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.

Clinical Outcomes After Traumatic Brain Injury and Exposure to Extracranial Surgery: A TRACK-TBI Study.

Importance: Traumatic brain injury (TBI) is associated with persistent functional and cognitive deficits, which may be susceptible to secondary insults. The implications of exposure to surgery and anesthesia after TBI warrant investigation, given that surgery has been associated with neurocognitive disorders. Objective: To examine whether exposure to extracranial (EC) surgery and anesthesia is related to worse functional and cognitive outcomes after TBI. Design, Setting, and Participants: This study was a retrospective, secondary analysis of data from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study, a prospective cohort study that assessed longitudinal outcomes of participants enrolled at 18 level I US trauma centers between February 1, 2014, and August 31, 2018. Participants were 17 years or older, presented within 24 hours of trauma, were admitted to an inpatient unit from the emergency department, had known Glasgow Coma Scale (GCS) and head computed tomography (CT) status, and did not undergo cranial surgery. This analysis was conducted between January 2, 2020, and August 8, 2023. Exposure: Participants who underwent EC surgery during the index admission were compared with participants with no surgery in groups with a peripheral orthopedic injury or a TBI and were classified as having uncomplicated mild TBI (GCS score of 13-15 and negative CT results [CT- mTBI]), complicated mild TBI (GCS score of 13-15 and positive CT results [CT+ mTBI]), or moderate to severe TBI (GCS score of 3-12 [m/sTBI]). Main Outcomes and Measures: The primary outcomes were functional limitations quantified by the Glasgow Outcome Scale-Extended for all injuries (GOSE-ALL) and brain injury (GOSE-TBI) and neurocognitive outcomes at 2 weeks and 6 months after injury. Results: A total of 1835 participants (mean [SD] age, 42.2 [17.8] years; 1279 [70%] male; 299 Black, 1412 White, and 96 other) were analyzed, including 1349 nonsurgical participants and 486 participants undergoing EC surgery. The participants undergoing EC surgery across all TBI severities had significantly worse GOSE-ALL scores at 2 weeks and 6 months compared with their nonsurgical counterparts. At 6 months after injury, m/sTBI and CT+ mTBI participants who underwent EC surgery had significantly worse GOSE-TBI scores (B = -1.11 [95% CI, -1.53 to -0.68] in participants with m/sTBI and -0.39 [95% CI, -0.77 to -0.01] in participants with CT+ mTBI) and performed worse on the Trail Making Test Part B (B = 30.1 [95% CI, 11.9-48.2] in participants with m/sTBI and 26.3 [95% CI, 11.3-41.2] in participants with CT+ mTBI). Conclusions and Relevance: This study found that exposure to EC surgery and anesthesia was associated with adverse functional outcomes and impaired executive function after TBI. This unfavorable association warrants further investigation of the potential mechanisms and clinical implications that could inform decisions regarding the timing of surgical interventions in patients after TBI.

Profiles of Cognitive Functioning at 6 Months After Traumatic Brain Injury Among Patients in Level I Trauma Centers: A TRACK-TBI Study.

Importance: Cognitive dysfunction is common after traumatic brain injury (TBI), with a well-established dose-response relationship between TBI severity and likelihood or magnitude of persistent cognitive impairment. However, patterns of cognitive dysfunction in the long-term (eg, 6-month) recovery period are less well known. Objective: To characterize the prevalence of cognitive dysfunction within and across cognitive domains (processing speed, memory, and executive functioning) 6 months after injury in patients with TBI seen at level I trauma centers. Design, Setting, and Participants: This prospective longitudinal cohort study used data from Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) and included patients aged 17 years or older presenting at 18 US level I trauma center emergency departments or inpatient units within 24 hours of head injury, control individuals with orthopedic injury recruited from the same centers, and uninjured friend and family controls. Participants were enrolled between March 2, 2014, and July 27, 2018. Data were analyzed from March 5, 2020, through October 3, 2023. Exposures: Traumatic brain injury (Glasgow Coma Scale score of 3-15) or orthopedic injury. Main Outcomes and Measures: Performance on standard neuropsychological tests, including premorbid cognitive ability (National Institutes of Health Toolbox Picture Vocabulary Test), verbal memory (Rey Auditory Verbal Learning Test), processing speed (Wechsler Adult Intelligence Scale [4th edition] Processing Speed Index), and executive functioning (Trail Making Test). Results: The sample included 1057 persons with TBI (mean [SD] age, 39.3 [16.4] years; 705 [67%] male) and 327 controls without TBI (mean [SD] age, 38.4 [15.1] years; 222 [68%] male). Most persons with TBI demonstrated performance within 1.5 SDs or better of the control group (49.3% [95% CI, 39.5%-59.2%] to 67.5% [95% CI, 63.7%-71.2%] showed no evidence of impairment). Similarly, 64.4% (95% CI, 54.5%-73.4%) to 78.8% (95% CI, 75.4%-81.9%) of participants demonstrated no evidence of cognitive decline (defined as performance within 1.5 SDs of estimated premorbid ability). For individuals with evidence of either cognitive impairment or decline, diverse profiles of impairment across memory, speed, and executive functioning domains were observed (ie, the prevalence was >0 in each of the 7 combinations of impairment across these 3 cognitive domains for most TBI subgroups). Conclusions and Relevance: In this cohort study of patients seen at level I trauma centers 6 months after TBI, many patients with TBI demonstrated no cognitive impairment. Impairment was more prevalent in persons with more severe TBI and manifested in variable ways across individuals. The findings may guide future research and treatment recommendations.

