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.

Multiple sclerosis (MS), an inflammatory autoimmune disease of the central nervous system, is characterized by damage to white matter via myelin degeneration with resulting sclerotic plaques and lesions. Upwards of 70% of people with MS show cognitive changes in multiple domains including verbal memory. Advances in disease-modifying therapies have increased the expected lifespan of people with MS, making aging with MS a critical emerging area of study. Memory declines during normal aging, yet the specific impact of MS on verbal memory in aging is inconclusive and understudied. To address this gap in knowledge, we examined whether MS was associated with verbal learning slope, total learning, delayed recall, and recognition performance in older adults. We further explored whether MS disease severity influenced these memory operations.

Participants included two cohorts: older adults with MS recruited from MS centers and patient registries, and healthy controls recruited from the community. A total of 164 adults age 60 and older without dementia were included in the current study, 79 in the MS group (mean age = 65.05 + 4.72; %female = 62) and 85 in the control group (mean age = 69.53 + 6.65; %female = 65.9). All participants were administered a neuropsychological battery including the Hopkins Verbal Learning Test-Revised (HVLT-R). The Patient Determined Disease Steps (PDDS), a patient-rated score of disability severity in MS comprised of eight steps related to walking ability, was used to operationalize MS severity. Using a median split, the PDDS was dichotomized into low (PDDS = 0-2) versus high (PDDS = 3-5) MS severity groups. Linear regression models were run to examine the effect of group (MS vs. control) and disease severity (PDDS) on four operations from the HVLT-R: learning slope, total learning, delayed recall, and recognition. Statistical analyses adjusted for age, years of education, and sex.

Linear regression models revealed that older adults with MS showed lower total learning compared to healthy controls (β = -.18, p = .03). Learning slope, delayed recall, and recognition did not differ by group (p > .05). Compared to healthy controls, older adults with high MS severity performed worse on total learning (β = -.21; p = .01) and delayed recall (β = -.18; p = .03). Group differences on learning slope and recognition were not significant (p > .05).

The presence of MS was associated with worse total learning. Moreover, high severity of MS was associated with worse total learning and delayed recall in older adults. These results delineate the influence of MS on specific memory operations and emphasize the potential utility of disease severity on cognitive performance in aging.

Risk factors that contribute to brain pathology and cognitive decline among older adults include demographic factors (e.g., age, educational attainment), genetic factors, health factors, and depression (Plassman et al., 2010). Variability within an individual’s performance across cognitive tasks is referred to as dispersion (Hultsch et al., 2002), which appears sensitive to subtle cognitive impairments associated with neurodegenerative pathology in older adults (Bangen et al., 2019; Kälin et al., 2014). Thaler and colleagues (2015) found that dispersion across domains of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was a useful indicator of cognitive changes associated with cardiovascular disease and mortality. Also, research by Manning and colleagues (2021) found that elevated ratings of depression and anxiety in older adults was associated with greater dispersion across neuropsychological testing. The present study aimed to replicate findings that greater dispersion in neuropsychological performance is associated with impaired neurocognitive performance and greater self-reported depression among older adults who present for neuropsychological evaluation with cognitive concerns.

Neuropsychological testing data was obtained from a university hospital. Chart reviews were conducted on 369 participants who met initial criteria (60 years or older with testing data from the RBANS Form A, Wechsler Test of Adult Reading, and Geriatric Depression Scale [GDS]). Retrospective analyses were conducted on a final sample of 293 participants from 60 to 94 years old (Mage = 74.41, SDage = 7.43; 179 females, 114 males). Diagnoses were used for group comparisons between cognitively intact individuals with subjective cognitive complaints (SCC, n = 49), persons with Mild Neurocognitive Disorder (mND, n =137), and persons with Major Neurocognitive Disorder (MND, n = 107).

As expected, results indicated that higher dispersion was related to lower Total RBANS Scores (r = -0.54, p < .001) and significant differences across diagnostic groupings (F(2, 289) = 29.19, p < 0.001; SCC, mND, MND) indicated that variability in performance was an indicator of greater neurocognitive impairment. Contrary to expectations, greater dispersion was very weakly associated with lower reported depressive symptomatology (r = -0.13, p = 0.03). A three-stage hierarchical linear regression was conducted with the RBANS Coefficient of Variation (CoV) as the dependent variable and three predictor variables (Age, Total RBANS, Total GDS). The regression analysis results indicated that age was not a significant predictor, but both Total RBANS and GDS Scores were. The most important predictor was Total RBANS Scores which uniquely explained 21% of the variation in dispersion.

