To assess the utility of the Mini Mental State Exam (MMSE) and Montreal Cognitive Assessment (MoCA) for tracking cognitive changes Huntington’s Disease.

Currently, the most frequently used brief assessment of global cognitive functioning is the MMSE. Although the MMSE is helpful for distinguishing individuals without significant cognitive impairment from those with dementia, it is not particularly sensitive to more subtle cognitive deficits. The MoCA is another brief cognitive screening tool that has been shown to be more sensitive to mild impairment and may have greater usefulness in subcortical dementias because of its more extensive assessment of executive function. Although the MoCA appears to have high sensitivity and specificity in a variety of neurological populations, there is currently little known about its efficacy in tracking cognitive decline in individuals with HD. We used a mixed effects model to analyze MMSE and MoCA scores collected prospectively during 5 years of follow-up for 163 patients with HD seen at one academic HDSA Center of Excellence. Baseline mean age for the HD cohort was 51.35 years, mean education 14.46 years, and a mean CAG repeat length 43.95. Mean follow-up time was 3.33 years.

Mean MMSE and MoCA scores at baseline were 25.13 (SD=1.66) and 22.76 (SD=3.70) respectively. At baseline, age and gender were not associated with MMSE and MoCA scores, while years of education were. Neither age nor gender predicted rate of decline for the MoCA while years of education predicted rate of decline for the MMSE. For the MMSE, each year of education predicted on average 0.51 points higher score at enrollment; for the MoCA, each year of education predicted on average 0.79 points higher score at enrollment. The mean rates of decline on the MMSE was 0.48 points per year (p<.001) while that on the MoCA was only 0.31 points annually (p<.001) in the first five years of observation.

The MMSE and MoCA decline significantly over time in an unselected HD population. The smaller rate of decline in the MoCA may be due, in part, to the greater variability in baseline, MoCA (SD=3.70) vs MMSE (SD=1.66) scores in our HD cohort. Unlike cortical dementias, such as Alzheimer’s disease (AD), where declines of 2-3 points per year have been described for the MMSE and MoCA, much lower annual rates of decline have been reported in subcortical dementias such as Parkinson’s disease. To our knowledge, this is the first report of rate of cognitive decline on the MMSE and MoCA in HD: such information is vital for adequately preparing patients and families for future needs, in addition to planning for interventional/treatment trials in HD.

Patients with early Alzheimer Disease (AD) and Mild Cognitive Impairment of the Amnestic type (MCI-A) have been reported to show large variability of tapping scores. Factors that contribute to that variability remain undetermined. This preliminary study aimed to identify predictors of finger tapping variability in older adults evaluated for a neurodegenerative memory disorder. Based on earlier research with normally functioning adults, we predicted that the number of “invalid” tapping responses (i.e. failure of the index finger to adequately lift off the tapping key once it is depressed to produce the next number on a mechanical counter) and the female gender would predict finger tapping variability, but age and educational level would not predict variability.

This preliminary study included 4 groups of participants, comprised of 8 healthy controls (HC, 3 males; 73±7years); 12 persons with subjective memory complaints (SMC, 3 males; 69±5 years); 12 with MCI-A (7 males; 76±5 years) and 7 early AD (5 males; 75±6years). All participants were administered a modified version of the Halstead Finger Tapping Test (HFTT). Mean, range of tapping score (i.e. a measure of variability), and number of invalid taps across 7 trials in each hand were calculated. ANOVA was performed for the HFTT metrics with the main effect of group. Tukey HSD tests were used for post hoc comparisons between groups. Multiple regression analysis was performed to determine the degree to which the number of invalid tapping responses, sex, age, and educational level predicted finger tapping variability using all 4 groups.

Mean tapping score did not vary significantly across groups in the dominant [F (3, 35) = 0.633, p = 0.599] or non-dominant [F (3, 35) = 2.345, p = 0.090] hand. Range score approached a significant difference between groups in the dominant hand [F (3, 35) = 2.745, p = 0.058], with a clear significant effect of group on range score in the non-dominant hand [F (3, 35) = 4.078, p = 0.014]. Range score in the nondominant hand was significantly higher in the AD compared to SMC (p = 0.018) and HC (p = 0.024). Regression analysis revealed statistically significant findings for the dominant hand (R2 = 0.327, F (4, 34) = 4.130, p = 0.008) and for the non-dominant hand (R2 = 0.330, F (4, 34) = 4.180, p = 0.007). For both the dominant and non-dominant hands, number of invalid taps significantly predicted range score (ß = 0.453, p = 0.044, and ß = 0.498, p = 0.012, respectively). Sex, age, and education years did not predict range scores.

Variability of finger tapping in patients evaluated for neurodegenerative memory disorders and aged matched controls is predicted by the number of invalid tapping responses (comprising over 30% of the variance), but not by demographic variables in this clinical sample. Neurodegenerative disorders may eliminate a sex effect.

Traumatic brain injury (TBI) and concussion are associated with increased dementia risk. Accurate TBI/concussion exposure estimates are relatively unknown for less common neurodegenerative conditions like frontotemporal dementia (FTD). We evaluated lifetime TBI and concussion frequency in patients diagnosed with a range of FTD spectrum conditions and related prior head trauma to cavum septum pellucidum (CSP) characteristics observable on MRI.

We administered the Ohio State University TBI Identification and Boston University Head Impact Exposure Assessment to 108 patients (age 69.5 ± 8.0, 35% female, 93% white or unknown race) diagnosed at the UCSF Memory and Aging Center with one of the following FTD or related conditions: behavioral variant frontotemporal dementia (N=39), semantic variant primary progressive aphasia (N=16), nonfluent variant PPA (N=23), corticobasal syndrome (N=14), or progressive supranuclear palsy (N=16). Data were also obtained from 217 controls (“HC”; age 76.8 ± 8.0, 53% female, 91% white or unknown race). CSP characteristics were defined based on width or “grade” (0-1 vs. 2+) and length of anterior-posterior separation (millimeters). We first describe frequency of any and multiple (2+) prior TBI based on different but commonly used definitions: TBI with loss of consciousness (LOC), TBI with LOC or posttraumatic amnesia (LOC/PTA), TBI with LOC/PTA or other symptoms like dizziness, nausea, “seeing stars,” etc. (“concussion”). TBI/concussion frequency was then compared between FTD and HC using chi-square. Associations between TBI/concussion and CSP characteristics were analyzed with chi-square (CSP grade) and Mann-Whitney U tests (CSP length). We explored sex differences due to typically higher rates of TBI among males.

