Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Deep learning to extract the meteorological by-catch of wildlife cameras.

Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors such as sunshine, hail and snow. Meanwhile, remote cameras have become a primary tool to monitor wild plants and animals, even at micro-scales, and deep learning tools rapidly convert images into ecological data. However, deep learning applications for wildlife imagery have focused exclusively on living subjects. Here, we identify an overlooked opportunity to extract latent, ecologically relevant meteorological information. We produce an annotated image dataset of micrometeorological conditions across 49 wildlife cameras in South Africa's Maloti-Drakensberg and the Swiss Alps. We train ensemble deep learning models to classify conditions as overcast, sunshine, hail or snow. We achieve 91.7% accuracy on test cameras not seen during training. Furthermore, we show how effective accuracy is raised to 96% by disregarding 14.1% of classifications where ensemble member models did not reach a consensus. For two-class weather classification (overcast vs. sunshine) in a novel location in Svalbard, Norway, we achieve 79.3% accuracy (93.9% consensus accuracy), outperforming a benchmark model from the computer vision literature (75.5% accuracy). Our model rapidly classifies sunshine, snow and hail in almost 2 million unlabelled images. Resulting micrometeorological data illustrated common seasonal patterns of summer hailstorms and autumn snowfalls across mountains in the northern and southern hemispheres. However, daily patterns of sunshine and shade diverged between sites, impacting daily temperature cycles. Crucially, we leverage micrometeorological data to demonstrate that (1) experimental warming using open-top chambers shortens early snow events in autumn, and (2) image-derived sunshine marginally outperforms sensor-derived temperature when predicting bumblebee foraging. These methods generate novel micrometeorological variables in synchrony with biological recordings, enabling new insights from an increasingly global network of wildlife cameras.

Southern Africa's Great Escarpment as an amphitheater of climate-driven diversification and a buffer against future climate change in bats.

Hosting 1460 plant and 126 vertebrate endemic species, the Great Escarpment (hereafter, Escarpment) forms a semi-circular "amphitheater" of mountains girdling southern Africa from arid west to temperate east. Since arid and temperate biota are usually studied separately, earlier studies overlooked the biogeographical importance of the Escarpment as a whole. Bats disperse more widely than other mammalian taxa, with related species and intraspecific lineages occupying both arid and temperate highlands of the Escarpment, providing an excellent model to address this knowledge gap. We investigated patterns of speciation and micro-endemism from modeled past, present, and future distributions in six clades of southern African bats from three families (Rhinolophidae, Cistugidae, and Vespertilionidae) having different crown ages (Pleistocene to Miocene) and biome affiliations (temperate to arid). We estimated mtDNA relaxed clock dates of key divergence events across the six clades in relation both to biogeographical features and patterns of phenotypic variation in crania, bacula and echolocation calls. In horseshoe bats (Rhinolophidae), both the western and eastern "arms" of the Escarpment have facilitated dispersals from the Afrotropics into southern Africa. Pleistocene and pre-Pleistocene "species pumps" and temperate refugia explained observed patterns of speciation, intraspecific divergence and, in two cases, mtDNA introgression. The Maloti-Drakensberg is a center of micro-endemism for bats, housing three newly described or undescribed species. Vicariance across biogeographic barriers gave rise to 29 micro-endemic species and intraspecific lineages whose distributions were congruent with those identified in other phytogeographic and zoogeographic studies. Although Köppen-Geiger climate models predict a widespread replacement of current temperate ecosystems in southern Africa by tropical or arid ecosystems by 2070-2100, future climate Maxent models for 13 bat species (all but one of those analyzed above) showed minimal range changes in temperate species from the eastern Escarpment by 2070, possibly due to the buffering effect of mountains to climate change.

Explaining the Decay of Nucleic Acid-Based Sensors under Continuous Voltammetric Interrogation.