This study adds to the current literature regarding the clinical utility of dispersion in neuropsychological performance as an indicator of early and subtle neurocognitive impairment. Depressive symptom reporting was expected to help predict the degree of variability, but this factor was only weakly associated with the RBANS CoV.

Limitations of this study include its retrospective use of archival data and the restricted range on some variables of interest. Further research is needed to examine the relative utility of different measures of dispersion and why increased cognitive performance variability is related to neurocognitive impairment and decline.

Cognitive sequelae are reported in 20-25% of patients following SARS-CoV-2 infection. It remains unclear whether post-infection sequelae cluster into a uniform cognitive syndrome. In this cohort study, we characterized post-COVID neuropsychological outcome clusters, identified factors associated with cluster membership, and examined 6-month recovery trajectories by cluster.

The Mayo Clinic Institutional Review Board approved study protocols. Informed consent was obtained from all participants. Participants (> 18 years old) were recruited from a hospital-wide registry of Mayo Clinic Florida patients who tested positive for SARS-CoV-2 infection from July 2020 to Feb 2022. We abstracted participant health history and COVID-19 disease severity (NIAID score) from the electronic health record and retrieved Area Deprivation Index (ADI) scores as a measure of neighborhood socioeconomic disadvantage. We assessed objective cognitive performance with the CNS Vital-Signs (CNSVS) and subjective neuropsychological symptoms with the Neuropsych Questionnaire-45 (NPQ-45). Results were used as input features in a K-means clustering analysis to derive neurophenotypes. Chi-square and analysis of variance (AnOvA) tests were used to identify clinical and sociodemographic factors associated with cluster membership. Participants repeated the CNS Vital Signs, NPQ-45, as well as the Medical Outcomes Survey (MOS SF-36) and a posttraumatic stress disorder (PTSD) checklist (PCL-C 17) 6 months following initial testing. Repeated-measures ANOVA was used to assess change in neurocognitive performance over time by cluster. Significance was set at P < 0.05.

Our cohort consisted of 205 participants (171 ambulatory, 34 hospitalized) who completed post-acute outcome assessment a mean of 5.7 (± 3.8) weeks following testing positive for SARS-CoV-2. K-means clustering with elbow method fitting identified three subgroups (see figure). The first cluster (N = 31) is characterized by executive dysfunction, greater socioeconomic disadvantage, and higher rates of obesity. The second cluster (N = 32) is characterized by memory and speed impairment, higher COVID severity, prevalent anosmia (70%), and greater severity of memory complaints, depression, anxiety, and fatigue. The third and largest cluster (N = 142) is absent cognitive impairment. Approximately 39% of participants completed the 6-month outcome assessment (N=79). Regardless of cluster membership, verbal memory, psychomotor speed, and reaction time scores improved over time. Regardless of timepoint, cluster 1 (dysexecutive) showed lower scores on cognitive flexibility and complex attention and cluster 2 (memory-speed impaired) showed lower scores on verbal memory, psychomotor speed, and reaction time. Modeling of cluster by timepoint interactions showed a steeper slope of improvement in complex attention and cognitive flexibility in cluster 1 (dysexecutive). Cluster 3 (normal) showed significant improvement in fatigue while cluster 2 (memory-speed impaired) continued to report moderate-severe fatigue, worse medical outcomes, and higher PTSD symptom severity scores at six months.

Most participants were cognitively normal or experienced cognitive recovery following SARS-CoV-2 infection. The 25-30% of participants who showed cognitive impairment cluster into two different neurophenotypes. The dysexecutive phenotype was associated with socioeconomic factors and medical comorbidities that are non-specific to COVID-19, while the amnestic phenotype was associated with COVID-19 severity and anosmia. These results suggest that cognitive sequelae following SARS-CoV-2 infection are not uniform. Deficits may be influenced by distinct patient- and disease-specific factors, necessitating differentiated treatment approaches.

Research examining dietary fat in relation to physical and cognitive health is mixed. Generally, it has been hypothesized that polyunsaturated fatty acids (PUFAs) have vascular, anti-inflammatory, and neuroprotective effects1,2,3. Monounsaturated fatty acids (MUFAs) commonly occur with saturated fatty acids (SFA) in certain foods, and some research suggests that consumption is associated with increased vascular risk4; however, there is limited research examining combined MUFAs and SFAs consumption from traditional Western diet foods (e.g., pizza, desserts) compared to animal (e.g., butter, cow milk, salmon) and plant products (e.g., coconut oil, cocoa butter). Furthermore, much of the research examining dietary components/supplementation and cognition is in older adult or at-risk samples, with limited research examining the relationships among middle-aged and cognitively unimpaired adults. We present preliminary data from an ongoing pilot study.

