BACKGROUND:Menopause has historically been viewed through the lens of hormonal influences on sex organs and reproduction, despite evidence of widespread systemic hormonal effects. When seen through a neuropsychological perspective, it is critical to understand that many sex hormones, including estrogen, progesterone, testosterone, luteinizing hormone, and anti-Mullerian hormone, directly influence brain functioning. With these considerations in mind, distinct changes in hormonal levels that affect women at different periods throughout their lifetime are a central consideration for neuropsychologists. Considering menopause specifically, the menopausal transition includes variations in estradiol and progesterone levels, leading to eventual cessation of ovarian function. Alongside vasomotor symptoms, urogenital symptoms, and mood symptoms, there is evidence to support both subjective and objective cognitive changes during menopause. METHODOLOGY & RESULTS:Overall, articles from the current special issue can broadly be divided into two categories: (1) research investigating subjective and/or objective cognitive functioning during periods of hormonal transitions, including midlife and (2) the influence of reproductive factors on long-term cognitive outcomes. Here, they are briefly overviewed, followed by a discussion on applications to clinical care. CONCLUSION:Overall, these articles in the present special issue address a dearth of research on the relationship between reproduction, female sex hormones, menopause, and other factors with women's neuropsychological functioning, and aim to provide a significant contribution to the field, as well as spark interest among clinicians and researchers alike to continue to pursue these understudied topics.
INTRODUCTION:Deficits in semantic fluency are commonly observed across many types of dementia. However, deficits in semantic fluency are not always representative of a decline in language skills. Prior studies have suggested that the examination of the lexical properties of words produced on semantic fluency tasks may reveal disruptions in discrete cognitive processes that could assist in the detection of specific types of dementia. METHOD:The mean word frequency, age of acquisition, and phonological neighborhood size of items generated on a semantic fluency task (fruits and vegetables) were compared between a sample of individuals with mild cognitive impairment or dementia (cognitively impaired, N = 65) and a sample of healthy older adults with normal cognition who were cognitively stable over an average of 5 years following initial assessment (cognitively stable, N = 72). Relations of these variables to scores on tests of language, executive functioning, and processing speed were also explored. RESULTS:After controlling for age and education, the cognitively impaired group produced words of higher mean word frequency and lower mean age of acquisition than the cognitively stable group. Mean phonological neighborhood displayed the opposite pattern to expectations, with the cognitively stable group generating words with more phonological neighbors. Relations of evaluated word properties to tests of varied cognitive domains were explored in the overall sample, with mixed results. CONCLUSIONS:Word properties of items generated on a semantic fluency task differed between cognitively impaired and cognitively stable groups. Future studies should investigate word properties of semantic fluency responses in the context of severity of cognitive impairment, thoroughly examine susceptibility to sociocultural factors, evaluate if findings are consistent across semantic fluency tasks, and explore ability to offer incremental validity for differential diagnosis and early detection over total scores alone.
INTRODUCTION:Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS:183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS:48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION:Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.
INTRODUCTION:Latent variable analyses have been used to model the cognitive and functional (cf) decline associated with cognitive changes. The present study replicated and expanded upon this latent variable approach to include a second factor reflecting caregiver burden and behavioral and psychological symptoms of dementia (br). METHODS:This study used ADNI data from 422 consented Wave 4 participants who had completed a MoCA, Functional Activity Questionnaire, Logical Memory II (delayed memory task), Trails Making Test - Part B, Neuropsychiatric Inventory, and Geriatric Depression Scale. Of the participants included in the analysis, 239 were considered cognitively normal, 110 had a diagnosis of MCI and 27 had a diagnosis of dementia. RESULTS:Confirmatory factor analysis supported a two-factor model (CFI = .964; RMSEA = .091). All cognitive and functional measures loaded significantly on the cf factor (range: r = -.707 to .747; ps < .0001). All behavioral-relational measures loaded significantly on the br factor (range: r = .237 to .760; ps < .0001). Additionally, both latent variables were significantly associated with diagnosis type, such that cf declined and br increased with diagnosis severity. DISCUSSION:This current study findings emphasize the importance of assessing cognitive performance from a whole-person perspective. Future research should focus on using these factors to predict dementia-related outcomes (e.g. nursing home placement, progression of decline).
