Characterizing major depressive disorder and substance use disorder using heatmaps and variable interactions: The utility of operant behavior and brain structure relationships.

BACKGROUND: Rates of depression and addiction have risen drastically over the past decade, but the lack of integrative techniques remains a barrier to accurate diagnoses of these mental illnesses. Changes in reward/aversion behavior and corresponding brain structures have been identified in those with major depressive disorder (MDD) and cocaine-dependence polysubstance abuse disorder (CD). Assessment of statistical interactions between computational behavior and brain structure may quantitatively segregate MDD and CD. METHODS: Here, 111 participants [40 controls (CTRL), 25 MDD, 46 CD] underwent structural brain MRI and completed an operant keypress task to produce computational judgment metrics. Three analyses were performed: (1) linear regression to evaluate groupwise (CTRL v. MDD v. CD) differences in structure-behavior associations, (2) qualitative and quantitative heatmap assessment of structure-behavior association patterns, and (3) the k-nearest neighbor machine learning approach using brain structure and keypress variable inputs to discriminate groups. RESULTS: This study yielded three primary findings. First, CTRL, MDD, and CD participants had distinct structure-behavior linear relationships, with only 7.8% of associations overlapping between any two groups. Second, the three groups had statistically distinct slopes and qualitatively distinct association patterns. Third, a machine learning approach could discriminate between CTRL and CD, but not MDD participants. CONCLUSIONS: These findings demonstrate that variable interactions between computational behavior and brain structure, and the patterns of these interactions, segregate MDD and CD. This work raises the hypothesis that analysis of interactions between operant tasks and structural neuroimaging might aide in the objective classification of MDD, CD and other mental health conditions.

Predicting COVID-19 Vaccination Uptake Using a Small and Interpretable Set of Judgment and Demographic Variables: Cross-Sectional Cognitive Science Study.

BACKGROUND: Despite COVID-19 vaccine mandates, many chose to forgo vaccination, raising questions about the psychology underlying how judgment affects these choices. Research shows that reward and aversion judgments are important for vaccination choice; however, no studies have integrated such cognitive science with machine learning to predict COVID-19 vaccine uptake. OBJECTIVE: This study aims to determine the predictive power of a small but interpretable set of judgment variables using 3 machine learning algorithms to predict COVID-19 vaccine uptake and interpret what profile of judgment variables was important for prediction. METHODS: We surveyed 3476 adults across the United States in December 2021. Participants answered demographic, COVID-19 vaccine uptake (ie, whether participants were fully vaccinated), and COVID-19 precaution questions. Participants also completed a picture-rating task using images from the International Affective Picture System. Images were rated on a Likert-type scale to calibrate the degree of liking and disliking. Ratings were computationally modeled using relative preference theory to produce a set of graphs for each participant (minimum R2>0.8). In total, 15 judgment features were extracted from these graphs, 2 being analogous to risk and loss aversion from behavioral economics. These judgment variables, along with demographics, were compared between those who were fully vaccinated and those who were not. In total, 3 machine learning approaches (random forest, balanced random forest [BRF], and logistic regression) were used to test how well judgment, demographic, and COVID-19 precaution variables predicted vaccine uptake. Mediation and moderation were implemented to assess statistical mechanisms underlying successful prediction. RESULTS: Age, income, marital status, employment status, ethnicity, educational level, and sex differed by vaccine uptake (Wilcoxon rank sum and chi-square P<.001). Most judgment variables also differed by vaccine uptake (Wilcoxon rank sum P<.05). A similar area under the receiver operating characteristic curve (AUROC) was achieved by the 3 machine learning frameworks, although random forest and logistic regression produced specificities between 30% and 38% (vs 74.2% for BRF), indicating a lower performance in predicting unvaccinated participants. BRF achieved high precision (87.8%) and AUROC (79%) with moderate to high accuracy (70.8%) and balanced recall (69.6%) and specificity (74.2%). It should be noted that, for BRF, the negative predictive value was <50% despite good specificity. For BRF and random forest, 63% to 75% of the feature importance came from the 15 judgment variables. Furthermore, age, income, and educational level mediated relationships between judgment variables and vaccine uptake. CONCLUSIONS: The findings demonstrate the underlying importance of judgment variables for vaccine choice and uptake, suggesting that vaccine education and messaging might target varying judgment profiles to improve uptake. These methods could also be used to aid vaccine rollouts and health care preparedness by providing location-specific details (eg, identifying areas that may experience low vaccination and high hospitalization).

