PyDesigner v1.0: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Magnetic Resonance Imaging.

PyDesigner is a Python-based software package based on the original Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline (Dv1) for dMRI preprocessing and tensor estimation. This software is openly provided for non-commercial research and may not be used for clinical care. PyDesigner combines tools from FSL and MRtrix3 to perform denoising, Gibbs ringing correction, eddy current motion correction, brain masking, image smoothing, and Rician bias correction to optimize the estimation of multiple diffusion measures. It can be used across platforms on Windows, Mac, and Linux to accurately derive commonly used metrics from DKI, DTI, WMTI, FBI, and FBWM datasets as well as tractography ODFs and .fib files. It is also file-format agnostic, accepting inputs in the form of .nii, .nii.gz, .mif, and dicom format. User-friendly and easy to install, this software also outputs quality control metrics illustrating signal-to-noise ratio graphs, outlier voxels, and head motion to evaluate data integrity. Additionally, this dMRI processing pipeline supports multiple echo-time dataset processing and features pipeline customization, allowing the user to specify which processes are employed and which outputs are produced to meet a variety of user needs.

A phase I trial of accelerated intermittent theta burst rTMS for amnestic MCI.

BACKGROUND: Emerging evidence suggests that repetitive transcranial magnetic stimulation (rTMS) enhances cognition in mild cognitive impairment (MCI). Accelerated intermittent theta burst stimulation (iTBS) rTMS protocols are promising as they substantially reduce burden by shortening the treatment course, but the safety, feasibility, and acceptability of iTBS have not been established in MCI. METHODS: 24 older adults with amnestic MCI (aMCI) due to possible Alzheimer's disease enrolled in a phase I trial of open-label accelerated iTBS to the left dorsolateral prefrontal cortex (8 stimulation sessions of 600 pulses of iTBS/day for 3 days). Participants rated common side effects during and after each session and retrospectively (at post-treatment and 4-week follow-up). They completed brain MRI (for safety assessments and electric field modeling), neuropsychiatric evaluations, and neuropsychological testing before and after treatment; a subset of measures was administered at follow-up. RESULTS: Retention was high (95%) and there were no adverse neuroradiological, neuropsychiatric, or neurocognitive effects of treatment. Participants reported high acceptability, minimal side effects, and low desire to quit despite some rating the treatment as tiring. Electric field modeling data suggest that all participants received safe and therapeutic cortical stimulation intensities. We observed a significant, large effect size (d=0.98) improvement in fluid cognition using the NIH Toolbox Cognition Battery from pre-treatment to post-treatment. CONCLUSIONS: Our findings support the safety, feasibility, and acceptability of accelerated iTBS in aMCI. In addition, we provide evidence of target engagement in the form of improved cognition following treatment. These promising results directly inform future trials aimed at optimizing treatment parameters. TRIAL REGISTRATION NUMBER: NCT04503096.

Cannabis Perceptions and Patterns of Use Among Older Adult Cancer Survivors.

Objectives: To descriptively assess cannabis perceptions and patterns of use among older adult cancer survivors in a state without a legal cannabis marketplace. Methods: This study used weighted prevalence estimates to cross-sectionally describe cannabis perceptions and patterns of use among older (65+) adults (N = 524) in a National Cancer Institute-designated center in a state without legal cannabis access. Results: Half (46%) had ever used cannabis (18% following diagnosis and 10% currently). Only 8% had discussed cannabis with their provider. For those using post-diagnosis, the most common reason was for pain (44%), followed by insomnia (43%), with smoking being the most common (40%) mode of use. Few (<3%) reported that cannabis had worsened any of their symptoms. Discussion: Even within a state without a legal cannabis marketplace, older cancer survivors might commonly use cannabis to alleviate health concerns but unlikely to discuss this with their providers.

Gray matter and episodic memory associations with olfaction in middle-aged to older adults.