History of any TBI with LOC (FTD=20.0%, HC=19.2%), TBI with LOC/PTA (FTD:32.2%, HC=31.5%), and concussion (FTD: 50.0%, HC=44.3%) was common but not different between study groups (p’s>.4). In both FTD and HC, prior TBI/concussion was nominally more frequent in males but not significantly greater than females. Frequency of repeat TBI/concussion (2+) also did not differ significantly between FTD and HC (repeat TBI with LOC: 6.7% vs. 3.3%, TBI with LOC/PTA: 12.2% vs. 10.3%, concussion: 30.2% vs. 28.7%; p’s>.2). Prior TBI/concussion was not significantly related to CSP grade or length in the total sample or within the FTD or HC groups.

TBI/concussion rates depend heavily on the symptom definition used for classifying prior injury. Lifetime symptomatic TBI/concussion is common but has an unclear impact on risk for FTD-related diagnoses. Larger samples are needed to appropriately evaluate sex differences, to evaluate whether TBI/concussion rates differ between specific FTD phenotypes, and to understand the rates and effects of more extensive repetitive head trauma (symptomatic and asymptomatic) in patients with FTD.

Findings from cognitive screenings have resulted in lower-than-expected scores amongst late-career physicians (Moutier et al., 2013). Similar to healthy aging samples and those with mild cognitive impairment, inconsistencies in self-report and objective neuropsychological functioning have been noted in physicians (Nasreddine et al., 2005). Little research has focused on neuropsychological functioning of other highly educated groups, including PhD and JD degrees. We addressed a lack of normative cognitive performance data for populations with advanced degrees by exploring cognitive test scores in a mixed clinical sample of adults.

Archival data are from 208 neuropsychology clinic outpatients with 20 years of education (Mage=67.7, SDage=12.3; 25% female; 95% White). Academic degrees were PhD (35.6%), JD (28.4%), MD/DO (21.6%), and 6% other. Referrals sources were physicians (93.8%), licensing boards/employers (3.8%), self-referrals (1.4%), and attorneys (1.0%). Employment status was 55.3% employed and 44.7% not employed. Final DSM-5 neurocognitive diagnosis (NCD) status was: no NCD (45.2%), mild NCD (35.6%), and major NCD (19.2%). Etiologies were: possible Alzheimer’s disease (41.2%), unspecified (13.2%), and possible vascular (12.3%). Chi-square tests denoted diagnostic status differences between degree type and employment status. ANOVAs denoted differences in global cognitive and intellectual functioning (on the Repeatable Battery for Neuropsychological Status [RBANS] Total Index, Weschler Adult Intelligence Scale-IV (WAIS-IV), Weschler Abbreviated Scale of Intelligence-II [WASI-II] FSIQ-4 and FSIQ-2) between degree types. Cumulative frequency rates for low scores in the entire sample on normally distributed tests of general intellectual and cognitive functioning were computed for -1.0, -1.5, -2.0, and -2.5 standard deviations (SDs) at or below the population mean.

NCD diagnosis did not differ by degree (X2[14]=8.73, p=.848) but did differ by employment status (x2[2]=40.98, p<.001, cp=0.44). Employment rate was highest for the no NCD group (66.0%), followed by mild NCD (37.8%), and major NCD (7.5%). For cases below retirement age (<65 years), employment status did not significantly differ between NCD diagnostic groups (x2[2]=5.97, p=.050). Low scores on an FSIQ measure were: -1 SD (7.0%), -1.5 SD (2.6%), -2.0 SD (0.9%), and -2.5 SD (0.0%) compared to general cognitive test scores which demonstrated 42.5% at -1 SD, 30.5% at -1.5 SD, 19.0% at -2.0 SD, and 9.2% at -2.5 SD below the population mean.

The high-education literature is limited to medical degree samples. This sample included multiple degree types. Unsurprisingly, employment rates were higher for healthy versus impaired samples; however, employment rates were similar across these groups for people below retirement age. Our findings suggest that cognitively impaired people with 20 years of education often perform at or near the general population average on tests of general intellectual functioning but below the general population average on tests of general cognitive functioning. Future work should include base rates of low scores on a broader array of cognitive tests across diagnostic groups.

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.

Spinocerebellar ataxia type one (SCA1) is an autosomal dominant neurodegenerative disease caused by an expanded CAG repeat that encodes glutamine (polyQ) in the affected ATXN1 gene. SCA1 pathology is commonly characterized by the degeneration of the cerebellar Purkinje cells (PC) and brainstem. Symptoms include motor dysfunction, cognitive impairments, bulbar dysfunction, and premature death. Atxn1175Q/2Q knock-in mice were previously developed to model SCA1 by inserting 175 expanded CAG repeats into one allele of the Atxn1 gene, producing mice expressing ATXN1 throughout the brain and displaying SCA1 symptoms. Previous research has indicated the role of localization of the ATXN1 protein to the nucleus in pathology. Therefore, the Atxn1175QK772T/2Q mouse model was created by disrupting the NLS in the expanded Atxn1175Q/2Q mice by replacing lysine with threonine at position 772 in the nuclear localization sequence (NLS). Since this amino acid change previously blocked PC disease in another mouse model, the Atxn1175QK772T/2Q mice were created to examine how the NLS mutation affects neuronal cells. RNA sequencing analysis was previously performed and found differentially expressed genes (DEG) with Atxn1175Q/2Q downregulated compared to Atxn1175QK772T/2Q and Atxn12Q/2Q in the cerebellum, medulla, cortex, hippocampus, and striatum. The aim was to analyze these brain regions to validate the RNAseq differential gene expression at a protein level.

Therefore, western blots were performed on the following mouse models (n=12): wild type mice (Atxn12Q/2Q), mice with the nuclear localization sequence mutation (Atxn12QK772T/2Q), and mice with 175 expanded CAG repeats (Atxn1175/2Q). Based off the RNAseq data, the cerebellum was tested with ion channel genes (Cav3.1, Kcnma1, and Trpc3) and the striatum was tested with a gene found in medium-spiny neurons (DARPP-32).

