using Spearman correlations.

Significant improvements occurred in egocentric and allocentric peri-personal visuospatial and personal neglect, primarily between weeks 3 and 5, followed by a plateau. The Line Bisection Test detected no changes. Higher initial severity predicted greater residual impairment. Cluster analysis identified near-normal, mild, and moderate-to-severe baseline subgroups with distinct recovery trajectories. Moderate-to-good correlations (ρ = 0.33 – 0.55) emerged between egocentric and allocentric neglect at week 3 and when timepoints were pooled.

Neglect improved mainly between weeks 3 and 5 after which recovery plateaued, mirroring motor and language recovery and suggesting a shared time-limited window. Initial severity was a determinant of recovery, highlighting the value of early severity stratification to monitor and support recovery potential after stroke. As subtypes are distinctive, assessment should include multiple neglect tests.

This study aimed to explore the correlates of zero, one, and multiple performance validity test (PVT) failures on cognitive test performance in patients with various degrees of severity of traumatic brain injury.

306 participants completed the Trail Making Test as part of a neuropsychological evaluation within 1–36 months post-injury. They were assigned to zero, one, or ≥ two fail groups on the basis of at least two independent PVTs. Group differences in Trail Making Test performance were analyzed with analysis of variance, with post hoc contrasts with the Bonferroni correction for multiple comparisons. Groups were also compared on various background characteristics.

Participants who passed all PVTs had statistically significantly better performance on both parts of the Trail Making Test as compared to those who failed either one or multiple PVTs, with the latter two groups not differing statistically significantly from each other. PVT failure was relatively more common in participants who were female, had an uncomplicated mild TBI, were involved in financial compensation-seeking, and were seen at a longer time point since injury.

Failure of even only one PVT is associated with lower neuropsychological test performance in patients with traumatic brain injury, especially when empirically validated criteria are used that are stratified by injury severity. Such failure does not always reflect malingering but must be interpreted and addressed in the context of patient background characteristics.

Sensory burden, a momentary experience of being bothered by sensory stimuli, is a frequent challenge following acquired brain injury (ABI). This study quantitatively tested a theoretical model conceptualizing sensory burden as a dynamic interaction between situational triggers and an individual’s biopsychosocial resources using an experience sampling method.

41 individuals with ABI (median age = 59 years, median time since injury = 6.3 years) provided real-time data at seven semi-random intervals per day over seven consecutive days. Multilevel regression modeling assessed the influence of situational triggers (setting, company, effort, activity dissatisfaction, and negative affect) and individual resources (processing speed, fatigue, and sleep quality) on sensory burden.

Momentary fluctuations in sensory burden varied in severity and variability across individuals. Sensory burden was associated with higher levels of negative affect (β = .58, p < .01), activity dissatisfaction (β = .07, p < .01), effort (β = .09, p < .01), and being in company (β = .39, p < .01). Moreover, sensory burden was related to slower processing speed (β = −0.04, p = .02) and higher fatigue (β = .19, p < .01). However, no interaction effects were found. Effort was the only positive, significant between-person predictor (β = .56, p < .01).

These findings underscore the dynamic and individualized nature of sensory burden after ABI, emphasizing the need for personalized interventions targeting sensory hypersensitivity. Future research should explore additional triggers, resources, and causal pathways to further elucidate the proposed mechanisms and inform treatment development.

To extend the current understanding of executive function (EF) deficits in youth with neurofibromatosis type 1 by investigating the impact of cognitive load on performance compared to typically developing children.

In this prospective multicenter study, 42 children with neurofibromatosis type 1 (NF1) (ages 7–18) completed neuropsychological assessments of intellect and executive functioning. Age- and sex-matched controls (n = 42) were drawn from the normative database for the tasks of executive control (TEC). Multivariate and supplementary univariate analyses examined group differences and task effects (inhibitory control and working memory demand). Associations between TEC performance and parent-reported executive dysfunction (BRIEF) were also explored.

Both groups showed reduced accuracy and speed with increased inhibitory demand and made fewer errors with increased working memory demand. However, children with NF1 were significantly less accurate and consistent across tasks, particularly under higher cognitive load, while controls improved or maintained performance. Significant group × cognitive load interactions were observed, and laboratory-based deficits in NF1 were associated with parent-reported executive dysfunction.

Children with NF1 experience unique and multidimensional decrements in EF performance in response to increased cognitive load, unlike typically developing peers. These deficits appear to be clinically relevant. Targeting working memory and inhibitory control may reduce susceptibility to cognitive overload and improve outcomes for children with NF1.

Neurocognitive assessment is an essential research instrument for autism spectrum disorder (ASD), as the clinical manifestations are rooted in diverse neurocognitive processes that cause variation in clinical presentation. Few instruments comprehensively capture relevant neurocognitive domains, and most require professional assessors. The Penn Computerized Neurocognitive Battery (CNB) is widely used in child and adolescent psychiatry research across cultures. This study adapted and validated the CNB for a clinical ASD cohort in Hong Kong.