In humans, striato-pallido-thalamic projections are largely segregated by their origin in either the striosome-like or matrix-like compartments.

Cortico-striato-thalamo-cortical (CSTC) loops are fundamental organizing units in mammalian brains. CSTCs process limbic, associative, and sensorimotor information in largely separated but interacting networks. CTSC loops pass through paired striatal compartments, striosome (aka patch) and matrix, segregated pools of medium spiny projection neurons with distinct embryologic origins, cortical/subcortical structural connectivity, susceptibility to injury, and roles in behaviors and diseases. Similarly, striatal dopamine modulates activity in striosome and matrix in opposite directions. Routing CSTCs through one compartment may be an anatomical basis for regulating discrete functions. We used differential structural connectivity, identified through probabilistic diffusion tractography, to distinguish the striatal compartments (striosome-like and matrix-like voxels) in living humans. We then mapped compartment-specific projections and quantified structural connectivity between each striatal compartment, the globus pallidus interna (GPi), and 20 thalamic nuclei in 221 healthy adults. We found that striosome-originating and matrix-originating streamlines were segregated within the GPi: striosome-like connectivity was significantly more rostral, ventral, and medial. Striato-pallido-thalamic streamline bundles that were seeded from striosome-like and matrix-like voxels transited spatially distinct portions of the white matter. Matrix-like streamlines were 5.7-fold more likely to reach the GPi, replicating animal tract-tracing studies. Striosome-like connectivity dominated in six thalamic nuclei (anteroventral, central lateral, laterodorsal, lateral posterior, mediodorsal-medial, and medial geniculate). Matrix-like connectivity dominated in seven thalamic nuclei (centromedian, parafascicular, pulvinar-anterior, pulvinar-lateral, ventral lateral-anterior, ventral lateral-posterior, ventral posterolateral). Though we mapped all thalamic nuclei independently, functionally-related nuclei were matched for compartment-level bias. We validated these results with prior thalamostriate tract tracing studies in non-human primates and other species; where reliable data was available, all agreed with our measures of structural connectivity. Matrix-like connectivity was lateralized (left > right hemisphere) in 18 thalamic nuclei, independent of handedness, diffusion protocol, sex, or whether the nucleus was striosome-dominated or matrix-dominated. Compartment-specific biases in striato-pallido-thalamic structural connectivity suggest that routing CSTC loops through striosome-like or matrix-like voxels is a fundamental mechanism for organizing and regulating brain networks. Our MRI-based assessments of striato-thalamic connectivity in humans match and extend the results of prior tract tracing studies in animals. Compartment-level characterization may improve localization of human neuropathologies and improve neurosurgical targeting in the GPi and thalamus.

Sustained activation in basal ganglia and cerebellum after repetitive movement in a non-task-specific dystonia.

We previously observed sustained fMRI BOLD signal in the basal ganglia in focal hand dystonia patients after a repetitive finger tapping task. Since this was observed in a task-specific dystonia, for which excessive task repetition may play a role in pathogenesis, in the current study we asked if this effect would be observed in a focal dystonia (cervical dystonia [CD]) that is not considered task-specific or thought to result from overuse. We evaluated fMRI BOLD signal time courses before, during, and after the finger tapping task in CD patients. We observed patient/control differences in post-tapping BOLD signal in left putamen and left cerebellum during the non-dominant (left) hand tapping condition, reflecting abnormally sustained BOLD signal in CD. BOLD signals in left putamen and cerebellum were also abnormally elevated in CD during tapping itself and escalated as tapping was repeated. There were no cerebellar differences in the previously studied FHD cohort, either during or after tapping. We conclude that some elements of pathogenesis and/or pathophysiology associated with motor task execution/repetition may not be limited to task-specific dystonias, but there may be regional differences in these effects across dystonias, associated with different types of motor control programs.