39 middle-aged (40-65 years, inclusive) cognitively unimpaired individuals were recruited from the community. The Food Frequency Questionnaire (Short-Form; SF-FFQ) was used to calculate diet components and servings during a “typical week.” Attention and working memory were measured using trial one of the California Verbal Learning Test - Third Edition (CVLT-III), Oral Trail Making Test Part B, Number Span (forward and backward), Stroop Color and Color-Word trials. Genetic and other plasma-based data for 25 participants have also been obtained, and analysis is in progress; we plan to analyze these additional components in greater detail once we have achieved our target sample size.

Nonparametric correlation analyses revealed no significant relationships between total dietary fat (as measured by the SF-FFQ) and cognitive performance, which included CVLT Trial 1 (r = .28, p = .09), Oral Trail Making Test Part B (r = .02, p = .89), Number Span Forward (r = .18, p = .27) and Number Span Backward (r = -.04, p = .83), Stroop Color trial (r = -.10, p = .56), and Stroop Color-Word trial (r = -.09, p = .58). Notably, however, data is continuing to be collected and these relationships will be examined further with additional data.

While total fat consumption was expected to be associated with attention and working memory measures, correlations revealed nonsignificant relationships. Notably, there are important limitations to consider, as other expected relationships based on previous research findings/theoretical relationships (e.g., positive correlation between waist-to-hip ratio and fat consumption) were lacking. A primary limitations of this study included a small sample size of cognitive and physically healthy middle-aged adults. Regardless, these relationships should be explored further with a greater and more diverse sample size.

Onset of Alzheimer’s disease (AD) pathology is estimated to begin 20-30 years prior to clinical symptom onset. Resting state EEG may yield useful early biomarkers of pathology, but its use along the AD clinical continuum is still limited, especially in individuals who are at high risk for AD but have yet to show symptoms. EEG waveform oscillations are classified based by frequency range (alpha, beta, theta, delta). Changes within these frequency bands have been identified in individuals with AD-dementia as compared to those with MCI and normal aging. Typical changes involve increases in low frequency power bands of delta and theta and decreases in beta and alpha frequencies, particularly in more posterior brain regions. However, these methods have yet to be explored in cognitively normal individuals who are at high risk for AD, as work has shown between individuals with MCI and healthy older adults.

We compared differences in resting state EEG between older adults (age 60+) at high risk for AD (positive family history, genetic risk defined as carrying 1 + ApoE ε4 alleles) and individuals at low risk (negative family history, no ε4 allele). We collected 1) neuropsychological test performance; 2) self-report measures of subjective cognitive complaints and cognitive reserve; and 3) five minutes of eyes-open resting state EEG using 64-channel active electrodes. Clusters of three electrodes were average for regions and absolute power within 5 frequency bands was calculated. Theta/beta ratio was calculated by dividing absolute power of bands at its respective site. Correlations between absolute power for specific regions, self-report measures, and neuropsychological test scores.

Analysis of 20 individuals collected to date (14 high risk, 6 low risk) found associations (p<0.05) between risk group and beta and gamma power across multiple electrode clusters, with high-risk individuals having higher power. Significant correlations were also found between calculated measures of cognitive reserve and posterior theta/beta ratio, subjective cognitive complaints and beta power, and neuropsychological test composites of learning performance with delta and executive functioning with frontal theta power.

This work provides preliminary evidence for differences in resting state EEG activity in those at risk for AD, prior to onset of clinical symptoms. Future work will examine patients with mild cognitive impairment as a comparison group to characterize resting state EEG across the early AD continuum.

Cognitive change affecting patients after anesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterward. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. This study aimed to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anesthesia and surgery.

A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions. Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anesthesia and surgery and may be useful for the inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature.

The working group recommends that 'perioperative neurocognitive disorders (PND)' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of the acute event (postoperative delirium) and cognitive and functional decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery (dNCR)) and up to 12 months (postoperative neurocognitive disorder (postoperative NCD).1 Further, the working group has undergone a further Delphi process to expand these recommendations for research purposes which will also be covered.

Perioperative neurocognitive disorders are the most common complication for patients aged 65y or more undergoing anesthesia and surgery. Moreover, they are associated with significant morbidity, mortality, loss of functional independence and extreme economic costs. A multi-disciplinary approach to PND, including neuropsychologists, is critical to reducing and preventing these disorders. Evered L, Silbert B, Knopman DS, et al. Recommendations for the nomenclature of cognitive change associated with anaesthesia and surgery-2018. Br J Anaesth 2018; 121: 1005-12

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

Researchers are increasingly finding that the presence of neuronal surface antibodies (NSAb) may account for a larger percentage of outpatient epilepsy cases than previously thought (Elisak et al., 2018; Brenner et al., 2013). However, systematic NSAb screening is not included in standard epilepsy care (Kambadja et al., 2022). The Montreal Cognitive Assessment (MoCA; Nasreddine, 2005) is one of the most commonly used screening tools among physicians (Judge et al., 2019) across various neurological conditions, and has previously been validated in populations with autoimmune encephalitis (Hebert et al., 2018). Because patients with NSAb associated epilepsy often present with cognitive dysfunction (Greco et al., 2006), a MoCA is often administered as part of standard clinical care. The present analysis compared MoCA performance profiles in epilepsy patients with and without the presence of serum NSAbs. We explored what specific cognitive profile, as defined by the MoCA, may predict NSAb positivity.