In the cerebellum, Atxn1175/2Q was significantly downregulated compared to Atxn1175QK772T/2Q in Cav3.1, Trpc3, and Kcnma1. Atxn1175Q/2Q was significantly downregulated compared to Atxn12Q/2Q in Trpc3 and Kcnma1. Atxn1175QK772T/2Q was significantly downregulated compared to Atxn12Q/2Q in Trpc3. In the striatum, there was significantly reduced DARPP-32 expression found between Atxn12Q/2Q and Atxn1175QK772T/2Q, Atxn12Q/2Q and Atxn1175Q/2Q, and Atxn1175Q/2Q and Atxn1175QK772T/2Q.

Therefore, the significantly reduced gene expression at the protein level in the cerebellum and striatum validate RNAseq differentially expressed genes. Additionally, the downregulation of both the Atxn1175Q/2Q and Atxn1175QK772TQ/2Q compared to Atxn12Q/2Q in the striatum supports the lack of learning of those mouse models on the rotarod, suggesting that the nuclear localization mutation does not rescue learning. Interestingly, the downregulation of Atxn1175Q/2Q compared to Atxn1175QK772TQ/2Q likely supports the age-related motor decline rescue in the rotarod seen in Atxn1175QK772T/2Q and not Atxn1175Q/2Q.

Parkinson’s disease (PD) is one of the most prevalent neurodegenerative conditions that leads to progressive degeneration in areas of the brain that control movement. As the disease progresses, cognition is also frequently affected, primarily executive functioning. Multiple factors may be involved in the relationship between PD and cognitive dysfunction. This study seeks to determine the association between disease duration (i.e., years since PD diagnosis), vascular comorbidities, and cognitive reserve (CR) and their relationship with executive functioning, in a clinic-referred PD population.

Participants included English-speaking subjects with a diagnosis of PD made by the patient’s treating neurologist (i.e., movement disorders specialist) who received their neurological care and had undergone a comprehensive neuropsychological evaluation at Thomas Jefferson University Hospital in Philadelphia, PA over the past five years. The sample consists of 67 patients. Comprehensive medical and psychiatric histories were obtained, and individuals with severe psychopathology (e.g., bipolar disorder or schizophrenia), medical or other neurological disorders (e.g., seizure disorder, stroke, documented head injury that was more severe than a mild TBI or intracranial bleeding) that could account entirely for cognitive impairment were excluded. An overall domain score of executive functioning was calculated by averaging each participant’s T-scores for the individual neuropsychological tests. Regression analysis was utilized to explore the relationship between number of vascular comorbidities, disease duration, and CR, as measured by a composite of formal education and literacy level, with executive functioning performance on neuropsychological testing for this sample.

The model explains 12.1% of the variance of executive functioning performance (F (3, 66) = 2.883, p = 0.043). A significant positive relationship was found between CR and executive functioning (b = .335, p = 0.008). No significant relationships were found between vascular comorbidities or disease duration with executive functioning. The relationship between CR and each neuropsychological measure was explored independently using Pearson correlation (2-tailed). Significant positive correlations were found between CR and WAIS-IV or WASI-II Similarities (r = .49, p < .001), CR and WAIS-IV or WASI-II Matrix Reasoning (r = .46, p = .001), and CR and FAS (r = .26, p = .037). No significant relationships were found between CR and TMT-B (r = .07, p = .565) or CR and Stroop Color and Word Interference (r = .17, p = .240).

Results suggest that CR may be a better predictor of executive functioning in patients with PD than number of vascular comorbidities or disease duration. Stronger premorbid cognitive functioning and better cognitive efficiency may be neuroprotective and stave off cognitive decline in Parkinson’s disease.

Mild cognitive impairment (MCI) in Parkinson’s disease (PD) is a critical state to consider. In fact, PD patients with MCI are more likely to develop dementia than the general population. Thus, identifying the risk factors for developing MCI in patients with PD could help with disease prevention. We aim to use the Cox regression model to identify the variables involved in the development of MCI in healthy controls (HC) and in a PD cohort.

The Parkinson’s Progressive Markers Initiative (PPMI) database was used to analyze data from 166 HC and 365 patients with PD. They were analyzed longitudinally, at baseline and at 3-year follow up. Both HC and PD were further divided in 2 groups based on the presence or absence of MCI. Conversion to MCI was defined as the first detection of MCI. For all participants, we extracted the (1) Neuropsychiatric symptoms (anxiety, impulsive-compulsive disorders and sleep impairment), (2) 3T MRI-based data (cortical and subcortical brain volumes based on the Desikan atlas, using FreeSurfer 7.1.1) and (3) genetic markers (MAPT and APOE £4 genes). We used Python 3.9 to perform three Cox proportional hazard models (PD-HC, HC only and PD only) and to model the risk of conversion to MCI, attributable to neuropsychiatric symptoms and cortical brain parameters. We included as covariates: age, sex, education, and disease duration (for the PD group). Hazard ratios (HRs) along with their 95% confidence intervals (CIs) are reported.

When including both HC and PD in the model, Cox regression analyses showed that age of onset, diagnosis, the State-Trait Anxiety Inventory (STAI) and sleep impairment are variables that are associated with a greater risk of conversion to MCI (p<.005). For HC, only the STAI and the genetic marker MAPT were significantly associated with a risk of cognitive decline (p<.05). These results further indicated that a greater anxiety score at the STAI leads to a greater chance of developing a MCI whereas being a carrier of the MAPT gene reduces the risk of MCI. Regarding analysis on PD, results revealed that the STAI and the cortical volumes of the frontal dorsolateral and temporal regions are involved with a greater risk of developing a MCI (p<.05).

These analyses show that the neuropsychiatric symptom of anxiety seem to play an important role in the development of a MCI (significant in all three analyses). For patients with PD, cortical volumes of the frontal dorsolateral and temporal regions are significantly related to risk of MCI. This study highlights the importance of considering neuropsychiatric symptoms as well as cerebral volumes as key factors in the development of MCI in PD.