Nucleic acid-based electrochemical sensors (NBEs) can support continuous and highly selective molecular monitoring in biological fluids, both in vitro and in vivo, via affinity-based interactions. Such interactions afford a sensing versatility that is not supported by strategies that depend on target-specific reactivity. Thus, NBEs have significantly expanded the scope of molecules that can be monitored continuously in biological systems. However, the technology is limited by the lability of the thiol-based monolayers employed for sensor fabrication. Seeking to understand the main drivers of monolayer degradation, we studied four possible mechanisms of NBE decay: (i) passive desorption of monolayer elements in undisturbed sensors, (ii) voltage-induced desorption under continuous voltammetric interrogation, (iii) competitive displacement by thiolated molecules naturally present in biofluids like serum, and (iv) protein binding. Our results indicate that voltage-induced desorption of monolayer elements is the main mechanism by which NBEs decay in phosphate-buffered saline. This degradation can be overcome by using a voltage window contained between -0.2 and 0.2 V vs Ag|AgCl, reported for the first time in this work, where electrochemical oxygen reduction and surface gold oxidation cannot occur. This result underscores the need for chemically stable redox reporters with more positive reduction potentials than the benchmark methylene blue and the ability to cycle thousands of times between redox states to support continuous sensing for long periods. Additionally, in biofluids, the rate of sensor decay is further accelerated by the presence of thiolated small molecules like cysteine and glutathione, which can competitively displace monolayer elements even in the absence of voltage-induced damage. We hope that this work will serve as a framework to inspire future development of novel sensor interfaces aiming to eliminate the mechanisms of signal decay in NBEs.

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Greater male than female variability in regional brain structure across the lifespan.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Human Cyclophilin B Nuclease Activity Revealed via Nucleic Acid-Based Electrochemical Sensors.

Human cyclophilin B (CypB) is oversecreted by pancreatic cancer cells, making it a potential biomarker for early-stage disease diagnosis. Our group is motivated to develop aptamer-based assays to measure CypB levels in biofluids. However, human cyclophilins have been postulated to have collateral nuclease activity, which could impede the use of aptamers for CypB detection. To establish if CypB can hydrolyze electrode-bound nucleic acids, we used ultrasensitive electrochemical sensors to measure CypB's hydrolytic activity. Our sensors use ssDNA and dsDNA in the biologically predominant d-DNA form, and in the nuclease resistant l-DNA form. Challenging such sensors with CypB and control proteins, we unequivocally demonstrate that CypB can cleave nucleic acids. To our knowledge, this is the first study to use electrochemical biosensors to reveal the hydrolytic activity of a protein that is not known to be a nuclease. Future development of CypB bioassays will require the use of nuclease-resistant aptamer sequences.

Direct Cytosolic Delivery of Proteins through Coengineering of Proteins and Polymeric Delivery Vehicles.

Nanocarrier-mediated protein delivery is a promising strategy for fundamental research and therapeutic applications. However, the efficacy of the current platforms for delivery into cells is limited by endosomal entrapment of delivered protein cargo with concomitantly inefficient access to the cytosol and other organelles, including the nucleus. We report here a robust, versatile polymeric-protein nanocomposite (PPNC) platform capable of efficient (≥90%) delivery of proteins to the cytosol. We synthesized a library of guanidinium-functionalized poly(oxanorborneneimide) (PONI) homopolymers with varying molecular weights to stabilize and deliver engineered proteins featuring terminal oligoglutamate "E-tags". The polymers were screened for cytosolic delivery efficiency using imaging flow cytometry with cytosolic delivery validated using confocal microscopy and activity of the delivered proteins demonstrated through functional assays. These studies indicate that the PPNC platform provides highly effective and tunable cytosolic delivery over a wide range of formulations, making them robust agents for therapeutic protein delivery.

Decreases in the Late Positive Potential to Alcohol Images Among Alcohol Treatment Seekers Following Mindfulness-Based Relapse Prevention.

