Efficacy of attention bias modification training for depressed adults: a randomized clinical trial.

BACKGROUND: This study examined the efficacy of attention bias modification training (ABMT) for the treatment of depression. METHODS: In this randomized clinical trial, 145 adults (77% female, 62% white) with at least moderate depression severity [i.e. self-reported Quick Inventory of Depressive Symptomatology (QIDS-SR) ⩾13] and a negative attention bias were randomized to active ABMT, sham ABMT, or assessments only. The training consisted of two in-clinic and three (brief) at-home ABMT sessions per week for 4 weeks (2224 training trials total). The pre-registered primary outcome was change in QIDS-SR. Secondary outcomes were the 17-item Hamilton Depression Rating Scale (HRSD) and anhedonic depression and anxious arousal from the Mood and Anxiety Symptom Questionnaire (MASQ). Primary and secondary outcomes were administered at baseline and four weekly assessments during ABMT. RESULTS: Intent-to-treat analyses indicated that, relative to assessment-only, active ABMT significantly reduced QIDS-SR and HRSD scores by an additional 0.62 ± 0.23 (p = 0.008, d = -0.57) and 0.74 ± 0.31 (p = 0.021, d = -0.49) points per week. Similar results were observed for active v. sham ABMT: a greater symptom reduction of 0.44 ± 0.24 QIDS-SR (p = 0.067, d = -0.41) and 0.69 ± 0.32 HRSD (p = 0.033, d = -0.42) points per week. Sham ABMT did not significantly differ from the assessment-only condition. No significant differences were observed for the MASQ scales. CONCLUSION: Depressed individuals with at least modest negative attentional bias benefitted from active ABMT.

Neurocognitive predictors of self-reported reward responsivity and approach motivation in depression: A data-driven approach.

BACKGROUND: Individual differences in reward-related processes, such as reward responsivity and approach motivation, appear to play a role in the nature and course of depression. Prior work suggests that cognitive biases for valenced information may contribute to these reward processes. Yet there is little work examining how biased attention, processing, and memory for positively and negatively valenced information may be associated with reward-related processes in samples with depression symptoms. METHODS: We used a data-driven, machine learning (elastic net) approach to identify the best predictors of self-reported reward-related processes using multiple tasks of attention, processing, and memory for valenced information measured across behavioral, eye tracking, psychophysiological, and computational modeling approaches (n = 202). Participants were adults (ages 18-35) who ranged in depression symptom severity from mild to severe. RESULTS: Models predicted between 5.0-12.2% and 9.7-28.0% of held-out test sample variance in approach motivation and reward responsivity, respectively. Low self-referential processing of positively valenced information was the most robust, albeit modest, predictor of low approach motivation and reward responsivity. CONCLUSIONS: Self-referential processing of positive information is the strongest predictor of reward responsivity and approach motivation in a sample ranging from mild to severe depression symptom severity. Experiments are now needed to clarify the causal relationship between self-referential processing of positively valenced information and reward processes in depression.

Magnetic resonance imaging improves 3-month outcome prediction in mild traumatic brain injury.

OBJECTIVE: To determine the clinical relevance, if any, of traumatic intracranial findings on early head computed tomography (CT) and brain magnetic resonance imaging (MRI) to 3-month outcome in mild traumatic brain injury (MTBI). METHODS: One hundred thirty-five MTBI patients evaluated for acute head injury in emergency departments of 3 LEVEL I trauma centers were enrolled prospectively. In addition to admission head CT, early brain MRI was performed 12 ± 3.9 days after injury. Univariate and multivariate logistic regression were used to assess for demographic, clinical, socioeconomic, CT, and MRI features that were predictive of Extended Glasgow Outcome Scale (GOS-E) at 3 months postinjury. RESULTS: Twenty-seven percent of MTBI patients with normal admission head CT had abnormal early brain MRI. CT evidence of subarachnoid hemorrhage was associated with a multivariate odds ratio of 3.5 (p = 0.01) for poorer 3-month outcome, after adjusting for demographic, clinical, and socioeconomic factors. One or more brain contusions on MRI, and ≥4 foci of hemorrhagic axonal injury on MRI, were each independently associated with poorer 3-month outcome, with multivariate odds ratios of 4.5 (p = 0.01) and 3.2 (p = 0.03), respectively, after adjusting for head CT findings and demographic, clinical, and socioeconomic factors. INTERPRETATION: In this prospective multicenter observational study, the clinical relevance of abnormal findings on early brain imaging after MTBI is demonstrated. The addition of early CT and MRI markers to a prognostic model based on previously known demographic, clinical, and socioeconomic predictors resulted in a >2-fold increase in the explained variance in 3-month GOS-E.