BACKGROUND: Age-related declines in olfaction contribute to low quality of life and appear to occur with declines in cognitive function, including diminished episodic memory. We tested the hypothesis that low gray matter volume within cortical regions that support olfaction and episodic memory can explain age-related differences in olfactory and episodic memory functions. METHODS: T1-weighted images, Sniffin' Sticks olfactory measures, and the NIH Toolbox-Cognition Battery were administered to 131 middle-aged to older adults (50-86 years; 66% female). Correlation was used to examine the associations between these measures. A network-based image processing approach was then used to examine the degree to which spatial patterns of gray matter variance were related to the olfactory and cognitive measures. Structural equation modeling was used to characterize the relative specificity of olfactory, cognitive, gray matter, and aging associations. RESULTS: Olfactory threshold, discrimination, and identification exhibited small to medium effect size associations with episodic memory performance (rs = 0.27-0.42, ps < 0.002). Gray matter volume within medial temporal and orbitofrontal cortex was also related to olfactory (discrimination and identification) and episodic memory function (rs = 0.21-0.36, ps < 0.019). Age and episodic memory explained the same variance in olfaction that was explained by the medial temporal and orbitofrontal pattern of gray matter volume. CONCLUSIONS: The results of this cross-sectional study suggest that identifying mechanisms contributing to differences in medial temporal and orbitofrontal cortex will advance our understanding of co-morbid olfactory and cognitive declines.

Functional Network Alterations Associated with Cognition in Pre-Clinical Alzheimer's Disease.

Objective: Accumulation of cerebral amyloid-ß (Aß) is a risk factor for cognitive decline and defining feature of Alzheimer's disease (AD). Aß is implicated in brain network disruption, but the extent to which these changes correspond with observable cognitive deficits in pre-clinical AD has not been tested. This study utilized individual-specific functional parcellations to sensitively evaluate the relationship between network connectivity and cognition in adults with and without Aß deposition. Participants and Methods: Cognitively unimpaired adults ages 45-85 completed amyloid positron emission tomography, resting-state-functional magnetic resonance imaging (fMRI), and neuropsychological tests of episodic memory and executive function (EF). Participants in the upper tertile of mean standard uptake value ratio were considered Aß+ (n = 50) while others were Aß- (n = 99). Individualized functional network parcellations were generated from resting-state fMRI data. We examined the effects of group, network, and group-by-network interactions on memory and EF. Results: We observed several interactions such that within the Aß+ group, preserved network integrity (i.e., greater connectivity within specific networks) was associated with better cognition, whereas network desegregation (i.e., greater connectivity between relative to within networks) was associated with worse cognition. This dissociation was most apparent for cognitive networks (frontoparietal, dorsal and ventral attention, limbic, and default mode), with connectivity relating to EF in the Aß+ group specifically. Conclusions: Using an innovative approach to constructing individual-specified resting-state functional connectomes, we were able to detect differences in brain-cognition associations in pre-clinical AD. Our findings provide novel insight into specific functional network alterations occurring in the presence of Aß that relate to cognitive function in asymptomatic individuals. Impact statement Elevated cerebral amyloid-ß is a biomarker of pre-clinical Alzheimer's disease (AD). Associations between amyloidosis, functional network disruption, and cognitive impairment are evident in the later stages of AD, but these effects have not been substantiated in pre-clinical AD. Using individual-specific parcellations that maximally localize functional networks, we identify network alterations that relate to cognition in pre-clinical AD that have not been previously reported. We demonstrate that these effects localize to networks implicated in cognition. Our findings suggest that there may be subtle, amyloid-related alterations in the functional connectome that are detectable in pre-clinical AD, with potential implications for cognition in asymptomatic individuals.

Optimized rectification of fiber orientation density function with background threshold.

PURPOSE: To describe an optimized fiber orientation density function (fODF) rectification procedure that removes negative values and absorbs all features below a specified threshold into a constant background. THEORY AND METHODS: The fODF for a white matter imaging voxel describes the angular density of axons. Because of signal noise and Gibbs ringing, fODFs estimated with diffusion MRI may take on unphysical negative values in some directions and contain spurious peaks. In order to suppress such artifacts, an fODF rectification procedure is proposed that both eliminates all negative values and incorporates all features below a specified threshold, η, into a constant background while at the same time minimizing the mean square deviation from the original, unrectified fODF. Calculating this fODF is straightforward, and the directions and shapes of peaks not absorbed into the background are preserved. The rectification method is illustrated for an analytic fODF model and for experimental diffusion MRI data obtained in healthy human brain, with the original fODFs being obtained from fiber ball imaging. RESULTS: Examples of optimal rectified fODFs are given for three choices of the background threshold referred to as minimal rectification (η = 0), average-level rectification (η ≈ 0.08), and fractional-anisotropy-axonal-based rectification (η ≈ 0.1). As η is increased, artifacts and other small features are more strongly suppressed, but the major fODF peaks are largely unaffected for the range of η values illustrated by these three alternatives. CONCLUSION: Artifactual features of fODFs estimated with diffusion MRI can be effectively suppressed by applying the proposed optimized rectification procedure. Since it minimizes fODF distortion in the mean square sense, it may be useful in the study of how fODF fine structure is affected by aging and disease.