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.

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.

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.

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.

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.

Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: A GPS-Focused Smartphone Sensing Study.

With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These changes required that students adapt and alter their daily routines accordingly. To investigate patterns associated with these behavioral changes, we collected smartphone sensing data using the Beiwe platform from two groups of undergraduate students at a major North American university, one from January to March of 2020 (74 participants), the other from May to August (52 participants), to observe the differences in students' daily life patterns before and after the start of the pandemic. In this paper, we focus on the mobility patterns evidenced by GPS signal tracking from the students' smartphones and report findings using several analytical methods including principal component analysis, circadian rhythm analysis, and predictive modeling of perceived sadness levels using mobility-based digital metrics. Our findings suggest that compared to the pre-COVID group, students in the mid-COVID group generally 1) registered a greater amount of midday movement than movement in the morning (8-10 a.m.) and in the evening (7-9 p.m.), as opposed to the other way around; 2) exhibited significantly less intradaily variability in their daily movement; 3) visited less places and stayed at home more everyday, and; 4) had a significant lower correlation between their mobility patterns and negative mood.

Association of Posttraumatic Epilepsy With 1-Year Outcomes After Traumatic Brain Injury.

Importance: Posttraumatic epilepsy (PTE) is a recognized sequela of traumatic brain injury (TBI), but the long-term outcomes associated with PTE independent of injury severity are not precisely known. Objective: To determine the incidence, risk factors, and association with functional outcomes and self-reported somatic, cognitive, and psychological concerns of self-reported PTE in a large, prospectively collected TBI cohort. Design, Setting, and Participants: This multicenter, prospective cohort study was conducted as part of the Transforming Research and Clinical Knowledge in Traumatic Brain Injury study and identified patients presenting with TBI to 1 of 18 participating level 1 US trauma centers from February 2014 to July 2018. Patients with TBI, extracranial orthopedic injuries (orthopedic controls), and individuals without reported injuries (eg, friends and family of participants; hereafter friend controls) were prospectively followed for 12 months. Data were analyzed from January 2020 to April 2021. Exposure: Demographic, imaging, and clinical information was collected according to TBI Common Data Elements. Incidence of self-reported PTE was assessed using the National Institute of Neurological Disorders and Stroke Epilepsy Screening Questionnaire (NINDS-ESQ). Main Outcomes and Measures: Primary outcomes included Glasgow Outcome Scale Extended, Rivermead Cognitive Metric (RCM; derived from the Rivermead Post Concussion Symptoms Questionnaire), and the Brief Symptom Inventory-18 (BSI). Results: Of 3296 participants identified as part of the study, 3044 met inclusion criteria, and 1885 participants (mean [SD] age, 41.3 [17.1] years; 1241 [65.8%] men and 644 [34.2%] women) had follow-up information at 12 months, including 1493 patients with TBI; 182 orthopedic controls, 210 uninjured friend controls; 41 patients with TBI (2.8%) and no controls had positive screening results for PTE. Compared with a negative screening result for PTE, having a positive screening result for PTE was associated with presenting Glasgow Coma Scale score (8.1 [4.8] vs.13.5 [3.3]; P < .001) as well as with anomalous acute head imaging findings (risk ratio, 6.42 [95% CI, 2.71-15.22]). After controlling for age, initial Glasgow Coma Scale score, and imaging findings, compared with patients with TBI and without PTE, patients with TBI and with positive PTE screening results had significantly lower Glasgow Outcome Scale Extended scores (mean [SD], 6.1 [1.7] vs 4.7 [1.5]; P < .001), higher BSI scores (mean [SD], 50.2 [10.7] vs 58.6 [10.8]; P = .02), and higher RCM scores (mean [SD], 3.1 [2.6] vs 5.3 [1.9]; P = .002) at 12 months. Conclusions and Relevance: In this cohort study, the incidence of self-reported PTE after TBI was found to be 2.8% and was independently associated with unfavorable outcomes. These findings highlight the need for effective antiepileptogenic therapies after TBI.