Cognitive tests on which performance is unrelated to brain pathology are considered “hold” tests and are often used to estimate cognitive abilities prior to injury or disease. Amongst the most commonly used “hold” tests are measures of irregular word reading, such as the Test of Premorbid Functioning (TOPF). Measures of irregular word reading assess ability to accurately pronounce phonetic irregularities based on prior experience and word knowledge, and tend to be insensitive to most forms of brain pathology (Lezak, 2012). However, research examining whether a relationship exists between neurodegenerative diseases and decline in irregular word reading is limited. The few studies completed have demonstrated a decline in irregular word reading in neurodegenerative disease in general (Berg, Durant, Banks, & Miller, 2016) and Alzheimer’s dementia specifically (McFarlane, Welch, & Rodgers, 2006). However, no known research has been published examining whether irregular word reading and TOPF scores differ depending on cognitive classifications commensurate with DSM-V diagnoses (i.e., mild or major neurocognitive disorder, etc.), or presumed neurological etiology.

Patients were enrolled from the University of Colorado Hospital Neuropsychology Clinic. This study was a retrospective review of consecutive referrals over the age of 65 to the University of Colorado Hospital Neuropsychology Clinic from 2019 to present. The TOPF was administered along with a full neuropsychological battery and patients were clinically classified by severity of cognitive impairment (e.g., Normal, Mild Neurocognitive Disorder, Major Neurocognitive Disorder) and presumed neurologic etiology (e.g., Alzheimer’s disease (AD), Parkinson’s disease (PD), vascular cognitive impairment (VCI), and mixed dementia (AD and VCI). TOPF Raw scores were used for all analyses. Correlation analysis was conducted to determine significant relationships between various demographic variables and TOPF performance. ANCOVA analyses were conducted to examine differences on TOPF performance by diagnostic classification and differences on TOPF performance by presumed neurologic etiology.

Correlation determined a significant relationship between TOPF performance and education (r = .51, p < .001), but not age (p = .092) or gender (p = .680). ANCOVA revealed a significant effect of TOPF performance on diagnostic group classification after controlling for education, F(2, 504)= 26.45, p < .001. Post hoc analysis revealed that those diagnosed with Major Neurocognitive Disorder performed the worst on the TOPF (M=39.801 ± .958), followed by those diagnosed with Mild Neurocognitive Disorder (M= 45.371 ± .767), while those diagnosed as cognitively normal performed the best (M= 49.826 ± .993). Additional ANCOVA analysis revealed a significant effect of TOPF performance on presumed neurologic etiology after controlling for education, F(3,148)=6.07, p = .001. Post hoc analyses revealed that participants with suspected AD (M= 40.728 ± 1.613) and those with suspected VCI (M= 32.804 ± 3.480) performed worse on the TOPF compared to those with suspected PD (M=46.964 ± 1.506), (p=.042 and p = .004, respectively).

Results suggest that TOPF performance in older individuals is sensitive to cognitive impairment. Furthermore, these results suggest that this sensitivity may be further influenced by presumed neurologic etiology. These findings are consistent with prior studies which demonstrated a decline in irregular word reading in individuals with neurodegenerative diseases.

Former professional American football players have a high relative risk for neurodegenerative diseases like chronic traumatic encephalopathy (CTE). Interpreting low cognitive test scores in this population occasionally is complicated by performance on validity testing. Neuroimaging biomarkers may help inform whether a neurodegenerative disease is present in these situations. We report three cases of retired professional American football players who completed comprehensive neuropsychological testing, but “failed” performance validity tests, and underwent multimodal neuroimaging (structural MRI, Aß-PET, and tau-PET).

Three cases were identified from the Focused Neuroimaging for the Neurodegenerative Disease Chronic Traumatic Encephalopathy (FIND-CTE) study, an ongoing multimodal imaging study of retired National Football League players with complaints of progressive cognitive decline conducted at Boston University and the UCSF Memory and Aging Center. Participants were relatively young (age range 55-65), had 16 or more years of education, and two identified as Black/African American. Raw neuropsychological test scores were converted to demographically-adjusted z-scores. Testing included standalone (Test of Memory Malingering; TOMM) and embedded (reliable digit span, RDS) performance validity measures. Validity cutoffs were TOMM Trial 2 < 45 and RDS < 7. Structural MRIs were interpreted by trained neurologists. Aß-PET with Florbetapir was used to quantify cortical Aß deposition as global Centiloids (0 = mean cortical signal for a young, cognitively normal, Aß negative individual in their 20s, 100 = mean cortical signal for a patient with mild-to-moderate Alzheimer’s disease dementia). Tau-PET was performed with MK-6240 and first quantified as standardized uptake value ratio (SUVR) map. The SUVR map was then converted to a w-score map representing signal intensity relative to a sample of demographically-matched healthy controls.

All performed in the average range on a word reading-based estimate of premorbid intellect. Contribution of Alzheimer’s disease pathology was ruled out in each case based on Centiloids quantifications < 0. All cases scored below cutoff on TOMM Trial 2 (Case #1=43, Case #2=42, Case #3=19) and Case #3 also scored well below RDS cutoff (2). Each case had multiple cognitive scores below expectations (z < -2.0) most consistently in memory, executive function, processing speed domains. For Case #1, MRI revealed mild atrophy in dorsal fronto-parietal and medial temporal lobe (MTL) regions and mild periventricular white matter disease. Tau-PET showed MTL tau burden modestly elevated relative to controls (regional w-score=0.59, 72nd%ile). For Case #2, MRI revealed cortical atrophy, mild hippocampal atrophy, and a microhemorrhage, with no evidence of meaningful tau-PET signal. For Case #3, MRI showed cortical atrophy and severe white matter disease, and tau-PET revealed significantly elevated MTL tau burden relative to controls (w-score=1.90, 97th%ile) as well as focal high signal in the dorsal frontal lobe (overall frontal region w-score=0.64, 74th%ile).

Low scores on performance validity tests complicate the interpretation of the severity of cognitive deficits, but do not negate the presence of true cognitive impairment or an underlying neurodegenerative disease. In the rapidly developing era of biomarkers, neuroimaging tools can supplement neuropsychological testing to help inform whether cognitive or behavioral changes are related to a neurodegenerative disease.

Among individuals with Parkinson’s Disease (PD), visual hallucinations (VH) and mild cognitive impairment (MCI) are highly prevalent and often co-occur. Atrophy in similar brain regions [e.g. cholinergic basal forebrain (BF) nuclei] as well as specific cognitive difficulties (e.g. posterior-cortical abilities such as semantic fluency and visuoperception) have been associated with the presentation of each symptom type. While there are separate lines of evidence implicating BF volume in MCI and VH, no study to date has examined BF integrity in patients with concurrent MCI and VH symptomology. Furthermore, no prior studies examining BF integrity in MCI and VH have accounted for the potential confounding effects of dopaminergic medications which are known to exacerbate both symptom types. The aims of this study were to harmonize or bridge the two bodies of literature to determine the common neural substrate of PD-VH and PD-MCI (with an emphasis on the BF), to examine the confounding effects of dopaminergic pharmacotherapy, and to examine whether nondopaminergic “posterior” cognitive abilities differ between PD-MCI with versus without VH.

