Concurrent brain structural and functional alterations in the thalamus of adult survivors of childhood brain tumors: a multimodal MRI study.

Adult survivors of childhood brain tumors often present with cognitive deficits that affect their quality of life. Studying brain structure and function in brain tumor survivors can help understand the underlying mechanisms of their cognitive deficits to improve long-term prognosis of these patients. This study analyzed voxel-based morphometry (VBM) derived from T1-weighted MRI and the amplitude of low-frequency fluctuation (ALFF) from resting-state functional magnetic resonance imaging (rs-fMRI) to examine the structural and functional alterations in 35 brain tumor survivors using 35 matching healthy individuals as controls. Compared with healthy controls, brain tumor survivors had decreased gray matter volumes (GMV) in the thalamus and increased GMV in the superior frontal gyrus. Functionally, brain tumor survivors had lower ALFF values in the inferior temporal gyrus and medial prefrontal area and higher ALFF values in the thalamus. Importantly, we found concurrent but negatively correlated structural and functional alterations in the thalamus based on observed significant differences in GMV and ALFF values. These findings on concurrent brain structural and functional alterations provide new insights towards a better understanding of the cognitive deficits in brain tumor survivors.

A deep learning approach for mental health quality prediction using functional network connectivity and assessment data.

While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approaches that visualize brain activity to questionnaires in the context of individualized prediction, we can gain new insights into the biology and behavioral aspects of brain health. Resting-state fMRI (rs-fMRI) can be used to identify biomarkers of these conditions and study patterns of abnormal connectivity. In this work, we estimate mental health quality for individual participants using static functional network connectivity (sFNC) data from rs-fMRI. The deep learning model uses the sFNC data as input to predict four categories of mental health quality and visualize the neural patterns indicative of each group. We used guided gradient class activation maps (guided Grad-CAM) to identify the most discriminative sFNC patterns. The effectiveness of this model was validated using the UK Biobank dataset, in which we showed that our approach outperformed four alternative models by 4-18% accuracy. The proposed model's performance evaluation yielded a classification accuracy of 76%, 78%, 88%, and 98% for the excellent, good, fair, and poor mental health categories, with poor mental health accuracy being the highest. The findings show distinct sFNC patterns across each group. The patterns associated with excellent mental health consist of the cerebellar-subcortical regions, whereas the most prominent areas in the poor mental health category are in the sensorimotor and visual domains. Thus the combination of rs-fMRI and deep learning opens a promising path for developing a comprehensive framework to evaluate and measure mental health. Moreover, this approach had the potential to guide the development of personalized interventions and enable the monitoring of treatment response. Overall this highlights the crucial role of advanced imaging modalities and deep learning algorithms in advancing our understanding and management of mental health.

Sleep quality and executive function in a diverse sample of healthy young adults.

Few studies examine the relationship between sleep and executive function in diverse samples of young adults. Our research aims to fill this gap by analyzing how self-reported sleep quality is related to informant-rated executive function as a whole and its working memory component in a diverse sample of 29 healthy college students. Using the self-report measure, the Pittsburgh Sleep Quality Index (PSQI), we divided our sample into two groups based on cutoff criteria (score ≥5: poor sleep): good sleep quality (n = 11) and poor sleep quality (n = 18). Participants were on average 20.86 years old. Informants rated participants' executive functioning and working memory using the Frontal Systems Behavior Scale (FrSBe) and Behavior Rating Inventory of Executive Function (BRIEF). Individuals in the poor sleep quality group were reported as having significantly worse executive function and working memory scores. Young adult college students who report less than 7 hours of sleep per night have lower scores on informant measures of working memory and executive function. This study raises awareness about how self-reported sleep experiences are related to other's observation of cognitive abilities in everyday life in a diverse young adult sample.

Concordance of informant and self-reported ratings on the Frontal Systems Behavior Scale in adult survivors of pediatric brain tumor.

