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Sequential testing with brief cognitive tools has been recommended to improve cognitive screening and monitoring, however the few available tools still depend on an external evaluator and periodic visits. We developed a self-administered computerized test intended for longitudinal cognitive testing (Brain on Track). The test can be performed from a home computer and is composed of several subtests, expected to evaluate different cognitive domains, all including random elements to minimize learning effects. An initial (A) and a refined version of the test (B) were applied to patients with mild cognitive impairment or early dementia (n = 88) and age and education-matched controls. A subsample of a population-based cohort (n = 113) performed the test at home every three months to evaluate test-retest reliability. The test’s final version Cronbach’s alpha was 0.90, test scores were significantly different between patients and controls ( p  = 0.001), the area under the receiver operating characteristic curve was 0.75 and the smallest real difference (43.04) was lower than the clinical relevant difference (56.82). In the test-retest reliability analysis 9/10 subtests showed two-way mixed single intraclass consistency correlation coefficient >0.70. These results imply good internal consistency, discriminative ability and reliability when performed at home, encouraging further longitudinal clinical and population-based studies.

Cognitive theories of depression contend that biased cognitive information processing plays a causal role in the development of depression. Extensive research shows that deeper processing of negative and/or shallower processing of positive self-descriptors (i.e., negative and positive self-schemas ) predicts current and future depression in adults and children. However, the neural correlates of the development of self-referent encoding are poorly understood. We examined children's self-referential processing using the self-referent encoding task (SRET) collected from 74 children at ages 6, 9, and 12; around age 10, these children also contributed structural magnetic resonance imaging data. From age 6 to age 12, both positive and negative self-referential processing showed mean-level growth, with positive self-schemas increasing relatively faster than negative ones. Further, voxel-based morphometry showed that slower growth in positive self-schemas was associated with lower regional gray matter volume (GMV) in ventrolateral prefrontal cortex (vlPFC). Our results suggest that smaller regional GMV within vlPFC, a critical region for regulatory control in affective processing and emotion development, may have implications for the development of depressogenic self-referential processing in mid-to-late childhood.

•Describes the ABCD study aims and design.•Covers issues surrounding estimation of meaningful associations, including population inferences, effect sizes, and control of covariates.•Outlines best practices for reproducible research and reporting of results.•Provides worked examples that illustrate the main points of the paper. The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and children's health in the United States. A cohort of n = 11,880 children aged 9–10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are applied to a computer-based assessment with a learning intervention. The results show the potential application of the proposed model to track the change of students' skills directly and provide immediate remediation as well as to evaluate the efficacy of different interventions by investigating how different types of learning interventions impact the transitions from nonmastery to mastery.

As research on cognitive training methods for older adults with mild cognitive impairment (MCI) progresses, fully immersive virtual reality cognitive training (fi-VRCT) has shown promise in enhancing cognitive function. However, its effectiveness in improving instrumental activities of daily living (IADL) and fostering independence is still unclear. This study aims to address these uncertainties by developing and validating a fi-VRCT program focused on IADL, with the goal of enhancing both cognitive function and IADL performance in older adults with MCI. This mixed methods program evaluation study consists of three phases: feasibility, intervention, and extension. In the feasibility phase, we will implement fi-VRCT in real-world community settings and invite 20 older adults with MCI to participate in a single training session. Participants will provide feedback through questionnaires and individual interviews. The intervention phase will involve a double-blind, cluster-randomized controlled trial with 52 older adults with MCI, who will be randomly assigned to either the fi-VRCT or control groups. Both groups will complete 16 sessions over eight weeks, with cognitive and functional performance assessed at various intervals. During the extension phase, feedback will be gathered from 26 participants who underwent fi-VRCT through focus group interviews and ongoing questionnaires. Quantitative and qualitative findings will be synthesized to refine the fi-VRCT program and elucidate training outcomes. Ultimately, fi-VRCT has the potential to enhance cognitive and functional abilities in older adults with MCI in community settings. Ethical approval has been obtained from the Research Ethics Committee at National Taiwan Normal University (202312EM009). The research findings will be disseminated through reputable, peer-reviewed journals and professional international conferences to engage and inform academic and clinical audiences. NCT06392412.