AIM: Heightened craving among individuals with alcohol use disorder (AUD) has been attributed to a hypersensitivity to alcohol cues in attentional brain networks. Active mindfulness training has been shown to help improve attentional control. Here, we examined alcohol cue-related hypersensitivity among individuals with AUD who received rolling group mindfulness-based relapse prevention (MBRP) in combination with transcranial direct current stimulation (tDCS), over right inferior frontal gyrus. METHODS: Participants (n = 68) viewed a series of emotionally negative, emotionally neutral and alcohol-related images. Following image presentation, participants were asked to rate their level of craving for the alcohol cues, and their level of negative affect evoked by neutral and negative cues. During the task, electroencephalogram (EEG) was recorded to capture an event-related component shown to relate to emotionally salient stimuli: the late positive potential (LPP). Participants who completed a follow-up EEG (n = 37) performed the task a second time after up to eight sessions of MBRP coupled with active or sham tDCS. RESULTS: We found that both craving ratings and the LPP significantly decreased in response to alcohol cues from pre- to post-treatment, but not for other image cues. The magnitude of alcohol image craving reductions was associated with the number of MBRP group sessions attended. Active tDCS was not associated with craving ratings, but it was associated with greater LPP amplitudes across image types. CONCLUSIONS: Taken together, these results suggest that disruption of alcohol-cue hypersensitivity in people with AUD may be a target mechanism of MBRP.

Closed-Loop Slow-Wave tACS Improves Sleep-Dependent Long-Term Memory Generalization by Modulating Endogenous Oscillations.

Benefits in long-term memory retention and generalization have been shown to be related to sleep-dependent processes, which correlate with neural oscillations as measured by changes in electric potential. The specificity and causal role of these oscillations, however, are still poorly understood. Here, we investigated the potential for augmenting endogenous slow-wave (SW) oscillations in humans with closed-loop transcranial alternating current stimulation (tACS) with an aim toward enhancing the consolidation of recent experiences into long-term memory. Sixteen (three female) participants were trained presleep on a target detection task identifying targets hidden in complex visual scenes. During post-training sleep, closed-loop SW detection and stimulation were used to deliver tACS matching the phase and frequency of the dominant oscillation in the range of 0.5-1.2 Hz. Changes in performance were assessed the following day using test images that were identical to the training ("repeated"), and images generated from training scenes but with novel viewpoints ("generalized"). Results showed that active SW tACS during sleep enhanced the postsleep versus presleep target detection accuracy for the generalized images compared with sham nights, while no significant change was found for repeated images. Using a frequency-agnostic clustering approach sensitive to stimulation-induced spectral power changes in scalp EEG, this behavioral enhancement significantly correlated with both a poststimulation increase and a subsequent decrease in measured spectral power within the SW band, which in turn showed increased coupling with spindle amplitude. These results suggest that augmenting endogenous SW oscillations can enhance consolidation by specifically improving generalization over recognition or cued recall.SIGNIFICANCE STATEMENT This human study demonstrates the use of a closed-loop noninvasive brain stimulation method to enhance endogenous neural oscillations during sleep with the effect of improving consolidation of recent experiences into long-term memory. Here we show that transient slow oscillatory transcranial alternating current stimulation (tACS) triggered by endogenous slow oscillations and matching their frequency and phase can increase slow-wave power and coupling with spindles. Further, this increase correlates with overnight improvements in generalization of recent training to facilitate performance in a target detection task. We also provide novel evidence for a tACS-induced refractory period following the tACS-induced increase. Here slow-wave power is temporarily reduced relative to sham stimulation, which nonetheless maintains a positive relationship with behavioral improvements.

A Randomized Trial of Combined tDCS Over Right Inferior Frontal Cortex and Cognitive Bias Modification: Null Effects on Drinking and Alcohol Approach Bias.