OBJECTIVE: It has been theorized that pediatric brain tumor survivors may have reduced insight into their executive functioning. Agreement between informants and survivors has been used to probe this theory, but findings have been inconsistent. This study sought to expand on prior work by examining the relationship between participant role and ratings on the Frontal Systems Behavior Scale (FrSBe) among 73 adult survivors and their informants. This study also sought to test whether agreement on scores varied as a function of tumor treatment. METHOD: Dyadic mixed effects models examined the relationship between participant ratings on FrSBe subscales and the role of a participant (survivor or informant). Intraclass correlations (ICC) were used to calculate reliable change indices to evaluate significant divergence in self and informant agreement. RESULTS: Dyadic mixed effects models showed an insignificant relationship between participant role and ratings on the FrSBe apathy and executive dysfunction subscales. Participant role was related to ratings on the disinhibition subscale of the FrSBe. The ICC for apathy was ICC = .583, for disinhibition ICC = .420, and for executive dysfunction ICC = .373. Significant divergence in scores did not vary by history of chemoradiation. CONCLUSIONS: Results demonstrate an effect of role on one FrSBe subscale and weak to moderate agreement between survivor and informant scores, which suggests that agreement between informants and survivors varies by FrSBe domain. The strongest relationship between survivors and informants was seen on apathy, which suggests that apathy is a shared concern for survivors and their families.

White matter predictors of PTSD: Testing different machine learning models in a sample of Black American women.

BACKGROUND: Machine learning neuroimaging studies of posttraumatic stress disorder (PTSD) show promise for identifying neurobiological signatures of PTSD. However, studies to date, have largely evaluated a single machine learning approach, and few studies have examined white matter microstructure as a predictor of PTSD. Further, individuals from minoritized racial groups, specifically, Black individuals, who experience disproportionate trauma frequency, and have relatively higher rates of PTSD, have been underrepresented in these studies. We used four different machine learning models to test white matter microstructure classifiers of PTSD in a sample of trauma-exposed Black American women with and without PTSD. METHOD: Participants included 45 Black women with PTSD and 89 trauma-exposed controls recruited from an ongoing trauma study. Current PTSD presence was estimated using the Clinician-Administered PTSD Scale. Average fractional anisotropy of 53 white matter tracts served as input features. Additional exploratory analysis incorporated estimates of interpersonal and structural racism exposure. Classification models included linear support vector machine, radial basis function support vector machine, multilayer perceptron, and random forest. RESULTS: Performance varied notably between models. With white matter features along, linear support vector machine demonstrated the best model fit and reached an average AUC = 0.643. Inclusion of estimates of exposure to racism increased linear support vector machine performance (AUC = 0.808). CONCLUSIONS: White matter microstructure had limited ability to predict PTSD presence in this sample. These results may indicate that the relationship between white matter microstructure and PTSD may be nuanced across race and gender spectrums.

Within-Individual BOLD Signal Variability and its Implications for Task-Based Cognition: A Systematic Review.

Within-individual blood oxygen level-dependent (BOLD) signal variability, intrinsic moment-to-moment signal fluctuations within a single individual in specific voxels across a given time course, is a relatively new metric recognized in the neuroimaging literature. Within-individual BOLD signal variability has been postulated to provide information beyond that provided by mean-based analysis. Synthesis of the literature using within-individual BOLD signal variability methodology to examine various cognitive domains is needed to understand how intrinsic signal fluctuations contribute to optimal performance. This systematic review summarizes and integrates this literature to assess task-based cognitive performance in healthy groups and few clinical groups. Included papers were published through October 17, 2022. Searches were conducted on PubMed and APA PsycInfo. Studies eligible for inclusion used within-individual BOLD signal variability methodology to examine BOLD signal fluctuations during task-based functional magnetic resonance imaging (fMRI) and/or examined relationships between task-based BOLD signal variability and out-of-scanner behavioral measure performance, were in English, and were empirical research studies. Data from each of the included 19 studies were extracted and study quality was systematically assessed. Results suggest that variability patterns for different cognitive domains across the lifespan (ages 7-85) may depend on task demands, measures, variability quantification method used, and age. As neuroimaging methods explore individual-level contributions to cognition, within-individual BOLD signal variability may be a meaningful metric that can inform understanding of neurocognitive performance. Further research in understudied domains/populations, and with consistent quantification methods/cognitive measures, will help conceptualize how intrinsic BOLD variability impacts cognitive abilities in healthy and clinical groups.

The role of tax-filing status in uncovering socioeconomic and physical activity differences in college-aged students.

Objective:  This study examined relationships among multifaceted measures of socioeconomic status (SES) and physical activity (PA) in undergraduates. Participants were classified into dependent and independent tax filers to encapsulate the atypical divide in financial responsibility. Participants: 366 diverse American undergraduates. Methods: Participants completed an online survey including three SES metrics and the International Physical Activity Questionnaire. Results: Participants engaged in the same amount of total PA, albeit different proportions depending on SES measure and PA type. Independent tax filers engaged in more occupational PA than dependent tax filers, regardless of SES. Students with low SES engaged in less leisure-time PA than students with high SES. Conclusion: Household Material Hardship and SES proxy measures should be considered in the context of tax filing status among undergraduates. Greater precision with multifactorial SES measures will assist in providing the nuanced context when optimizing interventions and reducing barriers to increase PA in young adults.

