Neurofibromatosis type 1 (NF1) is a neurogenetic disorder associated with increased risk of neuropsychological challenges. While research has evidenced associations between environmental factors and neurocognitive development, few studies have examined the role that socioeconomic status (SES) plays on neuropsychological development in NF1. The aim of this study is to examine the relationship between community SES and cognitive/psychosocial outcomes in a neuropsychology clinic sample of pediatric NF1 patients.

The sample consisted of 47 youth with NF1 (M age=11.91, SD=3.69). The sample was 51.1% female, 72.3% White, 19.1% Black/African American, and 4.3% Hispanic. All participants had completed neuropsychological assessments for clinical purposes at an outpatient clinic in an urban, midwestern medical center. Data from neuropsychological measures and demographic information were pulled from records and entered into a de-identified dataset. The Wechsler Intelligence Scales, California Verbal Learning Test (CVLT), Woodcock Johnson Test of Achievement, and parent- and teacher-report versions of the Behavior Assessment System for Children (BASC) and the Behavior Rating Inventory of Executive Function (BRIEF) were used to examine broad neuropsychological functioning. The Area Deprivation Index (ADI) measures SES at the community level, as opposed to the individual level. It is composed of 17 factors related to education, poverty, employment, and housing. This information is used to assign index scores by zip code, with scores on a scale of 110 and 10 indicating the highest level of socioeconomic disadvantage. Mean ADI for this sample was 4.02 (SD=1.93).

Mean neurocognitive scores were consistently in the low average to average range. Parent and teacher scores on the BASC were in the average range. Mean scores on the BRIEF indicated Global Executive Composite scores in the mildly and moderately elevated range for parents and teachers, respectively. Correlational analyses revealed significant associations between ADI scores and immediate recall performance on the CVLT (Trials 1-5; r=.37; p=.03) and the BRIEF Planning and Organization subscale (r=.35; p=.02). Both remained significant after controlling for FSIQ (CVLT: rFSIQ=.49, p=.003; BRIEF: rFSIQ=.38; p=.02).

Mean cognitive scores for the sample are consistent with existing literature demonstrating that individuals with NF1 are at risk of reduced functioning in several domains. Sample mean ADI of 4 indicates a relatively low level of disadvantage in this sample., ADI was significantly associated with two variables, and greater deprivation was associated with better list learning performance. This suggests that the role of community SES is likely nuanced in how it impacts neurocognitive development. Results provide mild evidence of an association between ADI and learning and planning/organization. However, limitations to the current study, including a small sample size, and the retrospective nature, likely limits a more detailed understanding of the true relationship between community resources and cognitive and psychosocial outcomes among children with NF1. Future research comparing larger low and high ADI samples is necessary to fully examine the relationship between these factors. With better understanding of how community SES may limit or support neurocognitive and psychological growth in this population, more effective interventions can be designed for this group whose members are at notable risk for cognitive and psychological challenges.

Fahr’s disease is a rare genetic neurological disorder characterized by abnormal idiopathic calcification of the basal ganglia, typically with extrapyramidal symptoms, speech difficulty, behavioral disturbances, and progressive neurologic dysfunction. A small number of case reports have explored the neuropsychological profile of Fahr’s disease patients, and even fewer have followed the course of neuropsychological functioning over time.

A 53-year-old Asian woman presented for a neuropsychological reevaluation (2021) after experiencing a recurrence of memory difficulties and mood changes. Relevant medical history was significant for systemic lupus erythematosus (SLE) and Fahr’s disease. Following an episode of acute confusion, the patient underwent a head CT (2019) which revealed extensive calcification throughout the cerebellum, central pons, and periventricular and subcortical white matter, suggestive of Fahr’s disease. Two months later, she underwent an initial neuropsychological evaluation (2019), which demonstrated prominent attention and processing speed deficits contributing to variably impaired new learning and memory along with spatial planning and problem-solving difficulties. The etiology of her cognitive deficits was determined to likely reflect metabolic and immune instability, consistent with her history of SLE and Fahr’s disease. An updated CT (2021) revealed increased calcification throughout the bilateral corona radiata, basal ganglia, cerebellar hemispheres, and midbrain, which was determined to be compatible with progressive Fahr’s disease.