Fiber Ball White Matter Modeling Reveals Microstructural Alterations in Healthy Brain Aging.

Age-related white matter degeneration is characterized by myelin breakdown and neuronal fiber loss that preferentially occur in regions that myelinate later in development. Conventional diffusion MRI (dMRI) has demonstrated age-related increases in diffusivity but provide limited information regarding the tissue-specific changes driving these effects. A recently developed dMRI biophysical modeling technique, Fiber Ball White Matter (FBWM) modeling, offers enhanced biological interpretability by estimating microstructural properties specific to the intra-axonal and extra-axonal spaces. We used FBWM to illustrate the biological mechanisms underlying changes throughout white matter in healthy aging using data from 63 cognitively unimpaired adults ages 45-85 with no radiological evidence of neurodegeneration or incipient Alzheimer's disease. Conventional dMRI and FBWM metrics were computed for two late-myelinating (genu of the corpus callosum and association tracts) and two early-myelinating regions (splenium of the corpus callosum and projection tracts). We examined the associations between age and these metrics in each region and tested whether age was differentially associated with these metrics in late- vs. early-myelinating regions. We found that conventional metrics replicated patterns of age-related increases in diffusivity in late-myelinating regions. FBWM additionally revealed specific intra- and extra-axonal changes suggestive of myelin breakdown and preferential loss of smaller-diameter axons, yielding in vivo corroboration of findings from histopathological studies of aged brains. These results demonstrate that advanced biophysical modeling approaches, such as FBWM, offer novel information about the microstructure-specific alterations contributing to white matter changes in healthy aging. These tools hold promise as sensitive indicators of early pathological changes related to neurodegenerative disease.

Unsupervised Clustering of Olfactory Phenotypes.

BACKGROUND: Current clinical classifications of olfactory function are based primarily upon a percentage of correct answers in olfactory identification testing. This simple classification provides little insight into etiologies of olfactory loss, associated comorbidities, or impact on the quality of life (QOL). METHODS: Community-based subjects underwent olfactory psychophysical testing using Sniffin Sticks to measure threshold (T), discrimination (D), and identification (I). The cognitive screening was performed using Mini-Mental Status Examination (MMSE). Unsupervised clustering was performed based upon T, D, I, and MMSE. Post hoc differences in demographics, comorbidities, and QOL measures were assessed. RESULTS: Clustering of 219 subjects, mean age 51 years (range 20-93 years) resulted in 4 unique clusters. Cluster 1 was the largest and predominantly younger normosmics. Cluster 2 had the worst olfaction with impairment in nearly all aspects of olfaction and decreased MMSE scores. This cluster had higher rates of smoking, heart disease, and cancer and had the worst olfactory-specific QOL. Cluster 3 had normal MMSE with relative preservation of D and I, but severely impaired T. This cluster had higher rates of smoking and heart disease with moderately impaired QOL. Cluster 4 was notable for the worst MMSE scores, but general preservation of D and I with moderate loss of T. This cluster had higher rates of Black subjects, diabetes, and viral/traumatic olfactory loss. CONCLUSION: Unsupervised clustering based upon detailed olfactory testing and cognitive testing results in clinical phenotypes with unique risk factors and QOL impacts. These clusters may provide additional information regarding etiologies and subsequent therapies to treat olfactory loss.

Neurodegeneration of the Globus Pallidus Internus as a Neural Correlate to Dopa-Response in Freezing of Gait.