A Systematic Review of Host Genomic Variation and Neuropsychological Outcomes for Pediatric Cancer Survivors.

Pediatric survivors of brain tumors and acute lymphoblastic leukemia (ALL) are at risk for long-term deficits in their neuropsychological functioning. Researchers have begun examining associations between germline single nucleotide polymorphisms (SNPs), which interact with cancer treatment, and neuropsychological outcomes. This review synthesizes the impact of treatment-related toxicity from germline SNPs by neuropsychological domain (i.e., working memory, processing speed, psychological functioning) in pediatric survivors. By focusing on specific neuropsychological domains, this review will examine outcome measurement and critique methodology. Fourteen studies were identified and included in this review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). All studies were published in peer-reviewed journals in English by November 24th, 2021. Reviewed studies were not of sufficient quality for a meta-analysis due to varying measurement strategies, gaps in reported descriptive variables, and low power. All neuropsychological domains evaluated in this review had associations with SNPs, except fine motor and visual integration abilities. Only five SNPs had consistent neuropsychological findings in more than one study or cohort. Future research and replication studies should use validated measures of discrete skills that are central to empirically validated models of survivors' long-term outcomes (i.e., attention, working memory, processing speed). Researchers should examine SNPs across pathophysiological pathways to investigate additive genetic risk in pediatric cancer survivors. Two SNPs were identified that confer resiliency in neuropsychological functioning, and future work should investigate resiliency genotypes and their underlying biological mechanisms.

A systematic review of pediatric neuropsychological outcomes with proton versus photon radiation therapy: A call for equity in access to treatment.

OBJECTIVE: There is increasing interest in the utilization of proton beam radiation therapy (PRT) to treat pediatric brain tumors based upon presumed advantages over traditional photon radiation therapy (XRT). PRT provides more conformal radiation to the tumor with reduced dose to healthy brain parenchyma. Less radiation exposure to brain tissue beyond the tumor is thought to reduce neuropsychological sequelae. This systematic review aimed to provide an overview of published studies comparing neuropsychological outcomes between PRT and XRT. METHOD: PubMed, PsychINFO, Embase, Web of Science, Scopus, and Cochrane were systematically searched for peer-reviewed published studies that compared neuropsychological outcomes between PRT and XRT in pediatric brain tumor patients. RESULTS: Eight studies were included. Six of the studies utilized retrospective neuropsychological data; the majority were longitudinal studies (n = 5). XRT was found to result in lower neuropsychological functioning across time. PRT was associated with generally stable neuropsychological functioning across time, with the exception of working memory and processing speed, which showed variable outcomes across studies. However, studies inconsistently included or considered medical and sociodemographic differences between treatment groups, which may have impacted neuropsychological outcomes. CONCLUSIONS: Despite methodological limitations, including limited baseline neuropsychological evaluations, temporal variability between radiation treatment and first evaluation or initial and follow-up evaluations, and heterogenous samples, there is emerging evidence of sociodemographic inequities in access to PRT. With more institutions dedicating funding towards PRT, there may be the opportunity to objectively evaluate the neuropsychological benefits of patients matched on medical and sociodemographic variables.

Relationships Among Structural Neuroimaging and Neurocognitive Outcomes in Adolescents and Young Adults with Congenital Heart Disease: A Systematic Review.

Congenital heart disease (CHD) is the most common cause of major congenital anomalies in the world. Disruptions to brain development in this population may impact cognitive outcomes. As individuals with CHD age, understanding of long-term neurocognitive and brain outcomes is essential. Synthesis of the current literature of brain-behavior relationships in adolescents and young adults with CHD is needed to understand long-term outcomes and identify literature gaps. This systematic review summarizes and integrates the current literature on the relationship between structural neuroimaging and neurocognitive outcomes in adolescents and young adults with CHD. Included papers were published through August 2, 2021. Searches were conducted on Pubmed and APA PsycInfo. Studies were eligible for inclusion if they evaluated adolescents or young adults (ages 10-35) with CHD, and without genetic comorbidity. Studies explored relationships among structural neuroimaging and neurocognitive outcomes, were in English, and were an empirical research study. A total of 22 papers were included in the current review. Data from each study was extracted and included in a table for comparison along with a systematic assessment of study quality. Results suggest worse brain outcomes (i.e., brain abnormality, reduced volume, lower fractional anisotropy, and brain topology) are related to poorer performance in neuropsychological domains of intelligence, memory, and executive functioning. Consistently, poorer memory performance was related to lower hippocampal and temporal region volumes. Statistically significant brain-behavior relationships in adolescents and young adults with CHD are generally observed across studies but there is a lack of consistency in investigated neuropsychological constructs and brain regions to be able to make specific conclusions. Further research with adult samples of CHD is needed to better understand the long-term impacts of early neurological insult.