The patient’s neurocognitive profile from current neuropsychological testing (2021) was marked by notable deficits in attention and processing speed, delayed memory, problem solving, visuospatial reasoning, and motor dexterity. Compared to her initial evaluation, her cognitive profile remained stable save for a slight decline in processing speed. The largest change was seen within the psychiatric domain. Self-reported depressive symptoms involving anhedonia, concentration difficulties, and anxiety symptoms involving nervousness and tension were more pronounced in her current evaluation. In addition, she endorsed an increase in apathy compared to her initial evaluation.

The cognitive profile seen in this patient is consistent with the current literature relating to the clinical sequelae of Fahr’s disease in patients that eventually went on to develop dementia. Despite an increase in brain calcification seen on CT imaging over an 18-month interval, the patient’s neurocognitive profile remained relatively stable. An increase in psychiatric symptoms appeared to be the most prominent change over repeated neuropsychological assessment, which elucidates the heterogenous course of Fahr’s disease from a neuropsychological perspective. Further exploration of this disorder is warranted to better understand the clinical progression of symptoms over time.

Children with neurofibromatosis type 1 (NF1) commonly have academic problems. While the neuropsychological profile of children with NF1 is variable, NF1 results in difficulties in a variety of cognitive domains including intellectual functioning, attention, executive functioning. Previous studies have suggested that cognitive functioning may relate to academic functioning in children with NF1; however, the evidence is limited and warrants further examination. Thus, this study will investigate the contribution of several cognitive domains (intellectual functioning, attention, working memory) on academic performance for school age children with NF1.

The association between cognitive functioning and academic performance was examined for school age children with NF1 (n = 40; ages 9-13). Intellectual functioning was assessed using the Differential Abilities Scales, Second Edition School-Age Version (DAS-II) General Conceptual Ability (GCA) score. Attention was examined using the DAS-II Recall of Digits-Forward (DF) subtest and Flanker Inhibitory Control and Attention Test (Flanker). Working memory was assessed using the DAS-II Recall of Digits-Backward (DB) subtest. Academic performance was measured using the Wechsler Individual Achievement Test, Third Edition (WIAT-III) Word Reading (WR), Pseudoword Decoding (PD), Reading Comprehension (RC), Numerical Operations (NO), and Math Problem Solving (MPS) subtests.

WR was significantly associated with DAS-II GCA (rs(38) = .689, p < .001) and DF (rs(38) = .470, p = .002) in addition to Flanker (rs(34) = .364, p = .029), but not DAS-II DB (rs(38) = .292, p = .072). PD was significantly correlated with DAS-II GCA (rs(38) = .695, p < .001), DF (rs(38) = .394, p = .012), and DB (rs(38) = .474, p = .002), but not Flanker (rs(34) = .306, p = .070). RC was significantly associated with DAS-II GCA (rs(38) = .483, p = .002) and DF (rs(38) = .346, p = .029), but not DAS-II DB (rs(38) = .306, p = .055) and Flanker (rs(34) = .269, p = .112). NO was significantly correlated with DAS-II GCA fc(38) = .777, p < .001), DF (rs(38) = .555, p = < .001), and DB (rs(38) = .576, p < .001) as well as Flanker (rs(34) = .386, p = .020). MPS was significantly associated with DAS-II GCA (rs(38) = .685, p < .001), DF (rs(38) = .586, p < .001), and DB (rs(38) = .543, p < .001), in addition to Flanker (rs(34) = .420, p = .011). Significant associations had medium to large effect sizes, while non-significant correlations had small to medium effect sizes. Notably, most of the non-significant correlations had trend-level statistical significance.

Concurrent cognitive functioning (intellectual functioning, attention, working memory) was associated with reading-related and mathematics functioning in school age children with NF1. Notably, intellectual functioning had the strongest association with academic performance across all reading-related and mathematics tasks. Future studies should examine the association between academic performance and additional cognitive domains (e.g., language, visuospatial abilities) in children with NF1 across a wider age range to allow for examination of developmental patterns.