Forty-eight epilepsy patients were enrolled through an outpatient epilepsy clinic or during non-intensive or elective hospital stays. Participants were eligible if they met one of three diagnostic categories: focal epilepsy of unknown cause (n = 33), lesional focal epilepsy (n = 5), or generalized epilepsy (n = 4). All participants signed consent, underwent a comprehensive interview, which included MoCA testing, and serum NSAb testing paralleling standard clinical practice. Mann-U Whitney tests were run to compare overall MoCA and subgroup domain performance between groups.

Six patients (13%), all with focal epilepsy of unknown cause, had positive NSAb panels (LGI1: n = 3; GAD65: n = 2; CASPR2: n = 1). There was no significant difference in overall MoCA scores between participants with focal epilepsy of unknown cause who were antibody positive versus negative, and antibody positive versus antibody negative lesional or generalized epilepsy. However, when analyzing by MoCA subgroup, we found that antibody positive patients performed significantly worse on delayed recall than antibody negative patients with focal epilepsy of unknown cause (Mdn = 1.5 vs 3), U(Nantibodynegative=27, Nantibodypositive=6) = 69.00, p = .02. There was no significant difference in other MoCA cognitive domain tests, and delayed recall scores did not significantly differ between antibody positive patients and those with lesional focal and generalized epilepsy.

These preliminary findings suggest that episodic memory impairment, as measured by delayed recall on the MoCA, may predict NSAb antibody positivity among patients with focal epilepsy of unknown cause. This may relate to specific predilection of the hippocampal regions in antibody-mediated epileptogenesis and pathology.

The Texas Functional Living Scale (TFLS) is a measure of adaptive functioning commonly utilized across the geriatric population. Current research suggests that those with Alzheimer’s disease and other dementias perform poorly on the TFLS, compared to those with mild cognitive impairment (MCI) and normal cognition (Cullum et al., 2001). Additional research is needed to examine the influence anxiety and depressive symptoms have on activities of daily living (ADLS) in individuals being evaluated for memory disorders. This study will examine the effects of anxiety and depression on adaptive functioning across all patients, and within samples of those with dementia and MCI. It is hypothesized that higher reported anxiety and depressive symptoms will predict lower scores of ADLS.

Patients at a memory disorder clinic (N = 756; 58.2% female) were screened for cognitive impairment using the Montreal Cognitive Assessment (MoCA). A brief neuropsychological evaluation (BNE) was then conducted in which the TFLS, Geriatric Depression Scale (GDS), and Geriatric Anxiety Inventory (GAI) were administered, among other measures.

A stepwise hierarchical regression was conducted on the entire sample to examine the effects of anxiety and depressive symptoms on TFLS performance, controlling for cognitive impairment using the MoCA. Lower MoCA scores explained a significant amount of variance in TFLS performance (R2 = 0.456, F(1, 754) = 632.78, p < .001). MoCA scores (b = 1.27, p < .001), the GAI (b = 0.14, p = .019), and the GDS (b = 0.10, p = 0.039) were significant predictors of poor TFLS performance across the entire sample. Although the MoCA, GDS, and GAI were each significant predictors of the TFLS, the increased variance explained by the GDS and GAI individually was incremental (AR2 = 0.003, F(1, 752) = 3.90, p = .049). Stepwise hierarchical regressions were also conducted on subsamples diagnosed with MCI (N = 171) and dementia (N = 394). For those with MCI, MoCA scores explained a significant amount of variance in TFLS performance (R2 = 0.044, F(1, 169) = 7.80, p = .006). Neither the GAI nor GDS explained significant additional variance. Only MoCA scores (b = .30, p =.006) predicted TFLS performance. For those with dementia, MoCA scores explained significant variance in TFLS scores (R2 = 0.338, F(1, 392) = 200.47, p < .001). The GAI explained additional significant variance when added (AR2 = 0.009, F(1, 391) = 5.26, p = .022). The GDS did not explain any additional variance. Both the MoCA (b = 1.29, p < .001) and the GAI (b = -0.15, p = .002) significantly predicted TFLS performance.