The effects of physical activity on sleep architecture and mood in naturalistic environments.

Physical activity has been found to alter sleep architecture, but these effects have been studied predominantly in the laboratory and the generalizability of these findings to naturalistic environments and longer time intervals, as well as their psychological effects, have not been evaluated. Recent technological advancements in wearable devices have made it possible to capture detailed measures of sleep outside the lab, including timing of specific sleep stages. In the current study, we utilized photoplethysmography coupled with accelerometers and smartphone ambulatory assessment to collect daily measurements of sleep, physical activity and mood in a sample of N = 82 over multi-month data collection intervals. We found a robust inverse relationship between sedentary behavior and physical activity and sleep architecture: both low-intensity and moderate-to-vigorous physical activity were associated with increased NREM sleep and decreased REM sleep, as well as a longer REM latency, while higher levels of sedentary behavior showed the opposite pattern. A decreased REM/NREM ratio and increased REM latency were in turn associated with improved wellbeing, including increased energy, reduced stress and enhanced perceived restfulness of sleep. Our results suggest that physical activity and sleep account for unique variance in a person's mood, suggesting that these effects are at least partially independent.

Altered electroencephalography resting state network coherence in remitted MDD.

Individuals with remitted depression are at greater risk for subsequent depression and therefore may provide a unique opportunity to understand the neurophysiological correlates underlying the risk of depression. Research has identified abnormal resting-state electroencephalography (EEG) power metrics and functional connectivity patterns associated with major depression, however little is known about these neural signatures in individuals with remitted depression. We investigate the spectral dynamics of 64-channel EEG surface power and source-estimated network connectivity during resting states in 37 individuals with depression, 56 with remitted depression, and 49 healthy adults that did not differ on age, education, and cognitive ability across theta, alpha, and beta frequencies. Average reference spectral EEG surface power analyses identified greater left and midfrontal theta in remitted depression compared to healthy adults. Using Network Based Statistics, we also demonstrate within and between network alterations in LORETA transformed EEG source-space coherence across the default mode, fronto-parietal, and salience networks where individuals with remitted depression exhibited enhanced coherence compared to those with depression, and healthy adults. This work builds upon our currently limited understanding of resting EEG connectivity in depression, and helps bridge the gap between aberrant EEG power and brain network connectivity dynamics in this disorder. Further, our unique examination of remitted depression relative to both healthy and depressed adults may be key to identifying brain-based biomarkers for those at high risk for future, or subsequent depression.

Self-reported physical functioning, cardiometabolic health conditions, and health care utilization patterns in Million Veteran Program enrollees with Traumatic Brain Injury Screening and Evaluation Program data.