Depression has a well-established negative effect on cognitive functioning. Variations in the apolipoprotein e (APOE) and brain-derived neurotrophic factor (BDNF) genes likely contribute to this relationship. APOE4 and the BDNF Val66Met polymorphism are independently associated with late-life depression and cognitive dysfunction. The current study investigated the moderating effects of APOE4 and BDNFMet (i.e., the presence of the BDNF Val66Met polymorphism) on the relationship between depression and cognitive functioning in older adults.

The sample included 103 older adults drawn from two clinical trials who were recruited from the VA Palo Alto Health Care System (VAPAHCS) and the Stanford/VA Alzheimer’s Disease Center. Depression was diagnosed using the Mini Neuropsychiatric Interview for the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). The presence of an APOE4 and BDNFMet allele were dichotomized (i.e., yes/no) and determined using venipuncture. A comprehensive neuropsychological battery was used to assess attention (RAVLT Trial 1, WAIS-IV DSF), processing speed (TMTA, SDMT, Stroop Word, Stroop Color), working memory (WAIS-IV DSB, DSS), visuospatial functioning (JLO), language (VNT), memory (RAVLT Delayed Recall, WMS-IV Logical Memory II), and executive function (TMTB, Stroop Color-Word). Separate moderation analyses were conducted with depression as the predictor and APOE4 or BDNFMet status as the moderator using the SPSS PROCESS macro v4.0. Age was a covariate for models with processing speed, memory, language, and executive function as outcome variables.

Participants were largely male (93%) and White (75%). Ten percent met criteria for depression, 26% were APOE4 carriers, and 32% were BDNFMet carriers. The overall model examining depression, APOE4, and memory was significant (p < .01, R2 = .14). Depression was associated with lower memory performance (p < .05), however, APOE4 was not a significant moderator (p > .05). Similarly, the overall model examining depression, APOE4, and language was also significant (p < .05, R2 = .10). While the direct effects of depression and APOE4 on language were nonsignificant (p > .05), there was a significant two-way interaction between APOE4 and depression (p = .03). The overall model with depression, BDNFMet, and memory was significant (p < .001, R2 = .18). While neither depression nor BDNFMet had significant direct effects on memory (p > .05), a two-way interaction emerged between depression and BDNFMet (p = .05). Simple slopes analyses were used to further investigate significant interactions. Depression, APOE4, and BDNFMet did not significantly impact attention, processing speed, working memory, visuospatial functioning, or executive function, and no significant interactions were noted among variables. BDNFMet had no direct impact on language.

APOE4 and BDNFMet were found to differentially moderate the relationship between depression and cognition. Specifically, APOE4 carriers with depression had worse language performance compared to those who were healthy, depressed, or APOE4 carriers. BDNFMet carriers with depression performed worse on measures of memory compared to those who were healthy, depressed, or BDNFMet carriers. The treatment of depression in APOE4 and BDNFMet carriers may reduce associated cognitive impairments. Limitations and future implications are also discussed.

Rubinstein-Taybi Syndrome (RSTS) is a rare multiple congenital autosomal dominant disorder, with an incidence of roughly 1/125,000 live births (Milani et al., 2015). RSTS is characterized by several typical somatic characteristics and developmental disabilities. Common neurological findings in patients with RSTS include mild or moderate intellectual impairment and delays in gross motor development (Taupiac et al., 2021; Hamilton et al., 2016). Additional characteristics observed among individuals with RSTS include hyperactivity, abnormalities in expressive language, inattention, motor difficulties, noise intolerance, maladaptive behaviors, and fewer modes of communication (Waite et al., 2015). Due to the condition’s rarity, very few studies have investigated the cognitive profiles of RSTS patients with clinical features of EP300 (Type 2; Morel et al., 2018) in effected youth. This case study represents the first reported comprehensive neuropsychological description to our knowledge of an individual with this condition.

Participant: The participant is an 8-year, 4-month-old young girl referred for neuropsychological evaluation. LX was diagnosed with failure to thrive due to her small size, although she met all developmental milestones on time. LX was diagnosed with RSTS, Type 2 through genetic testing and blood work following concerns about small stature, microcephaly discovered on an MRI, and feeding difficulties. A 4kb deletion of 22q13.2 which contains exon 2 of EP300 was identified. Method: Medical and school records review, a clinical interview with LX and her family, neuropsychological assessment, and parent-and teacher-report questionnaires were used to assess functioning. Raw scores were standardized for comparison against age- and (where appropriate) gender-matched peers.

