Illness perception, or the ways in which individuals understand and cope with injury, has been extensively studied in the broader medical literature and has been found to have important associations with clinical outcomes across a wide range of medical conditions. However, there is a dearth of knowledge regarding how perceptions of traumatic brain injury (TBI) influence outcome and recovery following injury, especially in military populations. The purpose of this study was to examine relationships between illness perception, as measured via symptom attribution, and neurobehavioral and neurocognitive outcomes in Veterans with TBI history.

This cross-sectional study included 44 treatment-seeking Veterans (86.4% male, 65.9% white) with remote history of TBI (75.0% mild TBI). All Veterans were referred to the TBI Cognitive Rehabilitation Clinic at VA San Diego and completed a clinical interview, self-report questionnaires, and a neuropsychological assessment. A modified version of the Neurobehavioral Symptom Inventory (NSI) was administered to assess neurobehavioral symptom endorsement and symptom attribution. Symptom attribution was assessed by having participants rate whether they believe each NSI item was caused by TBI. A total symptom attribution score was computed, as well as the standard NSI total and symptom cluster scores (i.e., vestibular, somatic, cognitive, and affective symptom domains). Three cognitive composite scores (representing mean performance) were also computed, including memory, attention/processing speed, and executive functioning. Participants were excluded if they did not complete the NSI attribution questions or they failed performance validity testing.

Results showed that the symptoms most frequently attributed to TBI included forgetfulness (82%), poor concentration (80%), and slowed thinking (77%). There was a significant positive association between symptom attribution and the NSI total score (r = 0.62, p < .001), meaning that greater attribution of symptoms to TBI was significantly associated with greater symptom endorsement overall.

Symptom attribution was also significantly associated with all four NSI symptom domains (r’s = 0.47-0.66; all p’s < .001), with the strongest relationship emerging between symptom attribution and vestibular symptoms. Finally, linear regressions demonstrated that symptom attribution but not symptom endorsement was significantly associated with objective cognitive functioning. Specifically, greater attribution of symptoms to TBI was associated with worse memory (ß = -0.33, p = .035) and attention/processing speed (ß = -0.40, p = .013) performance.

Results showed significant associations between symptom attribution and (1) symptom endorsement and (2) objective cognitive performance in Veterans with a remote history of TBI. Taken together, findings suggest that Veterans who attribute neurobehavioral symptoms to their TBI are at greater risk of experiencing poor long-term outcomes. Although more research is needed to understand how illness perception influences outcomes in this population, results highlight the importance of early psychoeducation regarding the anticipated course of recovery following TBI.

Many individuals who experienced a mild traumatic brain injury (mTBI) have persistent cognitive complaints. Traditional cognitive rehabilitation (TCR) interventions were primarily developed for severe neurological injury which has limited effectiveness in rehabilitation of active duty military personnel who have the goal of returning to full military operational status. To remain on active duty, warfighters must have sufficient mental competency to safely and effectively function in complex environments such as combat. There is need for a cognitive rehabilitation approach that addresses demands of military personnel to expedite return to duty. The Strategic Memory Advanced Reasoning Training (SMART) program is novel alternative to TCR. SMART is an evidence-based advanced reasoning protocol that enhances cognitive domains essential to military readiness (e.g., mental agility, strategic learning, problem solving, and focus) and requires less than half of the treatment time. The objective of this study was to assess the efficacy of SMART compared to TCR in terms of overall recovery as well as change in specific cognitive domains.

Participants were recruited from a military treatment facility. All patients had at least one diagnosed mTBI as well as persistent cognitive complaints. Participants completed the Rey-15 to ensure performance validity. Final sample was SMART n = 28 and SCORE n = 19. Primary dependent measure was the Global Deficit Scale (GDS). GDS was calculated from: Hopkins Verbal Learning Test-Revised (HVLT-R); Delis Kaplan Executive Functioning System Color Word (CW) and Trail Making (TM), Paced Auditory Serial Addition Test (PASAT), and the Symbol Digit Modality Test (SDMT). Demographically corrected t-scores were converted to deficit scores as follows: >40 = 0, 35-39 = 1, 30-34 = 2, 25-29 = 3, 20-24 = 4, <20 = 5. Deficit scores were averaged to calculate GDS. For each measure, Hohen’s g was analyzed for effect size comparisons pre-post treatment.

Average number of treatment hours was significantly lower in the SMART condition (SMART: M = 18.47 hours, SD = 2.17; TCR: M = 42.42 hours, SD = 3.79, p <.001). A repeated measures ANOVA showed a significant change on GDS post-treatment (F = 30.25, p < .001) with a large effect size (n2 = .402); however, the interventions did not differ on GDS change. Impact on cognitive domains was relatively equivalent for processing speed (SMART h = 0.67 vs TCR h = -.54) and executive function (SMART h = -0.92 vs TCR h = -.85); however, SMART had a larger impact on memory (SMART h = -0.81 vs TCR h = -.39). SMART resulted in large improvements in retention and recognition memory which were minimally impacted by TCR.

Both TCR and SMART had comparable effectiveness in improving cognitive impairment, though SMART was completed in less than half of the treatment time. Both interventions had large effect sizes on processing speed and executive functioning; however, SMART was more effective in improving long-term memory. Memory is an integral part of military readiness. Further investigation is required to determine the relative effectiveness of these two approaches to improving cognitive readiness of the warfighter.

Determine how characteristics of deployment mild traumatic brain injury (TBI) and blast exposure influence the relationship between the functional brain connectome with cognitive outcomes and symptom severity.

N = 181 Iraq and Afghanistan combat veterans completed structured clinical interviews, cognitive testing, self-report questionnaires, and magnetoencephalography (MEG). MEG data were acquired in the resting-state with eyes open. MEG data were beamformed to identify brain regions active at rest. Functional brain connectomes representing the unique network present for a given individual were created using active brain regions identified for each participant. Network metrics describing these connectomes were calculated at the participant level. Cognitive tests included the WAIS-IV, Trail Making Test Parts A&B, and the Controlled Oral Word Association test. Due to differences in normative data across tests, raw scores were used in analyses. Symptom measures included the PTSD Checklist - 5 (PCL-5), Patient Health Questionnaire (PHQ-9), Neurobehavioral Symptoms Inventory (NSI), Quality of Life After Brain Injury (QOLIBRI), Pittsburgh Sleep Quality Index (PsQi), the Distress Tolerance Scale (DTS), and the PROMIS Pain Interference Scale (PROMIS-PI).

