Mind-wandering—the spontaneous shift in attention away from the external task to internal thoughts (including daydreaming, fantasizing, rumination, and worrying)—is negatively associated with performance across a variety of tasks including the sustained attention to response task, the Stroop task, tasks of working memory, choice reaction time, visual search, as well as more ecologically related tasks like reading comprehension and mathematics. There has also been promising evidence suggesting a potential link between mind-wandering, functional connectivity of the canonical networks of the brain, and Alzheimer’s disease (AD). However, no study has directly examined the relationship between neural correlates of mind-wandering and AD pathogenesis. In prior work, our lab has identified a whole-brain, functional connectivity-based marker of mind-wandering—the mwCPM—which predicted response time variability in older adults. In this study, we sought to evaluate the ability of this mind wandering CPM, derived from response time variability, to predict CSF p-tau/Aß42 ratio in 289 older adults from the Alzheimer’s Disease Neuroimaging Initiative. We hypothesized that the combined mind-wandering model including functional connections that predict high mind-wandering and functional edges that predict stability in attention, would predict AD pathology.

Resting-state functional MRI data from 289 older adults (147 healthy older adults, 111 individuals with mild cognitive impairment, and 31 older adults with AD) from the Alzheimer’s Disease NeuroImaging Initiative was analyzed for the current study. Participants were only included in the analyses if they had resting-state fMRI data, CSF measures of amyloid beta and tau pathology, and performance on cognitive composites of global cognition, episodic memory, and executive functioning. Using the well-established methodology of connectome-based predictive modeling, the mind-wandering model was applied to the resting-state fMRI data to predict CSF-based biomarker levels of p-tau and Aß42. Moreover, we also examined if this mind-wandering model predicted individual differences in composite measures of global cognition, episodic memory, and executive functioning

The high mwCPM model successfully predicted measured CSF p-tau/Aß ratios (high model: p = .137, p = .0196), controlling for mean framewise displacement. However, the combined network and the low MW network were not significant (combined model: p = .0731, p = .216; low model: p = -.0027, p = .960). We next examined the association between connectivity strengths of the high mwCPM and cognitive functioning in the domains of general cognition, episodic memory, and executive functioning. Connectivity strength in the high mwCPM—functional edges that were associated with high behavioral variability—were negatively associated with all three cognitive composites (global cognition: r = -.239, p < .0001; episodic memory: r = -.208, p = < .0001; executive functioning: r = -.178, p < .0001).

This study provides the first empirical support for a link between a neuromarker of mind-wandering and AD pathophysiology. Moreover, mind-wandering also has downstream consequential effects for key domains of cognitive functioning in older adults. Interventions targeted at reducing mind-wandering, particularly before the onset of AD pathogenesis, may make a significant contribution to the prevention of AD-related cognitive decline.

Studies suggest that internally oriented cognitive processes are central to creativity. Here, we distinguish between intentional and unintentional forms of mind wandering and explore their component contributions to creativity. Furthermore, we describe resting-state connectivity profiles associated with these trait-level measures of mind wandering. Bearing in mind the role of the DMN in internally directed cognitive processes, we hypothesize that, in general, mind wandering will be associated with increased connectivity of voxels in the medial prefrontal and posterior cingulate cortices, key nodes in the DMN. We further hypothesize that intentional and unintentional mind wandering will be associated with distinct patterns of connectivity across DMN core regions.

We used a sample of 155 healthy adults from the mind-brain-body dataset, all of whom completed resting-state fMRI scans and trait-level measures of mind wandering. We analyzed intentional and unintentional mind wandering tendencies using self-report measures. Next, we explored the relationship between mind wandering tendencies and creativity, as measured by a divergent thinking task. Additionally, we describe patterns of resting-state network connectivity associated with mind wandering, using graph theory (weighted degree) functional connectivity analysis.

At the behavioral level, results showed a significant positive association between creativity and both intentional and unintentional mind wandering. Neuroimaging analysis revealed higher weighted degree connectivity associated with both forms of mind wandering, implicating core regions of the default network and the left temporal pole. We observed topological connectivity differences within the default network: intentional mind wandering was associated with degree connectivity in posterior regions, whereas unintentional mind wandering showed greater involvement of prefrontal areas.

In this study, we highlight patterns of resting-state network connectivity associated with intentional and unintentional mind wandering, and provide novel evidence of a link between mind wandering and creativity. These findings represent a promising step towards understanding the neurocognitive mechanisms that underlie productive mind wandering and demonstrate its relevance for the study of creative thinking.

Disruptions to mind-wandering are common across neuropsychiatric disorders. Whilst the large-scale brain networks associated with mind-wandering are increasingly well understood, we know very little about what neurobiological mechanisms trigger a mind-wandering episode and sustain the mind-wandering brain state. From a clinical perspective, we aimed to understand dysfunctional mind-wandering in neuropsychiatric diseases of ageing: frontotemporal dementia, Alzheimer’s disease and Parkinson’s disease. We also tested the hypothesis that mind-wandering relates to visual hallucinations in Parkinson’s disease. From a theoretical perspective, we advance the hypothesis that the hippocampal sharp wave-ripple is a compelling candidate for a brain state that can trigger mind-wandering episodes. The occurrence of the sharp wave-ripple is heavily dependent on hippocampal neuromodulatory tone. Neuromodulatory systems that regulate the sharp wave-ripple may be crucial for understanding the disruption to mind-wandering in neuropsychiatric disease.

We developed a thought-sampling task to probe mind-wandering in neuropsychiatric diseases of ageing. To explore brain patterns related to mind-wandering, we used multi-modal neuroimaging (i.e., resting state and structural scans). In separate studies, we applied these techniques in frontotemporal dementia and Alzheimer’s disease; and in Parkinson’s patients with and without visual hallucinations.

We showed reduced mind-wandering in frontotemporal dementia, associated with functional and structural changes across the default network. In Parkinson’s disease, we also found a reduction in mind-wandering compared with healthy controls. However, in patients with visual hallucinations, mind-wandering was preserved and associated with increased connectivity between the default network and early visual regions.