OBJECTIVE:The objective of this study was to characterize contemporary technology use in U.S. clinical neuropsychology and identify perceived barriers, facilitators, benefits, competencies, and training needs associated with technology adoption. METHOD:The AACN Disruptive Technology Initiative developed the Facilitators and Barriers to Adopting Technology in Neuropsychology survey, which was administered from October 2024 through February 2025 to licensed practitioners and trainees through professional organizations and social media. The Qualtrics survey included multiple-choice and open-ended items assessing practice characteristics, technology use, perceived productivity effects, and training experiences. After data cleaning, 302 valid responses were retained for analysis. Descriptive statistics were used to summarize quantitative data, and natural language processing-based topic modeling was applied to open-ended responses to identify thematic categories. RESULTS:Respondents most commonly reported routine use of computerized assessment platforms and automated scoring systems, whereas home-based, mobile, and ecologically embedded approaches were used less frequently. Commonly endorsed barriers included limited patient access to devices or reliable internet, insufficient validation of available tools, privacy and security concerns, institutional resistance, and financial disincentives related to billing and RVU structures. Reported benefits included greater scoring efficiency, streamlined workflow, faster report turnaround, and expanded access for geographically remote or mobility-limited patients. Although respondents generally endorsed moderate-to-high technological literacy, most reported minimal formal training and substantial reliance on self-directed learning. Younger clinicians also reported greater technological literacy and higher rates of technology uptake. CONCLUSION:U.S. clinical neuropsychology is in a transitional phase in which technology is increasingly integrated into practice but remains unevenly adopted across settings and modalities. These findings underscore the need for competency-based training across career stages, stronger validation and implementation infrastructure, and reimbursement models that support secure, ethical, and sustainable technology integration in neuropsychological practice.
This article provides a structured summary of "Leadership in Focus: Lessons Learned from Women Leaders," a conference panel organized by the American Psychological Association (APA) Division 40's Society for Clinical Neuropsychology (SCN)'s Women in Neuropsychology (WIN) committee at APA's annual conference in 2025. This panel brought together four prolific women leaders in neuropsychology and associated fields, Kim Gorgens, PhD, ABPP, Paula Shear, PhD, Chriscelyn Tussey, PsyD, ABPP, and Sara Weisenbach, PhD, ABPP, to discuss major themes related to women's leadership in neuropsychology, including: (1) a historical view of women in leadership positions, (2) systemic barriers faced by women in leadership, and (3) strategies used as a woman in leadership. Erin Sullivan-Baca, PhD, ABPP, and Rachael L. Ellison, PhD, co-moderated this panel discussion. The panel session and this resulting paper aim to disseminate the panelists' wisdom around best practices in knowledge and strategies for promoting gender equity and supporting the advancement of women in leadership within neuropsychology. Common themes across panelists and topics included celebrating and recognizing the strengths of women's unique leadership style, reflecting on personal strengths, seeking out mentorship and sponsorship, engaging in professional organizations, and not overplanning or waiting until conditions are perfect to volunteer for leadership opportunities. Panelists concluded by acknowledging continued barriers to women in leadership while also providing a vision of hope for the future of women leaders in neuropsychology.
AIM:To compare the facial emotion recognition (FER) accuracy and reaction time (RT) of patients with performance-type social anxiety disorder (pSAD) and generalized-type social anxiety disorder (gSAD) with healthy controls (HCs). METHOD:A total of 56 patients who were diagnosed as having SAD (31 gSAD and, 25 pSAD) according to the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) were included in the study. Forty individuals with no psychiatric disorders were included as the HCs. FER skills were assessed using a task that included Ekman's basic emotions and a neutral face. Additionally, the Beck Depression Inventory (BDI), State-Trait Anxiety Inventory (STAI), and the Liebowitz Social Anxiety Scale (LSAS) were administered to all participants. RESULTS:FER performances of patients with pSAD were similar to the HC group. The accuracy rates for emotions other than sadness in patients with gSAD were similar to those in the HC group. The RT to all facial expressions in patients with gSAD was statistically significantly shorter than in the HCs (p < 0.005). The RT given to facial emotions other than sadness was shorter in the pSAD patient group compared with the HC group. A negative correlation was found between STAI-state anxiety and neutral face recognition. (r = -0.308, p < 0.05). However, except for neutral face recognition, no significant correlation was observed between the BDI, STAI-state, STAI-trait, LSAS-fear, LSAS-avoidance, and FERT subscales. CONCLUSION:The current study casts doubt on some of the effects reported in the literature on SAD's FER ability. In this study, no significant difference was found in FER ability among SAD subtypes; this may suggest that a common mechanism exists in both subtypes.