Inhibition explains the relationship between the efficiency of brain networks and adaptive outcomes in pediatric brain tumor survivors.

OBJECTIVE: Research has found altered brain network connectivity in pediatric brain tumor survivors. Efficient brain networks are critical for performing complex behaviors involved in adaptive functioning (AF). The present study explored relationships between structural brain network characteristics and AF in survivors. We examined whether this relationship is mediated by inhibition and cognitive flexibility, important cognitive abilities for AF. METHOD: Thirty-seven young adult survivors and 37 matched healthy controls (HC; overall Mage = 23.1, SD = 4.9) underwent neuropsychological assessment. Informants completed the Scales of Independent Behavior-Revised (SIB-R) interview. Color-Word Interference Inhibition and Inhibition-Switching from the Delis-Kaplan Executive Functioning System measured inhibition and cognitive flexibility performance. Deterministic tractography was performed on diffusion-weighted imaging, the Automated Anatomical Labeling (AAL) atlas defined nodes, and edges were the average fractional anisotropy between nodes. Global efficiency (GE), average clustering coefficient (CC), and density were computed. Partial correlations and analysis of indirect effects were conducted. RESULTS: There were significant relationships between GE and all SIB-R scales, but findings with CC were limited to two subscales. Inhibition was moderately related to GE, but this was no longer significant after Holm's correction. Cognitive flexibility was not found to be related to graph metrics. Finally, significant indirect effects were found such that inhibition explained the relationship between GE and SIB-R Motor and Social/Communication. CONCLUSIONS: Based on these findings, higher levels of brain network integration, as measured by GE, is related to inhibition in survivors, which facilitates proficient adaptive motor and social/communication skills. Future work should investigate tumor location and treatment factors as potential moderators of the relationships found in this study to better understand specific risk factors in this group. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

White matter pathways associated with empathy in females: A DTI investigation.

Empathy is a component of social cognition that allows us to understand, perceive, experience, and respond to the emotional state of others. In this study, we seek to build on previous research that suggests that sex and hormone levels may impact white matter microstructure. These white matter microstructural differences may influence social cognition. We examine the fractional anisotropy (FA) of white matter pathways associated with the complex human process of empathy in healthy young adult females during the self-reported luteal phase of their menstrual cycle. We used tract-based spatial statistics to perform statistical comparisons of FA and conducted multiple linear regression analysis to examine the strength of association between white matter FA and scores on the Empathy Quotient (EQ), a self-report questionnaire in which individuals report how much they agree or disagree with 60 statements pertaining to their empathic tendencies. Results identified a significant negative relationship between EQ scores and FA within five clusters of white matter: in the left forceps minor/body of the corpus callosum, left corticospinal tract, intraparietal sulcus/primary somatosensory cortex, superior longitudinal fasciculus, and right inferior fronto-occipital fasciculus/forceps minor. These consistent findings across clusters suggest that lower self-reported empathy is related to higher FA across healthy young females in specific white matter regions during the menstrual luteal phase. Future research should seek to examine if self-reported empathy varies across the menstrual cycle, using blood samples to confirm cycle phase and hormone levels.

Cerebellum-cingulo-opercular network connectivity strengthens in adolescence and supports attention efficiency only in childhood.