Background Cognitive dysfunction is a disabling feature of migraine, affecting attention, memory, and executive functions. Differences between episodic and chronic migraine, as well as between interictal and ictal periods, remain unclear. We aimed to compare interictal cognitive performance in episodic and chronic migraine with healthy controls and to evaluate intra‐individual changes during attacks. Methods In this cross‐sectional study with within‐subject repeated measures, migraine patients (32 EM, 32 CM) and 30 matched healthy controls underwent standardized cognitive testing (Mini Mental State Examination, Clock Drawing Test, Stroop Test, Digit Span Forward/Backward Tests) assessing attention, short‐term and working memory, and executive function along with Beck Depression Inventory. Migraine cohorts were evaluated interictally (≥ 72 h attack‐free) and again within the first 3 h of an untreated spontaneous migraine attack. Results Interictally, CM patients demonstrated significant impairments in attention, short‐term memory, and working memory compared to healthy controls. EM patients, however, showed no cognitive dysfunction except for working memory. During migraine attacks, all cognitive domains deteriorated significantly in both groups. The magnitude of cognitive decline during an attack did not differ between EM and CM. Attack severity was associated with greater cognitive decline during attacks in the general migraine group, but this association was more pronounced in EM than in CM. Conclusions Migraine is a neurobiological disorder with cognitive consequences that extend beyond pain. Our findings highlight the importance of incorporating cognitive assessment into routine migraine management and reveal the need for longitudinal studies to elucidate the underlying mechanisms of cognitive dysfunction in migraine. Migraine is not only a pain disorder but a dynamic network disorder with measurable cognitive consequences. Interictally, working memory impairment was observed in episodic migraine, while chronic migraine showed broader deficits in attention and executive functions. During attacks, both subtypes demonstrated significant cognitive decline across all domains, independent of migraine type. Attack severity was associated with cognitive worsening, particularly in episodic migraine. Our findings highlight the clinical importance of incorporating routine cognitive assessment into migraine management.

Introduction Immune checkpoint inhibitors (ICI) have revolutionized cancer therapy in recent years. In addition to rejuvenating anti-cancer immunity, ICI may cause immune dysregulation, impacting homeostasis, including brain functions. Thus, the association of ICI with cognitive function needs further investigation. Using NIH’s PROMIS system, this study investigates self-reported cognitive impairment within a diverse cohort of ICI-treated patients. Additionally, we explore risk factors influencing self-reported cognitive function, including concurrent symptoms and racial/ethnic background. Methods This was a prospective, longitudinal study conducted between July 2021 and June 2023. Included patients were ≥ 18 years old, newly diagnosed with cancer, and scheduled to receive ICI therapy. Serial patient-reported outcomes (PROs) were collected from self-reported patient surveys at therapy initiation and while receiving treatment. Clinically significant cognitive impairment was defined as mild to severe symptoms measured on computer adaptive tests using the PROMIS Bank v2.0 — Cognitive Function. Multi-step analysis utilizing generalized estimating equations (GEE) was implemented to evaluate characteristics associated with cognitive function T-scores. Results Our study included 51 ICI patients, with 51% being of Asian or Hispanic descent. Of 126 PROMIS symptom survey sets collected, 16.7% reported clinically significant cognitive impairment, with incidence peaking in survey sets collected 1–2 months removed from therapy initiation at 26.1%. All concurrent PROMIS symptom scores significantly correlated with cognitive function, including physical function ( r  = 0.33, p  < 0.001), fatigue ( r  = − 0.61, p  < 0.001), depression ( r  = − 0.56, p  < 0.001), and anxiety ( r  = − 0.56, p  < 0.001). Multi-variable regression demonstrated impaired physical function (Coef = − 4.01, p  = 0.007), fatigue (Coef = − 5.15, p  = 0.005), and anxiety (Coef = − 4.45, p  < 0.001) are associated with decreased cognitive function scores, after adjusting for other patient characteristics. Conclusion Patients receiving ICI therapy experience significant cognitive impairment with therapy initiation and in subsequent weeks and months during their therapy course. Managing and monitoring concurrent symptoms and inflammatory biomarkers may help identify at risk patients and alleviate cognitive impairments.