Neurodiverse diagnoses (NDs) have been largely conceptualised as distinct categories with clear-cut diagnostic boundaries. However, converging research evidence is showing that this conventional approach may inadequately capture the individual variation and overlaps that are commonly observed in population studies. This study extended emerging quantitative research frameworks for understanding diagnostic complexity, adopting a transdiagnostic dimensional approach toward characterising the cognitive and mental health dimensions associated with NDs. A cohort of 175 adults with suspected or previously diagnosed neurodiverse conditions was recruited using convenience sampling. Cognitive domains of executive function, language, attention, processing speed, and memory were assessed using the National Institute of Health (NIH) Cognition Toolbox©. A battery consisting of the Extended Strengths and Weaknesses Assessment of Normal Behavior (E-SWAN), Strengths and Difficulties Questionnaire (SDQ), and Emotion Regulation Skills Questionnaire (ERSQ) was administered to provide additional proxy measures of mental health. Cluster analyses revealed that the sample of neurodivergent adults was best represented by three data-driven clusters, none of which mapped coherently onto traditional diagnostic labels. In contrast, these transdiagnostic groups were best characterised by a combination of strengths and weaknesses along two multivariate dimensions: 1) cognitive flexibility and processing speed, and 2) language, memory, emotional wellbeing, and behavioral regulation. This study provides novel, data-driven evidence to support the emerging dimensional structure of NDs, and highlights several component processes which may contribute to the complexity associated with neurodiversity in adults. These findings may be used to inform future assessment and/or support strategies for neurodivergent adults, beyond those framed by strictly categorical approaches.
OBJECTIVE:Specific learning disorder (SLD) diagnoses made in childhood are often assumed to be stable across development; however, diagnostic stability has frequently been conflated with diagnostic validity. This study examined (a) the accuracy of childhood SLD diagnoses at the time they were made, relative to objective academic impairment and (b) the stability of SLD diagnoses from childhood to young adulthood. METHOD:Archival data were analyzed from 325 postsecondary students who underwent comprehensive adult psychoeducational assessment and for whom childhood assessment documentation was available. Childhood reports were coded for assessment content, diagnostic clarity, and evidence of objective academic impairment. Diagnostic stability was evaluated by comparing childhood and adult SLD diagnoses across reading, written expression, and mathematics. RESULTS:Most childhood assessments included standardized measures of cognitive, academic, and behavioral functioning; however, fewer than half included measures of phonological processing, and only 52.3% contained a clear diagnostic statement. Across domains, 82-89% of childhood SLD diagnoses were supported by objective academic impairment at the time of assessment. Despite this, diagnostic stability from childhood to adulthood was moderate, with approximately 59% of childhood diagnoses retained across reading, writing, and mathematics, and roughly 40% not confirmed at adult reassessment. CONCLUSIONS:Findings indicate that while many childhood SLD diagnoses are supported by contemporaneous academic impairment, that impairment does not always persist into adulthood. These results underscore the importance of distinguishing diagnostic accuracy from diagnostic stability and highlight the need for careful reassessment of learning difficulties in postsecondary contexts rather than reliance on childhood diagnoses alone.