Hierarchical linear regression analyses revealed that several network metrics were significantly related to both cognitive outcomes and symptom severity after adjusting for demographic covariates and clinical characteristics.

The relationship between Global Efficiency (GE) and cognitive outcomes was moderated by deployment TBI on the WAIS-IV Full Scale Index (FSI), Perceptual Reasoning Index (PRI), and General Ability Index (GAI). In all cases, when deployment TBI was absent, greater GE was associated with poorer cognitive scores. The relationship between GE and symptom severity was moderated by the severity of blast exposure. Greater GE was associated with lower symptom severity at lower blast severities for the PHQ-9 and QOLIBRI A (thinking) and E (negative emotions). Moderation effects were also observed for the PSQI. In the absence of deployment TBI, greater GE was associated with better sleep quality; however, in the presence of deployment TBI, greater GE was associated with poorer sleep quality. Other connectome-outcome relationships were not consistently moderated by Deployment TBI or blast history

Results demonstrated relationships between several aspects the functional connectome of the brain with both cognitive outcomes and symptom severity beyond effects of common demographic and clinical variables. Moderation analyses revealed that the relationship between GE of the connectome and outcomes is frequently disrupted by deployment TBI and blast. GE is a measure of the ease of information transfer through the network. These results identified consistent relationships between GE and outcomes in the absence of deployment TBI or blast, but these relationships disappear when deployment TBI or blast are present. Participants in this study were on average 11 years post-TBI or blast exposure, suggesting these are chronic rather than acute effects. GE was significantly correlated with most symptom severity measures as well as the WAIS-IV PRI, GAI, VCI, and FSI. Future efforts to normalize the relationship between GE and outcomes following TBI may improve rehabilitation outcomes and directly affect areas of concern commonly reported by service members following TBI or blast exposure.

Identifying individuals at the earliest stages of Alzheimer’s Disease (AD) would enable development and study of interventions prior to onset of symptoms. However, differentiating age-related cognitive changes from subtle pathological changes remains a challenge in the field. Methods that would enable earlier detection of AD in elders with no subjective or objective cognitive concerns (i.e., individuals in the preclinical stage) would be of great interest. Community detection, a metric founded in graph theory, offers an alternative approach for characterizing subtle heterogeneity within aging samples and has the potential to inform cognitive variability in aging.

Using a hierarchical community detection, we examined whether cognitive subtypes could be identified in 226 cognitively normal older adults (from the Alzheimer’s Disease Neuroimaging Initiative [ADNI] study). Cognitive profiles of each community were characterized first using MANOVAs to examine the relationship between community membership and 12 age-, gender-, and education-corrected neuropsychological variables. Pair-wise comparisons were examined for significant main effects. We then examined whether these subtypes were related to biomarkers (cortical volumes, fluorodeoxyglucose (FDG)-positron emission tomography (PET) hypometabolism) or clinical progression. All p values were corrected for multiple comparisons.

Three communities (i.e., cognitive subtypes) were identified within the healthy aging sample. The first and largest community identified (N = 106) was characterized by a relative weakness on a single measure visuospatial executive function. Both the second (N = 76) and third community (N = 44) scored significantly lower on immediate, delayed, and recognition memory relative to the first community. The third community was characterized by a relative weakness in category fluency and speeded visual sequencing as well (p < .000). The three communities did not differ on age, gender, education, race, or ethnicity. Community membership was associated with entorhinal volume (with the second and third communities having significantly smaller entorhinal volumes than the first community), though community membership was not significantly associated with other biomarkers examined. Conversion rate reached trend level significance at 12 month follow up (more converters in the third community).

Hierarchical community detection is an alternative method for characterizing neuropsychological variation and it appears sensitive to relatively small differences that may be observed in a normal aging sample. While the sample size was relatively small, this approach shows promise for potentially leading to earlier detection of cognitive decline among individuals classified to be aging normally (e.g., community 3).

Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.

Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.

RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.

These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.

Exercise elicits a variety of physiological responses in the body. In the brain, exercise can modulate levels of neurotransmitters and other neurochemicals as well as sparking neurogenesis and structural changes. Downstream psychological effects of exercise include changes in mood and cognition. These changes vary depending on the type of exercise conducted (e.g., running versus strength training). While much is known about the effects of exercise in animals and adult humans, literature on the oldest-old (>= 85 years old) is sparse. The present cross-sectional study explores the relationship between exercise and cognition in the oldest-old.

The final sample includes 194 cognitively healthy participants (106 females, MoCA mean score = 24.75) aged 85 to 99 years old (mean = 88.48). Each participant completed the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire and a cognitive battery comprising of the NIH Toolbox, digit coding, symbol search, verbal fluency, and Stroop task. Three groups (sedentary, cardio, and cardio plus strength training) were derived from responses on CHAMPS.

The cardio plus strength training group performed significantly better on the cognitive measures compared to the sedentary group. For two measures, digit coding and symbol search, the cardio plus strength training group also performed significantly better than the cardio group. Cardio group did not significantly differ from the sedentary group on the cognitive measures. All at p < 0.05 and adjusted for multiple comparisons.

Our findings suggest exercise in the oldest-old is linked with higher fluid intelligence and better performance on cognitive measures of processing speed and that there may be an additive effect of exercise types on cognition.

Practice effects (PE) on cognitive testing impede our ability to accurately assess change. In particular, they hamper the detection of mild cognitive impairment (MCI) and progression to dementia by delaying the point at which test scores fall below diagnostic impairment cutoffs. When decline over time is expected, as with older adults or progressive diseases, failure to adequately address PEs may lead to inaccurate conclusions because PEs artificially boost scores while pathology-related or age-related decline reduces scores. The participant-replacement method accounts for PEs by comparing performance of demographically-matched replacement participants to returnees who have been tested previously. Unlike most methods, the participant-replacement method can separate pathology- or age-related decline from PEs; however, this method has only been used across two timepoints. Neuropsychologists tend to think that PEs level out after the first follow-up, but this issue has not been evaluated in models that allow PEs in the presence of overall decline. Including more than two timepoints makes it possible to determine if PEs level out after the first follow-up, but it is analytically challenging because individuals may not be assessed at every timepoint.