Together, disrupted mind-wandering occurs in neuropsychiatric diseases of ageing. It may contribute to some of the more recognisable symptoms in these conditions, including apathy and hallucinations. These findings also provide a unique clinical validation of current brain network models of mind-wandering that have been developed in healthy populations. Neuromodulatory influences over mind-wandering have implications for treating impairments in this process across neuropsychiatric conditions.

Over the past decade, resting state functional connectivity has shown great promise as a diagnostic and prognostic tool when applied to neurological and psychiatric populations. For example, the integrity of the default mode network - among other large-scale brain networks - has emerged as a common target of neurological disease and psychopathology. Despite this explosion in research, relatively little is understood about the cognitive characteristics of the mind at rest, and most inquiries have relied on retrospective self-report questionnaires that pose challenges for clinical populations with memory or metacognitive deficits. Understanding how different people mentally structure their idle thoughts may shed light on existing clinical neuroscience findings. Furthermore, the resting state is common context in daily life, and the lack of external stimulation during rest periods may foster the emergence of dysfunctional and/or impoverished thoughts for individuals with mental health or neurological conditions. Considering these important gaps, we conducted a line of research quantifying clinical and demographic sources of variability in resting state cognition.

Across three studies, resting state cognition was captured by training adults to voice aloud their thoughts in real time across 7-10 minute rest periods in the lab, the MRI scanner, and participants’ own home. Participants were audio recorded using this think aloud technique, while efforts to minimize thought censorship were also employed. Audio-recorded speech was then transcribed and analyzed for content and dynamic characteristics by external coders and automated text analysis. Relevant characteristics were isolated and examined in relation to variability across participants in trait rumination, divergent thinking (a measure of creativity assessed with a separate Alternate Uses Task), as well as age.

Across studies, the think aloud paradigm in resting state contexts showed promising ecological validity. Participants reported a low degree of thought censorship and a moderate-to-high degree of similarity of thoughts to everyday life. Additionally, total word counts across the transcripts were similar to typical rates of natural speech. Notable variability across participants also emerged in the content and dynamic characteristics of resting state thought.

Increased trait rumination was associated with the emergence of brooding in real time, including a) more negative, self-focused, and past-oriented thoughts, as well as b) dynamic signatures marked by an attraction towards negative conceptual states, and c) a narrowing of conceptual scope following negative content. In contrast, more creative individuals exhibited a pattern of exploration and curiosity in their idle thoughts, with thought transitions characterized as more loosely associative. Finally, older adults generated more linguistic diversity in their use of positive emotional words (a novel marker of emotional granularity), accompanied by increases in psychological well-being.

Taken together, these studies highlight substantial demographic and clinical sources of variability in resting state cognition, with important implications for resting state functional connectivity findings. They also offer a promising methodological tool and theoretical framework to promote further research in neuropsychology and related fields.

Smartphone-based cognitive assessments can provide unique information about cognition that is difficult or impossible with traditional cognitive assessments. Using high-frequency measurement “burst” designs, we have shown that older adults are capable and willing to participate in smartphone-based research, that this method dramatically improves between-subject reliability compared to traditional methods and demonstrates extraordinary test-retest reliabilities, and that high-frequency measurement can reveal time of day effects that are increased in those with elevated Alzheimer’s disease biomarkers. In this symposium session, we will provide an overview of our current work in older adults at risk for AD and highlight new analyses on the interaction between day to day variability in sleep and cognition. We will also cover our approach for measuring smartphone latencies, a critical aspect of bring-your-own-device (BYOD) studies.

The Ambulatory Research in Cognition (ARC) smartphone application for iOS and Android administers custom-designed tests of associate memory, processing speed, and spatial working memory. ARC uses a measurement burst design in which very brief (typically 60s or less) tests are completed at random times several times per day for up to one week. Measurement burst designs rely on principles from ecological momentary assessment, and can be described with a simple formula: 1. Test often and everywhere, 2. Keep assessments brief, and 3. Combine the data across sessions to increase reliability. At the Knight Alzheimer’s Disease Research Center at Washington University in St Louis, we have enrolled over 400 participants (ages 60-99 years) at risk for AD in ARC studies. These participants are comprehensively assessed with traditional cognitive tests, clinical examinations, neuroimaging, and fluid biomarkers. ARC also assesses sleep with the Pittsburgh Sleep Quality Index that captures essential sleep parameters, which are assessed daily during each 7-day measurement burst. Analyses of sleep and cognition focused on parameters including total sleep time, number of awakenings, sleep quality ratings, and an extremes analysis comparing cognition after nights with more sleep and after nights with less sleep.

Overall, participants reporting less total sleep time and more awakenings had lower memory and processing speed scores. This remained significant after modeling covariates including age, self-reported gender, education, and APOE ε4 status. Compared to nights with the most sleep, memory was worse after the nights with the poorest sleep.

When considering AD biomarkers in these analyses, participants with elevated AD biomarkers, including neurofilament light chain (NfL) and phosphorylated-tau181 (p-tau181), demonstrated more impacts of poor sleep on cogntion, such that the nights with the least sleep tended to impact cognition more than in those with normal biomarker levels, suggesting an important role for sleep in maintaining cognition in preclinical and early symptomatic AD. Interestingly, self-reported sleep quality was not associated with ARC cognitive tests, consistent with studies emphasizing the need for more quantitative assessments of sleep quality. In addition to these sleep data, we will review publications using the ARC platform, including a recently accepted manuscript in JINS (Nicosia et al., 2022).

There is a need to identify scalable cognitive paradigms that are sensitive enough to relate to Alzheimer's disease biomarkers (amyloid and tau) in the preclinical stage. Here, we determine whether initial performance and practice effects on the memory-focused Computerized Cognitive Composite (C3) relate to demographic variables, amyloid status [abnormal (A+), normal (A-)], and regional tau in clinically unimpaired (CU) older adults.