This study used a clinical chart review and MRI data to examine the associations between BF volume in a large group (n=296) of advanced PD patients (∼10 years disease duration) with and without each VH and MCI, covarying the effect of dopaminergic therapy. A two-way ANCOVA was run on total and regional BF volumes (i.e., total BF volume, and four nuclei including Ch4, Ch4p, Ch1-2, Ch3) using VH and MCI as independent variables, while covarying for dopaminergic medication. Using Mann-Whitney U tests, we compared the performance of individuals with MCI-VH versus that of individuals with MCI-noVH on tasks of semantic verbal fluency and of visuoperceptual skills (e.g., judgement of line orientation, object decision, and silhouettes).

There were two major findings: (1) atrophy of the Ch4 region in the BF was associated with MCI with VH while Ch1-2 was associated with MCI regardless of VH status, and (2) patients with both MCI and VH had poorer performance than individuals with MCI without VH on tasks measuring object recognition but not on tasks of visuospatial perception or semantic verbal fluency. These results remained stable regardless of whether or not dopaminergic medication was included in the model.

PD is a heterogeneous disease with different subtypes reflecting both dopaminergic and cholinergic dysfunction. Our findings suggest further dissociations within the cholinergic system. First, atrophy in Ch4, which projects to the cortical mantle, was preferentially associated with VH symptoms and object-based visuoperception deficits. This is consistent with proposals that VH are real-world manifestations of visuoperceptual deficits. Second, Ch1-2 atrophy, which projects primarily to the hippocampus, was associated with MCI regardless of VH. Future research will extend this work to other cognitive abilities such as memory, to analyses of brain networks that implicate the BF, and to the investigation of the relationship between anti-cholinergic medications and symptom presentation in PD.

Executive function (EF) abilities tend to decline with age, and disproportionately so for people with neurodegenerative disorders such as Parkinson’s Disease (PD), where EF deficits are commonly seen in the early stages of the disease. Due to their nature, EF are essential for performing tasks of daily life, particularly for the more complex instrumental activities of daily living (IADL), and deficits can impair the ability to execute IADL in PD participants. The aim of this study was to examine how EF impairments relate to IADL deficits in both healthy elderly controls and PD participants.

Seventy-four participants with idiopathic PD and 66 elderly controls were recruited. All participants were non-demented. A comprehensive neuropsychological assessment was administered including the following measures of EF: Hayling Sentence Completion, Brixton Spatial Anticipation, Trail Making Test A and B, Stroop Color-Word Test, Symbol Span (Wechsler Memory Scale-III), Digit Span (Wechsler Adult Intelligence Scale-III), F-A-S test, and Semantic Fluency (Animals and Actions). Z scores were calculated from respective test manuals. Independence was measured using the 8-item Lawton IADL Scale where items are coded from 0 (dependent) to 1 (independent) and the total score ranges from 0 to 8. Motor impairments were assessed using Part III of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale. Regression models were run with each cognitive measure as the dependent variable, with group (control vs. PD), age, sex, education, and motor severity as predictors, to examine the effect of group on each cognitive variable. Correlations were then run between the total IADL score, demographic variables, and cognitive variables for each participant group separately to identify the relationship between IADL and EF measures.

PD participants were predominantly males (n=51, 68.9%), with an average age of 70.64±6.03 and 15.22±2.78 education years. Controls were predominantly female (n=34, 51.5%) and had an average age of 71.19±7.75 and 15.85±2.82 education years. Regarding IADL function, all participants were relatively independent in their IADLs (PD: 7.72±0.69, range 4-8, Controls: 7.98±0.13, range 7-8). The most difficult IADL items for PD participants were shopping (8.2% dependent) and food preparation (12.2% dependent). When correcting for age, education, sex, and motor severity, only the Stroop Interference z-score was significant for participant group (b=0.44, t=2.14, p=0.034), where controls had slightly lower scores (-0.33±0.77) than PD participants (-0.31±0.91). Correlations in controls were significant between IADL total score and Hayling trials 1 (r=0.35, p=0.005) and 2 (r=0.33, p=0.008), and semantic fluency actions trial (r=0.34, p=0.006). In PD participants, IADL total score was only correlated with semantic fluency (animals trial, r=0.26, p=0.028).

There were only weak associations between EF abilities and IADL in both healthy controls and PD participants, suggesting that impairments in EF do not necessarily translate into worse ability to execute IADL in PD. More correlations were found in the control group, which may be confounded by the inclusion (in both groups) of participants who already had cognitive impairment. This highlights a further need to examine whether EF impairments in people with PD influence IADL functioning above and beyond normal aging and whether specific deficits have more real-life consequences not attainable through IADL questionnaires.

Semantic variant primary progressive aphasia (svPPA) is a progressive neurodegenerative syndrome characterized by prominent impairments in naming, conceptual knowledge, and comprehension, in the setting of preserved fluency, memory, and visuospatial perception. Generally, svPPA is caused by underlying TDP-43 neuropathology. In contrast, the clinical syndrome of Lewy Body Disease (LBD) is characterized by the presence of parkinsonism and prominent attentional and visuo-spatial deficits, with relative preservation of language skills and visual hallucinations. The underlying neuropathology is Lewy bodies. Here, we describe three unique cases from the UT Health San Antonio Brain Bank of patients with clinical diagnoses of svPPA, but primary neuropathological diagnoses of LBD.

We present three cases who had clinical presentations of svPPA but were found to have LB pathology as opposed to the expected TDP-43 or FTLD pathology. We studied demographic variables in these three patients, along with neuroimaging, clinical symptoms, and patterns of neuropathology, in order to demonstrate and further understand the similarities and connections between LBD and semantic deficits.