We examined 1190 older adults in the Alzheimer’s Disease Neuroimaging Initiative who were cognitively unimpaired (n=809) or had MCI (n=381) at baseline. Participants completed six neuropsychological measures (Trails A, Trials B, Boston Naming Test, Category Fluency, Logical Memory, Rey Auditory Verbal Learning Task) at three timepoints (baseline, 12-month, 24-month). We implemented the participant-replacement method using generalized estimating equations in comparisons of matched returnees and replacements to calculate PEs. Propensity scores matched individuals on age, education, sex, and an estimate of premorbid functioning. Generalized estimating equations modeled PEs and age-related decline separately for each cognitive measure.

We observed significant PEs for 5 of the 6 measures in the cognitively unimpaired group and 4 measures in the baseline MCI group. PEs did not uniformly decrease across time; some—specifically on episodic memory measures—continued to increase beyond the first follow-up for both groups of participants. Without accounting for PEs, cognitive function appeared to improve or stay the same. In contrast, when PEs were included in the models, cognitive function appeared to decline or stay the same across time.

The replacement method of PE adjustment revealed significant PEs across two follow-ups. PEs for episodic memory, in particular, did not level out, but actually increased after the first follow-up, two years after baseline. As expected in these older adults, accounting for PEs revealed cognitive decline, in some cases, even when PE-unadjusted scores improved. This method of assessing PEs, in turn, means earlier detection of cognitive deficits, including progression to MCI, and more accurate characterization of longitudinal change.

Despite growing evidence regarding the association between exercise training (ET) and functional brain connectivity, little is known about the effects of ET on within- and between-network functional connectivity (FC) of core brain networks. We investigated the effects of ET on within- and between-network functional connectivity of the default mode network (DMN), frontoparietal network (FPN), and salience network (SAL) in older adults with intact cognition (CN) and older adults diagnosed with mild cognitive impairment (MCI). We further examined whether the ET-induced changes in FC were associated with changes in cognitive performance.

33 older adults (78.0±7.0 years; 16 MCI and 17 CN) participated in the present study. Before and after a 12-week walking ET intervention, participants underwent cardiorespiratory fitness tests, the Controlled Oral Word Association Test (COWAT), the Rey Auditory Verbal Learning test (RAVLT), a narrative memory test (logical memory; LM), and a resting-state fMRI scan. We examined the within- and between-network connectivity of the DMN, FPN, and SAL before and after ET. We also used linear regression to examine associations between ET-related changes in the within- and between-network connectivity and cognitive function.

There were significant improvements in VO2peak, COWAT, RAVLT, and LM after ET across participants. Significant increases in within-network connectivity of the DMN and SAL were observed in response to ET across participants. FC between the DMN-FPN, DMN-SAL, and FPN-SAL were also increased after ET. Moreover, greater SAL within connectivity and FPN-SAL between connectivity were associated with enhanced LM immediate recall performance after ET. There were no significant interactions between Time (before vs after ET) and Group (CN vs MCI) for network connectivity or cognitive function.

Our findings suggest that increased within- and between-network connectivity following 12-weeks of walking exercise may subserve improvements in memory performance in older individuals with intact cognition and in those diagnosed with MCI.

Aging is associated with disruptions in functional connectivity within the default mode (DMN), frontoparietal control (FPCN), and cingulo-opercular (CON) resting-state networks. Greater within-network connectivity predicts better cognitive performance in older adults. Therefore, strengthening network connectivity, through targeted intervention strategies, may help prevent age-related cognitive decline or progression to dementia. Small studies have demonstrated synergistic effects of combining transcranial direct current stimulation (tDCS) and cognitive training (CT) on strengthening network connectivity; however, this association has yet to be rigorously tested on a large scale. The current study leverages longitudinal data from the first-ever Phase III clinical trial for tDCS to examine the efficacy of an adjunctive tDCS and CT intervention on modulating network connectivity in older adults.

This sample included 209 older adults (mean age = 71.6) from the Augmenting Cognitive Training in Older Adults multisite trial. Participants completed 40 hours of CT over 12 weeks, which included 8 attention, processing speed, and working memory tasks. Participants were randomized into active or sham stimulation groups, and tDCS was administered during CT daily for two weeks then weekly for 10 weeks. For both stimulation groups, two electrodes in saline-soaked 5x7 cm2 sponges were placed at F3 (cathode) and F4 (anode) using the 10-20 measurement system. The active group received 2mA of current for 20 minutes. The sham group received 2mA for 30 seconds, then no current for the remaining 20 minutes.

Participants underwent resting-state fMRI at baseline and post-intervention. CONN toolbox was used to preprocess imaging data and conduct region of interest (ROI-ROI) connectivity analyses. The Artifact Detection Toolbox, using intermediate settings, identified outlier volumes. Two participants were excluded for having greater than 50% of volumes flagged as outliers. ROI-ROI analyses modeled the interaction between tDCS group (active versus sham) and occasion (baseline connectivity versus postintervention connectivity) for the DMN, FPCN, and CON controlling for age, sex, education, site, and adherence.

Compared to sham, the active group demonstrated ROI-ROI increases in functional connectivity within the DMN following intervention (left temporal to right temporal [T(202) = 2.78, pFDR < 0.05] and left temporal to right dorsal medial prefrontal cortex [T(202) = 2.74, pFDR < 0.05]. In contrast, compared to sham, the active group demonstrated ROI-ROI decreases in functional connectivity within the FPCN following intervention (left dorsal prefrontal cortex to left temporal [T(202) = -2.96, pFDR < 0.05] and left dorsal prefrontal cortex to left lateral prefrontal cortex [T(202) = -2.77, pFDR < 0.05]). There were no significant interactions detected for CON regions.

These findings (a) demonstrate the feasibility of modulating network connectivity using tDCS and CT and (b) provide important information regarding the pattern of connectivity changes occurring at these intervention parameters in older adults. Importantly, the active stimulation group showed increases in connectivity within the DMN (a network particularly vulnerable to aging and implicated in Alzheimer’s disease) but decreases in connectivity between left frontal and temporal FPCN regions. Future analyses from this trial will evaluate the association between these changes in connectivity and cognitive performance post-intervention and at a one-year timepoint.

While loss of insight into one’s cognitive impairment (anosognosia) is a feature in Alzheimer’s disease dementia, less is known about memory self-awareness in cognitively unimpaired (CU) older adults or mild cognitive impairment (MCI) or factors that may impact self-awareness. Locus of control, specifically external locus of control, has been linked to worse cognitive/health outcomes, though little work has examined locus of control as it relates to self-awareness of memory functioning or across cognitive impairment status. Therefore, we examined associations between locus of control and memory self-awareness and whether MCI status impacted these associations.