OBJECTIVE:Persisting cognitive symptoms following SARS-CoV-2 infection (Long COVID) has become an increasingly common referral for neuropsychological evaluation. This study examined performance validity test (PVT) failure rates among adults referred for evaluation due to Long COVID cognitive complaints after mild SARS-CoV-2 disease severity. METHOD:Data from 57 demographically diverse outpatients (72% female; Mage = 44.23; Meducation = 15.39 years) consecutively referred for a focused neuropsychological evaluation due to Long COVID cognitive symptoms were analyzed. The neuropsychological test battery included one freestanding (Test of Memory Malingering-Trial 1) and four embedded PVTs (Reliable Digit Span; California Verbal Learning Test-Brief Form Forced Choice; Brief Visuospatial Memory Test-Revised Recognition Discriminability; Stroop Color and Word Test-Word Reading T-Score), as well as a 11 neuropsychological test scores assessing the major domains of cognition, which were used to compute an overall neuropsychological test battery mean composite score. RESULTS:Individual PVT failure rates ranged from 4% to 18%. Overall, 67% passed all PVTs, 24% failed one PVT, and 9% failed ≥ 2 PVTs. Patients failing two or more PVTs had an overall neuropsychological test battery mean performance that was significantly lower than the group failing one or zero PVTs and 1.0 standard deviations below the population mean. Patients with zero PVT failures also outperformed those with one PVT failure by 0.5 standard deviations. Nonsignificant differences in COVID disease characteristics emerged between groups. CONCLUSIONS:The majority of patients (67%) passed all PVTs, with 24% of patients failing one PVT and 9% failing ≥ 2 PVTs. Future research is warranted to understand implications of a single freestanding PVT failure in this population, and to establish base rates of invalidity in Long COVID and among those with more severe initial COVID infection necessitating hospitalization and/or medical intervention. Such practices ensure accurate diagnosis, guide treatment, and improve the reliability of research on the cognitive sequelae of COVID-19.
The problems with LD diagnosis are the logical consequence of a concept that, after 63 years, has never had a universally accepted definition or empirically validated diagnostic criteria. This essay is a personal odyssey over 50 years that explores the many problems with the LD concept and LD diagnosis that have affected my research, teaching, and clinical practice with children and adults. It is a critical, historical, and analytic journey about the LD story grounded in first-person clinical experience and explicit engagement with diagnostic theory that has implications for first-time adult LD diagnosis. The essay advances several claims about the evolution and current state of the LD concept and LD diagnosis across the lifespan with adult diagnosis as its destination: (1) intra- and inter-individual differences in achievement and cognition are normal and expected, yet were reframed as abnormal through the construct of "unexpected underachievement"; (2) even as the LD field promoted unexpected underachievement, it selectively treated only some individuals' underachievement as "unexpected," creating internal inconsistency; (3) reliance on discrepancy from presumed "potential" (IQ) made diagnosis unnecessarily complex and introduced inequities by excluding lower-achieving individuals; (4) these practices persisted despite substantial empirical evidence challenging their validity; (5) DSM-IV's retention of discrepancy-based approaches contributed to ongoing problems in adult diagnosis and pathologizing of normal variability and average performance; (6) disability standards emphasizing substantial limitation relative to the average person were overridden by continued reliance on discrepancy; and (7) discrepancy, potential, and unexpected underachievement were normalized as enduring conceptual and cultural assumptions. Together, these claims reframe LD as a construct shaped by a story, not science, and call for renewed attention to its theoretical foundations and practical consequences, especially for adult diagnosis.