BACKGROUND: Background: Parkinson's disease (PD) patients who develop freezing of gait (FOG) have reduced mobility and independence. While some patients experience improvement in their FOG symptoms with dopaminergic therapies, a subset of patients have little to no response. To date, it is unknown what changes in brain structure underlie dopa-response and whether this can be measured using neuroimaging approaches. OBJECTIVE: We tested the hypothesis that structural integrity of brain regions (subthalamic nucleus and globus pallidus internus, GPi) which link basal ganglia to the mesencephalic locomotor region (MLR), a region involved in automatic gait, would be associated with FOG response to dopaminergic therapy. METHODS: In this observational study, thirty-six participants with PD and definite FOG were recruited to undergo diffusion kurtosis imaging (DKI) and multiple assessments of dopa responsiveness (UPDRS scores, gait times ON versus OFF medication). RESULTS: The right GPi in participants with dopa-unresponsive FOG showed reduced fractional anisotropy, mean kurtosis (MK), and increased radial diffusivity relative to those with dopa-responsive FOG. Furthermore, using probabilistic tractography, we observed reduced MK and increased mean diffusivity along the right GPi-MLR tract in dopa-unresponsive FOG. MK in the right GPi was associated with a subjective dopa-response for FOG (r = -0.360, df = 30, p = 0.043) but not overall motor dopa-response. CONCLUSION: These results support structural integrity of the GPi as a correlate to dopa-response in FOG. Additionally, this study suggests DKI metrics may be a sensitive biomarker for clinical studies targeting dopaminergic circuitry and improvements in FOG behavior.

Greater Diffusion Restriction in White Matter in Preclinical Alzheimer Disease.

OBJECTIVE: The Alzheimer's continuum is biologically defined by beta-amyloid deposition, which at the earliest stages is superimposed upon white matter degeneration in aging. However, the extent to which these co-occurring changes is characterized is relatively underexplored. The goal of this study was to use diffusional kurtosis imaging (DKI) and biophysical modeling to detect and describe amyloid-related white matter changes in preclinical Alzheimer disease. METHODS: Cognitively unimpaired participants ages 45 to 85 years completed brain magnetic resonance imaging, amyloid positron emission tomography (florbetapir), neuropsychological testing, and other clinical measures at baseline in a cohort study. We tested whether beta-amyloid-negative (AB-) and -positive (AB+) participants differed on DKI-based conventional (ie, fractional anisotropy [FA], mean diffusivity [MD], mean kurtosis) and modeling (ie, axonal water fraction [AWF], extra-axonal radial diffusivity [De,⊥ ]) metrics, and whether these metrics were associated with other biomarkers. RESULTS: We found significantly greater diffusion restriction (higher FA/AWF, lower MD/De,⊥ ) in white matter in AB+ than AB- (partial η2 =0.08-0.19), more notably in the extra-axonal space within primarily late myelinating tracts. Diffusion metrics predicted amyloid status incrementally over age (area under the curve = 0.84) with modest yet selective associations, where AWF (a marker of axonal density) correlated with speed/executive functions and neurodegeneration, whereas De,⊥ (a marker of gliosis/myelin repair) correlated with amyloid deposition and white matter hyperintensity volume. INTERPRETATION: These results support prior evidence of a nonmonotonic change in diffusion behavior, where an early increase in diffusion restriction is hypothesized to reflect inflammation and myelin repair prior to an ensuing decrease in diffusion restriction, indicating glial and neuronal degeneration. ANN NEUROL 2022;91:864-877.

Comparison of conventional and actuarial neuropsychological criteria for mild cognitive impairment in a clinical setting.

INTRODUCTION: Evidence-based practice in neuropsychology involves the use of validated tests, cutoff scores, and interpretive algorithms to identify clinically significant cognitive deficits. Recently, actuarial neuropsychological criteria (ANP) for identifying mild cognitive impairment were developed, demonstrating improved criterion validity and temporal stability compared to conventional criteria (CNP). However, benefits of the ANP criteria have not been investigated in non-research, clinical settings with varied etiologies, severities, and comorbidities. This study compared the utility of CNP and ANP criteria using data from a memory disorders clinic. METHOD: Data from 500 non-demented older adults evaluated in a Veterans Affairs Medical Center memory disorders clinic were retrospectively analyzed. We applied CNP and ANP criteria to the Repeatable Battery for the Assessment of Neuropsychological Status, compared outcomes to consensus clinical diagnoses, and conducted cluster analyses of scores from each group. RESULTS: The majority (72%) of patients met both the CNP and ANP criteria and both approaches were susceptible to confounding factors such as invalid test data and mood disturbance. However, the CNP approach mislabeled impairment in more patients with non-cognitive disorders and intact cognition. Comparatively, the ANP approach misdiagnosed patients with depression at a third of the rate and those with no diagnosis at nearly half the rate of CNP. Cluster analyses revealed groups with: 1) minimal impairment, 2) amnestic impairment, and 3) multi-domain impairment. The ANP approach yielded subgroups with more distinct neuropsychological profiles. CONCLUSIONS: We replicated previous findings that the CNP approach is over-inclusive, particularly for those determined to have no cognitive disorder by a consensus team. The ANP approach yielded fewer false positives and better diagnostic specificity than the CNP. Despite clear benefits of the ANP vs. CNP, there was substantial overlap in their performance in this heterogeneous sample. These findings highlight the critical role of clinical interpretation when wielding these empirically-derived tools.