Participants from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (mean age=73.51; 76% women; 26% Black/African American) were classified as CU (n=2177) or MCI (amnestic n=313; non-amnestic n=170) using Neuropsychological Criteria. A memory composite score measured objective memory performance and the Memory Functioning Questionnaire measured subjective memory. Memory self-awareness was defined as objective memory minus subjective memory, with positive values indicating overreporting of memory difficulties relative to actual performance (hypernosognosia) and negative values indicating underreporting (hyponosognosia). Internal (i.e., personal skills/attributes dictate life events) and external (i.e., environment/others dictate life events) locus of control scores came from the Personality in Intellectual Aging Contexts Inventory. General linear models, adjusting for age, education, sex/gender, depressive symptoms, general health, and vocabulary examined the effects of internal and external locus of control on memory self-awareness and whether MCI status moderated these associations.

Amnestic and non-amnestic MCI participants reported lower internal and higher external locus of control than CU participants. There was a main effect of MCI status on memory self-awareness such that amnestic MCI participants showed the greatest degree of hyponosognosia/underreporting, followed by non-amnestic MCI, and CU participants slightly overreported their memory difficulties. While, on average, participants were fairly accurate at reporting their degree of memory difficulty, internal locus of control was negatively associated with self-awareness such that higher internal locus of control was associated with greater underreporting (ß=-.127, 95% CI [-.164, -.089], p<.001). MCI status did not moderate this association. External locus of control was positively associated with self-awareness such that higher external locus of control was associated with greater hypernosonosia/overreporting (ß=.259, 95% CI [.218, .300], p<.001). Relative to CU, amnestic, but not non-amnestic, MCI showed a stronger association between external locus of control and memory self-awareness. Specifically, higher external locus of control was associated with less underreporting of cognitive difficulties in amnestic MCI (ß=.107, 95% CI [.006, .208], p=.038).

In CU participants, higher external locus of control was associated with greater hypernosognosia/overreporting. In amnestic MCI, the lower external locus of control associations with greater underreporting of objective cognitive difficulties suggests that perhaps reduced insight in some people with MCI may result in not realizing the need for external supports, and therefore not asking for help from others. Alternatively, in amnestic participants with greater external locus of control, perhaps the environmental cues/feedback translate to greater accuracy in their memory self-perceptions. Longitudinal analyses are needed to determine how memory self-awareness is related to future cognitive declines.

In normative aging, there is a decline in associative memory that appears to relate to self-reported everyday use of general memory strategies (Guerrero et al., 2021). Self-reported general strategy use is also strongly associated with self-reported memory abilities (Frankenmolen et al., 2017), which, in turn, are weakly associated with objective memory performance (Crumley et al., 2014). Associative memory abilities and strategy use appear to differ by gender, with women outperforming men and using more memory strategies (Hertzog et al., 2019). In this study, we examine how actual performance and self-reported use of specific strategies on an associative memory task relate to each other and to general, everyday strategy use, and whether these differ by gender.

An international sample of older adults (N = 566, 53% female, aged 60-80) were administered a demographic questionnaire and online tasks, including 1. the Multifactorial Memory Questionnaire (MMQ) which measures self-reported memory ability, satisfaction, and everyday strategy use (Troyer & Rich, 2018); and 2. the Face-Name Task which measures associative memory (Troyer et al., 2011). Participants were also asked about specific strategies that were used to complete the Face-Name Task.

On the Face-Name Task, participants who reported using more strategies performed better (F(3, 562) = 6.51, p < 0.001, n2 = 0.03), with those who reported using three or four strategies performing best (p < .05). There was a significant difference in performance based on the type of strategy used (p(2, 563) = 11.36, p < 0.001, n2 = 0.04), with individuals who relied on a “past experiences/knowledge” strategy performing best (p < .01). Women (M = 0.79, SD = 0.19) outperformed men (M = 0.71, SD = 0.20), f(545) = -4.64, p < 0.001, d = -0.39. No gender differences were found in the number (X2(3, N = 564) = 2.06, p = 0.561) or type (x2(2, N = 564) = 5.49, p = 0.064) of strategies used on the Face-Name Task. Only participants who reported using no strategies on the Face-Name Task had lower scores on the MMQ everyday strategy use subscale (p < .05). A multiple-regression model was used to investigate the relative contributions of the number of strategies used on the Face-Name Task, MMQ everyday strategy subscale score, gender, age, education, and psychological distress to Face-Name Task performance. The only significant predictors in the model were gender (B = 0.08, t(555) = 4.55, p < 0.001) and use of two or more strategies (B = 0.07, f(555) = 2.82, p = 0.005).

Reports of greater self-initiated strategy use, and use of a semantic strategy in particular, related to better performance on an associative memory test in older adults. Self-initiated, task-specific strategy use also related to everyday strategy use. The findings extend past work on gender differences to show that women outperform men on an associative memory task but that this is unlikely to be due to self-reported differences in strategy use. The results suggest that self-reported strategy use predicts actual associative memory performance and should be considered in clinical practice.

Learning curve patterns on list-learning tasks can help clinicians determine the nature of memory difficulties, as an “impaired” score may actually reflect attention and/or executive difficulties rather than a true memory impairment. Though such pattern analysis is often qualitative, there are quantitative methods to assess these concepts that have been generally underutilized. This study aimed to develop a model that decomposes learning over repeated trials into separate cognitive processes and then include other testing data to predict performance at each trial as a function of general cognitive functioning.

Data for CVLT-II learning trials were obtained from an outpatient neuropsychology service within an academic medical center referred for clinical reasons. Participants with a cognitive diagnosis of non-demented (ND) or probable Alzheimer’s disease (AD) were included. The final sample consisted of 323 ND [Mage = 58.6 (14.8); Medu = 15.4 (2.7); 55.7% female] and 915 AD [Mage = 72.6 (9.0); Medu = 14.2 (3.1); 60.1% female cases. A Bayesian non-linear beta-binomial multilevel model was used, which uses three parameters to predict CVLT-II recall-by-trial: verbal attention span (VAS), maximal learning potential (MLP), and learning rate (LR). Briefly, VAS predicts expected first trial performance while MLP, conversely, predicts the expected best performance as trials are repeated, and LR weights the influence of VAS versus MLR over repeated trials. Predictors of these parameters included age, education, sex, race, and clinical diagnosis, in addition to raw scores on Trail Making Test Parts A and B, phonemic (FAS) fluency, animal fluency, Boston Naming Test, Wisconsin Card Sorting Test (WCST) Categories Completed, and then age-adjusted scaled scores from WAIS-IV Digit Span, Block Design, Vocabulary, and Coding. Random intercepts were included for each parameter and extracted for comparison of residual differences by diagnosis.