The Relationship Between a History of High-risk and Destructive Behaviors and COVID-19 Infection: Preliminary Study.

BACKGROUND: The COVID-19 pandemic has heightened mental health concerns, but the temporal relationship between mental health conditions and SARS-CoV-2 infection has not yet been investigated. Specifically, psychological issues, violent behaviors, and substance use were reported more during the COVID-19 pandemic than before the pandemic. However, it is unknown whether a prepandemic history of these conditions increases an individual's susceptibility to SARS-CoV-2. OBJECTIVE: This study aimed to better understand the psychological risks underlying COVID-19, as it is important to investigate how destructive and risky behaviors may increase a person's susceptibility to COVID-19. METHODS: In this study, we analyzed data from a survey of 366 adults across the United States (aged 18 to 70 years); this survey was administered between February and March of 2021. The participants were asked to complete the Global Appraisal of Individual Needs-Short Screener (GAIN-SS) questionnaire, which indicates an individual's history of high-risk and destructive behaviors and likelihood of meeting diagnostic criteria. The GAIN-SS includes 7 questions related to externalizing behaviors, 8 related to substance use, and 5 related to crime and violence; responses were given on a temporal scale. The participants were also asked whether they ever tested positive for COVID-19 and whether they ever received a clinical diagnosis of COVID-19. GAIN-SS responses were compared between those who reported and those who did not report COVID-19 to determine if those who reported COVID-19 also reported GAIN-SS behaviors (Wilcoxon rank sum test, α=.05). In total, 3 hypotheses surrounding the temporal relationships between the recency of GAIN-SS behaviors and COVID-19 infection were tested using proportion tests (α=.05). GAIN-SS behaviors that significantly differed (proportion tests, α=.05) between COVID-19 responses were included as independent variables in multivariable logistic regression models with iterative downsampling. This was performed to assess how well a history of GAIN-SS behaviors statistically discriminated between those who reported and those who did not report COVID-19. RESULTS: Those who reported COVID-19 more frequently indicated past GAIN-SS behaviors (Q<0.05). Furthermore, the proportion of those who reported COVID-19 was higher (Q<0.05) among those who reported a history of GAIN-SS behaviors; specifically, gambling and selling drugs were common across the 3 proportion tests. Multivariable logistic regression revealed that GAIN-SS behaviors, particularly gambling, selling drugs, and attention problems, accurately modeled self-reported COVID-19, with model accuracies ranging from 77.42% to 99.55%. That is, those who exhibited destructive and high-risk behaviors before and during the pandemic could be discriminated from those who did not exhibit these behaviors when modeling self-reported COVID-19. CONCLUSIONS: This preliminary study provides insights into how a history of destructive and risky behaviors influences infection susceptibility, offering possible explanations for why some persons may be more susceptible to COVID-19, potentially in relation to reduced adherence to prevention guidelines or not seeking vaccination.

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction.

The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

The Prevalence of Psychotic Symptoms, Violent Ideation, and Disruptive Behavior in a Population With SARS-CoV-2 Infection: Preliminary Study.