Posterior cerebellar lobules are active during executive function (EF) tasks and are functionally connected to EF-associated cortical networks such as the fronto-parietal network (FPN) and cingulo-opercular network (CON). Despite evidence that EF and cerebello-cortical connectivity develop on a similar time scale, developmental relationships between EFs and cerebello-cortical connectivity have not been directly investigated. We therefore examined relationships between cerebello-cortical connectivity and EF performance in a typically developing sample ages 8 - 21. Resting-state functional connectivity between posterior cerebellum and FPN (middle frontal gyrus, posterior parietal lobules)/CON (anterior cingulate, insula) was computed using independent components analysis. Using conditional process models, we tested the hypothesis that cerebellum - PFC connectivity would mediate the relationship between FPN/CON and EF, and that cerebello-cortical connectivity, and connectivity - EF relationships, would become stronger with increasing age. Cerebellum - CON connectivity strengthened with age, but a relationship between cerebellum - anterior cingulate cortex (ACC) connectivity and attention efficiency was significant only in younger children. Results suggest that during childhood, the posterior cerebellum and ACC may support sustained and executive attention, though age has a stronger effect on EF. These findings may help to guide further studies of executive dysfunction in neurodevelopmental disorders.

Within-individual BOLD signal variability in the N-back task and its associations with vigilance and working memory.

In a group of healthy adults (N = 48), this study evaluated how fMRI Blood Oxygen Level-Dependent (BOLD) signal variability differed across letter n-back task load and quantified the extent to which BOLD signal variability was associated with in-scanner accuracy and reaction time as well as out-of-scanner measures of vigilance and working memory (WM). Within-individual BOLD signal variability in regions of interest (ROIs, identified as peak coordinates in an attention/vigilance and WM network using Neurosynth) was differentially modulated across vigilance and WM trials. Within-individual BOLD signal variability was significantly greater across the majority of the ROIs in the working memory trials (2- and 3-back trials) compared to 0-back trials. Notably, this increased variability across the network was accompanied by significantly less variability in the left cingulate gyrus and left inferior temporal lobe during the working memory trials. Significantly fewer differences in within-individual BOLD signal variability were identified for vigilance trials (0- and 1-back trials) compared to crosshair. We hypothesized that increased BOLD signal variability would be associated with n-back task performance and with out-of-scanner measures of vigilance (Digit Span Forward) and WM (Auditory Consonant Trigrams and Digit Span Backward). These results were non-significant after correcting for multiple comparisons. Furthermore, using multivariate analyses (partial least squares regression; PLS-R), within-individual BOLD signal variability in regions associated with a WM-vigilance network did not significantly predict out-of-scanner test performance after appropriate cross validation, yet provided a promising trend for WM trials; greater within-individual BOLD signal variability during WM n-back trials was associated with decreased performance on all included neuropsychological measures, which provides partial support for previous findings. This study demonstrates that patterns of variability differ based on task load in the scanner and illustrates an intriguing association between within-individual BOLD signal variability and out-of-scanner behavioral performance that may be better explored in future studies with a larger sample size.

MTHFR single nucleotide polymorphism associated with working memory in pediatric medulloblastoma survivors.

Background: Associations have been found between single nucleotide polymorphisms (SNPs) in the MTHFR gene and cognitive outcomes in cancer survivors. Prior research has demonstrated that the presence of MTHFR SNPs (rs1801131 and rs1801133) in survivors of acute lymphoblastic leukemia (ALL) corresponds to impairments in attention and executive functioning. The current study examines the associations between rs1801131 and/or rs1801133 SNPs and cognitive performance in long-term survivors of medulloblastoma. Procedure: Eighteen pediatric medulloblastoma survivors, on average 12.42 years post-diagnosis, completed the Digit Span Forward, Digit Span Backward, California Verbal Learning Test Trial 1, and Auditory Consonant Trigrams tests. MTHFR SNPs were detected using whole genome sequencing data and custom scripts within R software. Results: Survivors with a rs1801131 SNP performed significantly worse on Digit Span Backward than survivors without this SNP exhibiting a large effect (p = 0.049; d = 0.95). Survivors with a rs1801131 SNP performed worse on Digit Span Forward (d = 0.478) and the CVLT Trial 1 (d = 0.417) with medium effect sizes. In contrast to rs1801131, relationships were not identified between a rs1801133 SNP and these performance measures. Conclusions: Our findings demonstrate the potential links between MTHFR SNPs and cognitive outcomes following treatment in brain tumor survivors. The current findings establish a novel relationship between rs1801131 and working memory in medulloblastoma. Increases in homocysteine levels and oxidative damage from radiation may lead to adverse long-term outcomes. This establishes the need to look beyond leukemia and methotrexate treatment to consider the risk of MTHFR SNPs for medulloblastoma survivors.

Considerations for Reliable Digit Span as a performance validity test for long-term survivors of childhood brain tumors.