The model explained 84% of the variance in CVLT-II raw scores. VAS reduced with age and time-to-complete Trails B but improved with both verbal fluencies and confrontation naming. MLP increased as a function of WAIS Digit Span, animal fluency, confrontation naming, and WCST categories completed. Finally, LR was greater for females and WAIS-IV Coding and Vocabulary performances but reduced with age. Participants with AD had lower estimates of all three parameters: Cohen’s d = 2.49 (VAS) - 3.48 (LR), though including demographic and neuropsychological tests attenuated differences, Cohen’s d = 0.34 (LR) - 0.95 (MLP).

The resulting model highlights how non-memory neuropsychological deficits affect list-learning test performance. At the same time, the model demonstrated that memory patterns on the CVLT-II can still be identified beyond other confounding deficits since having AD affected all parameters independent of other cognitive impairments. The modeling approach can generate conditional learning curves for individual patient data, and when multiple diagnoses are included in the model, a person-fit statistic can be computed to return the mostly likely diagnosis for an individual. The model can also be used in research to quantify or adjust for the effect of other patient data (e.g., neuroimaging, biomarkers, medications).

The prevalence of mild to moderate cognitive impairment, including episodic memory deficits, in people living with HIV (PLWH) remains high despite the life-extending success of antiretroviral pharmacotherapy. With PLWH now reaching near-normal life expectancy, questions concerning a potential synergy between age- and HIV disease-related effects, including degradation in fronto-limbic circuits, neural systems also compromised in Parkinson’s disease (PD), have emerged.

This cross-sectional study examined the similarities and differences in component processes of verbal episodic memory and their neural correlates in 42 PLWH, 41 individuals with PD, and 37 controls (CTRL) (all participants aged 45-79 years). Learning over five trials, short-delay (SD) and long-delay, (LD), free-recall (FR) and cued-recall (CR) indices were assessed using the California Verbal Learning Test-2. Retention scores for FR and CR were derived adjusting for Trial 5 performance. All memory scores were age- and education-corrected based on the control group and reported as Z-scores. Regional brain volumes were calculated using 3T MRI data and the SRI24 atlas to delineate frontal (precentral, superior, orbital, middle, inferior, supplemental motor, and medial) and limbic (hippocampus, thalamus) regions. Brain volumes were age- and head-sized corrected based on 238 controls (19-86 years old).

Compared with the CTRL group, the HIV and PD groups were impaired on learning across trials and on SD and LD free- and cued-recall, with no group difference between the HIV and PD groups on any score. All three groups benefited similarly from cues compared with free-recall. The HIV and PD groups did not differ from CTRL on retention scores. Regarding brain volumes, the HIV group had smaller middle frontal volumes than the PD or CTRL groups and smaller thalamic volumes than the PD group. Correlational analyses (Bonferroni correction for 8 comparisons, p<.01) indicated that fewer total number of words recalled on Trial 5, learning over Trials 1-5, total words recalled on SD-CR, LD-FR, and LD-CR were associated with smaller orbitofrontal volume in the HIV but not the PD group; the correlations between orbitofrontal volume and memory scores were significantly different between the HIV and PD groups. In PD, but not HIV, lower retention scores on SD-FR and LD-CR correlated to smaller hippocampal volume.

Impairment in learning and cued recall performance indicate that both encoding and retrieval processes are affected in PLWH and PD. Neural correlates of verbal memory differed between groups, with orbitofrontal volume associated with learning and recall in PLWH, whereas hippocampal volume was associated with retention scores in PD. Together, these results suggest that different nodes within the fronto-limbic mnemonic circuitry underlie the mutual verbal episodic memory deficits observed in older PLWH and PD. Support: AA023165, AA005965, AA107347, AA010723, NS07097, MH113406, and the Michael J. Fox Foundation for Parkinson’s Research

Memory is a critical piece of the human experience and impairments in neural memory networks can have devastating consequences for the affected person. A subtype of memory, episodic memory generates context for the present based on past experience and allows us to make predictions about the future. Episodic memories become stable fixtures through long-term memory consolidation. It is believed that consolidation of episodic memory requires a dynamic interplay between connected hippocampal-cortical networks, mainly during sleep. Sleep oscillations, slow oscillations and thalamocortical spindles, coupled with hippocampal sharp wave ripples (SWR) is proposed to be mechanistically involved in establishing the crucial cortical-subcortical dialog. The current study aimed to determine alterations in typical sleep oscillations and oscillation coupling in patients with and without structural hippocampal damage and correlate them with neuropsychological measures believed to be sensitive to hippocampal dysfunction, i.e., Rey Auditory Verbal Learning Task (RAVLT) and Verbal Paired Associates (VPA-II).

We used intracranial electroencephalography (iEEG) in 14 patients with epilepsy to directly record hippocampal and neocortical oscillations and neuropsychological measures obtained prior to implantation. Half of the participants were diagnosed with mesial temporal sclerosis (MTS) in the left hippocampus and healthy tissue in the right hippocampus. The other half did not have MTS and had either mesial temporal epilepsy without MTS or extra-temporal seizures. We analyzed hippocampal SWR output from both hippocampi and characterized neocortical slow oscillations and spindles and their coupling for each participant. We correlated electrophysiological data with behavioral results of neuropsychological testing in order to characterize the clinical relevance.

SWR analysis revealed significant differences in the frequency, t(7639) = 15.52, p>.001, p > .001), amplitude, t(7664) = -23.93, p > .001, and waveforms (p > .001) of SWR in the sclerotic versus healthy hippocampi. Patients with a sclerotic hippocampus but relatively preserved verbal memory scores (RAVLT, VPA-II) showed increased SWR amplitudes in the contralateral hippocampus compared to patients with low verbal memory scores. Additionally, we found differences between hemispheres in phase amplitude coupling of SWRs to spindles and SOs (p > 0.001). Results of our correlational analysis were variable and dependent upon additional factors, such as age of onset and diagnosis duration.