BACKGROUND:The altered gut microbiota substantially impacts the onset and progression of Alzheimer's disease (AD) and Parkinson's disease (PD), the two most widely studied neurodegenerative conditions. Microbiome-derived metabolites have been increasingly associated with disease onset, progression, and therapeutic targets in neurodegenerative disorders. Exploring the diagnostic and therapeutic implications of gut microbiome-derived biomarkers is critical to advancing our understanding and management of neurodegeneration. METHODOLOGY:We systematically reviewed both clinical and preclinical studies published from 2010 to 2025. Studies examining gut microbiota composition, microbial-derived metabolites, or therapeutic interventions targeting the gut microbiome were included. Identification of gut microbiome alterations, discovery of microbial or metabolite-based biomarkers, association with disease onset or progression, and/or therapeutic effects on cognitive, neurological, or inflammatory outcomes were evaluated. RESULT:Short-chain fatty acids(SCFAs) such as butyrate and acetate were found to be noninvasive biomarkers in patients with Alzheimer's disease (AD), mild cognitive impairment (MCI), and Parkinson's disease (PD). Lower SCFA levels correlated with cognitive decline. Diagnostic accuracy improved when SCFA combinations were used, with AUCs ranging from 0.75 to 0.87. Trimethylamine N-oxide(TMAO) levels showed inconsistent associations, with both elevated and reduced levels linked to disease risk. Therapeutic approaches targeting gut microbiota, including probiotics, prebiotics, dietary changes, and fecal microbiota transplantation, demonstrated cognitive benefits and modulation of gut-brain signaling pathways. CONCLUSION:Overall, gut-derived biomarkers offer a promising avenue for early diagnosis and novel therapeutic approaches in AD and PD, while acknowledging that evidence in other neurodegenerative diseases remains limited through modulation of the gut-brain axis.
BACKGROUND:Reproductive factors have been associated with cognition in older women, yet findings have been inconsistent. Moreover, recent studies have also found similar associations in men. OBJECTIVE:Examine the relationship between reproductive and cognitive factors in both sexes, controlling for multiple covariates. METHODS:We analyzed data from 914 women with natural menopause (MAGE = 72.65±5.57) and 811 men (MAGE = 74.43±5.37) from the HELIAD study. Participants provided reproductive, medical, and social histories and had a comprehensive neuropsychological assessment, including Mild Cognitive Impairment and dementia diagnosis. Covariates included age, education, medical, genetic, lifestyle, and socioeconomic factors. RESULTS:Controlling for age and education, in women, later menarche, earlier menopause, fewer menstrual years, shorter interpregnancy intervals, and menstrual regularity were associated with poorer cognitive outcomes. Earlier first childbirth (<25y), greater parity (especially, before 20y), and older age at fourth childbirth were linked to better cognition (ORs:.95-2.20). In men, older age at third and fourth child birth, having more children at ages 20-29 or 40+, the last child at >35y, and childlessness were associated with poorer cognition, while having the first child at >35y (language tasks) and having more children overall were associated with better cognition (ORs:1.37-2.20). After full-adjustment and Bonferroni correction, no associations remained. CONCLUSIONS:Reproductive patterns may affect cognition differentially based on sex. Moderate reproductive activity may be protective, whereas extreme patterns (e.g. very early/late childbirth, childlessness) may be linked to cognitive decline. These associations attenuate after statistical adjustment and correction, necessitating further controlled and longitudinal studies to clarify these relationships.
CONTEXT:Adults with Tourette syndrome (TS) are more prone to depression and comorbid anxiety disorders than neurotypical individuals. Conflicting findings regarding their cognitive performance may stem from various factors, including comorbidities. OBJECTIVE:Our primary goal is to assess patients' inhibition to interference, motor dexterity, nonverbal memory, and visuospatial functions, and to examine the impact of concomitant anxious-depressive symptoms that often accompany TS. It is hypothesized that individuals with TS who also have anxiety and depression symptoms will demonstrate significantly altered inhibition, motor dexterity, and visuospatial skills compared to both the neurotypical and non-comorbid clinical groups. We also propose identifying neuropsychological variables that best discriminate between comorbid and non-comorbid groups, as well as between these groups and neurotypical controls. METHODS:We compared the neuropsychological profile of 128 participants divided into three groups: a TS+ clinical group with anxiety and depression comorbidities (n = 21), a TS- clinical group without significant comorbidity (n = 37), and a neurotypical control group (n = 70). Neuropsychological assessments included the Stroop Color-Word Test (inhibition), the Purdue pegboard (motor dexterity), and Rey-Osterrieth Complex Figures (visuospatial functions and nonverbal memory). RESULTS:No significant group differences emerged in interference inhibition. Both TS- and TS+ participants outperformed controls in fine motor dexterity tasks. However, only the TS+ group showed impairments in visuospatial functions and nonverbal memory. CONCLUSIONS:These results suggest that anxiety and depressive comorbidity in individuals with TS may specifically alter nonverbal memory and visuospatial functions.