BACKGROUND: Examining the health outcomes of veterans who have completed the United States Veterans Health Administration's (VHA's) Traumatic Brain Injury (TBI) Screening and Evaluation Program may aid in the refinement and improvement of clinical care initiatives within the VHA. This study compared self-reported physical functioning, cardiometabolic health conditions, and health care utilization patterns in Million Veteran Program enrollees with TBI Screening and Evaluation Program data (collected between 2007 and 2019), with the goal of enhancing understanding of potentially modifiable health conditions in this population. METHODS: In this observational cohort study, veterans (n = 16,452) were grouped based on the diagnostic outcome of the TBI Screening and Evaluation Program: 1) negative TBI screen (Screen-); 2) positive TBI screen but no confirmed TBI diagnosis [Screen+/ Comprehensive TBI Evaluation (CTBIE)-]; or 3) positive TBI screen and confirmed TBI diagnosis (Screen+/CTBIE+). Chi-square tests and analysis of covariance were used to explore group differences in physical functioning, cardiometabolic health conditions, and health care utilization patterns, and logistic regressions were used to examine predictors of Screen+/- and CTBIE+/- group status. RESULTS: The results showed that veterans in the Screen+/CTBIE- and Screen+/CTBIE+ groups generally reported poorer levels of physical functioning (P's < 0.001, np2 = 0.02 to 0.03), higher rates of cardiometabolic health conditions (P's < 0.001, φ = 0.14 to 0.52), and increased health care utilization (P's < 0.001, φ = 0.14 to > 0.5) compared with the Screen- group; however, health outcomes were generally comparable between the Screen+/CTBIE- and Screen+/CTBIE+ groups. Follow-up analyses confirmed that while physical functioning, hypertension, stroke, healthcare utilization, and prescription medication use reliably distinguished between the Screen- and Screen+ groups (P's < 0.02, OR's 0.78 to 3.38), only physical functioning distinguished between the Screen+/CTBIE- and Screen+/CTBIE+ groups (P < 0.001, OR 0.99). CONCLUSIONS: The findings suggest that veterans who screen positive for TBI, regardless of whether they are ultimately diagnosed with TBI, are at greater risk for negative health outcomes, signifying that these veterans represent a vulnerable group that may benefit from increased clinical care and prevention efforts.

Association Between Insomnia and Mental Health and Neurocognitive Outcomes Following Traumatic Brain Injury.

We previously described five trajectories of insomnia (each defined by a distinct pattern of insomnia severity over 12 months following traumatic brain injury [TBI]). Our objective in the present study was to estimate the association between insomnia trajectory status and trajectories of mental health and neurocognitive outcomes during the 12 months after TBI. In this study, participants included N = 2022 adults from the Federal Inter-agency Traumatic Brain Injury Repository database and Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study. The following outcome measures were assessed serially at 2 weeks, and 3, 6, and 12 months post-injury: Insomnia Severity Index, Patient Health Questionnaire, Post-Traumatic Stress Disorder (PTSD) Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), Patient Reported Outcomes Measurement Information System-Pain, and Quality of Life After Brain Injury-Overall Scale. Neurocognitive performance was assessed at 2 weeks, and 6 and 12 months using the Wechsler Adult Intelligence Scales Processing Speed Index and the Trails Making Test Parts A and B. Results indicated that greater insomnia severity was associated with greater abnormality in mental health, quality of life, and neuropsychological testing outcomes. The pattern of insomnia over time tracked the temporal pattern of all these outcomes for all but a very small number of participants. Notably, severe insomnia at 3 or 6 months post-TBI was a risk factor for poor recovery at 12 months post-injury. In conclusion, in this well-characterized sample of individuals with TBI, insomnia severity generally tracked severity of depression, pain, PTSD, quality of life, and neurocognitive outcomes over 12 months post-injury. More intensive sleep assessment is needed to elucidate the nature of these relationships and to help inform best strategies for intervention.

Inter-individual variation in blood pressure is associated with regional white matter integrity in generally healthy older adults.

Prior studies have documented a range of brain changes that occur as a result of healthy aging as well as neural alterations due to profound dysregulation in vascular health such as extreme hypertension, cerebrovascular disease and stroke. In contrast, little information exists about the more transitionary state between the normal and abnormal physiology that contributes to vascular disease and cognitive decline. Specifically, little information exists with regard to the influence of systemic vascular physiology on brain tissue structure in older individuals with low risk for cerebrovascular disease and with no evidence of cognitive impairment. We examined the association between resting blood pressure and diffusion tensor imaging (DTI) indices of white matter microstructure in 128 healthy older adults (43-87 years) spanning the normotensive to moderate-severe hypertensive range. Mean arterial blood pressure (MABP) was related to diffusion measures in several regions of the brain with greatest associations in the anterior corpus callosum and lateral frontal, precentral, superior frontal, lateral parietal and precuneus white matter. Associations between white matter integrity and blood pressure remained when controlling for age, when controlling for white matter lesions, and when limiting the analyses to only normotensive, pharmacologically controlled and pre-hypertensive individuals. Of the diffusion measures examined, associations were strongest between MABP and radial diffusivity which may indicate that blood pressure has an influence on myelin structure. Associations between MABP and white matter integrity followed spatial patterns resembling those often attributed to the effects of chronological age, suggesting that systemic cerebrovascular health may play a role in neural tissue degeneration classically ascribed to aging. These results demonstrate the importance of the consideration of vascular physiology in studies of cognitive and neural aging, and that this significance extends to even the normotensive and medically controlled population. These data additionally suggest that optimal management of blood pressure may require consideration of the more subtle influence of vascular health on neural health in addition to the primary goal of prevention of a major cerebrovascular event.