We examined pre-randomization data from CU older adults screened for the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study. We focused on participants who completed the C3 (n=3287), most of whom completed an alternate version of the C3 again approximately 51 days later (n=4141), as well as a subset of preclinical AD participants (i.e., A+ CU) who completed the C3 and tau PET imaging with [18]F-flortaucipir (initial C3: n=354; repeat C3: n=343). C3 initial performance and practice effects were examined in relation to amyloid status (A+, A-) and continuous regional tau burden.

Initial C3 performance was associated with amyloid status [B(SE) = -0.075 (0.021), p < 0.001] across all participants, as well as tau burden in the medial temporal lobe (MTL) [B (SE) = -0.728 (0.220), p = 0.001], inferior temporal (IT) cortex [B (SE) = -0.782 (0.264), p = 0.003], and inferior parietal (IP) cortex [B (SE) = -0.721 (0.281), p = 0.011] amongst preclinical AD individuals. Short-term practice effects were also associated with reduced tau burden in MTL [B (SE) = -0.471 (0.202), p = 0.020], IT [B (SE) = -0.640 (0.240), p = 0.008], and IP [B( SE) = - 0.584 (0.255), p = 0.023] amongst preclinical AD participants, but were not associated with amyloid status [B (SE) = -0.018 (0.020), p = 0.348]. Critically, these effects with tau were only detected when baseline performance was accounted for presumably due to opposing influence from both practice effects and regression to the mean effects.

This is the first study to show that performance on a brief cognitive battery administered in a multisite context is associated with both amyloid and tau among CU older adults. These findings suggest that computerized assessments may be a cost-effective and scalable approach for early detection efforts. Further, diminished practice effects on memory-based measures are associated with elevated tau burden in preclinical AD, suggesting that high-frequency cognitive testing collected over a short follow-up period may provide additional insights regarding early disease processes than single assessments.

To evaluate the feasibility, usability, and preliminary validity of a digital phenotyping protocol to capture everyday cognition and activities in vivo among older adults.

Eight participants (M age=69.1 + 2.6; M education=18.0 + 1.4; 50% female; 88% non-Hispanic White) with normal cognition or mild cognitive impairment used an open-source smartphone application (mindLAMP) to passively and continuously capture sensor data including global positioning system (GPS) trajectories for a 4-week study period. Baseline neuropsychological tests and measures of depression, self-reported cognitive decline and mobility patterns were collected as external validators for digital data. Participants downloaded mindLAMP onto their smartphones and resumed their daily routines for 4 weeks before removing mindLAMP and completing a debriefing questionnaire. A cognitive composite was derived by averaging T-scores across domains of attention, executive functioning, processing speed, memory, and language. GPS raw data were processed to generate monthly average and standard deviation mobility metrics for each participant, including time spent at home, distance travelled, radius of gyration, flight length, and circadian routine. Feasibility and usability findings are presented along with correlation coefficients >.4 between GPS metrics and external validators.

100% of enrolled participants completed the 4-week study without requesting to withdraw. Usability ratings ranged from poor to excellent. 75% of participants agreed that mindLAMP was easy to use, whereas only 1 participant enjoyed using mindLAMP. 100% of participants were satisfied with the study team’s explanation of procedures, privacy safeguards, data encryption methods and risks/benefits, reflected in an average score of 98.8% on the comprehension of consent quiz. No participants reported feeling uncomfortable, suspicious, or paranoid due to the study application running on their smartphone. No participants endorsed new problems using their smartphone, though 75% reported charging it more frequently during the study period. On average each day, participants spent 1121 + 227 minutes at home, travelled 38727 + 36210 geodesic units, and had 201 + 149 minutes of missing GPS data. Overall, greater amounts of activity (monthly average) and higher variability (monthly standard deviation) in GPS metrics were associated with better outcomes. Specifically, less time spent at home, greater distance travelled, larger radius of gyration, greater flight length, and greater variability in home time, distance travelled, radius of gyration and flight length were associated with less depression, less self-reported cognitive decline, better cognition, and greater self-reported mobility (.40< |r| <.69). On the other hand, greater circadian routine was associated with more self-reported cognitive decline (r=.66) and less self-reported mobility (r=-.43).

Smartphone digital phenotyping is a feasible and acceptable method to capture everyday activities in older adults. Continuous collection of data from personal devices warrants caution; however, participants denied privacy concerns and expressed an overall positive experience. High frequency GPS data collection impacts battery life and should be considered among relative risks and confounds to naturalistic assessment. Patterns of behavior from passive smartphone data show promise as an unobtrusive method to identify cognitive risk and resilience in older adults. Subsequent analyses will evaluate additional sensor metrics across a larger and more heterogeneous cohort.

Historically, assessment of financial decision making (FDM) has largely relied on self- or informant-reports, and paper-and-pencil tests. However, subjective report is prone to under/over-estimation biases, and most available tests probe increasingly outdated tasks such as writing checks and checkbook management. Advances in technology have made online methods one of the most common and preferred styles of managing money. There is thus a critical need to develop modern and objective methods to assess financial decision making that can be used in clinical settings. The current study aimed to develop and validate a novel, simulated online money management (OMM) credit card task mimicking a real-world task.

Development. The OMM task was conceptualized based on collaborations with a diverse team of experts spanning neuropsychology, geriatrics, computer science, and economics. Administration. The task involves several sub-tasks including logging into a simulated credit card account, navigating a few pages to download a statement for a specific month, answering questions about where certain pieces of information are in the statement, identifying erroneous transactions in the account activity section, and answering questions involving practical aspects of managing a credit card. Pilot phase. Using an iterative process, the task was refined and piloted in ten participants. Validation. Performance was examined in relation to an existing online automated teller machine (ATM) task. Design & Setting. Cross-sectional, community-based prospective study.

OMM task. The newly developed OMM credit card task consists of two broad areas, (i) online navigation and (ii) content-focused (simple literacy, complex literacy, monitoring, awareness). ATM task. This measure consists of sequential tasks such as checking the balance in one’s account, transferring money between accounts, and withdrawing cash. Both the OMM and ATM tasks were administered remotely by a neuropsychologist using Zoom and Team Viewer on a Dell laptop.