INTRODUCTION White matter hyperintensities (WMH), a key imaging biomarker of small vessel injury, may play a complex role in Alzheimer's disease (AD). We hypothesize that WMH not only directly contributes to cognitive decline but also moderates the relationship among AD pathology, treatment, and cognitive decline. METHODS A total of 1169 participants with 240‐week follow‐up in the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's (A4) study were analyzed. Linear regression models examined WMH's contribution to cognitive decline, its interaction with Aβ on p‐Tau217 level, and its interaction with anti‐amyloid treatment on cognitive decline. RESULTS Increase in WMH volume independently contributed to cognitive decline (p = 0.0028). Baseline WMH significantly moderated the relationship between Aβ change and p‐Tau217 change (p = 0.0035). Specifically, Aβ accumulation correlated with p‐Tau217 increase only in participants with low baseline WMH. WMH growth was associated with cognitive decline only in the treatment group (p < 0.0001). DISCUSSION WMH modulates the interplay of pathologies, emphasizing the need for comprehensive treatment approaches targeting multiple pathways. Highlights White matter hyperintensity (WMH) independently contributed to cognitive decline. WMH modulated the longitudinal relationship between Aβ and p‐Tau217. WMH interacted with anti‐amyloid treatment on longitudinal cognitive decline.

Cognitive impairments are commonly observed in individuals who use stimulants, yet few studies have tracked these individuals longitudinally. This prospective, 12-month longitudinal study investigated changes in cognitive functioning among active stimulant users and explored the associated factors. Adults with recent stimulant use were recruited from substance misuse treatment clinics and the community. Their demographics, history of drug use, and stimulant use disorder severity were assessed with structured clinical interviews. Global cognitive function and frontal executive function were measured every three months using the Montreal Cognitive Assessment (MoCA) and the Frontal Assessment Battery (FAB) over one year. Linear mixed-effects models evaluated temporal trajectories and associated factors related to the Changes in cognitive functions. Among 76 analysed participants, their frequency of stimulant uses were active and stable over 12 months. The MoCA scores averaged below the clinical cut-off at baseline, although no further persistent decline was observed. In contrast, FAB scores presented no systematic temporal changes. Being female and being of older ages were found to be associated with lower MoCA and FAB. None of severity, education, recent stimulant use, and lifetime duration of use, were found to be associated with cognition. While stimulant users exhibited some modest cognitive declines at baseline, no further substantial cognitive deterioration was observed over the one-year study period. Cognitive outcomes were more strongly associated with demographic factors than SUD severity or stimulant use patterns. These findings highlight the need for more sensitive tools to detect subtle cognitive changes associated with stimulant uses.

INTRODUCTION Remote neuropsychological testing can monitor brain health in individuals with or at risk of Alzheimer's disease (AD). We evaluated acceptability and validity of the Cogstate Brief Battery (CBB) for remote administration. METHODS Non‐demented adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) completed the CBB in‐clinic under supervision, then remotely every six months, with annual in‐clinic reassessments. Groups included cognitively unimpaired (CU) adults with normal amyloid (CU Aβ−) or elevated amyloid (CU Aβ+), and individuals with mild cognitive impairment with or without amyloid (MCI Aβ+, MCI Aβ−). Performance was compared across contexts and longitudinal changes were examined. RESULTS At baseline, MCI Aβ+ participants performed worse than CU Aβ−. CBB performance was similar across contexts, with consistent group differences. Over time, MCI Aβ+ participants showed greater decline on remote CBB measures than CU Aβ− adults. DISCUSSION Remote unsupervised CBB assessments are valid, reliable, and sensitive to AD‐related cognitive impairment. Highlights The Cogstate Brief Battery (CBB) was evaluated for remote, unsupervised detection of cognitive impairment and decline in Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. CBB performance was comparable across supervised in‐clinic and remote unsupervised contexts. Remote CBB assessments were found to be valid, reliable, and sensitive to amyloid‐associated cognitive impairment and decline.