In addition to her medical diagnoses of RSTS, Type 2, and her prior diagnosis of ADHD - Combined Subtype, LX also met diagnostic criteria for Specific Learning Disability with Impairment in Reading and a Mixed Receptive-Expressive Language Disorder. LX also met criteria for Encephalopathy as characterized by weakness in visual perception, visuospatial judgment and reasoning, and working memory. LX demonstrated adaptive functioning weaknesses in domains such as self-direction, and self-care, while communication skills were reported to be average. Overall, LX’s current levels of general cognitive ability and adaptive functioning were consistent with Borderline Intellectual Functioning; however, the diagnosis was deferred at present. Parents and teachers reported difficulties with peer relationships, hyperactivity, and aggression, consistent with known features of this condition. Strengths were noted in verbal and nonverbal reasoning, spelling, math calculation, verbal and visual memory, and improvement in attention with medication, which all fell within the broadly average range of functioning.

LX’s presentation and pattern of neuropsychological findings are consistent with the current conceptualization of development in RSTS, Type 2, but reflect a more nuanced clinical picture. In particular, although general cognitive ability was borderline overall, deficits were largely circumscribed to spatial reasoning, with broadly average verbal and nonverbal reasoning abilities. This case highlights the importance of comprehensive neuropsychological testing of patients with RSTS. Reporting of general cognitive ability scores alone may obscure underlying patterns of relative strengths and weaknesses that have important ramifications for both targeted interventions and for a more positive prognosis related to functioning in academic, home, and community environments.

Children who suffer from brain insults (i.e., traumatic brain injury (TBI), chemotherapy and radiation treatment for brain tumors) are susceptible to late-emerging cognitive sequelae. Even with similar neurological risk variables, variability in long-term cognitive outcomes remains an area of investigation for researchers of acquired brain injury. Given the potential for genetic factors to influence response to chemoradiation, researchers have examined associations between germline, inherited, single nucleotide polymorphisms (SNPs), and neurocognitive outcomes for cancer survivors. Children who sustain an uncomplicated mild TBI generally recover without long-term neuropsychological consequences. However, TBI survivors have overlapping mechanism categories with cancer survivors through secondary injury variables that can be influenced by genomic variation (e.g., oxidative stress and neuroinflammation). Furthermore, the study of genomic vulnerability is limited in heterogenous groups of pediatric TBI survivors. This study aims to identify associations between genotype and long-term neurocognitive outcomes for acquired brain injury survivors by utilizing machine learning to uncover pathophysiological similarities and differences between groups.

Fourteen brain tumor survivors, 139 traumatic brain injury survivors, and 63 healthy, age-matched controls completed the Letter N-back task to obtain performances on core neurocognitive skills (attention, working memory, and processing speed). Ten targeted genotypes were examined across five pathophysiological pathways (neurotransmission, oxidative stress, neuroinflammation, plasticity, growth and repair, and folate metabolism). Data were trained and tested utilizing three regression machine learning models. Mean estimated error and R2 were generated for each neurocognitive outcome. A feature importance score for models with positive variance was generated to determine how predictive a given SNP is for neurocognitive outcomes.

Genotype only accounted for a small amount of variance in cognitive outcomes when all clinical groups were combined. The mean absolute error for the best-fitting models from analyses where all groups were combined decreased when groups were examined separately; however, the differences in model R2 values were not significant. The relationship between brain tumor survivors and processing speed performance depended on genotype. Two SNPs had positive feature importance at the interaction level (rs58225473 and rs1801394). These SNPs are located on the CACNB2 and MTR genes and have functional consequences for neurotransmission and folate metabolism. Models of traumatic brain injury survivors did not explain positive variance and could not be examined for feature importance. Additionally, even when removing the only mechanism of action that should not be relevant for TBI survivors (folate metabolism polymorphisms), the TBI models still did not explain positive variance.