Chronic cannabis smoking-enriched oral pathobiont drives behavioral changes, macrophage infiltration, and increases ß-amyloid protein production in the brain.

BACKGROUND: Little is known about chronic cannabis smoking-associated oral microbiome and its effects on central nervous system (CNS) functions. METHODS: In the current study, we have analyzed the saliva microbiome in individuals who chronically smoked cannabis with cannabis use disorder (n = 16) and in non-smoking controls (n = 27). The saliva microbiome was analyzed using microbial 16S rRNA sequencing. To investigate the function of cannabis use-associated oral microbiome, mice were orally inoculated with live Actinomyces meyeri, Actinomyces odontolyticus, or Neisseria elongata twice per week for six months, which mimicked human conditions. FINDINGS: We found that cannabis smoking in humans was associated with oral microbial dysbiosis. The most increased oral bacteria were Streptococcus and Actinomyces genus and the most decreased bacteria were Neisseria genus in chronic cannabis smokers compared to those in non-smokers. Among the distinct species bacteria in cannabis smokers, the enrichment of Actinomyces meyeri was inversely associated with the age of first cannabis smoking. Strikingly, oral exposure of Actinomyces meyeri, an oral pathobiont, but not the other two control bacteria, decreased global activity, increased macrophage infiltration, and increased ß-amyloid 42 protein production in the mouse brains. INTERPRETATION: This is the first study to reveal that long-term oral cannabis exposure is associated oral enrichment of Actinomyces meyeri and its contributions to CNS abnormalities.

Brain Reserve in a Case of Cognitive Resilience to Severe Leukoaraiosis.

OBJECTIVE: Leukoaraiosis, or white matter rarefaction, is a common imaging finding in aging and is presumed to reflect vascular disease. When severe in presentation, potential congenital or acquired etiologies are investigated, prompting referral for neuropsychological evaluation in addition to neuroimaging. T2-weighted imaging is the most common magnetic resonance imaging (MRI) approach to identifying white matter disease. However, more advanced diffusion MRI techniques may provide additional insight into mechanisms that influence the abnormal T2 signal, especially when clinical presentations are discrepant with imaging findings. METHOD: We present a case of a 74-year-old woman with severe leukoaraoisis. She was examined by a neurologist, neuropsychologist, and rheumatologist, and completed conventional (T1, T2-FLAIR) MRI, diffusion tensor imaging (DTI), and advanced single-shell, high b-value diffusion MRI (i.e., fiber ball imaging [FBI]). RESULTS: The patient was found to have few neurological signs, no significant cognitive impairment, a negative workup for leukoencephalopathy, and a positive antibody for Sjogren's disease for which her degree of leukoaraiosis would be highly atypical. Tractography results indicate intact axonal architecture that was better resolved using FBI rather than DTI. CONCLUSIONS: This case illustrates exceptional cognitive resilience in the face of severe leukoaraiosis and the potential for advanced diffusion MRI to identify brain reserve.

A Bayesian hierarchical change point model with parameter constraints.

Alzheimer's disease is the leading cause of dementia among adults aged 65 or above. Alzheimer's disease is characterized by a change point signaling a sudden and prolonged acceleration in cognitive decline. The timing of this change point is of clinical interest because it can be used to establish optimal treatment regimens and schedules. Here, we present a Bayesian hierarchical change point model with a parameter constraint to characterize the rate and timing of cognitive decline among Alzheimer's disease patients. We allow each patient to have a unique random intercept, random slope before the change point, random change point time, and random slope after the change point. The difference in slope before and after a change point is constrained to be nonpositive, and its parameter space is partitioned into a null region (representing normal aging) and a rejection region (representing accelerated decline). Using the change point time, the estimated slope difference, and the threshold of the null region, we are able to (1) distinguish normal aging patients from those with accelerated cognitive decline, (2) characterize the rate and timing for patients experiencing cognitive decline, and (3) predict personalized risk of progression to dementia due to Alzheimer's disease. We apply the approach to data from the Religious Orders Study, a national cohort study of aging Catholic nuns, priests, and lay brothers.