BACKGROUND: Deriving novel treatments for alcohol use disorders (AUDs) is of critical importance, as existing treatments are only modestly effective for reducing drinking. Two promising strategies for treating AUDs include cognitive bias modification (CBM) and transcranial direct current stimulation (tDCS). While each strategy has shown positive results in reducing drinking or alcohol-related constructs (e.g., craving), initial tests of the combination of CBM and tDCS have shown mixed results. The present study investigated the degree to which combining CBM and tDCS (2.0 mA anodal current over F10) could reduce alcohol approach biases and alcohol consumption. METHODS: Seventy-nine at-risk drinkers were randomized to 1 of 4 conditions in a 2 × 2 factorial design: verum CBM/verum tDCS, verum CBM/sham tDCS, sham CBM/verum tDCS, or sham CBM/sham tDCS. Participants completed a baseline assessment of alcohol approach bias and drinking quantity/frequency (i.e., drinks per drinking day [DDD] and percent heavy drinking days [PHDD]), 4 sessions of combined CBM and tDCS, and follow-up assessments of approach bias and alcohol consumption. RESULTS: Results indicated that while participants did demonstrate significant alcohol approach biases at baseline, neither CBM, tDCS, nor the interaction reduced the bias at the follow-up. In addition, there was evidence of a trend toward reducing DDD from baseline to the 1-week/1-month follow-ups, but there was no significant effect of the intervention on either DDD or PHDD. CONCLUSIONS: These results partially replicated null results presented in similar CBM/tDCS trials and suggest that this combination, at least with anodal stimulation over dorsolateral or inferior frontal sites, may have limited utility to reduce drinking.

Mindfulness-Based Relapse Prevention and Transcranial Direct Current Stimulation to Reduce Heavy Drinking: A Double-Blind Sham-Controlled Randomized Trial.

BACKGROUND: Mindfulness-based relapse prevention (MBRP) and transcranial direct current stimulation (tDCS) have independently shown benefits for treating alcohol use disorder (AUD). Recent work suggests tDCS may enhance mindfulness. The combination of MBRP and tDCS may provide synergistic benefits and may target both behavioral and neurobiological dysfunctions in AUD. The goal of this double-blind sham-controlled randomized trial was to examine the efficacy of a rolling group MBRP treatment combined with tDCS among individuals interested in reducing their drinking. METHODS: Individuals who were interested in reducing their alcohol use (n = 84; 40.5% female; mean age = 52.3; 98.9% with current AUD) were randomized to receive active (2.0 milliamps) or sham (0.0 milliamps) anodal tDCS (5 cm × 3 cm electrode) of the right inferior frontal gyrus with the 5 cm × 3 cm cathodal electrode applied to the left upper arm, combined with 8 weeks of outpatient MBRP rolling group treatment. Assessments were conducted at baseline, posttreatment, and 2 months following treatment. The primary outcome was drinks per drinking day, and secondary outcomes were percent heavy drinking days, self-reported craving, alcohol cue reactivity in an alcohol cue task, and response inhibition in a stop signal reaction time task. RESULTS: Results indicated significant reductions in drinks per drinking day over time, B(SE) = -0.535 (0.16), p = 0.001, and a significant dose effect for number of groups attended, B(SE) = -0.259 (0.11), p = 0.01. There were also significant effects of time and dose for number of groups attended on secondary outcomes of percent heavy drinking days and alcohol cue reactivity. There were no effects of active versus sham tDCS on primary or secondary outcomes. CONCLUSIONS: Findings from the current study provide initial support for the effectiveness of rolling group MBRP as an outpatient treatment for drinking reduction. The current study did not find additive effects of this tDCS protocol in enhancing MBRP among individuals with drinking reduction goals.

Optimizing Deep Brain Stimulation of the Nucleus Accumbens in a Reward Preference Rat Model.