Acute alcohol effects on contextual memory BOLD response: differences based on fragmentary blackout history.

BACKGROUND: Contextual memory, or memory for source details, is an important aspect of episodic memory and has been implicated in alcohol-induced fragmentary blackouts (FBs). Little is known, however, about how neural functioning during contextual memory processes may differ between individuals with and without a history of FB. This study examined whether neural activation during a contextual memory task differed by history of FB and acute alcohol consumption. METHODS: Twenty-four matched individuals with (FB+; n = 12) and without (FB-; n = 12) a history of FBs were recruited from a longitudinal study of alcohol use and behavioral risks and completed a laboratory beverage challenge followed by 2 functional magnetic resonance imaging (fMRI) sessions under no alcohol and alcohol (breath alcohol concentration = 0.08%) conditions. Task performance and brain hemodynamic activity during a block design contextual memory task were examined across 48 fMRI sessions. RESULTS: Groups demonstrated no differences in performance on the contextual memory task, yet exhibited different brain response patterns after alcohol intoxication. A significant FB group by beverage interaction emerged in bilateral dorsolateral prefrontal cortex and posterior parietal cortex with FB- individuals showing greater blood oxygenation level-dependent response after alcohol exposure (p < 0.05). CONCLUSIONS: Alcohol had differential effects on neural activity for FB+ and FB- individuals during recollection of contextual information, perhaps suggesting a neurobiological mechanism associated with alcohol-induced FB.

circadian rhythms are not captured equal: Exploring Circadian metrics extracted by differentcomputational methods from smartphone accelerometer and GPS sensors in daily life tracking.

Objective: To identify the differences between circadian rhythm (CR) metrics characterized by different mobile sensors and computational methods. Methods: We used smartphone tracking and daily survey data from 225 college student participants, applied four methods (survey construct automation, cosinor regression, non-parametric method, Fourier analysis) on two types of smartphone sensor data (GPS, accelerometer) to characterize CR. We explored the inter-relations among the extracted circadian metrics as well as between the circadian metrics and participants' self-reported mood and sleep outcomes. Results: Compared to GPS signals, smartphone accelerometer activity follows an intradaily distribution that starts earlier in the day, winds down later, reaches half cumulative activity about the same time, conforms less to a sinusoidal wave, and exhibits more intradaily fragmentation but higher CR strength and lower interdaily disruption. We found a notable negative correlation between intradaily variability and CR strength especially pronounced in GPS activity. Self-reported sleep and mood outcomes showed significant correlations with particular CR metrics. Conclusions: We revealed significant inter-relations and discrepancies in the circadian metrics discovered from two smartphone sensors and four CR algorithms and their bearings on wellbeing indicators such as sleep quality and loneliness.

Neural regions associated with gain-loss frequency and average reward in older and younger adults.

Research on the biological basis of reinforcement-learning has focused on how brain regions track expected value based on average reward. However, recent work suggests that humans are more attuned to reward frequency. Furthermore, older adults are less likely to use expected values to guide choice than younger adults. This raises the question of whether brain regions assumed to be sensitive to average reward, like the medial and lateral PFC, also track reward frequency, and whether there are age-based differences. Older (60-81 years) and younger (18-30 years) adults performed the Soochow Gambling task, which separates reward frequency from average reward, while undergoing fMRI. Overall, participants preferred options that provided negative net payoffs, but frequent gains. Older adults improved less over time, were more reactive to recent negative outcomes, and showed greater frequency-related activation in several regions, including DLPFC. We also found broader recruitment of prefrontal and parietal regions associated with frequency value and reward prediction errors in older adults, which may indicate compensation. The results suggest greater reliance on average reward for younger adults than older adults.