Thirty-five cognitively healthy older adults were included with mean age=70.06 years (SD=3.82) and mean education=21.89 (SD=1.76). 72% were women, the majority were White (77%) while 20% were Black and 3% belonged to other races; 91% were non-Hispanic.

Bivariate correlations between the OMM task, ATM task and demographic variables were examined. Time and steps/clicks to complete the OMM task were the primary outcome metrics.

All participants were able to complete the OMM task. No significant associations were found between demographics (age, gender, education) and OMM metrics, and among OMM metrics (time and clicks). Significant associations in the expected direction were present between the OMM and ATM tasks. Time taken to answer the questions on the OMM task was associated with time required to complete the ATM task (r = 0.57, p < 0.001). Increased number of clicks on the OMM task was associated with increased number of errors (r = 0.54, p < 0.001) and increased time to complete the ATM task (r = 0.41, p = 0.01).

This is one of the first studies to develop and demonstrate the validity of a technologically based and practically relevant measure of financial decision making. Studies are ongoing to more comprehensively understand the psychometric properties of this novel task.

The COVID-19 pandemic has affected the continuity of cognitive rehabilitation (CR) worldwide. However, the use of teleneuropsychology (TNP) to provide CR has contributed significantly to the continuity of treatment. The objective of this study was to measure the effects of CR via the TNP on cognition, neuropsychiatric symptoms, and memory strategies in a cohort of patients with Mild Cognitive Impairment (MCI).

A sample of 60 patients (60% female; age: 72.4±6.96) with MCI according to Petersen criteria was randomly divided into two groups: 30 cases (treatment group) and 30 controls (waiting list group). Subjects were matched for age, sex, and MMSE or MoCA.

The treatment group received ten weekly CR sessions of 45 minutes weekly. Pre-treatment (week 0) and post-treatment (week 10) measures were assessed for both groups. Different Linear Mixed Models were estimated to test treatment effect (CR vs. Controls) on each outcome of interest over Time (Pre/Post), controlling for Diagnosis, Age, Sex, and MMSE/MoCA performance.

A significant Group (Control/Treatment) x Time (pre/post) interaction revealed that the treatment group at 10 weeks had better scores in cognitive variables: memory (RAVLT learning trials p=0.030; RAVLT delayed recall p=0.029), phonological fluency(p=0.001), activities of daily living (FAQ p=0.001), satisfaction with memory performance (MMQ Satisfaction p=0.004) and use of memory strategies (MMQ Strategy p=0.00), and a significant reduction of affective symptomatology: depression (GDS p=0.00), neuropsychiatric symptoms (NPIQ p=0.045), Forgetfulness (EDO-10 p=0.00), Stress (DAS Stress p=0.00).

This is the first study to test CR using teleNP in South America. Our results suggest that CR through teleNP is an effective intervention to improve performance on cognitive variables and reduce neuropsychiatric symptomatology compared to patients with MCI. These results have great significance in the context of the COVID-19 pandemic in South America, where teleNP is proving to be a valuable tool.

Neuropsychological assessment of preschool children is essential for early detection of delays and referral for intervention prior to school entry. This is especially relevant in low-and middle-income countries (LMICs), which are disproportionately impacted by micronutrient deficiencies and teratogenic exposures. There are limited options for assessment of preschool learning and memory, developed and validated in resource-limited regions. The Grenada Learning and Memory Scale (GLAMS) was created for use in the Caribbean using an indigenous “ground-up” approach, with feedback from regional stakeholders at various stages of development. The GLAMS contains two subtests - a verbal list-learning task, which imagines a trip to the shop to buy culturally familiar items, and a face-name associative learning task using locally-drawn faces of Caribbean children. There are two versions: a 4-item version for 3-year-olds and a 6-item version for 4 and 5-year-olds. Here we present descriptive data and psychometric features for the GLAMS from an initial preschool sample.

Participants were recruited from a social-emotional intervention study (SGU IRB#14099) in Grenada between 2019-2021. Children were between 36 and 72 months of age, primarily English-speaking, and had no known history of neurodevelopmental disorders. Trained Early Childhood Assessors administered the GLAMS and NEPSY-II in public preschools and homes across Grenada. Exploratory descriptive statistics characterized participant sociodemographics and test score distributions. Spearman correlations, MannWhitney U, and Kruskal-Wallis tests examined the impact of sociodemographics on test scores. Internal reliability was assessed with coefficient alpha. NEPSY-II subtests were used to assess convergent validity, with the prediction that the highest correlations would be observed for NEPSY-II Sentence Repetition. Test engagement (as reflected by “zero-learning”, “some learning”, and “positive learning curves”) was assessed across each age bracket (in 6-month increments). We assessed and summarized barriers to engagement qualitatively.

The sample consisted of 304 children (152 males,152 females). Participants were predominantly Afro-Caribbean and Indo-Caribbean. Parent education and household income (Mdn=$370-740 USD per month) were consistent with the general population. GLAMS internal consistency was reliable (a=0.713). There were age effects on list-learning (rs=0.51; p<0.001), list recall (rs=0.51; p<0.001), face-name learning (rs=0.30;p<0.001), and face-name recall (rs=0.25; p<0.001). There were gender effects on list-learning (p=0.02) and list recall (p=0.01) but not face-name learning or recall. All GLAMS subtests were correlated with NEPSY Sentence Repetition (rs=0.22-0.34; p<0.001). There was sufficient sampling of males and females across all 6 age brackets. As age increased, a higher proportion of children showed a positive learning curve (and fewer “zero-scores”) on verbal learning (X2 =30.88, p<0.001) and face-name learning (X2=22.19, p=0.014), demonstrating increased task engagement as children mature. There were various qualitative observations of why children showed “zero-scores”, ranging from environmental distractions to anxiety and inattention.