OBJECTIVE/HYPOTHESIS: Deep brain stimulation (DBS) has become the preferred therapy for a growing number of treatment-resistant neuropsychiatric conditions, offering the benefit of being amenable to fine-tuning to enhance its efficacy. However, while some DBS parameters are routinely adjusted, the stimulation is almost always delivered in a continuous "tonic" pattern, which may be suboptimal at times. Our overall aim is to investigate the application of differing levels of rewarding DBS to the reconditioning of behavioral "trigger" and "non-trigger" stimuli in impulse-control disorders (including addiction). As a first step, we used a rat model of nucleus accumbens (NAc) DBS to rigorously compare the relative reward values of different stimulation paradigms. We hypothesized that delivering pulses in a more physiological pattern would prove more rewarding than delivering tonic stimulation. MATERIALS AND METHODS: We implanted microelectrodes in the left NAc shell and trained rats to initiate and terminate DBS to demonstrate their "preference" between different brain stimulation reward (BSR) paradigms. We tested a range of BSR paradigms, including tonic, intermittent tonic, and burst paradigms. Two paradigms were compared at a time, and paired t-tests were used to determine whether the rats significantly "preferred" one paradigm over another. RESULTS: The rats significantly preferred intermittent tonic BSR paradigms to continuous and burst paradigms, and generally preferred paradigms that delivered more pulses over the stimulation period. CONCLUSIONS: These findings highlight that the standard approach of delivering tonic DBS is not optimal under all circumstances. Further research should investigate which DBS paradigms are best for different brain disorders.

Neuroenhancement: enhancing brain and mind in health and in disease.

Humans have long used cognitive enhancement methods to expand the proficiency and range of the various mental activities that they engage in, including writing to store and retrieve information, and computers that allow them to perform myriad activities that are now commonplace in the internet age. Neuroenhancement describes the use of neuroscience-based techniques for enhancing cognitive function by acting directly on the human brain and nervous system, altering its properties to increase performance. Cognitive neuroscience has now reached the point where it may begin to put theory derived from years of experimentation into practice. This special issue includes 16 articles that employ or examine a variety of neuroenhancement methods currently being developed to increase cognition in healthy people and in patients with neurological or psychiatric illness. This includes transcranial electromagnetic stimulation methods, such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), along with deep brain stimulation, neurofeedback, behavioral training techniques, and these and other techniques in conjunction with neuroimaging. These methods can be used to improve attention, perception, memory and other forms of cognition in healthy individuals, leading to better performance in many aspects of everyday life. They may also reduce the cost, duration and overall impact of brain and mental illness in patients with neurological and psychiatric illness. Potential disadvantages of these techniques are also discussed. Given that the benefits of neuroenhancement outweigh the potential costs, these methods could potentially reduce suffering and improve quality of life for everyone, while further increasing our knowledge about the mechanisms of human cognition.

Battery powered thought: enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation.

This article reviews studies demonstrating enhancement with transcranial direct current stimulation (tDCS) of attention, learning, and memory processes in healthy adults. Given that these are fundamental cognitive functions, they may also mediate stimulation effects on other higher-order processes such as decision-making and problem solving. Although tDCS research is still young, there have been a variety of methods used and cognitive processes tested. While these different methods have resulted in seemingly contradictory results among studies, many consistent and noteworthy effects of tDCS on attention, learning, and memory have been reported. The literature suggests that although tDCS as typically applied may not be as useful for localization of function in the brain as some other methods of brain stimulation, tDCS may be particularly well-suited for practical applications involving the enhancement of attention, learning, and memory, in both healthy subjects and in clinical populations.

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia.

Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal additional structure, but raises further statistical challenges. We present a novel analysis method for extracting complex activity networks from such multifaceted imaging data sets. Compared to previous methods, we choose a new point in the trade-off space, sacrificing detailed generative probability models and explicit latent variable inference in order to achieve robust estimation of multivariate, nonlinear group factors ("network clusters"). We apply our method to identify relationships of task-specific intrinsic networks in schizophrenia patients and control subjects from a large fMRI study. After identifying network-clusters characterized by within- and between-task interactions, we find significant differences between patient and control groups in interaction strength among networks. Our results are consistent with known findings of brain regions exhibiting deviations in schizophrenic patients. However, we also find high-order, nonlinear interactions that discriminate groups but that are not detected by linear, pairwise methods. We additionally identify high-order relationships that provide new insights into schizophrenia but that have not been found by traditional univariate or second-order methods. Overall, our approach can identify key relationships that are missed by existing analysis methods, without losing the ability to find relationships that are known to be important.