Trajectories of Insomnia in Adults After Traumatic Brain Injury.

Importance: Insomnia is common after traumatic brain injury (TBI) and contributes to morbidity and long-term sequelae. Objective: To identify unique trajectories of insomnia in the 12 months after TBI. Design, Setting, and Participants: In this prospective cohort study, latent class mixed models (LCMMs) were used to model insomnia trajectories over time and to classify participants into distinct profile groups. Data from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study, a longitudinal, multisite, observational study, were uploaded to the Federal Interagency Traumatic Brain Injury Repository (FITBIR) database. Participants were enrolled at 1 of 18 participating level I trauma centers and enrolled within 24 hours of TBI injury. Additional data were obtained directly from the TRACK-TBI investigators that will be uploaded to FITBIR in the future. Data were collected from February 26, 2014, to August 8, 2018, and analyzed from July 1, 2020, to November 15, 2021. Exposures: Traumatic brain injury. Main Outcomes and Measures: Insomnia Severity Index assessed serially at 2 weeks and 3, 6, and 12 months thereafter. Results: The final sample included 2022 participants (1377 [68.1%] men; mean [SD] age, 40.1 [17.2] years) from the FITBIR database and the TRACK-TBI study. The data were best fit by a 5-class LCMM. Of these participants, 1245 (61.6%) reported persistent mild insomnia symptoms (class 1); 627 (31.0%) initially reported mild insomnia symptoms that resolved over time (class 2); 91 (4.5%) reported persistent severe insomnia symptoms (class 3); 44 (2.2%) initially reported severe insomnia symptoms that resolved by 12 months (class 4); and 15 (0.7%) initially reported no insomnia symptoms but had severe symptoms by 12 months (class 5). In a multinomial logistic regression model, several factors significantly associated with insomnia trajectory class membership were identified, including female sex (odds ratio [OR], 1.65 [95% CI, 1.02-2.66]), Black race (OR, 2.36 [95% CI, 1.39-4.01]), history of psychiatric illness (OR, 2.21 [95% CI, 1.35-3.60]), and findings consistent with intracranial injury on computed tomography (OR, 0.36 [95% CI, 0.20-0.65]) when comparing class 3 with class 1. Conclusions and Relevance: These results suggest important heterogeneity in the course of insomnia after TBI in adults. More work is needed to identify outcomes associated with these insomnia trajectory class subgroups and to identify optimal subgroup-specific treatment approaches.

Thickness of the human cerebral cortex is associated with metrics of cerebrovascular health in a normative sample of community dwelling older adults.

We examined how wide ranges in levels of risk factors for cerebrovascular disease are associated with thickness of the human cerebral cortex in 115 individuals ages 43-83 with no cerebrovascular or neurologic history. Cerebrovascular risk factors included blood pressure, cholesterol, body mass index, creatinine, and diabetes-related factors. Variables were submitted into a principal components analysis that confirmed four orthogonal factors (blood pressure, cholesterol, cholesterol/metabolic and glucose). T1-weighted MRI was used to create models of the cortex for calculation of regional cortical thickness. Increasing blood pressure factor scores were associated with numerous regions of reduced thickness. Increasing glucose scores were modestly associated with areas of regionally decreased thickness. Increasing cholesterol scores, in contrast, were associated with thicker cortex across the whole brain. All findings were primarily independent of age. These results provide evidence that normal and moderately abnormal levels of parameters used to assess cerebrovascular health may impact brain structure, even in the absence of cerebrovascular disease. Our data have important implications for the clinical management of vascular health, as well as for what is currently conceptualized as "normal aging" as they suggest that subclinical levels of risk may impact cortical gray matter before a disease process is evident.

With age comes wisdom: decision making in younger and older adults.