In this Hong Kong version of the CNB (CNB-HK), thirteen cognitive tasks were translated and adapted, with one task for sensorimotor speed and twelve belonging to four specific domains (episodic memory, social cognition, complex cognition, and executive function). The CNB-HK was administered to 636 normal-IQ children with ASD (mean age: 8.4 years, 87.1% male) and 412 children without ASD (mean age: 8.6 years, 55.1% male). Factor structure was examined using factor analyses.

The CNB-HK had high feasibility for children with ASD, with <7% invalid data across all tasks. The original four-factor and bi-factor structures were replicated with good model fit, and partial scalar invariance was achieved between children with and without ASD. The factor scores correlated positively with estimated IQ in the ASD group. The ASD group had worse performance across all four cognitive domains and the g factor compared to the group without ASD.

The CNB-HK is a valid, multi-domain cognitive assessment tool for children with ASD in Hong Kong, offering a feasible and reliable approach for research and clinical settings.

Thai researchers developed a new self-report measure of executive functions for adolescents based on Diamond’s framework (the Behavioral Inventory Measure of Executive Functions [BIMEFs]). How it was developed, its psychometric properties, and norms by sex and age are reported here.

An independent panel of experts evaluated the content validity of BIMEFs. Reliability was checked using Cronbach’s alpha with a sample of 45 secondary students. 1,865 students, ages 12 – 18 years (65% female) from across Thailand participated in the normative study.

The BIMEFs consists of 42 items that assess inhibitory control (IC), working memory (WM), and cognitive flexibility (CF), including eight subcomponents. For all items, the index of item-objective congruence was >0.5 and Cronbach’s alpha was >0.7. Confirmatory factor analysis (CFA) showed the adjusted goodness of fit index to be 0.9. The strongest sex difference was for IC. Students of 13 years scored lower on EFs overall, IC, WM, CF, and all subcomponents than older students. Self-control, verbal working memory, and being able to change perspectives showed the most pronounced differences by age.

The BIMEFs, which is designed to be culturally-appropriate for Thailand and cross-culturally generally, is the first EF questionnaire based on Diamond’s framework. It shows good psychometric properties and sensitivity to age and sex differences. It indicates that IC development, at least in Thailand, plateaus earlier than WM and CF and that CF shows a more protracted development during adolescence than IC or WM.

Language deficits are frequently described by patients with multiple sclerosis (MS); however, objective characterization remains somewhat limited due to its omission from standard MS cognitive evaluation and the inconsistent findings that arise from current language measures.

To establish alternative approaches to characterizing single-word level language in MS, this study (i) validates the Sydney Language Battery (SYDBAT) visual confrontation naming subtest and (ii) examines the insights provided by examining naming errors and latencies.

40 MS patients from Royal Melbourne Hospital’s Cognitive Neuroimmunology Clinic and 40 matched controls completed a series of neuropsychological tests, including the SYDBAT and ‘gold standard’ confrontation naming task, the Boston Naming Test (BNT). Error types and latencies on the SYDBAT were extracted from assessment audio recordings.

SYDBAT and BNT scores were highly correlated (r = 0.81, p < .001) and these tasks reported comparable receiver operating characteristic curves (p = .091). Latency analysis captured lexical retrieval difficulties, with patients displaying significantly longer mean latencies than controls on the SYDBAT (p = .012, β = 0.54).

These findings support the validity of the SYDBAT and value of the latency analysis in characterizing language impairment in MS. Use of the SYDBAT and latency considerations contribute to a broader assessment with a briefer administration time compared to gold-standard evaluation. The study thereby offers clinicians an enhanced toolkit to more effectively and appropriately evaluate language functioning and supplement standard cognitive evaluation in this population.

This study aimed to update normative data and establish cut-off scores for a fruit-based semantic verbal fluency (SVF) task among older Taiwanese adults as a method for detecting mild cognitive impairment (MCI). The task was chosen due to its familiarity and cultural neutrality for Mandarin-speaking populations.

SVF performance was evaluated in 245 healthy control participants and 360 individuals diagnosed with MCI. The influence of demographic variables was examined, and regression-based correction formulas were developed. Receiver operating characteristic (ROC) analyses determined optimal cut-off values according to established clinical classifications of MCI.

Age, education, and sex significantly influenced SVF performance. A demographically corrected 15th percentile threshold of 10 words was proposed for community screening. An optimal ROC-derived cut-off of 11.5 words yielded an AUC of .716 (95% CI: .68–.76), with sensitivity of 57.8% and specificity of 73.9%. SVF scores were significantly correlated with global cognition, memory, and processing speed.

The fruit-based SVF task is a quick, culturally relevant tool for detecting early cognitive impairment. Revised norms and cut-off scores can improve MCI identification in Mandarin-speaking seniors.