Reduced fMRI activity predicts relapse in patients recovering from stimulant dependence.

Relapse presents a significant problem for patients recovering from stimulant dependence. Here we examined the hypothesis that patterns of brain function obtained at an early stage of abstinence differentiates patients who later relapse versus those who remain abstinent. Forty-five recently abstinent stimulant-dependent patients were tested using a randomized event-related functional MRI (ER-fMRI) design that was developed in order to replicate a previous ERP study of relapse using a selective attention task, and were then monitored until 6 months of verified abstinence or stimulant use occurred. SPM revealed smaller absolute blood oxygen level-dependent (BOLD) response amplitude in bilateral ventral posterior cingulate and right insular cortex in 23 patients positive for relapse to stimulant use compared with 22 who remained abstinent. ER-fMRI, psychiatric, neuropsychological, demographic, personal and family history of drug use were compared in order to form predictive models. ER-fMRI was found to predict abstinence with higher accuracy than any other single measure obtained in this study. Logistic regression using fMRI amplitude in right posterior cingulate and insular cortex predicted abstinence with 77.8% accuracy, which increased to 89.9% accuracy when history of mania was included. Using 10-fold cross-validation, Bayesian logistic regression and multilayer perceptron algorithms provided the highest accuracy of 84.4%. These results, combined with previous studies, suggest that the functional organization of paralimbic brain regions including ventral anterior and posterior cingulate and right insula are related to patients' ability to maintain abstinence. Novel therapies designed to target these paralimbic regions identified using ER-fMRI may improve treatment outcome.

Deepening biomedical research training: Community-Building Wellness Workshops for Post-Baccalaureate Research Education Program (PREP) Trainees.

Problem: All trainees, especially those from historically minoritized backgrounds, experience stresses that may reduce their continuation in science, technology, engineering, math, and medicine (STEMM) careers. The Johns Hopkins University School of Medicine is one of ~45 institutions with a National Institutes of Health funded Postbaccalaureate Research Education Program (PREP) that provides mentoring and a year of fulltime research to prepare students from historically excluded groups for graduate school. Having experienced the conflation of stresses during the COVID-19 pandemic and related shutdown, we realized our program lacked a component that explicitly helped PREP Scholars recognize and cope with non-academic stresses (financial, familial, social, mental) that might threaten their confidence and success as scientists and future in STEMM. Intervention: We developed an early-intervention program to help Scholars develop life-long skills to become successful and resilient scientists. We developed a year-long series comprised of 9 workshops focused on community, introspection, financial fitness, emotional intelligence, mental health, and soft-skills. We recruited and compensated a cohort of PhD students and postdoctoral fellows to serve as Peer Mentors, to provide a community and the safest 'space' for Scholars to discuss personal concerns. Peer Mentors were responsible for developing and facilitating these Community-Building Wellness Workshops (CBWW). Context: CBWW were created and exectued as part of the larger PREP program. Workshops included a PowerPoint presentation by Peer Mentors that featured several case studies that prompted discussion and provided time for small-group discussions between Scholars and Peer Mentors. We also included pre- and post-work for each workshop. These touch-points helped Scholars cultivate the habit of introspection. Impact: The CBWW exceeded our goals. Both Peer Mentors and Scholars experienced strong mutual support, and Scholars developed life-long skills. Notably, several Scholars who had been experiencing financial, mental or mentor-related stress immediately brought this to the attention of program leadership, allowing early and successful intervention. At the completion of CBWW, PREP Scholars reported implementing many workshop skills into practice, were reshaping their criteria for choosing future mentors, and evaluating career decisions. Strikingly, Peer Mentors found they also benefitted from the program as well, suggesting a potential larger scope for the role of CBWW in academia. Lessons Learned: Peer Mentors were essential in creating a safe supportive environment that facilitated discussions, self-reflection, and self-care. Providing fair compensation to Peer Mentors for their professional mentoring and teaching contributions was essential and contributed meaningfully to the positive energy and impact of this program.