While results suggest that anxiety and depressive symptoms alone do not explain a significant degree of variance within scores of adaptive functioning across the entire sample, elevated ratings of anxiety and depressive symptoms were significant predictors of lower scores of ADLS, suggesting some support for our hypothesis. Additionally, anxiety symptoms significantly explained increased variance in TFLS scores for those diagnosed with dementia, suggesting a potential relationship between anxiety levels and poor adaptive functioning for dementia patients.

Memory impairment is a common comorbidity in individuals with temporal lobe epilepsy (TLE). Further, in medication-resistant epilepsy the frontline option, neurosurgical epileptogenic zone destruction, places memory at significant risk. Research has highlighted that TLE causes whole-brain network efficiency disruption, but it is not established how this may explain pre- and post-surgical cognition. Here we examine whether white matter structural network organization predicts pre-operative memory function and/or risk for post-operative memory decline.

Patients with drug-resistant TLE were recruited from two epilepsy centers in a prospective longitudinal study. The pre-operative sample included 51 individuals with left TLE (L-TLE), 52 with right TLE (R-TLE), and 57 healthy controls who underwent T1- and diffusion-weighted MRI (dMRI), and neuropsychological tests of verbal and visual memory. Forty-four patients (n=21 L-TLE) subsequently underwent temporal lobe surgery (36 anterior temporal lobectomy; 7 stereotactic laser amygdalohippocampectomy; 1 amygdalohippocampectomy) and completed post-operative memory testing. Whole-brain connectomes were generated via diffusion tractography and analyzed using graph theory, focusing on network integration (path length) and specialization (transitivity). In the preoperative dataset, first we compared TLE versus controls with analysis of covariance (ANCOVAs) controlling for age. Next, linear regressions examined the association between memory scores and network efficiency between L-TLE, R-TLE and controls. In the post-operative sample, bivariate correlations examined the association between pre- to post-operative memory change and 1) global network efficiency and 2) asymmetry of mesial temporal efficiency (i.e., local efficiency of the hippocampal, parahippocampal, and entorhinal nodes). Finally, efficiency metrics were entered into stepwise regressions along with established predictors of memory decline.

Compared to controls, TLE showed longer path length (p < .05; ηp2 = .03) and lower transitivity (p = .01; ηp2 = .04). Pre-operatively, better verbal learning and memory were associated with both shorter path length (β = -0.23 to -0.32; psadjusted < .05) and increased transitivity (β = 0.20 to 0.31; psadjusted < .05). These associations were greater in L-TLE than R-TLE (i.e., a significant interaction; β = -0.29 to 0.25; psadjusted <.05). Post-operatively, global metrics predicted decline on list learning for LTLEs (rs = -.57 to .58; ps < .01), and were marginal on list recall (rs = -.42 to .40; ps < .10). Leftward asymmetry of mesial temporal local efficiency predicted greater decline across most verbal memory measures for L-TLE (rs -.47 to -59; psadjusted <.05), but not R-TLE. Asymmetry of mesial network efficiency uniquely explained at least 20 to 43% of the variance in list learning, recall, and story learning for L-TLE, outperforming hippocampal asymmetry and preoperative score (psadjusted <.05).

Our findings suggest that global white matter network abnormalities contribute to verbal memory impairment pre-operatively and vulnerability to decline post-operatively in L-TLE. Asymmetry of a predefined mesial temporal sub-network may help predict post-operative memory function following left temporal lobe surgery, such that greater efficiency in the to-beresected mesial temporal network may be an important risk factor for decline. Our findings extend the importance of network approaches in TLE to include the relationships between neurobiological networks and memory function.

Studies on vulnerability to interference have shown promise in distinguishing between normal and pathological aging, such as the early stage of Alzheimer’s disease (AD) or amnestic Mild Cognitive Impairment (aMCI). However, these studies did not include a non-semantic condition essential in distinguishing between what is attributable specifically to semantic memory impairments and more generalized vulnerability to interference. The present study aimed to determine whether the increased vulnerability to semantic interference previously observed in individuals at increased risk of AD (aMCI) is specifically associated with the semantic nature of the material, or if it also affects other types of material, suggesting more generalized executive and inhibitory impairment.

Seventy-two participants (N = 72) divided into two groups (33 aMCI and 39 NC) matched for age and education were included in the study. They underwent a comprehensive neuropsychological examination, and took the adapted French version of the LASSI-L (semantic interference test), as well as a homologous experimental phonemic test, the TIP-A. Independent sample t-tests, mixed ANOVA and ANCOVA on memory and vulnerability to interference scores with the Group (NC, aMCI) as between-group factor and the Type of material (semantic, phonemic) as within-subject factor were conducted to compare memory and interference in both contexts for both groups.