Findings of the importance of two key SNPs on MTR and CACNB2 genes align with recent systematic reviews, which found associations between these polymorphisms and neuropsychological outcomes in more than one group or cohort of pediatric cancer survivors. Models for TBI survivors were limited by the heterogeneity of the group and ceiling effects on performance. An understanding of genetic vulnerabilities influenced by treatment and injury-related factors in acquired brain injury will inform our understanding of the developing and recovering childhood brain. The current study is an initial contribution to this goal and highlights the utility of machine learning methodology for future studies that examine the influence of genetic heterogeneity in pediatric acquired brain injury.

Wiedemann-Steiner syndrome (WSS) is a rare Mendelian disorder of epigenetic machinery caused by a mutation in KMT2A, with hallmark features that include intellectual disability and developmental delay. Animal models have helped identify the critical roles KMT2A plays in prefrontal neuron maturation and executive function (i.e. working memory) development. However, the neurobehavioral phenotype of individuals with WSS, including executive functioning, remains poorly characterized. Accordingly, this study aimed to 1.) examine the neurobehavioral profile (adaptive, psychosocial, and executive functioning) associated with WSS and 2.) the correlations between executive functioning and these domains.

A total of 25 mothers of individuals with WSS (13 females, Mean age=12.78 years, SD=7.88) completed a combination of parent-informant questionnaires. The caregivers completed the Adaptive Behavior Assessment System 3rd Edition (ABAS-3), the Strengths and Difficulties Questionnaire (SDQ), and a version of the Behavior Rating Inventory of Executive Function (BRIEF). Descriptive analyses were conducted to examine proportion of the sample with clinically significant concerns on the BRIEF and SDQ, and low to very low adaptive skills based on ratings on the ABAS-3. Partial correlations were computed to examine the relationships between overall executive functioning (BRIEF General Executive Composite, GEC) with adaptive domains (ABAS-3 Conceptual, Practical, Social), and psychosocial functioning (SDQ Emotional Problems, Conduct Problems, Hyperactivity, Peer Relations, Prosocial Behaviors) while accounting for age. Associations that survived Benjamin Hochberg correction are reported.

Of our sample, 64% were rated in the very elevated range for executive functioning problems (BRIEF GEC), with a greater proportion endorsing clinically significant concerns with behavior regulation (68%) relative to cognitive regulation (48%). Majority of participants was rated in the low or very low range for ABAS-3 General Adaptive Composite (72%), with a greater proportion showing problems in Practical (64%) and Conceptual Domains (64%) relative to Social Domain (44%). Among those who completed the SDQ, caregiver ratings implicate elevated Total Problems (90%) with greater concerns observed in Emotional Problems (62%), Hyperactivity (81%) and Peer Relationship difficulties (95%). After controlling for age, executive functioning difficulties were associated with weaker skills in the Conceptual (r=-0.56, p=0.003), Social (r=-0.44, p=0.028) and Practical domains (r=-0.51, p=0.009); as well as more Hyperactivity (r=0.49, p=0.025) and Conduct problems (r=0.58, p=0.007). Specifically, day-to-day challenges with executive functions were related to weaker adaptive skills in Self-Care (r=-0.54, p=0.006), Self-Direction (r=-0.53, p=0.007), and Communication (r=-0.49, p=0.01).

Individuals with WSS are at risk for executive functioning deficits, which in turn may impact the development of and/or day-today application of adaptive skills and behavior regulation. Future clinical research should further explore the development and neurophysiology of executive functions among those with WSS with multidisciplinary methods, including behavioral, cognitive and neurobiological metrics. Those working with individuals with WSS may consider executive functioning interventions, which may yield indirect benefits to self-regulation and daily use of life skills.

The purpose of the present study is to characterize the trajectory of internalizing and externalizing behaviors in children with NF1 longitudinally from the early childhood period to the school age period on a broad psychosocial norm-referenced measure using linear mixed model growth curves.

Children with NF1 (n=28) were seen at least once between the ages of 3-8 years old and then again between the ages of 9-13 years old. Parents completed the Behavior Assessment System for Children (BASC) Second Edition; the version of the BASC administered depended on age (i.e., preschool form or child form). Linear mixed model growth curve analyses were used to examine the developmental trajectories of children with NF1 on the following scales, which were selected due to findings in the literature: Externalizing Problems, Internalizing Problems, Hyperactivity, Anxiety, Depression, Attention, and Executive Function. T-scores (M=50, SD=10) were used. Higher scores indicate more challenges.