In two experiments, younger and older adults performed decision-making tasks in which reward values available were either independent of or dependent on the previous sequence of choices made. The choice-independent task involved learning and exploiting the options that gave the highest rewards on each trial. In this task, the stability of the expected reward for each option was not influenced by the previous choices participants made. The choice-dependent task involved learning how each choice influenced future rewards for two options and making the best decisions based on that knowledge. Younger adults performed better when rewards were independent of choice, whereas older adults performed better when rewards were dependent on choice. These findings suggest a fundamental difference in the way in which younger adults and older adults approach decision-making situations. We discuss the results in the context of prominent decision-making theories and offer possible explanations based on neurobiological and behavioral changes associated with aging.

The effects of priming on frontal-temporal communication.

Repeated exposure to a stimulus facilitates its processing. This is reflected in faster and more accurate identification, reduced perceptual identification thresholds, and more efficient classifications for repeated compared with novel items. Here, we test a hypothesis that this experience-based behavioral facilitation is a result of enhanced communication between distinct cortical regions, which reduces local processing demands. A magnetoencephalographic investigation revealed that repeated object classification led to decreased neural responses in the prefrontal cortex and temporal cortex. Critically, this decrease in absolute activity was accompanied by greater neural synchrony (a measure of functional connectivity) between these regions with repetition. Additionally, the onset of the enhanced interregional synchrony predicted the degree of behavioral facilitation. These findings suggest that object repetition results in enhanced interactions between brain regions, which facilitates performance and reduces processing demands on the regions involved.

The Effects of 24-hour Sleep Deprivation on the Exploration-Exploitation Trade-off.

Sleep deprivation has a complex set of neurological effects that go beyond a mere slowing of mental processes. While cognitive and perceptual impairments in sleep deprived individuals are widespread, some abilities remain intact. In an effort to characterize these effects, some have suggested an impairment of complex decision making ability despite intact ability to follow simple rules. To examine this trade-off, 24-hour total sleep deprived individuals performed two versions of a resource acquisition foraging task, one in which exploration is optimal (to succeed, abandon low value, high saliency options) and another in which exploitation is optimal (to succeed, refrain from switching between options). Sleep deprived subjects exhibited decreased performance on the exploitation task compared to non-sleep deprived controls, yet both groups exhibited increased performance on the exploratory task. These results speak to previous neuropsychological work on cognitive control.

Rest-activity rhythms and white matter microstructure across the lifespan.

STUDY OBJECTIVES: The purpose of this study was to examine how rest-activity (RA) rhythm stability may be associated with white matter microstructure across the lifespan in healthy adults free of significant cardiovascular risk. METHODS: We analyzed multi-shell diffusion tensor images from 103 healthy young and older adults using tract-based spatial statistics (TBSS) to examine relationships between white matter microstructure and RA rhythm stability. RA measures were computed using both cosinor and non-parametric methods derived from 7 days of actigraphy data. Fractional anisotropy (FA) and mean diffusivity (MD) were examined in this analysis. Because prior studies have suggested that the corpus callosum (CC) is sensitive to sleep physiology and RA rhythms, we also conducted a focused region of interest analysis on the CC. RESULTS: Greater rest-activity rhythm stability was associated with greater FA across both young and older adults, primarily in the CC and anterior corona radiata. This effect was not moderated by age group. While RA measures were associated with sleep metrics, RA rhythm measures uniquely accounted for the variance in white matter integrity. CONCLUSIONS: This study strengthens existing evidence for a relationship between brain white matter structure and RA rhythm stability in the absence of health risk factors. While there are differences in RA stability between age groups, the relationship with brain white matter was present across both young and older adults. RA rhythms may be a useful biomarker of brain health across both periods of adult development.

Change in negative attention bias mediates the association between attention bias modification training and depression symptom improvement.

OBJECTIVE: Attention bias modification training (ABMT) is purported to reduce depression by targeting and modifying an attentional bias for sadness-related stimuli. However, few tests of this hypothesis have been completed. METHOD: The present study examined whether change in attentional bias mediated a previously reported association between ABMT condition (active ABMT, sham ABMT, assessments only; N = 145) and depression symptom change among depressed adults. The preregistered, primary measure of attention bias was a discretized eye-tracking metric that quantified the proportion of trials where gaze time was greater for sad stimuli than neutral stimuli. RESULTS: Contemporaneous longitudinal simplex mediation indicated that change in attentional bias early in treatment partially mediated the effect of ABMT on depression symptoms. Specificity analyses indicated that in contrast to the eye-tracking mediator, reaction time assessments of attentional bias for sad stimuli (mean bias and trial level variability) and lapses in sustained attention did not mediate the association between ABMT and depression change. Results also suggested that mediation effects were limited to a degree by suboptimal measurement of attentional bias for sad stimuli. CONCLUSION: When effective, ABMT may improve depression in part by reducing an attentional bias for sad stimuli, particularly early on during ABMT. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Multifactorial prediction of depression diagnosis and symptom dimensions.