In Case 1, the patient exhibited fluent but empty speech with profound anomia. Symptoms started in his late 50s and progressed until he lost all purposeful capacity for language before his death at age 66. DaT scan was normal and brain MRI was unremarkable. Underlying neuropathology revealed diffuse LBD throughout the neocortex with intermediate Alzheimer’s disease neuropathic change (ADNC), and moderate cerebrovascular disease. In Case 2, the patient exhibited language comprehension difficulties with symptom onset in his early 70s before passing away at age 76. The patient also developed changes in judgment and trouble with activities of daily living. MRI revealed left more than right mesial temporal atrophy, left more than right mild to moderate frontal and insular atrophy, and moderate small vessel disease. FDG-PET was significant for hypometabolism in the left mid-frontal region and in the bilateral anterior cingulate and medial prefrontal cortices. Neuropathology revealed diffuse LBD throughout the neocortex with a high level of ADNC, along with limbic-predominant age-related TDP-43 encephalopathy (LATE) stage 1 and moderate cerebrovascular disease. In Case 3, the patient displayed dysgraphia and anomia, starting in his mid-50s, as well as REM behavior sleep disorder. The patient’s neuropathology revealed a high level of ADNC with diffuse LBD throughout the neocortex, and moderate, non-occlusive cerebrovascular disease. None of the patients exhibited the typical Parkinsonism symptoms associated with LBD, but all had prominent visual hallucinations.

This small case series illustrates that a small portion of subjects with underlying LBD pathology may exhibit profound language disturbance suggestive of svPPA. Additional study is warranted, and future endeavors will explore larger pathologically-confirmed samples of subjects with clinical svPPA and high degree of underlying LBD pathology.

Sleep deprivation and depressive symptoms have been shown to negatively impact cognitive function within older adult populations (Gilley, 2022; Donovan et al., 2016). However, there is minimal research on interactions between sleep disturbance and depressive symptoms in relation to their shared impact on cognitive impairment. The purpose of this study is to examine possible interactions between sleep disorders and depression and their relationship with cognition among relatively good functioning and healthy older adults.

The sample was obtained from the Memory and Aging Project (Rush Alzheimer's Disease Center, Rush University, 2019) and consisted of 3,345 community dwelling older adults. The study analyzed data from 2552 women (76.3%) and 1093 men (23.7%). The average age of participants was 80 years and ranged from 45 to 98 years old. Measures used included the Berlin Questionnaire (risk for sleep apnea), Center for Epidemiological Studies Depression Scale (CES-D; depression), and a neuropsychological battery (visuospatial ability/perceptual reasoning and processing speed).

ANOVA analyses exhibited a significant main effect of depression on visuospatial ability/perceptual reasoning (p <.001), processing speed (p <.001), and semantic memory (p <.001). No significant main effect was found for sleep apnea on these cognitive domains. However, when sleep apnea was analyzed between those with any depressive symptoms versus those without, significant interactions were found for visuospatial ability/perceptual reasoning (p =.027), processing speed (p <.001), and semantic memory (p =.016). Sleep apnea symptoms had a greater detrimental effect on visuospatial skills and perceptual reasoning (F=4.90; p=.027) only when any depression symptom is present. In contrast, there was a steeper decline of processing speed when only depressive symptoms were present apart from sleep apnea symptoms (F=10.34; p =.001) Similarly, depressive symptoms had a greater negative effect on semantic memory for older adults who reported no sleep apnea symptoms compare to those who did (F=5.83, p=.016).

The current study indicated that while sleep apnea was negatively related to several cognitive domains, the impact became greater with the presence of depression on visuospatial skills and perceptual reasoning among older adults. However, the detrimental impact of sleep apnea was somewhat less with the presence of depression for processing speed and semantic memory. This may be due to likely higher endorsements of depressive symptoms compared to sleep apnea symptoms within the study sample. These findings suggest that there are differential interactive effects of sleep impairment and depressive symptoms on cognitive domains among older adults. Considering the relationship that exists between depression and increased disease burden among older adults, it is crucial for clinicians to also take sleep behaviors into account when examining and treating their patients. Clinicians should be mindful of their older patient's sleep health and depression measures when cognitive declines are suspected. They also suggest that cognitive performance may be improved with treating any symptoms of sleep apnea and depression in older adults.

Insomnia affects 30-45% of the world population, is related to mortality (i.e., auto accidents and job-related accidents), and is related to mood and affect disorders such as anxiety and depression. Better understanding of insomnia via increased research will decrease the burden on insomnia. The neurocognitive model of sleep proposes that conditioned somatic and cognitive hyperarousal develop in response to repeated pairings of sleep-related stimuli with insomnia-related wakefulness. The purpose of this study was to examine the neurocognitive model of sleep using a novel laboratory paradigm, the Sleep Approach Avoidance Task (SAAT). It was hypothesized that individuals who report symptoms of insomnia will display a bias for negative sleep-related images from the SAAT, which is presumably a reflection of cognitive, behavioral and physiological processes associated with hyperarousal. It was also hypothesized that participants who report poor sleep would provide different subjective ratings for negative images (i.e., stronger valence and arousal) than individuals who reported better sleep.

An initial sample of 66 healthy college-aged participants completed the Insomnia Severity Index (ISI), the Pittsburgh Sleep Quality Index (PSQI) the Dysfunctional Attitudes and Beliefs about Sleep (DBAS) scale and the Epworth Sleepiness Scale (ESS). Participants also completed the SAAT. The SAAT was developed to assess sleep-related bias in adults. The SAAT is a visual, joystick controlled reaction time task that measures implicit bias for positive and negative sleep-related images. At the end of the task the participants are also asked to rate each image along three dimensions included valence, arousal and dominance.

There was a positive correlation between the SAAT and the ISI [r(61) = .30, p = .01], indicating that symptoms of insomnia are related to negative approach-related bias for sleep-related images. No other correlations were observed between the SAAT and self-report sleep measures. With regard to rating of images, higher dominance ratings for negative images were correlated with the SAAT [r(62) = .24, p = .03], which indicates that the approach bias for negative images is associated with “being in control.” Multiple linear regression was used to test if ISI scores and dominance ratings for negative images significantly predicted SAAT bias scores. The overall regression was statistically significant [r2 = .13, F(2, 58) = 4.15, p = .02]. ISI scores significantly predicted SAAT scores (ß = .27, p = .04), whereas dominance ratings for negative images did not significantly predict SAAT scores (ß = .20, p = .11). Exploratory correlational analyses were also completed for ratings of images and other sleep self-report measures. Valence ratings for positive sleep-related images were positively correlated with the ESS [r(64) = .36, p = .01], whereas valence ratings for negative sleep-related images were negatively correlated with the ESS [r(64) = -.24, p = .03].