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).

Multi-modal data collection for measuring health, behavior, and living environment of large-scale participant cohorts.

BACKGROUND: As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes. RESULTS: To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants' mood, sleep, behavior, and living environment. CONCLUSIONS: We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.

Predictors of six-month inability to return to work in previously employed subjects after mild traumatic brain injury: A TRACK-TBI pilot study.

INTRODUCTION: Return to work (RTW) is an important milestone of mild traumatic brain injury (mTBI) recovery. The objective of this study was to evaluate whether baseline clinical variables, three-month RTW, and three-month postconcussional symptoms (PCS) were associated with six-month RTW after mTBI. METHODS: Adult subjects from the prospective multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot study with mTBI (Glasgow Coma Scale 13-15) who were employed at baseline, with completed three-and six-month RTW status, and three-month Acute Concussion Evaluation (ACE), were extracted. Univariate and multivariable analyses were performed for six-month RTW, with focus on baseline employment, three-month RTW, and three-month ACE domains (physical, cognitive, sleep, and/or emotional postconcussional symptoms (PCS)). Odds ratios (OR) and 95% confidence intervals [CI] were reported. Significance was assessed at p < 0.05. RESULTS: In 152 patients aged 40.7 ± 15.0years, 72% were employed full-time at baseline. Three- and six-month RTW were 77.6% and 78.9%, respectively. At three months, 59.2%, 47.4%, 46.1% and 31.6% scored positive for ACE physical, cognitive, sleep, and emotional PCS domains, respectively. Three-month RTW predicted six-month RTW (OR = 19.80, 95% CI [7.61-51.52]). On univariate analysis, scoring positive in any three-month ACE domain predicted inability for six-month RTW (OR = 0.10-0.11). On multivariable analysis, emotional symptoms predicted inability to six-month RTW (OR = 0.19 [0.04-0.85]). Subjects who scored positive in all four ACE domains were more likely to be unable to RTW at six months (4 domains: 58.3%, vs. 0-to-3 domains: 9.5%; multivariable OR = 0.09 [0.02-0.33]). CONCLUSIONS: Three-month post-injury is an important time point at which RTW status and PCS should be assessed, as both are prognostic markers for six-month RTW. Clinicians should be particularly vigilant of patients who present with emotional symptoms, and patients with symptoms across multiple PCS categories, as these patients are at further risk of inability to RTW and may benefit from targeted evaluation and support.

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.

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.

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.

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.

Memory distortion for orthographically associated words in individuals with depressive symptoms.

While major depressive disorder has been associated with increased veridical memory for negative information, prior false memory literature has linked high depressive symptoms to increased false memory for negative information. We tested whether these contradictory findings may be due to semantic and emotional cohesion inflating false alarm rates in the most commonly used false memory paradigm - the Deese-Roediger-McDermott (DRM). In Experiment 1, healthy controls and depressive participants completed two emotional false memory tasks: the DRM, using semantically associated words, and an adaptation using orthographically associated words. Participants encoded words associated with neutral or negative critical lures. During subsequent recognition memory testing, errors were greater for negative than neutral semantic critical lures, but the opposite pattern was observed for orthographic critical lures. These findings support that orthographically associated stimuli provide a non-confounded method to test emotional false memory. In Experiment 2, we deployed the orthographic paradigm with simultaneous electroencephalography (EEG) and a state measure of negative mood (Positive and Negative Affective Scale) to better understand neurocognitive components of emotional false memory. Replicating Experiment 1, we found fewer false alarms for negative than neutral novel orthographically associated words. The EEG data showed significant differences in two memory-related event-related potentials: the familiarity-related N400, and the recollection-related late positive component (LPC). N400 amplitudes were larger for true versus false endorsements. For LPC, increasing depressive symptoms predicted greater amplitude differences for true versus false negative items and reduced differences for neutral items. However, increasingly negative mood predicted reduced amplitude differences for negative items, and greater amplitude differences for neutral items. Although depressive symptoms and negative mood state are highly correlated, they may inform differentially influence shifts in memory retrieval strategies, with depressive symptoms predicting reduced false alarms for negative information, and negative mood state predicting increased recollection errors for negative information.