Results from this work will aid in establishing a criterion for characterizing a relationship between subcortical and cortical oscillations as they relate to memory performance. Besides aiding our understanding of the neural mechanisms underpinning memory consolidation this will ideally help with developing neurophysiological biomarkers that may predict possible memory decline in resective or ablative neurosurgery absent of structural lesion. In addition, this work may potentially provide first evidence of a neurophysiological biomarker directly recorded from the human hippocampus to support possible reorganization of memory functioning in the non-sclerotic hippocampus.

Tryptophan is an essential amino acid and precursor to several compounds of neurobiological significance, including serotonin, melatonin, and nicotinamide adenine dinucleotide. However, the tryptophan-kynurenine metabolic pathway exhibits “double-edged sword” effects on neurons with neuroprotective metabolites and neurotoxic intermediates. Given its involvement in neurodegenerative diseases and recent reports of alterations in the pathway in response to obesity, we set out to investigate the potential moderating effect of the kynurenine/tryptophan ratio (KTR) on the relationship between adiposity and verbal memory performance in midlife. Our study is important in providing insight into mechanisms underlying the association between adiposity and cognition through the life course and sheds light on the role of metabolic risk factors before senescence. With the current epidemic of obesity and the expected age-related increase in dementia incidence, even a small association between obesity and cognitive decline may have far-reaching public health implications.

A total of 110 middle-aged adults aged 40-61 years participated in this cross-sectional study. Serum levels of kynurenine and tryptophan, body adiposity measured through bioimpedance, and non-contextual verbal memory performance on the California Verbal Learning Test, Second Edition (CVLT-II) were evaluated. Using factor analysis, the composite score of memory indices from Short Delay Free Recall, Long Delay Free Recall, and Long Delay Recognition tasks were calculated. We used linear regression models with the interaction between KTR and adiposity. Sex, age, years of education, and physical activity were included as covariates, as they predict cognitive performance.

Higher KTR was associated with greater adiposity (p < 0.01). Linear regression analyses for assessing interaction effects indicated that KTR moderated the relation between adiposity and composite memory score (F(7, 100) = 5.22, p < 0.001, R2 = 0.27). These results were robust across individual memory indices and composite memory scores. These findings remained significant even with adjusting for relevant covariates. Interestingly, the marginal effects of adiposity on composite memory score were estimated to be statistically significant and negative (higher adiposity = poorer memory) only when KTR was low (< 0.03).

The present study indicates that KTR may influence the association between adiposity and verbal memory in midlife as KTR moderated the relationship between adiposity and composite memory score even after adjusting for relevant covariates. In contrast to the notion that high KTR is related to increases in neurotoxic metabolites such as quinolinic acid, individuals with high adiposity and low KTR exhibited the weakest memory performance. Unfortunately, our study did not include measurements of quinolinic acid or kynurenic acid, which may have neuroprotective and anti-inflammatory properties. Future studies expanding the number of measured KT metabolites could shed light on the interactions between obesity and KTR on memory function in midlife.

Previous research has demonstrated that individuals with Agenesis of the Corpus Callosum (AgCC), the congenital absence of all or part of the corpus callosum, exhibit a pattern of cognitive and psychosocial deficits, even with a FSIQ in the normal range (FSIQ > 80; Brown & Paul, 2019). This includes a core deficit in their complex reasoning and novel problem-solving (Brown & Paul, 2019), with secondary deficits in capacity to imagine complex emotional/cognitive consequences of potential actions involving others (Young et al, 2019), deficits in emotion

perception (Symington et at., 2010, Bridgman et al 2014), and difficulty with cognitively processing emotions within the context of social interactions (Anderson et al., 2017). This constellation of deficits is likely to also impact moral reasoning. While previous research has demonstrated differences in moral reasoning among other neuropsychological populations such as those with ventromedial prefrontal damage (Moretto et al., 2010) and frontotemporal dementia (Gleichgerrcht et al., 2011), there is no research reported regarding moral judgements in AgCC. This study employed the Moral Dilemmas Scale (Greene, 2001) to compare the moral judgements of persons with AgCC to neurotypical controls. It was predicted that individuals with AgCC would be less contextually nuanced than neurotypical controls in responding to moral dilemmas.

Results consist of data derived from 57 neurotypical control participants (ages 23 to 64 years) recruited from MTurk Cloud and 19 AgCC participants (ages 23 to 77 years) with normal-range FSIQ (>80) drawn from the individuals with AgCC involved with the Human Brain and Cognition Lab at the Travis Research Institute. All participants completed an online version of the Moral Dilemmas Scale (Greene, 2001). The scale consists of 25 dilemmas, of which 11 are considered high-conflict, 7 low-conflict and 7 impersonal. Participants were instructed to read each dilemma and rate whether they found the action to be “appropriate” or not. The high-conflict dilemmas share a similar structure in which responses reflect either a utilitarian or deontological judgement.

“Approve” responses to each of the 3 categories of dilemma were separately tallied for each individual and subjected to a 2group ANOVA. Results revealed the control group produced a significantly higher rate of “appropriate” responses to high-conflict dilemmas than did the individuals with AgCC (F=8.17, p = .006, n2 =.113). However, no significant differences were found among the two groups for results on low (n2 = .013) and impersonal (n2 = .003) dilemmas alone. Furthermore, a X2 analysis of responses to each high conflict dilemma revealed a significant difference in 5 out of the 11 such that more persons with AgCC gave a deontological judgement.

Results suggested that adults with AgCC respond similarly to neurotypical controls with respect to the low conflict or

impersonal dilemmas. However, with respect to high conflict dilemmas, compared to controls they tend to respond in a more deontological than utilitarian basis - that is, based on general principles without contextual nuance. These findings are consistent with the conclusion of Renteria-Vasquez et al. (2021) that persons with AgCC have difficulty imagining the wider implications of present information.

Neurocognitive decline is prevalent in patients with metastatic cancers, attributed to various disease, treatment, and individual factors. Whether the presence of brain metastases (BrMets) contributes to neurocognitive decline is unclear. Aims of this study are to examine neurocognitive performance in BrMets patients and compare findings to patients with advanced metastatic cancer without BrMets. Here, we present baseline findings from an ongoing, prospective longitudinal study.