Hypotheses were partially supported with the ISI being the only self-report measure associated with negative bias for sleep-related images. While ratings of dominance are associated with bias for negative sleep-related images, these ratings do not provide unique variance. These findings indicate a cognitive processing bias for sleep-related stimuli among young adult poor sleepers. Limitations, implications for assessment and intervention are discussed.

Resiliency has been shown to attenuate and even protect against cognitive impairment from mental and physical stressors. Recently, it has been demonstrated that individuals who score high in psychological resilience tend to have less impairment following a mTBI.The COVID-19 pandemic proved to be an uncertain time for many. Periods of isolation, unemployment, and of course, sickness, meant more time at home. The partial or complete breakdown of an individual’s day-to-day routine paired with the stress of the pandemic has reinforced the need for psychological resilience. This analysis investigates the relationship between self-reported routine adherence and an individual’s corresponding psychological resilience. We hypothesize that individuals who maintained a structured daily routine during the pandemic will have higher levels of psychological resilience, enabling them to better handle periods of extreme stress.

8963 English-speaking adults (18-92 years old; 59.5% female) from across the U.S. completed an online, monthly cross-sectional (∼1000 participants per month), battery of questions that included the Connor-Davidson Resilience Scale (CD-RISC), and a self-reported sleep and routine rating(s) between June 2020 and April 2021. We measured the level of an individual’s routine by adding the self-reported survey scores of waking at the same time and maintaining a routine throughout the day. Both questions were scored 0-4 (Likert-style) for a score range of 0 to 8; higher scores indicated a higher adherence to a daily structure. Weeknight sleep (Sun-Thurs) was a self-reported average of the hours of sleep obtained over the past 4 weeks. A two-way ANCOVA was used to analyze the effects that routine had on subsequent psychological resilience scores while controlling for average sleep duration.

A significant main effect routine on psychological resilience was found F(8,8953) =227, p=<.00001 after controlling for average reported weeknight sleep. An independent t-test was performed to determine the differences between those who fall above and below the average score (M= 5.1) for routine adherence. Individuals who were above average in adherence (M=71.1, SD=15.5) had significantly higher CD-RISC scores than individuals who did not (M=59.2, SD=16.7); t(9166)=35.1, p <0.001.

Individuals who maintained a more structured day throughout the pandemic were more likely to score higher on psychological resilience assessments than those who did not. Chronic stress is known to contribute to the development and exacerbation of many common psychiatric conditions like anxiety and depression. These results suggest that having a regular routine may have positive effects on an individual’s ability to bounce back from stressful cognitive and psychological events. This relationship should be further investigated in clinical populations as a potential intervention or adjunctive treatment for common neuropsychiatric conditions.

Sleep has been shown to directly impact cognitive function throughout the lifespan; good quality sleep benefits and improves cognitive function, including processing speed and attention, while poor quality sleep can contribute to negative cognitive outcomes1. In particular, attention, learning, and memory have been demonstrated to be sensitive to sleeping changes, including fragmentation and restriction2. Subjective sleeping scales are utilized in both research and clinical practice, allowing sleep to be measured via self-report on various domains, including duration and factors that can contribute to sleep disruption and disturbances3. This study aims to examine the possible relation between subjective sleep quality and cognitive function among middle-aged adults to inform future research for early interventions of modifiable behaviors that can contribute to abnormal cognitive decline.

Data for this analysis is part of the preliminary results of an ongoing pilot study. 29 middle-aged (40-65 years, inclusive), cognitively unimpaired individuals were recruited from the community. Subjective sleep quality was measured with the Pittsburgh Sleep Quality Index (PSQI). Attention and memory were measured using the California Verbal Learning Test, Third Edition (CVLT-III).

Multiple hierarchical regression analyses were conducted to evaluate if aspects of sleep quality were significantly correlated to complex attention and learning performance in this sample. First, correlation amylases showed significant relationships between PSQI Component 6 (Use of Sleeping Medication) and Trials 1 to 2 Learning Slope (R2 = -0.56, p =0.002) and CVLT-III Trials 1 through 5 Recall Discriminability (R2 = -0.42, p = 0.02), each with significant regression analyses outcomes (b =0.42, p = 0.04 and b = -0.46, p = 0.04, respectively). There were other variables that were found to be significantly correlated; however, after adjusting for relevant demographic variables (age, education, sex), the hierarchical regression analyses revealed no association between the aforementioned variables.

While multiple aspects of sleep quality were expected to influence measures of attention and learning, only PSQI Component 6 was found to be statistically significantly associated with only two learning variables. Limitations of this study included a small sample size which was limited to cognitive and relatively physically healthy middle-aged adults. Further, sleep quality was measured with one subjective measure and no objective data was collected to support the hypotheses. Future analysis is needed to continue to explore the relation between subjective sleep quality and cognitive outcomes. As this is an ongoing study, we look forward to exploring this research question in more detail as the study progresses.

Stress is well known to increase the severity of somatization and insomnia. A recent major stressor that could have influenced the severity of these presentations was world-wide COVID-19 Pandemic. Somatization is the physical expression of stress and emotional distress that can manifest itself throughout various corporal domains and can be a comorbidity to insomnia. Headaches represent some of the most common complaints associated with brain injuries and neurological disorders but are common in somaticized disorders as well. In large survey study we examined whether exercise was associated with severity of somatization and headaches. We hypothesized that both healthy individuals and those with insomnia who exercised during the pandemic would report less severe somatic symptoms and headaches than those who did not.

A large survey was sent out to 4,073 individuals to measure their experience in numerous domains during the COVID-19 pandemic. This survey included a short symptom questionnaire used to measure somatization and the Insomnia Scale Index to measure insomnia. These questionnaires were administered along with a “yes or no” question on whether the participants exercised regularly in that period. A univariate ANOVA was performed to analyze the data to determine if exercise during the pandemic was beneficial in the reduction of somatic symptoms and headache severity. Furthermore, these tests were run to determine if the effect was greater on those with insomnia.