For all memory scores, results revealed a significant main effect of group (NC > aMCI), a significant main effect of the type of material (semantic > phonemic) and a significant Group x Type interaction (disproportionately poorer performance in a semantic context for aMCI compared to NC). Word recognition was equivalent in both contexts for aMCI, whereas NC were better in a semantic context. aMCI also committed more phonemic false recognition errors, were disproportionately more vulnerable to retroactive semantic interference and showed a disproportionately higher percentage of intrusion errors associated with proactive semantic interference than NC.

To our knowledge, this is the first study to meticulously compare aMCI and elderly control vulnerability to inter-list interference and its impact on memory processes in two very similarly designed conditions using different types of material (semantic vs. phonemic). Indeed, many studies on interference focused solely on intra-list buildup of interference or on semantic material. Taken together, our results suggest that aMCI patients present generalized difficulties in source memory and inhibition, but that their inability to benefit normally from the depth of processing of semantic material results in even more semantic intrusion errors during proactive interference. This superficial semantic processing also significantly impacts the ability of aMCI to show good recall after being exposed to an interference list and the passage of time, resulting in a greater vulnerability to semantic retroactive interference than controls. In summary, our results suggest that impairment of semantic memory, and, more precisely, the loss of benefit from the depth of semantic processing, represents the cornerstone of their memory and vulnerability to interference patterns. The classical level of processing theory therefore constitutes an ideal, simple framework to predict aMCI patients’ performance when facing interference, a parallel too rarely addressed in the literature.

The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.

Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

Korsakoff’s syndrome (KS) is a neuropsychiatric disorder, caused by malnutrition. Central to KS are severe amnesia and executive dysfunctions. KS patients often fail to remember future intentions (prospective memory),and rely heavily on external support by caregivers. Recently, specialized smartwatches have been developed to support prospective memory verbally and by displaying pictures of future events. We investigated the benefit of a smartwatch and smartphone compared to no aid in supporting time accuracy and the ability to carry out future intentions in one case study. In three subsequent case studies, we investigated the possible benefits of a smartwatch aid for prospective memory (PM) compared to verbal in-person reminders.

In the first case study, one high-functioning KS patient with a WAIS IQ of 127 points, performed a total of 36 novel prospective memory tasks in three conditions (smartwatch, smartphone and no-aid).

In the second case series, three KS patients with average IQ performed 30 everyday PM tasks in two conditions (smartwatch, in-person).

Two dependent variables were indexed in both studies: PM time accuracy (in minutes), this was calculated as minutes difference from the assigned time, and precision of the PM task (correct or incorrect).

In the first study, time accuracy was improved with a smartwatch compared to a smartphone and no-aid condition. Furthermore, the smartwatch and smartphone conditions were more effective than no aid in assisting memory for task content. In the second study, both the smartwatch and in-person instructions were equally effective in supporting prospective memory tasks.

Since prospective memory is compromised in KS, patients require assistance throughout the day in performing everyday and non-everyday tasks. The results of our case studies suggest that a smartwatch that gives specific verbal and visual reminders can be particularly helpful in supporting prospective memory for KS patients. Giving in-person instructions was equally effective as the use of this smartwatch, highlighting the possibility to support KS patients with less intensive everyday coaching. Together, these results are promising in applying smartwatches clinically to support prospective memory.

Visual deficits are common after stroke and are powerful predictors for the chronic functional outcome. However, while basic visual field and recognition deficits are relatively easy to assess with standardized methods, selective deficits in visual primitives, such as shape or motion, are harder to identify, as they often require a symmetrical bilateral posterior lesion in order to provoke full field deficits. We aimed to investigate the prevalence and co-occurrence of hemifield “mid-range” visual deficits. In addition, we looked at the repercussions of these mid-range deficits on higher-order visual cognitive functions, such as visuoconstruction and memory. At a more theoretical level, we investigated whether associations between deficits in 'mid-range’ visual functions and deficits in higher-order visual cognitive functions are in line with a hierarchical, two-pathway model of the visual brain.

In 220 stroke patients and a healthy control group (N=49), we assessed the perception of colour (isoluminant stimuli in the red-green range), shape (Efron shapes), location (dot in a circle), orientation (lines at different angles), contrast (bars with converging grey-level differences), texture (from Brodatz grayscale texture album) and correlated motion (different percentages of dots moving in the same direction). All tasks started with a fixation dot presented at the centre of the screen. After one second, a target stimulus was presented on the horizontal midline at either 5° to the left or at 5° to the right side of the fixation. Then, after 1.5 seconds, two response items appeared in addition to the target stimulus for three seconds. To control for eye movements, we used an eye-tracker to present the target in a gaze contingent fashion. Thus, the target always remained in the correct retinal position independent of eye movements. In a subset of 182 ischemic stroke patients, we also assessed visuoconstruction (Copy Rey-Complex Figure Test), visual emotion recognition (FEEST test) and visual memory (Doors-test).