BACKGROUND: The COVID-19 disease results from infection by the SARS-CoV-2 virus to produce a range of mild to severe physical, neurological, and mental health symptoms. The COVID-19 pandemic has indirectly caused significant emotional distress, triggering the emergence of mental health symptoms in individuals who were not previously affected or exacerbating symptoms in those with existing mental health conditions. Emotional distress and certain mental health conditions can lead to violent ideation and disruptive behavior, including aggression, threatening acts, deliberate harm toward other people or animals, and inattention to or noncompliance with education or workplace rules. Of the many mental health conditions that can be associated with violent ideation and disruptive behavior, psychosis can evidence greater vulnerability to unpredictable changes and being at a greater risk for them. Individuals with psychosis can also be more susceptible to contracting COVID-19 disease. OBJECTIVE: This study aimed to investigate whether violent ideation, disruptive behavior, or psychotic symptoms were more prevalent in a population with COVID-19 and did not precede the pandemic. METHODS: In this preliminary study, we analyzed questionnaire responses from a population sample (N=366), received between the end of February 2021 and the start of March 2021 (1 year into the COVID-19 pandemic), regarding COVID-19 illness, violent ideation, disruptive behavior, and psychotic symptoms. Using the Wilcoxon rank sum test followed by multiple comparisons correction, we compared the self-reported frequency of these variables for 3 time windows related to the past 1 month, past 1 month to 1 year, and >1 year ago among the distributions of people who answered whether they tested positive or were diagnosed with COVID-19 by a clinician. We also used multivariable logistic regression with iterative resampling to investigate the relationship between these variables occurring >1 year ago (ie, before the pandemic) and the likelihood of contracting COVID-19. RESULTS: We observed a significantly higher frequency of self-reported violent ideation, disruptive behavior, and psychotic symptoms, for all 3 time windows of people who tested positive or were diagnosed with COVID-19 by a clinician. Using multivariable logistic regression, we observed 72% to 94% model accuracy for an increased incidence of COVID-19 in participants who reported violent ideation, disruptive behavior, or psychotic symptoms >1 year ago. CONCLUSIONS: This preliminary study found that people who reported a test or clinician diagnosis of COVID-19 also reported higher frequencies of violent ideation, disruptive behavior, or psychotic symptoms across multiple time windows, indicating that they were not likely to be the result of COVID-19. In parallel, participants who reported these behaviors >1 year ago (ie, before the pandemic) were more likely to be diagnosed with COVID-19, suggesting that violent ideation, disruptive behavior, in addition to psychotic symptoms, were associated with COVID-19 with an approximately 70% to 90% likelihood.

Metabolomic response to collegiate football participation: Pre- and Post-season analysis.

Contact sports participation has been shown to have both beneficial and detrimental effects on health, however little is known about the metabolic sequelae of these effects. We aimed to identify metabolite alterations across a collegiate American football season. Serum was collected from 23 male collegiate football athletes before the athletic season (Pre) and after the last game (Post). Samples underwent nontargeted metabolomic profiling and 1131 metabolites were included for univariate, pathway enrichment, and multivariate analyses. Significant metabolites were assessed against head acceleration events (HAEs). 200 metabolites changed from Pre to Post (P < 0.05 and Q < 0.05); 160 had known identity and mapped to one of 57 pre-defined biological pathways. There was significant enrichment of metabolites belonging to five pathways (P < 0.05): xanthine, fatty acid (acyl choline), medium chain fatty acid, primary bile acid, and glycolysis, gluconeogenesis, and pyruvate metabolism. A set of 12 metabolites was sufficient to discriminate Pre from Post status, and changes in 64 of the 200 metabolites were also associated with HAEs (P < 0.05). In summary, the identified metabolites, and candidate pathways, argue there are metabolic consequences of both physical training and head impacts with football participation. These findings additionally identify a potential set of objective biomarkers of repetitive head injury.

A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality.

Research suggests contact sports affect neurological health. This study used permutation-based mediation statistics to integrate measures of metabolomics, neuroinflammatory miRNAs, and virtual reality (VR)-based motor control to investigate multi-scale relationships across a season of collegiate American football. Fourteen significant mediations (six pre-season, eight across-season) were observed where metabolites always mediated the statistical relationship between miRNAs and VR-based motor control ( p S o b e l p e r m ≤ 0.05; total effect > 50%), suggesting a hypothesis that metabolites sit in the statistical pathway between transcriptome and behavior. Three results further supported a model of chronic neuroinflammation, consistent with mitochondrial dysfunction: (1) Mediating metabolites were consistently medium-to-long chain fatty acids, (2) tricarboxylic acid cycle metabolites decreased across-season, and (3) accumulated head acceleration events statistically moderated pre-season metabolite levels to directionally model post-season metabolite levels. These preliminary findings implicate potential mitochondrial dysfunction and highlight probable peripheral blood biomarkers underlying repetitive head impacts in otherwise healthy collegiate football athletes.

Eye Movements Detect Differential Change after Participation in Male Collegiate Collision versus Non-Collision Sports.