As far as we know, the GLAMS is the first preschool measure of learning and memory developed indigenously from within the Caribbean. It shows reliable internal consistency, expected age and gender effects and convergent validity. These initial results are encouraging and support continued efforts to establish test-retest and inter-rater reliability. Plans include validation in clinical samples, scale-up to other Caribbean countries, and eventual adaptation across global LMICs.

Concerns that exposure to more than one language in the home might negatively impact language development in young children with autism spectrum disorder (ASD) are common among caregivers. Although research directly examining the impact of a multilingual home environment in ASD is scarce, emerging evidence shows that language outcomes might be equivalent or better in children with ASD exposed to more than one language (Romero & Uddin, 2021). However, no evidence to date exists on whether exposure to more than one language affects early brain functional development in children with ASD. The current study aims to examine the (1) cross-sectional and (2) longitudinal associations between home language environment (exposure to one v. multiple languages at home, H1l vs. H>1l) and receptive and expressive language skills in young children with and without ASD, and (3) to investigate links between home language environment and brain functional network organization.

Participants included young children with ASD (n=67, mean age: 35±13 months, H>1l n=43) and typically developing (TD) children (n=39, mean age: 32±16 months, H>1l n=17) enrolled in a longitudinal study of early brain markers of autism. A subset of children with ASD for whom longitudinal behavioral data from two study visits were available (n=21, H>1l n=11) were used for exploratory analysis. Receptive language (RL) and expressive language (EL) skills were assessed by the Mullen Scales of Early Learning at each study visit. Data from 42 children with ASD (H>1l n=27) and 38 TD children (H>1l n= 15) for whom functional MRI data were acquired during natural sleep were included in functional connectivity (FC) analysis. ANCOVAs were employed to examine the effect of diagnosis, home language environment (H1l vs. H>1l) and its interaction on RL and EL skills while controlling for socioeconomic variables (i.e., maternal education level, income-to-needs ratio) and gestational age at birth. Linear mixed models were applied to explore the longitudinal effect of home language environment on RL and EL skills across two study visits in the ASD group. Lastly, FC analysis was conducted to compare functional connectivity across 7 canonical brain networks in children with and without ASD who were raised in H1l and H>1l.

We found significant diagnosis by home language environment interaction effect on EL skills, with children with ASD and H1l exhibiting the lowest EL skills. Longitudinal analysis identified a significant home language environment by study visit interaction effect on EL skills in children with ASD. Specifically, children with ASD and H1l showed lower EL skills at study visit 1 but equivalent EL skills at study visit 2 compared to children with ASD and H>1l. FC analysis revealed that children with ASD and H>1l displayed more typical brain network organization (similar to TD children) compared to those with H1l, specifically for FC between language, frontoparietal, and default mode networks.

These results suggest that early exposure to more than one language in the home may be linked with better expressive language skills in young children with ASD. Results of functional connectivity analysis also suggest that exposure to more than one language may be associated with more neurotypical functional network organization, particularly involving language and high-order networks.

Children born to mothers infected with human immunodeficiency virus (HIV) during pregnancy experience increased risk of neurocognitive impairment. In Botswana, HIV infection is common, but standardized cognitive testing is limited. The Penn Computerized Neurocognitive Battery (PennCNB) is a widely used cognitive test battery that streamlines evaluation of neurocognitive functioning. Our group translated and culturally adapted the PennCNB for use among children and adolescents in this high-burden, low-resource setting. The current study examined the construct validity and sensitivity to HIV infection and exposure of the culturally adapted PennCNB among a cohort of HIV-affected children and adolescents in Gaborone, Botswana.

628 school-aged children aged 7-17 years (n=223 children living with HIV [HIV+]; n=204 HIV exposed, uninfected [HEU]; and 201 HIV unexposed, uninfected [HUU]) completed the PennCNB. Participants were recruited from a clinic specializing in the care and treatment of HIV+ children and adolescents in Gaborone, Botswana, as well as from local schools. Confirmatory factor analyses were performed on efficiency measures for 13 PennCNB tests. Multiple regressions examined associations between HIV and neurocognitive functioning while controlling for age and sex. Multivariate normative comparisons were used to examine rates of overall cognitive impairment by comparing individual profiles of test scores to the multivariate distribution of test scores using age-normed data from the HUU group.

Confirmatory factor analysis supported four hypothesized neurocognitive domains: executive functioning, episodic memory, complex cognition, and sensorimotor/processing speed. As expected, there were main effects of age on cognitive performance across all domains (ps < .001), and there were small sex differences, with females performing better in executive functioning and males performing better on visuospatial processing. Children and adolescents living with HIV performed significantly worse than HUU across all domains (ps < .001), with the largest effect sizes on measures of abstraction, working memory, and processing speed. HEU also performed worse than HUU across several domains, with smaller effect sizes. Multivariate normative comparisons indicated that 27% of the HIV+ group evidenced global neurocognitive impairment.

Overall, results support the validity of a neurocognitive battery adapted for use in Botswana, a non-Western, resource-limited setting. Results indicated that the adapted battery applied to children and adolescents with limited computer familiarity had a similar factor structure as in Western settings, indicating that the PennCNB appeared to assess the hypothesized neurocognitive domains. Hypothesized associations with age and sex supported the battery’s construct validity. Moreover, the battery appears to be sensitive to cognitive impairments associated with perinatally-acquired HIV and in utero HIV-related exposures, as it discriminated between the HUU, HIV+, and HEU groups. Differences were found in specific domains and in detection of overall impairment, including approximately one quarter of children and adolescents living with HIV in this cohort evidencing global neurocognitive impairment. Together, these results provide evidence that the PennCNB could serve as a useful tool for the assessment of neurocognitive functioning in school-aged children and adolescents from Botswana and, potentially, other resource-limited settings.