The results showed that deficits in motion-perception were most prevalent (26%), followed by colour (22%), texture (22%), location (21%), orientation (18%), contrast (14%), shape (14%) and glossiness (13%). 63% of the stroke patients showed one or more mid-range visual deficits. Overlap of deficits was small; they mostly occurred in isolation or co-occurred with only one or two other deficits. Impairments in mid-range visual functions could not predict performance on higher-order visual cognitive tasks. Impaired visuoconstruction and visual memory were only modestly predicted by a worse location perception. Impaired emotion perception was modestly predicted by a worse orientation perception. In addition, double dissociations were found: there were patients with selective deficits in 'mid-range’ visual functions without higher-order visual deficits and vice versa.

First, deficits in “mid-range” visual functions are very prevalent. Since we found no strong patterns of co-occurrences, we suggest that an assessment of deficits at this level of visual processing requires screening the full range of visual functions. Second, the relationship between mid-range visual tasks and higher-order visual cognitive tasks is weak. Finally, our findings are not supportive of the hierarchical, two-pathway model but more in line with an alternative patchwork model.

To determine if the degree of split between phonemic verbal fluency and semantic verbal fluency at initial visit is predictive of decline in memory performance between initial evaluation and follow-up.

Data from a retrospective multidisciplinary memory clinic database at Spectrum Health was utilized. We examined data from 90 participants who had both an initial and follow-up evaluation completed (initial age = 77.1±4.7 years, follow-up age = 78.4±4.7 years, education = 13.9±3.1 years, race = 91% White, 7% Black, & 2% Hispanic, sex = 61% female, time between evaluations = 15.2±9.9 months). Patients who returned for follow-up did not meet criteria for dementia at time one. Split between phonemic and semantic fluency, termed the semantic-phonological delta (SPD) was measured at the initial evaluation by subtracting the Controlled Oral Word Association Test (COWAT; FAS) T-score from the Animal Naming Test (ANT) T-score. Change in memory score was defined in two ways: 1) subtracting the follow-up evaluation Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) List Recognition Score (RBANS percentiles were converted to a scaled score) from the initial evaluation List Recognition Score (List Recognition Delta), and 2) computing the difference in the RBANS Delayed Memory Index Standard Score between the initial evaluation and the follow-up evaluation (RBANS Memory Delta).

Average semantic fluency T scores were (M = 40.3, SD = 12.3) and phonemic fluency T scores were (M = 42.7, SD = 10.3) at initial evaluation. Bivariate correlations were used to determine the relationship between the clinical variables. SPD was significantly correlated with List Recognition Delta, r(88) = .23, p = .026, with greater discrepancies in verbal fluency scores associated with higher level of decline in List Recognition at follow-up. By comparison, Semantic Fluency performance itself at initial evaluation was not significantly correlated with List Recognition Delta, r(88) = .17, p = .097. The correlation between SPD and the RBANS Memory Delta was also not significant, r(88) = .14, p = .166. At follow-up evaluation, 39% of the sample received a diagnosis of Alzheimer’s disease. Of those diagnosed with Alzheimer’s disease, 66% had a negative SPD split at time one, performing worse on semantic fluency compared to phonemic fluency.

SPD is a better predictor of decline in RBANS List Recognition performance between evaluations than semantic fluency alone, with a larger negative SPD score (worse semantic fluency performance compared to phonemic fluency) at initial evaluation predicting decline in List Recognition performance at follow-up evaluation. SPD at initial evaluation was not significantly correlated with change in RBANS Delayed Memory Index score between evaluations. This may be because there are some patients who are similarly impaired in both semantic and phonemic verbal fluency at initial evaluation who later demonstrate progressive decline in memory retrieval due to hippocampal-sparing etiologies (e.g., vascular dementia). Overall, these findings are consistent with previous work suggesting that declines in the semantic memory system precede declines in episodic memory retention in conditions such as Alzheimer’s disease.

The International Classification of Cognitive Disorder in Epilepsy (IC-CoDE) is a new consensus-based taxonomy that classifies patients into one of four cognitive phenotypes (i.e., cognitively intact, single-domain impairment, bi-domain impairment, generalized impairment). The IC-CoDE has been effectively applied to patients with temporal lobe epilepsy (TLE), but little is known about the relationship between pre-operative cognitive phenotype and post-operative cognitive outcome following epilepsy surgery. The purpose of this study was to examine whether the IC-CoDE classifications are related to memory decline following surgery for TLE.