Although neuroimaging studies of collision (COLL) sport athletes demonstrate alterations in brain structure and function from pre- to post-season, reliable tools to detect behavioral/cognitive change relevant to functional networks associated with participation in collision sports are lacking. This study evaluated the use of eye-movement testing to detect change in cognitive and sensorimotor processing among male club collegiate athletes after one season of participation in collision sports of variable exposure. We predicted that COLL (High Dose [hockey], n = 8; Low Dose [rugby], n = 9) would demonstrate longer reaction times (antisaccade and memory-guided saccade [MGS] latencies), increased inhibitory errors (antisaccade error rate), and poorer spatial working memory (MGS spatial accuracy) at post-season, relative to pre-season, whereas non-collision collegiate athletes (NON-COLL; n = 17) would remain stable. We also predicted that whereas eye-movement performance would detect pre- to post-season change, ImPACT (Immediate Post-Concussion Assessment and Cognitive Test) performance would remain stable. Our data showed that NON-COLL had shorter (improved performance) post- versus pre-season antisaccade and MGS latencies, whereas COLL groups showed stable, longer, or attenuated reduction in latency (ps ≤ 0.001). Groups did not differ in antisaccade error rate. On the MGS task, NON-COLL demonstrated improved spatial accuracy over time, whereas COLL groups showed reduced spatial accuracy (p < 0.05, uncorrected). No differential change was observed on ImPACT. This study provides preliminary evidence for eye-movement testing as a sensitive marker of subtle changes in attentional control and working memory resulting from participation in sports with varying levels of subconcussive exposure.

Preliminary Report: Localized Cerebral Blood Flow Mediates the Relationship between Progesterone and Perceived Stress Symptoms among Female Collegiate Club Athletes after Mild Traumatic Brain Injury.

Female athletes are under-studied in the field of concussion research, despite evidence of higher injury prevalence and longer recovery time. Hormonal fluctuations caused by the natural menstrual cycle (MC) or hormonal contraceptive (HC) use impact both post-injury symptoms and neuroimaging findings, but the relationships among hormone, symptoms, and brain-based measures have not been jointly considered in concussion studies. In this preliminary study, we compared cerebral blood flow (CBF) measured with arterial spin labeling between concussed female club athletes 3-10 days after mild traumatic brain injury (mTBI) and demographic, HC/MC matched controls (CON). We tested whether CBF statistically mediates the relationship between progesterone serum levels and post-injury symptoms, which may support a hypothesis for progesterone's role in neuroprotection. We found a significant three-way relationship among progesterone, CBF, and perceived stress score (PSS) in the left middle temporal gyrus for the mTBI group. Higher progesterone was associated with lower (more normative) PSS, as well as higher (more normative) CBF. CBF mediates 100% of the relationship between progesterone and PSS (Sobel p value = 0.017). These findings support a hypothesis for progesterone having a neuroprotective role after concussion and highlight the importance of controlling for the effects of sex hormones in future concussion studies.

Brain Perfusion Bridges Virtual-Reality Spatial Behavior to TPH2 Genotype for Head Acceleration Events.

Neuroimaging demonstrates that athletes of collision sports can suffer significant changes to their brain in the absence of concussion, attributable to head acceleration event (HAE) exposure. In a sample of 24 male Division I collegiate football players, we examine the relationships between tryptophan hydroxylase 2 (TPH2), a gene involved in neurovascular function, regional cerebral blood flow (rCBF) measured by arterial spin labeling, and virtual reality (VR) motor performance, both pre-season and across a single football season. For the pre-season, TPH2 T-carriers showed lower rCBF in two left hemisphere foci (fusiform gyrus/thalamus/hippocampus and cerebellum) in association with higher (better performance) VR Reaction Time, a dynamic measure of sensory-motor reactivity and efficiency of visual-spatial processing. For TPH2 CC homozygotes, higher pre-season rCBF in these foci was associated with better performance on VR Reaction Time. A similar relationship was observed across the season, where TPH2 T-carriers showed improved VR Reaction Time associated with decreases in rCBF in the right hippocampus/amygdala, left middle temporal lobe, and left insula/putamen/pallidum. In contrast, TPH2 CC homozygotes showed improved VR Reaction Time associated with increases in rCBF in the same three clusters. These findings show that TPH2 T-carriers have an abnormal relationship between rCBF and the efficiency of visual-spatial processing that is exacerbated after a season of high-impact sports in the absence of diagnosable concussion. Such gene-environment interactions associated with behavioral changes after exposure to repetitive HAEs have been unrecognized with current clinical analytical tools and warrant further investigation. Our results demonstrate the importance of considering neurovascular factors along with traumatic axonal injury to study long-term effects of repetitive HAEs.