Self-reported cognition and marijuana use in older adults: Results from the national epidemiologic survey on alcohol and related conditions-III.

Marijuana use among older adults is on an unprecedented rise, yet little is known about its effects on cognition in this population where, due to advanced age, risk for cognitive decline is high. Thus, we investigated whether marijuana use and use characteristics were associated with self-reported cognition among older adults ages ≥ 50 years using the National Epidemiologic Survey on Alcohol and Related Conditions-III. Respondents either had never used marijuana ("never": n = 10,976), used but not in the past 12 months ("former": n = 2990), or used in the past 12 months ("current": n = 712). Self-reported cognition was measured using the Executive Function Index. Marijuana and substance use characteristics were obtained using the Alcohol Use Disorder and Associated Disabilities Interview Schedule-5. Covariates included demographics, mental health and disability, and comorbid mental and substance use disorder. Using general linear models of cross-sectional data, we found that current users, particularly those with cannabis use disorder, reported worse cognition than never or former users, but these effects were small in magnitude. Among both former and current users, greater duration of past use was associated with worse cognition. Frequent use within the past 12 months was associated with worse cognition among current users, but daily users reported better cognition compared to monthly or weekly users. Thus, marijuana use may impact self-reported cognition in older adulthood, although these effects may be subtle, specific to particular use characteristics, and possibly affected by self-awareness of deficits. Future work using objective measures such as neuropsychological testing or neuroimaging may better elucidate these effects.

Psychometric Properties of the NIH Toolbox Cognition Battery in Healthy Older Adults: Reliability, Validity, and Agreement with Standard Neuropsychological Tests.

OBJECTIVE: Few independent studies have examined the psychometric properties of the NIH Toolbox Cognition Battery (NIHTB-CB) in older adults, despite growing interest in its use for clinical purposes. In this paper we report the test-retest reliability and construct validity of the NIHTB-CB, as well as its agreement or concordance with traditional neuropsychological tests of the same construct to determine whether tests could be used interchangeably. METHODS: Sixty-one cognitively healthy adults ages 60-80 completed "gold standard" (GS) neuropsychological tests, NIHTB-CB, and brain MRI. Test-retest reliability, convergent/discriminant validity, and agreement statistics were calculated using Pearson's correlations, concordance correlation coefficients (CCC), and root mean square deviations. RESULTS: Test-retest reliability was acceptable (CCC = .73 Fluid; CCC = .85 Crystallized). The NIHTB-CB Fluid Composite correlated significantly with cerebral volumes (r's = |.35-.41|), and both composites correlated highly with their respective GS composites (r's = .58-.84), although this was more variable for individual tests. Absolute agreement was generally lower (CCC = .55 Fluid; CCC = .70 Crystallized) due to lower precision in fluid scores and systematic overestimation of crystallized composite scores on the NIHTB-CB. CONCLUSIONS: These results support the reliability and validity of the NIHTB-CB in healthy older adults and suggest that the fluid composite tests are at least as sensitive as standard neuropsychological tests to medial temporal atrophy and ventricular expansion. However, the NIHTB-CB may generate different estimates of performance and should not be treated as interchangeable with established neuropsychological tests.

A Systematic Review of the Neurocognitive Effects of Cannabis Use in Older Adults.

PURPOSE OF REVIEW: Older adults currently represent the fastest growing demographic of cannabis users, yet few studies have investigated the effects of cannabis use on cognitive functioning in aging. We conducted a systematic review of the recent literature examining cognitive outcomes associated with cannabis use in older adults, with and without neurocognitive disorders, to clarify the potential neuroprotective benefits and risks of cognitive decline in this population. RECENT FINDINGS: We identified 26 studies examining cognitive outcomes associated with medical and recreational use of cannabis in healthy aging, dementia, Parkinson's disease, multiple sclerosis, HIV, and pain populations. Although variability in the cannabis products used, outcomes assessed, and study quality limits the conclusions that can be made, modest reductions in cognitive performance were generally detected with higher doses and heavier lifetime use. SUMMARY: This review highlights the need for additional high-quality research using standardized, validated assessments of cannabis exposure and cognitive outcomes. Reliable measures and longitudinal data are necessary to better characterize the effects of cannabis use on cognitive aging, as well as differential effects of recreational and medical cannabis.