English-speaking adults with advanced metastatic cancers were recruited from the brain metastases and lung clinics at the Princess Margaret Cancer Centre. Participants completed standardized tests (WTAR, HVLT-R, BVMT-R, COWAT, Trailmaking test, WAIS-IV Digit Span) and questionnaires (FACT-Cog v3, EORTC-QLQ C30 and BN20, PROMIS Depression(8a) and Anxiety(6a)) prior to cranial radiotherapy for those who required it. Test scores were converted to z-scores based on published normative data and averaged to create a composite neurocognitive performance score and domain scores for memory, attention/working memory, processing speed and executive function. Neurocognitive impairment was defined according to International Cancer and Cognition Task Force criteria. Univariate and multivariate regressions were used to identify individual, disease and treatment variables that predict cognitive performance.

76 patients (mean (SD) age: 63.2 (11.7) years; 53% male) with BrMets were included. 61% experienced neurocognitive impairment overall; impairment rates varied across domains (38% memory, 39% executive functioning, 13% attention/working memory, 8% processing speed). BrMets quantity, volume, and location were not associated with neurocognitive performance. Better performance status (ECOG; ß[95%CI];-0.38[-0.70,-0.05], p=0.021), higher premorbid IQ (0.34[0.10,0.58], p=0.005) and greater cognitive concerns (0.02[-3.9e-04,0.04], p=0.051) were associated with better neurocognitive performance in univariate analyses. Only premorbid IQ (0.37[0.14,0.60], p=0.003) and cognitive concerns (0.02[0.0004, 0.03], p=0.05) remained significant in multivariate analysis. We also recruited 31 patients with metastatic non-small cell lung cancer (mNSCLC) with no known BrMets (age: 67.5 (8.3); 32% male) and compared them to the subgroup of BrMets patients in our sample with mNSCLC (N=32; age: 67.8 (11.7); 53% male). We found no differences in impairment rates (BrMets/non-BrMets: Cognitive Composite, 59%/55%; Memory, 31%/32%; Executive Functioning, 35%/29%; Attention/working memory, 16%/13%; Processing speed, 7%/6%; Wilcoxon rank-sum test, all p-value’s > 0.5). The presence or absence of BrMets did not predict neurocognitive performance. Among patients with mNSCLC, higher education (0.11[0.03,0.18], p=0.004) and premorbid IQ (0.36[0.12,0.61], p=0.003), fewer days since primary diagnosis (0.00290[-0.0052,-0.0005], p=0.015) fewer pack-years smoking history (0.01[0.02,-0.001], p=0.027) and greater cognitive concerns (0.02[7e-5,0.04], p=0.045) were associated with better neurocognitive performance in univariate analyses; only premorbid IQ (0.26[0.02,0.51], p=0.04) and cognitive concerns (0.02[0.01,0.04], p=0.02) remained significant in multivariate analysis.

Cognitive impairment is prevalent in patients with advanced metastatic cancers, particularly affecting memory and executive functioning. However, 39% of patients in our sample were not impaired in any domain. We found no associations between the presence of BrMets and neurocognitive function in patients with advanced cancers prior to cranial radiation. Premorbid IQ, a proxy for cognitive reserve, was associated with cognitive outcomes in our sample. Our longitudinal study will allow us to identify risk and resilience factors associated with neurocognitive changes in patients with metastatic cancers to better inform therapeutic interventions in this population.

Many people with HIV (PWH) are at risk for age-related neurodegenerative disorders such as Alzheimer’s disease (AD). Studies on the association between cognition, neuroimaging outcomes, and the Apolipoprotein E4 (APOE4) genotype, which is associated with greater risk of AD, have yielded mixed results in PWH; however, many of these studies have examined a wide age range of PWH and have not examined APOE by race interactions that are observed in HIV-negative older adults. Thus, we examined how APOE status relates to cognition and medial temporal lobe (MTL) structures (implicated in AD pathogenesis) in mid- to older-aged PWH. In exploratory analyses, we also examined race (African American (AA)/Black and non-Hispanic (NH) White) by APOE status interactions on cognition and MTL structures.

The analysis included 88 PWH between the ages of 45 and 68 (mean age=51±5.9 years; 86% male; 51% AA/Black, 38% NH-White, 9% Hispanic/Latinx, 2% other) from the CNS HIV Antiretroviral Therapy Effects Research multi-site study. Participants underwent APOE genotyping, neuropsychological testing, and structural MRI; APOE groups were defined as APOE4+ (at least one APOE4 allele) and APOE4- (no APOE4 alleles). Eighty-nine percent of participants were on antiretroviral therapy, 74% had undetectable plasma HIV RNA (<50 copies/ml), and 25% were APOE4+ (32% AA/Black/15% NH-White). Neuropsychological testing assessed seven domains, and demographically-corrected T-scores were calculated. FreeSurfer 7.1.1 was used to measure MTL structures (hippocampal volume, entorhinal cortex thickness, and parahippocampal thickness) and the effect of scanner was regressed out prior to analyses. Multivariable linear regressions tested the association between APOE status and cognitive and imaging outcomes. Models examining cognition covaried for comorbid conditions and HIV disease characteristics related to global cognition (i.e., AIDS status, lifetime methamphetamine use disorder). Models examining the MTL covaried for age, sex, and

relevant imaging covariates (i.e., intracranial volume or mean cortical thickness).

APOE4+ carriers had worse learning (ß=-0.27, p=.01) and delayed recall (ß=-0.25, p=.02) compared to the APOE4- group, but APOE status was not significantly associated with any other domain (ps>0.24). APOE4+ status was also associated with thinner entorhinal cortex (ß=-0.24, p=.02). APOE status was not significantly associated with hippocampal volume (ß=-0.08, p=0.32) or parahippocampal thickness (ß=-0.18, p=.08). Lastly, race interacted with APOE status such that the negative association between APOE4+ status and cognition was stronger in NH-White PWH as compared to AA/Black PWH in learning, delayed recall, and verbal fluency (ps<0.05). There were no APOE by race interactions for any MTL structures (ps>0.10).

Findings suggest that APOE4 carrier status is associated with worse episodic memory and thinner entorhinal cortex in mid- to older-aged PWH. While APOE4+ groups were small, we found that APOE4 carrier status had a larger association with cognition in NH-White PWH as compared to AA/Black PWH, consistent with studies demonstrating an attenuated effect of APOE4 in older AA/Black HIV-negative older adults. These findings further highlight the importance of recruiting diverse samples and suggest exploring other genetic markers (e.g., ABCA7) that may be more predictive of AD in some races to better understand AD risk in diverse groups of PWH.