The effect of insomnia and exercise on total somatic symptoms were significant at F(1, 3445)=650.5, p<0.001 and F(1, 3445)=26.1, p<0.001, respectively. For reported headache severity, there was a significant effect of exercise F(1, 4073)=14.5, p<0.001 and insomnia F(1, 4073)=160.5, p<0.001; therefore, those who exercised reported less severe headaches and those who suffered from insomnia reported more severe somatic symptoms. This meant that those who exercised reported less severe somatization and headaches than those who didn’t and those with insomnia reported more severe somatization and headaches than healthy individuals. However, the interaction between exercise and insomnia on overall somatization severity was not significant at F(1, 3445)=3.4, p=0.066 nor for reported headache severity F(1, 4073)=0.81, p=0.370. Despite there not being a significant interaction, the benefit of exercise was slightly greater on healthy individuals than those with insomnia.

Those with insomnia reported more severe headaches and overall somatic symptoms than non-insomniacs regardless of whether they exercised or not. Exercise did make a difference on the reported severity of headaches and somatization in both groups; however, the benefit of exercise on headaches and somatization was greater in individuals who do not suffer from insomnia. Thus, exercise was noted to be beneficial to those in the general population and those suffering from insomnia as it can potentially reduce the severity of somatization and headaches. Of course, this research was cross sectional and correlational, so the directionality of the effects cannot be inferred. For future research, it would be instrumental to use experimental methods to help determine the duration and type of exercise that may optimize its potential benefits on headaches and somatic symptoms.

Sleep is a restorative function that supports various aspects of well-being, including cognitive function. College students, especially females, report getting less sleep than recommended and report more irregular sleep patterns than their male counterparts. Inadequate and irregular sleep are associated with neuropsychological deficits including more impulsive responding in lab-based tasks. Although many lab-based experiments ask participants to report their sleep patterns, few studies have analyzed how potential changes in sleep affect their findings. Utilizing data from a previously collected study, this study aims to investigate relations between sleep (i.e., sleep duration and changes in sleep duration) and performance-based measures of inhibition among female college students.

Participants (n = 39) were majority first-year students (Mage =19.27) and Caucasian (51%). Participants were recruited to participate in a larger study exploring how food commercials affect inhibitory control. Participants were randomized to each study condition (watching a food or non-food commercial) over two visits to the lab (T1 and T2). During both visits, they completed questionnaires asking about their 1) sleep duration the night before and 2) their “typical” sleep duration to capture changes in sleep duration. They also completed a computer-based stop signal task (SST) which required them to correctly identify healthy food images (stop signal accuracy [SSA] healthy) and unhealthy food images (SSA unhealthy) while inhibiting their response during a stop signal delay (SSD) which became increasingly more difficult (or delayed) as they successfully progressed. Since the main aim of the study was to explore the impact of sleep, analyses controlled for study condition. Analyses involving changes in sleep also accounted for sleep duration the night before the study visit.

On average, students reported being under slept the night before the lab visit, reporting that they got 38 minutes less sleep than their “typical” sleep (7 hrs 3 min). Hierarchical regression analyses demonstrated that sleep duration the night before the lab visit was not associated with inhibition (i.e., SSA unhealthy, SSA healthy, SSD). In contrast, a greater change in sleep, or getting less sleep than “typical,” was associated with worsened inhibition across inhibition variables (SSA healthy, SSA unhealthy, SSD) above and beyond sleep duration at T1. At T2, only one analysis remained significant, such that getting less sleep than “typical” was associated with lower accuracy of appropriately identifying unhealthy images (SSA unhealthy) whereas other analyses only approached statistical significance.

These findings suggest that changes in sleep, or getting less sleep than typical, may impact inhibition performance measured in a lab, even when accounting for how much sleep they got the night before. Specifically, getting less sleep than typical was associated with reduced accuracy in selecting unhealthy images, a finding that was consistent across two visits to the lab. These preliminary findings offer opportunities for lab-based experiments to investigate the role of sleep when measuring inhibition performance. Further, clinicians conducting neuropsychological assessments in clinical settings may benefit from assessing sleep the night before the appointment and determine if this represents a change from their typical sleep pattern.

Caregivers to persons with dementia (PWD) consistently report lower sleep quality than non-caregiving controls. Low sleep quality, in addition to being unhealthy for the caregiver, may also impact the quality of care provided to the PWD. One factor that may contribute to poor sleep among caregivers is neurobehavioral symptoms (NBS) of the PWD. NBS, such as mood changes, lack of motivation, and disinhibition, are consistently rated as some of the most distressing symptoms by caregivers. Furthermore, they can include some symptoms related to sleep, such as nighttime wandering and REM sleep behaviors. Prior correlational research indicates a very strong association between NBS of the PWD and sleep quality of the caregiver. However, there are third variables, particularly demographics of the caregiver, which may better explain this relationship. When these variables are controlled in research, findings on the association between PWD NBS and caregiver sleep quality are mixed. Thus, we sought to investigate the relation between PWD NBS and caregiver sleep quality while controlling for caregiver demographics.

Fifty caregivers to PWD completed a survey containing the Mild Behavioral Impairment Checklist as a measure of PWD NBS, the Pittsburgh Sleep Quality Index as a measure of caregiver sleep quality, and caregiver demographics. The relationship between PWD NBS and caregiver sleep quality was assessed using hierarchical linear regression. First, we examined the relationship between caregiver demographics (age, gender, income) and caregiver sleep quality. Second, we added NBS to the model to assess for incremental predictive utility by examining change in R2.

A significant correlation was found between PWD NBS and caregiver sleep quality, with higher PWD NBS associated with worse caregiver sleep quality (r(48) = .34, p = .014). A hierarchal regression found that caregiver demographics explained a non-significant proportion of variance in reported caregiver sleep quality (F(3, 44) = 1.05, p = .382, R2 = .07). When PWD NBS was added in model two, there was a significant change in variance explained in the overall model (F(1,43) = 2.65, p = .046, AR2 = .13, R2 = .20). Across both models, PWD NBS was the only variable significantly associated with caregiver sleep quality (B = .08, p = .011).

In line with previous studies, these results indicate a moderate relationship between PWD NBS and caregiver sleep quality. Furthermore, findings suggested that PWD NBS is a risk factor for poor caregiver sleep quality, above and beyond caregiver demographic characteristics. Individuals designing interventions aimed at improving caregiver sleep quality should consider including PWD NBS as an intervention target. Future research should replicate these findings in a longitudinal sample to further evaluate causality.