Social determinants of health (SDOH) are social conditions (e.g., employment, access to healthcare, quality schools) which are shown by a growing body of literature to impact many health outcomes, including cognition. The development of community-level measures including the Child Opportunity Index (COI) have allowed for increased understanding of the resources and conditions in neighborhoods and their impact on children’s health. Given the limited existing research on how neighborhood factors impact cognitive development, this study aimed to examine associations between neighborhood context (COI) and cognitive outcomes in children and adolescents who presented for neuropsychological evaluations.

Participants included 4,633 youth (ages 2-22; M = 10.8 years; SD = 4.1 years; 63% Male; 33% with a medical condition involving the central nervous system [CNS]) living in the DC-VA-MD-WV Metro Area who presented to an outpatient clinic for evaluation and completed an intellectual functioning (IQ) measure (88% Weschler, 11% DAS, <1% Leiter, <1% RIAS). COI values were extracted from electronic medical records based on home address. COI values include an overall index and three domain scores in educational (educational access, quality, and outcomes), health/environment (access to healthy food, healthcare, and greenspace) and social/economic (income, employment, poverty); higher scores indicate higher opportunity. Using metro-based norms, children from all opportunity levels were represented (14% Very Low, 13% Low, 18% Moderate, 21% High, 34% Very High). Multiple regression analyses were conducted to examine main effect associations between COI and Full-Scale IQ (FSIQ), Verbal IQ (VIQ), and Non-Verbal IQ (NVIQ) and explore moderation of age, gender, and medical condition on these associations. Additional regression analyses examined these relationships for the three COI domains.

Controlling for age, gender, and medical condition, neighborhood opportunity was positively associated with cognitive function (FSIQ: ß=0.198; VIQ: ß=0.202; NVIQ: ß=0.148, p’s <0.01). Models accounted for approximately 10-14% percent of the variance in cognitive outcomes (FSIQ: F[6,4476]=180.331), Adj.R2=0.138; VIQ: F[6,4556]=161.931), Adj.R2=0.124; NVIQ: F[6,4548]=123.893), Adj.R2=0.098). Age moderated the association between overall COI and cognitive outcomes (FSIQ: ß=0.005, p=0.018; VIQ: ß=0.005, p=0.043; NVIQ: ß=0.005, p<0.01) such that the association between neighborhood opportunity and cognitive outcomes was stronger at older ages, though this was a small effect. When examining subdomains of COI, cognitive outcomes were associated with educational (FSIQ: ß=0.094; VIQ: ß=0.099; NVIQ: ß=0.078, p’s <0.01) and social/economic opportunity (FSIQ: ß=0.115; VIQ: B=0.121; NVIQ: ß=0.084, p’s <0.01) but not health/environmental opportunity (FSIQ: ß=-0.001, p=0.991; VIQ: ß=-0.008, p=0.581; NVIQ: ß=-0.008, p=0.553). Medical diagnosis moderated the association between social/economic opportunity and FSIQ; there was a stronger association between IQ and COI in youth with a medical diagnosis (ß=-0.071, p<0.05).

These findings demonstrate the importance of neighborhood factors, especially education and social/economic opportunities, on cognitive development. Children living in higher opportunity neighborhoods showed higher cognitive functioning. Older age and CNS-involved medical conditions were associated with higher risk in the context of reduced neighborhood opportunities. These findings emphasize the need for advocacy and other efforts to improve community resources (e.g., access to early childhood education) to address inequities in cognitive development.

Compensatory strategies (CS) can assist in supporting everyday memory and functional independence. Digital compensatory strategies (e.g., calendar and notes apps) are being used more by older adults, but their effectiveness compared to paper-based strategies has been questioned due to their novelty and potential suitability. This study examined whether digital and non-digital strategies vary in quality and lead to accuracy differences in carrying out a set of real-world prospective memory (PM) tasks.

Seventy community-dwelling older adults (Mage= 70.80, SD = 7.87) completed two testing sessions remotely from home via Zoom. Participants were presented four real-world PM tasks (packing for overnight trip, creating physical activity summary, paying bill by due date, and calling lab to leave message) and were encouraged to use their typical CS to support task completion. The type and quality of CS, as well as accuracy of PM task completion, were assessed using lab-developed coding schemas. Quality scores were on a 0-3 point scale per task step (maximum total score = 63), and accuracy scores were on a 0-4 point scale (maximum score = 16). Participants were differentiated into two groups: those who used at least one digital CS (40 participants) and those who did not use digital CS (30 participants). T-tests were examined for group differences in number of CS utilized, CS quality, and PM accuracy. Within each group, correlations between CS quality and PM accuracy were conducted. Group comparisons were also conducted for demographics, cognitive test performances, and questionnaires.

The technology group (M = 13.90, SD = 5.43) utilized significantly more strategies than the non-technology group (M = 9.50, SD = 4.12), t(68) = -3.71, p < .05, d = 0.91, and the technology group’s strategies (M = 42.48, SD = 10.47) were significantly higher quality than the non-technology groups (M = 33.80, SD = 13.02), t(68) = -3.09, p < .05, d = 0.73. However, the technology (M = 12.30, SD = 2.48) and non-technology (m = 11.87, SD = 3.16) groups completed the four PM tasks with equivalent accuracy, p > .05. Correlational analyses revealed that higher quality strategies were associated with better PM performance for both the technology (r = .67, p < .001) and the non-technology group (r = .71, p < .001). Although the technology group reported higher comfort with technology, both groups reported comparable levels of quality of life and functional independence and performed similarly on cognitive tests. The technology group trended towards being younger and having a higher level of global cognitive status (p = .07), but there were no group differences in education level or premorbid verbal ability.

Digital compensatory strategies resulted in higher CS quality scores and more strategies used, but there was no significant difference in PM accuracy scores between digital and non-digital CS. Regardless of technology use, using high quality CS supported real-world PM performance. Interventions that focus on improving the quality of compensatory strategies being utilized by older adults may enhance everyday functioning.