By using loess lines to qualitatively describe the patterns of ratings across time, it is evident that most scales (Externalizing Problems, Internalizing Problems, Hyperactivity, Attention Problems, Executive Function) demonstrated curvilinear trajectory patterns, with scores peaking in the 8-10-year-old range, then decreasing again. However, there was no statistically significant effect of age on any of the scales. Notably, trajectories largely included standard scores within the normative range (T-scores between 45-55).

Overall, the models also suggest that most children with NF1 are within the average range of functioning on all scales examined across the childhood period. Furthermore, with the exception of the Depression and Anxiety scales, ratings tend to peak around the 8-10-year period, and then decrease into early adolescence. Thus, when working with patients with NF1, it may be the case that clinicians note relative increases in challenges across these domains in late childhood, though these challenges may decrease over time during this age range. Linear growth curve modeling identified that the developmental trajectories of internalizing and externalizing behaviors of children with NF1, as rated by parents, remain stable across the childhood period. Importantly, low power may have contributed to the lack of observed age effects. Longitudinal research would be beneficial to capture patterns that may emerge in adolescence or adulthood.

To explore the usefulness of the Lowenstein-Acevedo Scales for Semantic Interference and Learning (LASSI-L) [Crocco et al, 2013], a novel memory-based cognitive stress test capitalizing on semantic interference, in Huntington’s Disease (HD).

12 healthy adults (HA) and 14 individuals with manifest HD were administered the LASSI-L as part of an annual research visit with the UCSD Huntington’s Disease Clinical Research Center (HDCRC.) Participants in each group were well matched with regard to age and education. Individuals with manifest HD had an average MoCA score of 26, total functional capacity score of 10, and total motor score of 21 suggesting that they were in the early stages of HD. The LASSI-L examines different types of semantic interference that occur in the learning/encoding process. There are free and cued recall trials for two lists of semantically related words with certain trials specific to different aspects of semantic interference including proactive, retroactive, and failure to recover from proactive interference. T-tests for all recall trials and number of intrusions for each trial were conducted between HA and those with HD to examine whether HD renders one more prone to semantic interference in both encoding and retrieval memory processes.

Individuals with HD recalled fewer words on average than HA across all recall trials except for the initial free recall of the first word list. HD individuals recalled significantly fewer (∼1.5) words during the initial (t=-2.8, p=.005, Cohen’s d=2.7) and secondary (t=-2.9, p=.003, Cohen’s d=2.6) cued recall trials from the words on the first list. Individuals with HD also recalled significantly fewer words on initial free recall (t=-2.9, p=.003, Cohen’s d=2.6) and cued recall trials of the second list, with the initial cued recall (t=-2.8, p=.005, Cohen’s d=3.1) sensitive to proactive semantic interference and the second cued recall (t=-3.3, p=.001, Cohen’s d=2.6) sensitive to failure to recover from proactive semantic interference. In addition, individuals with HD also recalled significantly fewer (∼2.2) words on delayed cued recall of the first list, a measure of retroactive semantic interference, than HA (t=-4.8, p<.001, Cohen’s d=2.4). Lastly, individuals with HD recalled fewer (∼4.1) words than HA on delayed free recall of both word lists (t=-3.5, p<.001, Cohen’s d=5.9). The groups did not differ significantly with regard to number of total intrusions per trial.

Overall, our study supports the usefulness of the LASSI-L for neuropsychological assessment of HD in clinical and research settings. In comparison to a demographically similar group of HA, individuals with manifest HD showed significant differences in frontally mediated retrieval processes as well as semantic interference processes that affect efficient encoding of novel information.

Psychosocial factors show a significant relationship between child behavior problems, family functioning, and cognitive performance in children with Sickle Cell Disease, marking those as important targets for intervention among this population. The purpose of this research is to address the effects of psychosocial factors impact on specific cognitive domains.