Brain Perfusion Mediates the Relationship Between miRNA Levels and Postural Control.

Transcriptomics, regional cerebral blood flow (rCBF), and a virtual reality-based spatial motor task were integrated using mediation analysis in a novel demonstration of "imaging omics." Data collected in National Collegiate Athletic Association (NCAA) Division I football athletes cleared for play before in-season training showed significant relationships in 1) elevated levels of miR-30d and miR-92a to elevated putamen rCBF, 2) elevated putamen rCBF to compromised Balance scores, and 3) compromised Balance scores to elevated microRNA (miRNA) levels. rCBF acted as a consistent mediator variable (Sobel's test P < 0.05) between abnormal miRNA levels and compromised Balance scores. Given the involvement of these miRNAs in inflammation and immune function and that vascular perfusion is a component of the inflammatory response, these findings support a chronic inflammatory model in these athletes with 11 years of average football exposure. rCBF, a systems biology measure, was necessary for miRNA to affect behavior.

Cutting to the Pathophysiology Chase: Translating Cutting-Edge Neuroscience to Rehabilitation Practice in Sports-Related Concussion Management.

SYNOPSIS: Mild traumatic brain injury, or concussion, is a common sports injury. Concussion involves physical injury to brain tissue and vascular and axonal damage that manifests as transient and often nonspecific clinical symptoms. Concussion diagnosis is challenging, and the relationship between brain injury and clinical symptoms is unclear. The purpose of this commentary was to translate cutting-edge neuroscience to rehabilitation practice. We (1) highlight potential biomarkers that may improve our understanding of concussion and its recovery, (2) explain why researchers must address the paucity of concussion research in female athletes, and (3) present female-specific factors that should be accounted for in future studies. Integrating objective, quantitative measures of concussion pathophysiology with concussion history, genetics, and genomics will help caregivers identify concussed athletes, tailor recovery protocols, and protect athletes from potential long-term effects of cumulative head impact. J Orthop Sports Phys Ther 2019;49(11):811-818. Epub 1 Jun 2019. doi:10.2519/jospt.2019.8884.

White Matter Changes in Cervical Dystonia Relate to Clinical Effectiveness of Botulinum Toxin Treatment.

In a previous report showing white matter microstructural hemispheric asymmetries medial to the pallidum in focal dystonias, we showed preliminary evidence that this abnormality was reduced 4 weeks after botulinum toxin (BTX) injections. In the current study we report the completed treatment study in a full-size cohort of CD patients (n = 14). In addition to showing a shift toward normalization of the hemispheric asymmetry, we evaluated clinical relevance of these findings by relating white matter changes to degree of symptom improvement. We also evaluated whether the magnitude of the white matter asymmetry before treatment was related to severity, laterality, duration of dystonia, and/or number of previous BTX injections. Our results confirm the findings of our preliminary report: we observed significant fractional anisotropy (FA) changes medial to the pallidum 4 weeks after BTX in CD participants that were not observed in controls scanned at the same interval. There was a significant relationship between magnitude of hemispheric asymmetry and dystonia symptom improvement, as measured by percent reduction in dystonia scale scores. There was also a trend toward a relationship between magnitude of pre-injection white matter asymmetry and symptom severity, but not symptom laterality, disorder duration, or number of previous BTX injections. Post-hoc analyses suggested the FA changes at least partially reflected changes in pathophysiology, but a dissociation between patient perception of benefit from injections and FA changes suggested the changes did not reflect changes to the primary "driver" of the dystonia. In contrast, there were no changes or group differences in DTI diffusivity measures, suggesting the hemispheric asymmetry in CD does not reflect irreversible white matter tissue loss. These findings support the hypothesis that central nervous system white matter changes are involved in the mechanism by which BTX exerts clinical benefit.