Older adults often spontaneously use compensatory strategies (CS) to support everyday memory and daily task completion. Recent work suggests that evaluating the quality of CS provides utility in predicting real-world prospective memory (PM) task completion. However, there has been little exploration of how CS quality may vary based on PM demands. This study examined differences in CS use and task completion accuracy across time-based (TB) and event-based (EB) PM tasks. Based on differences in self-monitoring demands and ability to engage in cognitive offloading, it was hypothesized that participants would utilize better quality strategies for TB tasks than EB tasks, which would lead to superior accuracy in completing TB tasks.

Seventy community-dwelling older adults (Mage = 70.80, SD = 7.87) completed two testing sessions remotely from home via Zoom. Participants were presented two TB PM tasks (paying bill by due date, calling lab at specified time) and two EB PM tasks (presenting a packed bag to examiner upon a cue, initiating discussion about physical activity log upon cue). Participants were encouraged to use their typical CS to support task completion. Quality of CS (0-3 points per task step) and accuracy of task completion (0-4 points per task) were evaluated through lab-developed coding schemas. For each task, CS Quality scores were assigned based on how well strategies supported retrospective memory (RM) and PM task elements, and RM and PM Quality scores were summed to yield a Total Quality score. Because each task consisted of a different number of steps, CS Quality scores for each task were divided by their respective number of steps to yield measures of average quality. Paired-samples t-tests examined differences in average CS quality (Total, RM, and PM) and PM accuracy across TB and EB tasks.

Participants’ Total CS Quality was equivalent for TB tasks (M = 1.92, SD = 0.64) and EB tasks (M = 1.87, SD = 0.68), t(69) = 0.60, p = .55. Comparisons of subscores revealed that while participants used similar quality RM supports for TB tasks (M = 1.67, SD = 0.66) and EB tasks (M = 1.78, SD = 0.68), t(69) = 1.39, p = .17, participants utilized superior quality PM supports for TB tasks (M = 2.16, SD = 0.70) compared to EB tasks (M = 1.97, SD = 0.73), t(69) = 2.46, p = .02. Additionally, participants completed TB tasks with greater accuracy (M = 3.21, SD = 0.74) than EB tasks (M = 2.84, SD = 0.89), t(69) = 3.62, p < .001.

While participants exhibited similar quality CS for RM components across TB and EB tasks, they displayed superior quality CS for PM components of TB tasks. This difference in quality may have contributed to participants completing real-world TB PM tasks with greater accuracy than EB tasks. Results contrast with trends in lab-based PM tasks, in which participants usually complete EB tasks more accurately. Findings may have implications for interventions, such as an enhanced focus on teaching high-quality CS to support real-world EB tasks.

One of the greatest challenges of the Alzheimer’s disease (AD) epidemic is identifying the disease prior to substantial neurological compromise. The established biomarkers of AD, such as measures of cognitive impairment, hippocampal atrophy, and CSF measures of beta amyloid and tau, used in research and drug trials are less indicative of AD pathology in preclinical, non-demented, populations. Olfactory dysfunction, a well-established sensory impairment of AD found to correlate strongly with tau burden and hippocampal volume measures, has shown to be a promising preclinical biomarker for AD progression. Several studies have found either impaired odor identification or odor memory at baseline to predict 5-year follow-up cognitive decline and conversion from MCI to AD, but less is known about how olfactory performance reflects the integrity of associated brain regions such as the hippocampus. The present analysis aims to explore the value of psychophysical olfactory assessment as biomarker measure in preclinical AD studies and drug trials by investigating its relationships with structural measures of the hippocampus.

A sample consisted of non-demented older adults (age >75), recruited from the UCSD Alzheimer’s Disease Research Center as part of a ongoing olfactory biomarker study. Participants completed the AD Assessment Scale-Cognitive Subscale-13 (ADAS-Cog-13), San Diego Odor Identification Test (SDOIT), tests of odor recognition memory (ORMem) and odor associative memory (OAM), and MRI derived hippocampal volumes and average hippocampal occupancy (Avg HOC). Left and right hippocampal volumes were adjusted for each participant’s estimated intracranial volume. Bivariate correlations were calculated for ADAS-Cog-13 and SDOIT total scores, performance scores for odor recognition and odor associative memory tests, and the three hippocampal measures (bilateral volumes and average occupancy).

ADAS-Cog-13 score did not show significant correlations with either hippocampal measure at the .05 level. SDOIT scores were significantly correlated with the measure of Avg HOC (p<.05). ORMem false positive responses were significantly correlated with Avg HOC (p<.01) and right hippocampal volume (p<.05). ORMem miss responses and OAM errors were both correlated with left (p<.05) and right (p<.01) hippocampal volumes.

These results demonstrate that psychophysical assessments of odor identification and odor memory can better reflect the integrity of the hippocampus in nondemented older adults, compared to the neuropsychological ADAS-Cog-13. This is congruent with olfactory dysfunction preceding cognitive-memory decline in AD cases and provides support for the utility of psychophysical olfactory assessment along with other established AD biomarkers in research and drug trials in preclinical populations.

Supported by NIH grant # R01AG062006-04 from the National Institute on Aging to CM. Special thank you to the staff and participants of the UCSD ADRC, especially Christina Gigliotti, and Aaron Jacobson at the UCSD Center for fMRI.

Neurofilament light chain (NfL), a plasma-based biomarker for neurodegeneration, is a promising marker for early Alzheimer disease (AD) detection in individuals at increased risk. We previously reported that Presenilin1 (PSEN1) E280A carriers have increased levels of plasma NfL relative to non-carrier family members twenty years before the onset of clinical symptoms. Abstract reasoning is one of the first cognitive abilities to deteriorate in AD. Here, we examined whether levels of plasma NfL were associated with non-verbal abstract reasoning performance in non-demented PSEN1-E280A carriers and non-carriers.

A total of 798 members of the Colombian kindred with the PSEN1 E280A mutation (462 cognitively-unimpaired and 336 non-carriers; mean age= 34.02 (10.53), mean education= 8.23(4.60), 57% females and 43% males) were included in the study. Participants completed the Raven’s Progressive Matrices (RPM), Mini Mental State Examination (MMSE), and underwent blood sampling. Plasma NfL concentrations were measured with a single molecule array (Simoa) method. Mann-Whitney U test and education-adjusted Spearman partial correlation were used to examine group differences and associations between abstract reasoning performance and NfL levels.