Archival data from the National Institutes of Health’s Cooperative Study of Sickle Cell Disease was used. Data was restricted to individuals aged 14 or younger (N= 2,408), with 47.8% (n = 1,152) identified as female and 52.2% (n = 1,256) as male. Black or African American (96.9%, n = 2,334) children made up the majority of the sample, with the remainder coded as “other” (2.8%, n = 68). The measures utilized included the Wechsler Intelligence Scale for Children-Revised (WISC-R), Wechsler Intelligence Scale for Children-Third Edition (WISC-III), Peabody Picture Vocabulary Test (PPVT), Achenbach Child Behavior Checklist, and Family Environment Scale (FES).

Bivariate correlations were completed with significant correlations found between FES and performance on the WISC-R/III and PPVT. Supportiveness subscale on the FES demonstrated several statistically significant correlations with WAIS FSIQ (r = .21, p = .000) as well as the Information (r = .22, p = .000), Similarities (r = .17, p = .001), Arithmetic (r = .13, p = .021), Block Design (r = .11, p = .036), Vocabulary (r = .22, p = .000), Object Assembly (r = .12, p = .033), Comprehension (r = .19, p = .000), and Digit Span (r = .13, p = .014) subscales. A statistically significant correlation was observed between the PPVT and the Supportiveness subscale (r = .34, p = .000).

Various areas of cognitive functioning are affected by family dynamics. Improvement in family functioning would benefit the cognitive functioning of children with SCD. To increase aspects of family functioning including supportiveness, early identification of children with SCD, targeted interventions, and family and/or individual therapy for caregivers are suggested.

To examine neurocognitive correlates of oculomotor performance among U.S. military personnel with history of mild traumatic brain injury (mTBI).

A series of studies (total n=356) were conducted to examine saccadic eye movements and manual button presses collected in response to attention stimuli, and to compare these findings to the results of standardized neuropsychological tests. Study 1 included n=27 with remote mTBI and n=54 controls who completed the Bethesda Eye and Attention Measure (BEAM), an eye tracking task that was designed to measure visual attention and executive function. In Study 2, n=51 with chronic mTBI and n=33 controls completed the Fusion n-Back task, an eye tracking task that was designed to assess the impact of working memory load on visual attention performance. Study 3 examined psychometric characteristics of BEAM among n=191 military personnel with remote mTBI. In all studies, participants completed eye tracking tasks, a structured TBI diagnostic interview, and a brief battery of standardized neuropsychological tests.

In Study 1, BEAM saccadic and manual metrics demonstrated strong reliability and high sensitivity to multiple cognitive cues designed to elicit spatial orienting, temporal alerting, executive interference, perceptual release (gap) and inhibition (n2p=.76, p<.001). However, corresponding saccadic and manual measurements were weakly related to each other, and only manual (not saccadic) measurements were related to estimated verbal intelligence or years of education. Standardized neuropsychological measures did not differ between groups, but mTBI participants were more likely to be impaired on saccadic metrics than controls.

In Study 2, Standardized cognitive measures and estimated premorbid intelligence were positively associated with all manual metrics from the Fusion n-Back test, but were not associated with mTBI history or with saccadic metrics. Fusion n-Back saccadic and manual metrics had strong reliability and complementary sensitivity to chronic mTBI, with combined predictive power of PPV=.78, NPV=.72, r2=.44 for classification of remote mild TBI vs. controls on the more cognitively-challenging 1-back task condition.

In Study 3, BEAM metrics including manual RT latency and consistency, saccadic RT consistency, and saccadic inhibition errors showed consistent correlations with standardized measures of visual attention, processing speed, task switching, working memory, and executive functions. Hierarchical regressions showed that BEAM saccadic and manual metrics were independently predictive of cognitive test performance, above and beyond effects of demographic factors and clinical characteristics.

Results demonstrated some surprising findings related to neurocognitive influences on oculomotor performance. While both saccadic and manual performance were strongly and similarly influenced by attention cues, these two modalities were only weakly correlated to one another. Additionally, manual metrics were more strongly and consistently related to standardized cognitive test performance and premorbid intelligence than saccadic metrics. However, saccadic metrics demonstrated superior sensitivity to remote/chronic mTBI relative to manual metrics and standardized neuropsychological measures. Overall, these results suggest that saccadic eye tracking measures may provide unique value in assessment of mTBI and neurocognitive functions that is complementary with more common forms of assessment relying upon somatomotor response modalities.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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