Recent advances in biomarker testing for Alzheimer's disease (AD), most notably the introduction of blood-based biomarkers (BBMs), have prompted a revision in diagnostic criteria for AD. In comparison to other established neurodiagnostic testing (i.e. amyloid positron emission tomography [PET] and cerebral spinal fluid [CSF] assays), AD BBMs offer a scalable, low-cost, and accessible method to aid in the diagnosis of AD which, in turn, may offer more expedient intervention. Despite this headway in AD diagnosis, several concerns about the clinical implementation of BBMs remain--and specifically, who should be receiving them. Palmqvist et al. (2025) recently published clinical practice guidelines to clarify the use of BBMs in specialty care settings; however, there remains variability in the administration and interpretation of test results to patients. As BBMs expand, it is critical that clinicans do not overlook the consideration of alternative causes of cognitive decline, which can lead to misdiagnosis of AD. This article expands on current clinical guidelines for biomarker testing, discussing ethical and practical considerations of AD BBMs, and offering a shared decision-making (SDM) framework to encourage patient-centered care when considering appropriateness of BBMs in specialty care settings. The framework includes 1) patient education, 2) clarifying patient values, and 3) offering clinical guidance. Future directions of AD BBMs and health disparities are also discussed.
BACKGROUND:Psychopathology and cognitive impairment are common consequences of moderate-severe traumatic brain injury (TBI), but their interrelationships remain poorly understood. Clarifying these relationships is important for understanding cognition's role in post-TBI psychopathology and for informing targeted, holistic assessment and treatment strategies. Traditional categorical approaches to psychiatric diagnosis have produced inconsistent results. The recently developed Hierarchical Taxonomy of Psychopathology Following TBI (HiTOP-TBI) model, a transdiagnostic-dimensional framework, was applied to examine associations between psychopathology and cognitive functioning. METHODS:Ninety-nine adults with moderate-severe TBI participated (Mage = 50.86 years; 72% male; Mtime post-injury = 14.6 years,SD = 8.2; MGCS = 8.03; MPTA = 24.3 days). Psychopathology was assessed using self-report questionnaires completed predominantly online (96%). Cognitive performance was assessed via telephone-administered tasks. Linear regressions examined associations between ten hierarchically organizedHiTOP-TBI dimensions (one general factor, two broad internalizing and externalizing spectra, seven lower-order factors) and cognitive measures, with false discovery rate correction applied. RESULTS:After correction, higher scores (indicating greater psychopathology) on the HiTOP-TBI dimensions of Externalizing Problems, Rigid Constraint, and Self-Harm and Psychoticism were associated with poorer performance on verbal encoding and the episodic memory domain (encompassing both immediate and delayed recall). In comparison, General Problems, Internalizing Problems, Somatic Symptoms, Detachment, Compensatory and Phobic Reactions, Dysregulated Negative Emotionality, and Harmful Substance Use, were notsignificantly associated with cognitive functioning, after correction. CONCLUSIONS:Applying the transdiagnostic, dimensional HiTOP-TBI framework, we identified several associations between psychopathology and cognitive functioning after moderate-severe TBI. Verbal encoding and memory were most consistently implicated, particularly within externalizing domains. Findings highlight the importance of holistic neuropsychological formulation and integrative interventions aimed at improving both emotional and cognitive outcomes in TBI and demonstrate the value of transdiagnostic approaches in neuropsychology research and practice.