Elevations in MicroRNA Biomarkers in Serum Are Associated with Measures of Concussion, Neurocognitive Function, and Subconcussive Trauma over a Single National Collegiate Athletic Association Division I Season in Collegiate Football Players.

This prospective controlled observational cohort study assessed the performance of a novel panel of serum microRNA (miRNA) biomarkers on indicators of concussion, subconcussive impacts, and neurocognitive function in collegiate football players over the playing season. Male collegiate student football athletes participating in a Division I Football Bowl Subdivision of the National Collegiate Athletic Association (NCAA) were enrolled. There were a total of 53 participants included in the study, 30 non-athlete control subjects and 23 male collegiate student football athletes. Neurocognitive assessments and blood samples were taken within the week before the athletic season began and within the week after the last game of the season and measured for a panel of pre-selected miRNA biomarkers. All the athletes had elevated levels of circulating miRNAs at the beginning of the season compared with control subjects (p < 0.001). Athletes with the lowest standard assessment of concussion (SAC) scores at the beginning of the season had the highest levels of miRNAs. The area under the curve (AUC) for predicting pre-season SAC scores were miR-195 (0.90), miR-20a (0.89), miR-151-5p (0.86), miR-505* (0.85), miR-9-3p (0.77), and miR-362-3p (0.76). In athletes with declining neurocognitive function over the season, concentrations of miRNAs increased over same period. There were significant negative correlations with miR-505* (p = 0.011), miR-30d (p = 0.007), miR-92 (p = 0.033), and (p = 0.008). The miRNAs correlating with balance problems were miR-505* (p = 0.007), miR-30d (p = 0.028), and miR-151-5p (p = 0.023). Those correlating with poor reaction times were miR-20a (0.043), miR-505* (p = 0.049), miR-30d (p = 0.031), miR-92 (p = 0.015), and miR-151-5p (p = 0.044). Select miRNAs were associated with baseline concussion assessments at the beginning of the season and with neurocognitive changes from pre to post-season in collegiate football players. Should these findings be replicated in a larger cohort of athletes, these markers could potentially serve as measures of neurocognitive status in athletes at risk for concussion and subconcussive injuries.

KIAA0319 Genotype Predicts the Number of Past Concussions in a Division I Football Team: A Pilot Study.

This candidate gene study evaluated the relationship of a past history of concussion with single nucleotide polymorphisms (SNPs) in nine genes in a small cohort (N = 87) of a nationally ranked Division I football team. Genes and SNPs studied were selected based on their published connection to brain injury and brain development, as well as impulsivity. We used multinomial logistic regression analysis (MLRA) to quantify how well genotype predicted the number of previously diagnosed concussions (three categories: none, one, two or more), while covarying race and number of years participating in football. The rs4504469 SNP for KIAA0319 was the only locus that significantly predicted number of previously diagnosed concussions (p = 0.005, meeting Bonferroni correction for multiple comparisons). The KIAA0319 results raise the hypothesis that having the CT or TT genotype of KIAA0319 may be predictive of a lower incidence of previously diagnosed concussion. This finding raises a number of hypotheses for future pre-clinical research, particularly whether alterations in neural organization related to KIAA0319 rs4504469 lead to reduced susceptibility for lasting head trauma, or greater resilience in the face of repeated subconcussive injury.

Recent Self-Reported Cannabis Use Is Associated With the Biometrics of Delta-9-Tetrahydrocannabinol.