While depression is a leading cause of disability, prior investigations of depression have been limited by studying correlates in isolation. A data-driven approach was applied to identify out-of-sample predictors of current depression from adults (N = 217) sampled on a continuum of no depression to clinical levels. The current study used elastic net regularized regression and predictors from sociodemographic, self-report, polygenic scores, resting electroencephalography, pupillometry, actigraphy, and cognitive tasks to classify individuals into currently depressed (MDE), psychiatric control (PC), and no current psychopathology (NP) groups, as well as predicting symptom severity and lifetime MDE. Cross-validated models explained 20.6% of the out-of-fold deviance for the classification of MDEs versus PC, 33.2% of the deviance for MDE versus NP, but -0.6% of the deviance between PC and NP. Additionally, predictors accounted for 25.7% of the out-of-fold variance in anhedonia severity, 65.7% of the variance in depression severity, and 12.9% of the deviance in lifetime depression (yes/no). Self-referent processing, anhedonia, and psychosocial functioning emerged as important differentiators of MDE and PC groups. Findings highlight the advantages of using psychiatric control groups to isolate factors specific to depression.

Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.

Importance: An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability. Objective: To validate the classification accuracy of a previously derived, machine learning, multimodal, brain electrical activity-based Concussion Index in an independent cohort of athletes with concussion. Design, Setting, and Participants: This prospective diagnostic cohort study was conducted at 10 clinical sites (ie, US universities and high schools) between February 4, 2017, and March 20, 2019. A cohort comprising a consecutive sample of 207 athletes aged 13 to 25 years with concussion and 373 matched athlete controls without concussion were assessed with electroencephalography, cognitive testing, and symptom inventories within 72 hours of injury, at return to play, and 45 days after return to play. Variables from the multimodal assessment were used to generate a Concussion Index at each time point. Athletes with concussion had experienced a witnessed head impact, were removed from play for 5 days or more, and had an initial Glasgow Coma Scale score of 13 to 15. Participants were excluded for known neurologic disease or history within the last year of traumatic brain injury. Athlete controls were matched to athletes with concussion for age, sex, and type of sport played. Main Outcomes and Measures: Classification accuracy of the Concussion Index at time of injury using a prespecified cutoff of 70 or less (total range, 0-100, where ≤70 indicates it is likely the individual has a concussion and >70 indicates it is likely the individual does not have a concussion). Results: Of 580 eligible participants with analyzable data, 207 had concussion (124 male participants [59.9%]; mean [SD] age, 19.4 [2.5] years), and 373 were athlete controls (187 male participants [50.1%]; mean [SD] age, 19.6 [2.2] years). The Concussion Index had a sensitivity of 86.0% (95% CI, 80.5%-90.4%), specificity of 70.8% (95% CI, 65.9%-75.4%), negative predictive value of 90.1% (95% CI, 86.1%-93.3%), positive predictive value of 62.0% (95% CI, 56.1%-67.7%), and area under receiver operator characteristic curve of 0.89. At day 0, the mean (SD) Concussion Index among athletes with concussion was significantly lower than among athletes without concussion (75.0 [14.0] vs 32.7 [27.2]; P < .001). Among athletes with concussion, there was a significant increase in the Concussion Index between day 0 and return to play, with a mean (SD) paired difference between these time points of -41.2 (27.0) (P < .001). Conclusions and Relevance: These results suggest that the multimodal brain activity-based Concussion Index has high classification accuracy for identification of the likelihood of concussion at time of injury and may be associated with the return to control values at the time of recovery. The Concussion Index has the potential to aid in the clinical diagnosis of concussion and in the assessment of athletes' readiness to return to play.