Non-carriers were older (p<.001) and had higher levels of education than carriers (p=.025). Compared to non-carriers, carriers had higher levels of NfL (p=.014), lower performance on the MMSE (p<.001) and on the RPM (p=.001). In the whole sample, performance on the RPM was significantly associated with age (r= -.144, p<.001), and MMSE score (r=.198, p<.001). In carriers only, performance on the RPM was negatively associated with NfL levels (r=-.121, p=.009). This association was not significant in non-carriers.

Our findings support the hypothesis that plasma NfL levels may be indicators of disease progression and early cognitive dysfunction in autosomal dominant AD. Future work with NfL, abstract reasoning and memory with larger samples across the preclinical/prodromal spectrum will allow a more comprehensive examination of these associations.

Intraindividual variability (IIV) is defined as fluctuations in an individual’s cognitive performance over time1. IIV has been identified as a marker of neurobiological disturbance making it a useful method for detecting changes in cognition among cognitively healthy individuals as well as those with prodromal syndromes2. IIV on laboratory-based computerized tasks has been linked with cognitive decline and conversion to mild cognitive impairment (MCI) and/or dementia (Haynes et al., 2017). Associations between IIV and AD risk factors including apolipoprotein (APOE) ε4 carrier status, neurodegeneration seen on brain imaging, and amyloid (Aß) Positron emission tomography (PET) scan status have also been observed1. Recent studies have demonstrated that evaluating IIV on smartphone-based digital cognitive assessments is feasible, has the capacity to differentiate between cognitively normal (CN) and MCI individuals, and may reduce barriers to cognitive assessment3. This study sought to evaluate whether such differences could be detected in CN participants with and without elevated AD risk.

Participants (n=57) were cognitively normal older adults who previously received an Aß PET scan through the Butler Hospital Memory and Aging Program. The sample consisted of primarily non-Hispanic (n=49, 86.0%), White (n=52, 91.2%), college-educated (M=16.65 years), females (n=39, 68.4%). The average age of the sample was 68 years old. Approximately 42% of the sample (n=24) received a positive PET scan result. Participants completed brief cognitive assessments (i.e., 3-4 minutes) three times per day for eight days (i.e., 24 sessions) using the Mobile Monitoring of Cognitive Change (M2C2) application, a mobile app-based cognitive testing platform developed as part of the National Institute of Aging’s Mobile Toolbox initiative (Sliwinski et al., 2018). Participants completed visual working memory, processing speed, and episodic memory tasks on the M2C2 platform. Intraindividual standard deviations (ISDs) across trials were computed for each person at each time point (Hultsch et al., 2000). Higher ISD values indicate more variability in performance. Linear mixed effects models were utilized to examine whether differences in IIV existed based on PET scan status while controlling for age, sex at birth, and years of education.

n interaction between PET status and time was observed on the processing speed task such that Aß- individuals were less variable over the eight assessment days compared to Aß + individuals (B= -5.79, SE=2.67, p=.04). No main or interaction effects were observed on the visual working memory task or episodic memory task.

Our finding that Aß- individuals demonstrate less variability over time on a measure of processing speed is consistent with prior work. No associations were found between IIV in other cognitive domains and PET status. As noted by Allaire and Marsiske (2005), IIV is not a consistent phenomenon across different cognitive domains. Therefore, identifying which tests are the most sensitive to early change is crucial. Additional studies in larger, more diverse samples are needed prior to widespread clinical use for early detection of AD.

Using a humanized APOE3/4 (Alzheimer’s disease genetic risk allele) mouse model we investigated the potential modulating effects of exercise on systemic risk factors and the ability of this mouse model to translate to active or sedentary, midlife, human participants. We present preliminary results of an ongoing, translational pilot study.

26 Midlife individuals, ages 40-65, were recruited from the community and dichotomized into active or sedentary groups following health screening and cognitive assessment. Blood samples were drawn from human participants for lipid assessment and other general health measures as well as peripheral growth factors concentrations (VEGF, BDNF and FGF21). Traditional, transgenic mouse models have helped the scientific community to understand biological mechanisms of Alzheimer’s disease (AD), but they do not develop significant neuronal loss, a hallmark of AD pathology. The MODEL-AD consortium has created a new “humanized” APOE4 model that has the human APOE4 allelic sequence in place of the mouse APOE gene; the model has shown known human phenotypes including deficits in cholesterol trafficking, amyloid clearance and BBB integrity. Of upmost importance, this model does not develop a full AD phenotype indicating that additional genetics and/or environmental factors are required as would be seen in human populations. We used males and females of this model to complete identical sedentary and active measures of each APOE genotype.

Lipid and general health marker assessment between mouse and human were similar and reproduced published literature. In both humans and mice we saw increased total cholesterol and HDL in active females and decreased total cholesterol and HDL in active males. We also saw similar relationships between APOE genotype, sex, and activity with regards to triglycerides. Although total cholesterol, HDL and LDL measures are the primary lipids needed to confirm or deny translation, other lipid measurements were not equivalent between the two models. Growth factor assessment in both species are also similar and reproduce published literature with regards to VEGF and BDNF as we see trending elevated levels in the active group. Less published on is the finding seen between active females and these elevated growth factors levels; our results indicates that although elevated as a result of exercise, this increase may be more prominent in females.

Based on the results found here we conclude that The Jackson Laboratory’s humanized APOE3/4 mouse model is a translatable model of vascular dysfunction, dementia and Alzheimer’s disease. We also conclude that exercise modulates these aspects by growth factor activation and increases resulting in downstream effects that reduce peripheral vascular risk factors and therefore reduce the risk of Alzheimer’s disease as a result of neuroinflammation. Complete, APOE genotype results from human participants are still ongoing. Descriptive analysis is limited by human samples size.