Modeling white matter tract integrity in aging with diffusional kurtosis imaging.

Myelin breakdown and neural fiber loss occur in aging. This study used white matter tract integrity metrics derived from biophysical modeling using Diffusional Kurtosis Imaging to assess loss of myelin (i.e., extraaxonal diffusivity, radial direction, De,⊥) and axonal density (i.e., axonal water fraction) in cognitively unimpaired older adults. Tract-based spatial statistics and region of interest analyses sought to identify ontogenic differences and age-related changes in white matter tracts using cross-sectional and longitudinal data analyzed with general linear and mixed-effects models. In addition to pure diffusion parameters (i.e., fractional anisotropy, mean diffusivity, mean kurtosis), we found that white matter tract integrity metrics significantly differentiated early- from late-myelinating tracts, correlated with age in spatially distinct regions, and identified primarily extraaxonal changes over time. Percent metric changes were |0.3-0.9|% and |0.0-1.9|% per year using cross-sectional data and longitudinal data, respectively. There was accelerated decline in some late- versus early-myelinating tracts in older age. These results demonstrate that these metrics may inform further study of the transition from age-related changes to neurodegenerative decline.

Voices of leadership: wisdom from women leaders in neuropsychology.

OBJECTIVE: Inspired by panel discussions at various neuropsychology conferences, the aim of this paper is to share wisdom that women in neuropsychology acquired from their leadership experiences. METHOD: We identified 46 women leaders in governance and academic research through reviews of organizational websites and journal editorial boards, and requested their response to brief questions via email. Twenty-one leaders provided responses to three questions formulated by the authors. RESULTS: This paper summarizes the primary themes for the following questions: (1) What advice would you give to a woman neuropsychologist who is seeking to move into a leadership role? Responses included: increase visibility, make connections, know yourself, be confident, and gather information. (2) What leadership style(s) works best? No respondents endorsed a 'best' leadership style; however, they suggested that leaders should know their own personal style, be open and transparent, find a shared mission, and most importantly - use a collaborative approach. (3) What helps a woman earn respect as a leader in neuropsychology? Respondents recommended that leaders should: get involved in the work, demonstrate integrity, do your homework, be dependable, and keep meetings focused. CONCLUSIONS: It is the authors' intent that by gathering and distilling advice from successful women leaders in neuropsychology, more women may be catalyzed to pursue leadership roles in our profession.

Women's leadership in neuropsychology: historical perspectives, present trends, and future directions.

OBJECTIVE: Although psychology has become a female-dominated field, this pattern of gender representation has not held true within the specialty of neuropsychology. In recent years more women have been pursuing careers in neuropsychology, and while the balance of male and female neuropsychologists as a whole has shifted, it is unclear whether the gender composition of leadership has also changed. Our goal was to survey various neuropsychological organizations, training programs, editorial boards, and organizations granting board certification to determine the current gender composition of leadership positions within neuropsychology. METHOD: A literature review was conducted to examine past trends of gender composition in neuropsychology, psychology, medicine, and academia. Data on current gender compositions of the field were culled from publicly available websites and through personal communication with representatives from major psychological and neuropsychological organizations. RESULTS: We found that the overall composition of the field has changed over time, but notable gender disparities in leadership positions remain. Women still comprise the minority of leadership positions within most neuropsychological organizations, editorial boards for neuropsychology journals, and fellow positions in major neuropsychological organizations. More equitable representation has been achieved in the directorships of training programs and ABPP/ABCN board certification. CONCLUSION: We review the historical trends in gender discrepancies in leadership in neuropsychology and discuss these within the broader arenas of academia, research, and medicine. We conclude with a summary addressing potential causes for these discrepancies, including work-life balance issues, discrimination, institutional bias, and various other factors. We also provide pragmatic suggestions to help address these continued disparities.