INTRODUCTION:Spontaneous speech is commonly disrupted in persons with Alzheimer's disease (AD) and/or Alzheimer's clinical syndrome (ACS). Importantly, different aspects of speech (e.g. formulaic versus more novel or flexible speech) place different demands on distinct cognitive systems. Formulaic language may rely on automatized procedural processes, while more novel or diverse speech requires more flexible lexical-semantic processes associated with the subsystems of declarative memory. Given that AD/ACS are associated with impaired declarative processes and relatively spared procedural processes, we predicted that individuals with ACS may show increased reliance on formulaic language along with reduced diversity in speech. METHOD:We analyzed the spontaneous speech of 81 individuals with ACS (aged 56-88) and 61 healthy controls (aged 47-80) who completed a picture description task using computational tools for the analysis of formulaic language (operationalized as proportion of frequent trigrams produced and mutual information score of trigrams) and novel language (operationalized as root type-token ratio, measure of textual lexical diversity, and semantic diversity). RESULTS:Across all measures, individuals with ACS produced significantly more formulaic language than control participants and significantly less novel language than control participants, with small-to-medium overall model effect sizes. Machine learning classifiers trained on these patterns of formulaic and novel language distinguished between controls and individuals with ACS with reasonable accuracy, sensitivity, and specificity. CONCLUSION:The spontaneous speech of individuals with ACS contains more formulaic language and less novel language than that of healthy controls, consistent with the Dual-Process Model. These differences may have clinical relevance and warrant further investigation. Keywords: Alzheimer's Disease, Alzheimer's clinical syndrome, formulaic language, lexical diversity, spontaneous speech.
INTRODUCTION:A range of demographic, reproductive, and health-related factors influence brain health in postmenopausal women, though their relative and combined contributions are not fully understood. Using data from the Canadian Longitudinal Study on Aging (CLSA), this study examined predictors of cognitive performance in postmenopausal women, including hormone therapy (HT) use, age at menopause, and relevant sociodemographic and health-related variables. METHOD:We included baseline and follow-up data from 10,978 CLSA participants. Multiple linear regressions were employed to examine the associations between predictors and cognitive test scores at a 3-year follow-up, adjusting for baseline scores. Cognitive performance was assessed using a neuropsychological battery, which included six tests probing verbal learning, episodic memory, executive function, and verbal and semantic fluency. RESULTS:Later age at menopause was predictive of better cognitive performance on specific cognitive tests, including verbal learning and delayed recall, as measured by the CLSA-modified REY I (β = .01, 95% CI [-.04, .02], p = .006) and REY II (β = .02, 95% CI [.01, .03], p < .001), as well as inhibitory control measured by Stroop test interference (β = -.01, 95% CI [-.01, -.02], p = .004). Sociodemographic factors, including education and income, were also consistent predictors of cognitive performance across domains. CONCLUSIONS:Overall, findings suggest that cognitive performance in postmenopausal women may reflect a combination of reproductive and sociodemographic influences. Future studies incorporating longer follow-up periods and more detailed reproductive and health measures are needed to better characterize the contribution of menopause-related factors to cognitive aging.
INTRODUCTION:Due to sex differences in cognitive aging and dementia burden, there is increased focus on the role of the menopause transition on cognitive functioning across midlife. This study aimed to characterize cognitive profiles among midlife women and to examine the demographic, social, and health factors associated with profile membership. METHOD:Midlife women (N = 202; Age 40-60 years) from the Human Connectome Project - Aging completed NIH Toolbox cognitive and emotion measures. Latent profile analysis was used to identify cognitive profiles utilizing nine performance-based measures. Emergent profiles were then characterized in terms of demographic, cardiovascular and metabolic health indicators, and medication use (e.g. hormone therapy). Multinomial regression was then used to determine whether sleep, physical activity, depressive symptoms, and psychological stress varied by cognitive profile. RESULTS:Four distinct cognitive profiles were identified, the most common reflecting strength in verbal learning and memory (43% of women) and the next most common reflecting weaknesses in those same domains (39%). Black race and elevated depressive and anxiety symptoms were associated with the latter profile. A third profile (12%) reflected weakness in executive function (e.g. divided attention, picture vocabulary, working memory, task switching). The fourth (6%) was a mixed group showing strengths in pattern recognition and picture vocabulary but weaknesses in verbal memory and inhibitory control. CONCLUSION:Midlife women show heterogeneity in cognitive performance, with nearly half showing a profile of strength in verbal memory. However, two menopause-relevant profiles emerged that were characterized by subtle weaknesses. One was in the domain of verbal memory and, consistent with earlier work, related to sadness and anxiety. The second was in executive function. Though less common, that vulnerability is notable given reports of attention-deficit hyperactivity disorder (ADHD)-like symptoms at menopause. Longitudinal studies are underway to determine the stability and predictors of cognitive profiles among midlife women.