The Reliable Digit Span (RDS) is a performance validity test (PVT) used widely within non-clinical samples, but its utility is in question in clinical groups with cognitive impairment. To investigate, RDS scores were calculated and correlated with the Neurological Predictor Scale, an informant-reported Activities of Daily Living score, and a proxy measure of intelligence (Vocabulary) for 83 adult survivors of childhood brain tumors and 105 healthy controls. Analyses were covaried for age at examination. Participants were divided into passing and failing groups at each RDS cutoff, and ANCOVAs for each of the three variables of interest covaried for age at the examination were run. RDS was correlated with all three variables of interest in survivors but only Vocabulary in controls. At the ≤7 cutoff, passing and failing survivors demonstrated significant differences across all variables of interest, while passing and failing controls differed only on Vocabulary. Differences were also found between passing and failing survivors at lower cutoffs. RDS is related to and likely impacted by various neurological and cognitive challenges faced by brain tumor survivors. Using the standard RDS cutoff of ≤7 may result in inaccurate interpretation of valid performance in this population; therefore, the use of other PVTs is recommended.

Graph Theoretical Analysis of Brain Network Characteristics in Brain Tumor Patients: A Systematic Review.

Graph theory is a branch of mathematics that allows for the characterization of complex networks, and has rapidly grown in popularity in network neuroscience in recent years. Researchers have begun to use graph theory to describe the brain networks of individuals with brain tumors to shed light on disrupted networks. This systematic review summarizes the current literature on graph theoretical analysis of magnetic resonance imaging data in the brain tumor population with particular attention paid to treatment effects and other clinical factors. Included papers were published through June 24th, 2020. Searches were conducted on Pubmed, PsycInfo, and Web of Science using the search terms (graph theory OR graph analysis) AND (brain tumor OR brain tumour OR brain neoplasm) AND (MRI OR EEG OR MEG). Studies were eligible for inclusion if they: evaluated participants with a primary brain tumor, used graph theoretical analyses on structural or functional MRI data, MEG, or EEG, were in English, and were an empirical research study. Seventeen papers met criteria for inclusion. Results suggest alterations in network properties are often found in people with brain tumors, although the directions of differences are inconsistent and few studies reported effect sizes. The most consistent finding suggests increased network segregation. Changes are most prominent with more intense treatment, in hub regions, and with factors such as faster tumor growth. The use of graph theory to study brain tumor patients is in its infancy, though some conclusions can be drawn. Future studies should focus on treatment factors, changes over time, and correlations with functional outcomes to better identify those in need of early intervention.

White matter hyperintensities relate to executive dysfunction, apathy, but not disinhibition in long-term adult survivors of pediatric cerebellar tumor.

White matter hyperintensities (WMHs) have been related to executive dysfunction, apathy and disinhibition in a wide range of neurological populations. However, this relationship has not been examined in survivors of pediatric brain tumor. The goal of this study was to investigate how executive dysfunction, apathy, and disinhibition relate to WMHs in 31 long-term survivors of pediatric cerebellar brain tumor and 58 controls, using informant-report data from the Frontal Systems Behavior Scale. Total WMH volume was quantified using the Lesion Growth Algorithm. Further, periventricular, and subcortical volumes were identified based on proximity to custom ventricle masks generated in FSL. A ratio of WMH volume to whole brain volume was used to obtain normalized WMH volumes. Additionally, a multivariate regression analysis was performed. On average, informant-report scores were within normal limits and only executive dysfunction was significantly higher in survivors compared to controls (t(47.9) = -2.4, p=.023). Informants reported clinically significant levels of apathy in 32.3% of survivors. Informants also reported clinically significant executive dysfunction in 19.4 % of survivors and clinically significant disinhibition in, again, 19.4 % of survivors. Increased volume of WMHs was positively correlated with executive dysfunction (r = 0.33, p = 0.02) and apathy (r = 0.23, p = .04). Similarly, multivariate regression demonstrated correlations with executive dysfunction (p=.05, FDR corrected) and apathy (p=.05, FDR corrected). Exploratory analysis demonstrated an interaction wherein the relationship between total WMHs and executive dysfunction and apathy depends on whether the participant was a survivor. The current findings indicate that increased WMH volumes are associated with higher ratings of apathy and executive dysfunction, and that these results are likely unique to cerebellar brain tumor survivors. WMH burden may serve as a useful marker to identify survivors at risk of executive dysfunction or increased apathy.