OBJECTIVE: Research typically characterizes cannabis use by self-report of cannabis intake frequency. In an effort to better understand relationships between measures of cannabis use, we evaluated if Δ-9-tetrahydrocannabinol (THC) and metabolite concentrations (biometrics) were associated with a calibrated timeline followback (TLFB) assessment of cannabis use. METHOD: Participants were 35 young adult male cannabis users who completed a calibrated TLFB measure of cannabis use over the past 30 days, including time of last use. The calibration required participants handling four plastic bags of a cannabis substitute (0.25, 0.5, 1.0, and 3.5 grams) to quantify cannabis consumed. Participants provided blood and urine samples for analysis of THC and metabolites, at two independent laboratories. Participants abstained from cannabis use on the day of sample collection. We tested Pearson correlations between the calibrated TLFB measures and cannabis biometrics. RESULTS: Strong correlations were seen between urine and blood biometrics (all r > .73, all p < .001). TLFB measures of times of use and grams of cannabis consumed were significantly related to each biometric, including urine 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THCCOOH) and blood THC, 11-hydroxy-THC (11-OH-THC), THCCOOH, THCCOOH-glucuronide (times of use: r > .48-.61, all p < .05; grams: r > .40-.49, all p < .05). CONCLUSIONS: This study extends prior work to show TLFB methods significantly relate to an extended array of cannabis biometrics. The calibration of cannabis intake in grams was associated with each biometric, although the simple TLFB measure of times of use produced the strongest relationships with all five biometrics. These findings suggest that combined self-report and biometric data together convey the complexity of cannabis use, but allow that either the use of calibrated TLFB measures or biometrics may be sufficient for assessment of cannabis use in research.

Increased insula-putamen connectivity in X-linked dystonia-parkinsonism.

Preliminary evidence from postmortem studies of X-linked dystonia-parkinsonism (XDP) suggests tissue loss may occur first and/or most severely in the striatal striosome compartment, followed later by cell loss in the matrix compartment. However, little is known about how this relates to pathogenesis and pathophysiology. While MRI cannot visualize these striatal compartments directly in humans, differences in relative gradients of afferent cortical connectivity across compartments (weighted toward paralimbic versus sensorimotor cortex, respectively) can be used to infer potential selective loss in vivo. In the current study we evaluated relative connectivity of paralimbic versus sensorimotor cortex with the caudate and putamen in 17 individuals with XDP and 17 matched controls. Although caudate and putamen volumes were reduced in XDP, there were no significant reductions in either "matrix-weighted", or "striosome-weighted" connectivity. In fact, paralimbic connectivity with the putamen was elevated, rather than reduced, in XDP. This was driven most strongly by elevated putamen connectivity with the anterior insula. There was no relationship of these findings to disease duration or striatal volume, suggesting insula and/or paralimbic connectivity in XDP may develop abnormally and/or increase in the years before symptom onset.

Keypress-Based Musical Preference Is Both Individual and Lawful.

Musical preference is highly individualized and is an area of active study to develop methods for its quantification. Recently, preference-based behavior, associated with activity in brain reward circuitry, has been shown to follow lawful, quantifiable patterns, despite broad variation across individuals. These patterns, observed using a keypress paradigm with visual stimuli, form the basis for relative preference theory (RPT). Here, we sought to determine if such patterns extend to non-visual domains (i.e., audition) and dynamic stimuli, potentially providing a method to supplement psychometric, physiological, and neuroimaging approaches to preference quantification. For this study, we adapted our keypress paradigm to two sets of stimuli consisting of seventeenth to twenty-first century western art music (Classical) and twentieth to twenty-first century jazz and popular music (Popular). We studied a pilot sample and then a separate primary experimental sample with this paradigm, and used iterative mathematical modeling to determine if RPT relationships were observed with high R2 fits. We further assessed the extent of heterogeneity in the rank ordering of keypress-based responses across subjects. As expected, individual rank orderings of preferences were quite heterogeneous, yet we observed mathematical patterns fitting these data similar to those observed previously with visual stimuli. These patterns in music preference were recurrent across two cohorts and two stimulus sets, and scaled between individual and group data, adhering to the requirements for lawfulness. Our findings suggest a general neuroscience framework that predicts human approach/avoidance behavior, while also allowing for individual differences and the broad diversity of human choices; the resulting framework may offer novel approaches to advancing music neuroscience, or its applications to medicine and recommendation systems.