A recent review called for a more robust assessment of cannabis use (CU), including amount and timing of recent use to assess neurocognitive effects of CU among people living with HIV (PWH) (Ellis et al., 2021). The current study addresses some issues raised by investigating between group neurocognitive differences among healthy controls and PWH who differ on their cannabis use histories, using strict inclusion criteria, robust classification of CU, and administration of an established neurocognitive test battery.

Among this community sample of adults (N=309), 58 were classified as CU+/HIV+ group (84.5% Male), 76 as CU-/HIV+ (57.9% M), 86 as CU+/HIV- (58.1% M), and 89 as CU-/HIV- (53.9% M). Exclusion criteria included history of past 12-month dependence and extensive lifetime dependence or significant use of illicit substances other than cannabis, severe or current mood or thought disorder, and other medical conditions that adversely impact neurocognitive functioning. Inclusion criteria for CU+ groups included <30-days since last CU, >10 times of CU in last month, 3 times of CU per month in last 12 months, > 1 year of CU, and > 500 times used in lifetime. CU parameters did not statistically differ between HIV+/CU+ and HIV-/CU+. CU- groups’ inclusion criteria required no CU in last 6 months, 196 lifetime number of times used, and no history of CU dependance. Lifetime CU did not statistically differ between CU-/HIV+ and CU-/HIV- groups. HIV+ groups did not differ significantly on HIV viral load in plasma or nadir CD4+ counts. Significant between group differences included age, sex, years of education, and amount of alcohol and nicotine use within 12 months. The aforementioned sociodemographic and substance use variables that differed between groups were covariates in analyses. A battery of 10 neurocognitive measures, two measures per each domain of learning, memory, motor, executive functioning, and processing speed. Global composite summary scores for overall neurocognitive performance were calculated by averaging M T-scores for each neurocognitive domain. Data transformations were used to address any violations of statistical assumptions.

To facilitate data reduction, neurocognitive task scores were standardized to T-scores using the M and SD of the CU-/HIV-group. An omnibus model of between-group comparisons on global neurocognitive task performance revealed no significant differences, F(3) = .16, p = .923. Subsequent Tukey’s post hoc test revealed no significant differences among the four groups. Results also revealed nonsignificant differences between groups in neurocognitive performance within each domain. However, the CU-/HIV- group performed significantly worse than the CU-/HIV+ group on the Executive Functioning domain, based on Tukey’s post hoc test.

We found no significant global neurocognitive differences among groups; however, there was some evidence for domain-specific neurocognitive differences in executive functioning. This contrasts somewhat with existing literature on HIV and cannabis-associated neurocognitive deficits. Several factors may have contributed to this, including our relatively healthy PWH sample. Future analyses will examine interactive effects of HIV severity and severity of CU on neurocognition. This analysis will better determine who, among PWH, are most at-risk for cannabis-associated neurocognitive effects and what factors may exacerbate them.

Due to decades of structural and institutional racism, minoritized individuals in the US are more likely to live in low socioeconomic neighborhoods, which may underlie the observed greater risk for neurocognitive impairment as they age. However, these relationships have not been examined among people aging with HIV. To investigate neurocognitive disparities among middle- and older-aged Latino and non-Latino White people living with HIV (PWH), and whether neighborhood socioeconomic deprivation may partially mediate these relationships.

Participants were 372 adults ages 40-85 living in southern California, including 186 Latinos (94 PWH, 92 without HIV) and 186 non-Latino (NL) Whites (94 PWH, 92 without HIV) age-matched to the Latino group (for the overall cohort: Age M=57.0, SD=9.1, Education: M=12.7, SD=3.9, 38% female; for the group of PWH: 66% AIDS, 88% on antiretroviral therapy [ART]; 98% undetectable plasma RNA [among those on ART]). Participants completed psychiatric and neuromedical evaluations and neuropsychological tests of verbal fluency, learning and memory in person or remotely. Neuropsychological results were converted to demographically-unadjusted global scaled scores for our primary outcome. A neighborhood socioeconomic deprivation variable (SESDep) was generated for census tracts in San Diego County using American Community Survey 2013-2017 data. Principal components analysis was used to create one measure using nine variables comprising educational (% with high school diploma), occupational (% unemployed), economic (rent to income ratio, % in poverty, (% female-headed households with dependent children, % with no car, % on public assistance), and housing (% rented housing, % crowded rooms) factors. Census tract SESDep values were averaged for a 1km radius buffer around participants’ home addresses.

Univariable analyses (independent samples t-tests and Chi-square tests) indicated Latinos were more likely to be female and had fewer years of formal education than NL-Whites (ps<.05). Latino PWH had higher nadir CD4 than White PWH (p=.02). Separate multivariable regression models in the overall sample, controlling for demographics and HIV status, showed Latinos had significantly lower global scaled scores than Whites (b=-0.59; 95%CI-1.13, -0.06; p=.03) and lived in more deprived neighborhoods (b=0.62; 95%CI=0.36, 0.88; p<.001). More SES deprivation was significant associated with worse global neurocognition in an unadjusted linear regression (b=-0.55; 95%CI=-0.82, -0.28; p<.001), but similar analyses controlling for demographics and HIV status, showed SESDep was not significantly related to global scaled scores (b=-0.11; 95%CI= -0.36, 0.14; p=.40). Exploratory analyses examined primary language (i.e., English vs Spanish) as a marker of Hispanic heterogeneity and its association with neurocognition and SESDep. Controlling for demographics and HIV status, both English-speaking (b=0.33; 95%CI=0.01. 0.64; p=.04) and Spanish-speaking Latinos (b=0.88; 95%CI=0.58, 1.18; p<.001) lived in significantly greater SESDep neighborhoods than Whites, with SESDep greater for Spanish-speakers than English-speakers (p<.001). However, only English-speaking Latinos had significantly lower neurocognition than Whites (b=-0.91; 95%CI=0-1.57, -0.26; p<.01; Spanish-speakers: b=-0.27; 95%CI=-0.93, 0.38; p=.41).

Among our sample of diverse older adults living with and without HIV, English-speaking Latinos showed worse neurocognition than Whites. Though SES neighborhood deprivation was worse among Latinos (particularly Spanish-speakers) it was not associated with neurocognitive scores after adjusting for demographics. Further studies investigating other neighborhood characteristics and more nuanced markers of Hispanic heterogeneity (e.g., acculturation) are warranted to understand factors underlying aging and HIV-related neurocognitive disparities among diverse older adults.