347 patients (ages 16-66; 57% female) with pharmacoresistant TLE completed comprehensive pre- and post-surgical neuropsychological assessments. Patients were classified into IC-CoDE phenotypes based on pre-surgical pattern of cognitive impairment using a threshold of >1.5 standard deviations (SD) below the normative mean. Change scores were calculated from delay trial scores of the following memory tests: Rey Auditory Verbal Learning Test (RAVLT), and Logical Memory (LM) and Verbal Paired Associates (VPA) subtests from the Wechsler Memory Scale - Third Edition (WMS-III). Cutoffs were applied using epilepsy-specific reliable change indices and patients were classified within the ‘decline’ group if they experienced significant decline on any of the three memory measures.

The distribution of IC-CoDE phenotypes in our sample were as follows: 57% intact, 29% single-domain, 10% bi-domain, and 5% generalized impairment. 108 patients (31%) demonstrated post-surgical memory decline. Patients who underwent dominant temporal lobectomy were more likely to show post-surgical memory decline compared to non-dominant temporal lobectomy. However, there was no significant difference in phenotype distribution between patients who underwent left versus right-sided resections; thus, analyses were conducted on the entire sample to increase power. Chi-square analyses revealed unique patterns of post-surgical memory decline across phenotypes, X2 = 8.79, p = .032. There was a significantly higher proportion of patients with memory decline in the single-domain phenotype (39%) and this was followed by the bi-domain phenotype (33%) and the intact phenotype (29%). In contrast, patients with generalized impairment were unlikely to show memory decline (.06%). Within the single domain impaired phenotype, there were no differences between the specific domains impaired and memory decline. Logistic regression model was also significant; after controlling for surgery side, the IC-CoDE phenotypes significantly predicted the likelihood of a patient experiencing post-surgical memory decline; X2 = 8.18, p = .043.

In addition to the IC-CoDE providing a useful cognitive classification scheme in epilepsy, the IC-CoDE phenotypes appear helpful in identifying those at risk for post-operative memory decline. Previous literature has suggested that those with better pre-surgical cognition are generally at highest risk for cognitive decline. Our results generally follow this trend, but interestingly, patients with single domain impairment were at the highest risk of memory decline, even above those in the cognitively intact group. Future studies are important to confirm this pattern in other samples and examine additional contributing factors and underlying mechanisms that may influence risk of memory decline across these cognitive phenotypes.

Over 80% of hospitalized COVID-19 patients have neurological symptoms, including memory loss, attention difficulties, and trouble thinking clearly that can last for months. The long-term neurological impact of the SARS-CoV-2 virus is unknown and it remains to be seen whether it would create a surge in cases of dementia and cognitive decline years later, which is already a global public health challenge. Examining the cognitive effects of the virus will help with understanding its impact on the brain and inform treatment options. The goal of the present study was to examine cognitive performance among those who have had COVID-19 via mobile-based assessments using smartphone-based cognitive tests. Participants with a previous COVID-19 diagnosis (COVID+) were expected to have worse cognitive performance at baseline than those without COVID-19 (COVID-).

Participants (n=23) with self-reported positive or negative COVID-19 statuses based on polymerase chain reaction or antigen testing were recruited from the Boston area. Inclusion criteria included access to a smartphone with an Android or iOS operation

system and to internet connectivity, along with proficiency in English. Cognitive performance was measured using Defense Automated Neurobehavioral Assessment (DANA) from AnthroTronix. Welch’s 2-sample t-test was used to compare cognitive performance among those with and without COVID-19.

The sample was comprised primarily of COVID+ (59%), female (59%), and Caucasian (50%) participants that were generally well educated (77% with a bachelor’s degree), and had >1 COVID vaccination (95%). About 50% of the sample reported symptoms of depression and mild anxiety. Results were not indicative of significant differences between COVID+ and COVID- groups at baseline: Simple Reaction Time (Immediate; M = 5.62; p = 0.81), Code Substitution (M = 1.25; p = 0.77), Procedural Reaction Time (M = -7.26; p = 0.49), Spatial Processing (M = -3.14; p = 0.50), Go No Go (M = -1.37; p = 0.89), Match to Sample (M = 2.00; p = 0.57), Memory Search (M = -2.62; p = 0.75), and Simple Reaction Time (Delayed; M = 2.99; p = 0.81).

Results indicate that cognitive performance at baseline does not differ based on COVID status, emphasizing the need for examination of longitudinal cognitive performance. Future directions include examining the impact of COVID disease severity and reinfection on cognition.

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.