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.

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.

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.

Substance use on admission toxicology screen is associated with peri-injury factors and six-month outcome after traumatic brain injury: A TRACK-TBI Pilot study.

Substance use is commonly associated with traumatic brain injury (TBI). We investigate associations between active substance use, peri-injury factors, and outcome after TBI across three U.S. Level I trauma centers. TBI subjects from the prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) with Marshall computed tomography (CT) score 1-3, no neurosurgical procedure/operation, and admission urine toxicology screen (tox+/-) were extracted. Associations between tox+/-, comorbidities, hospital variables, and six-month functional (GOSE) and neuropsychiatric (PCL-C, BSI18, RPQ-13, SWLS) outcomes were analyzed. Multivariable regression was performed for associations significant on univariate analysis with odds ratios (mOR) presented. Significance assessed at p < 0.05. In 133 subjects, tox+/tox- were 29.1%/72.9%. Tox+ was younger (35.5/43.6-years, p = 0.018), trended toward male sex (80.6%/63.9%, p = 0.067), was associated with history of seizures (27.8%/10.3%, p = 0.012), self-reported substance use (44.4%/17.5%, p = 0.001), prior TBI (58.8%/34.1%, p = 0.009), GCS < 15 (69.4%/48.4%, p = 0.031) and blood alcohol level >0.08-mg/dl (55.6%/30.8%, p = 0.022). In CT-negative subjects, tox+ was associated with increased hospital admission (95.7%/66.7%, p = 0.034). At six-months, tox+ was associated with screening positive for post-traumatic stress disorder (PCL-C: 40.0%/15.9%; mOR = 8.24, p = 0.022) and psychiatric symptoms (BSI18: 40.0%/14.3%, mOR = 11.06, p = 0.023). Active substance use in TBI may confound GCS assessment, triage to higher level of care, and be associated with increased six-month neuropsychiatric symptoms. Substance use screening should be integrated into standard emergency/acute care TBI protocols to optimize management and resource utilization. Clinicians should be vigilant in providing education, counselling, and follow-up for TBI patients with substance use.

Polytrauma Is Associated with Increased Three- and Six-Month Disability after Traumatic Brain Injury: A TRACK-TBI Pilot Study.

Polytrauma and traumatic brain injury (TBI) frequently co-occur and outcomes are routinely measured by the Glasgow Outcome Scale-Extended (GOSE). Polytrauma may confound GOSE measurement of TBI-specific outcomes. Adult patients with TBI from the prospective Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study had presented to a Level 1 trauma center after injury, received head computed tomography (CT) within 24 h, and completed the GOSE at 3 months and 6 months post-injury. Polytrauma was defined as an Abbreviated Injury Score (AIS) ≥3 in any extracranial region. Univariate regressions were performed using known GOSE clinical cutoffs. Multi-variable regressions were performed for the 3- and 6-month GOSE, controlling for known demographic and injury predictors. Of 361 subjects (age 44.9 ± 18.9 years, 69.8% male), 69 (19.1%) suffered polytrauma. By Glasgow Coma Scale (GCS) assessment, 80.1% had mild, 5.8% moderate, and 14.1% severe TBI. On univariate logistic regression, polytrauma was associated with increased odds of moderate disability or worse (GOSE ≤6; 3 month odds ratio [OR] = 2.57 [95% confidence interval (CI): 1.50-4.41; 6 month OR = 1.70 [95% CI: 1.01-2.88]) and death/severe disability (GOSE ≤4; 3 month OR = 3.80 [95% CI: 2.03-7.11]; 6 month OR = 3.33 [95% CI: 1.71-6.46]). Compared with patients with isolated TBI, more polytrauma patients experienced a decline in GOSE from 3 to 6 months (37.7 vs. 24.7%), and fewer improved (11.6 vs. 22.6%). Polytrauma was associated with greater univariate ordinal odds for poorer GOSE (3 month OR = 2.79 [95% CI: 1.73-4.49]; 6 month OR = 1.73 [95% CI: 1.07-2.79]), which was conserved on multi-variable ordinal regression (3 month OR = 3.05 [95% CI: 1.76-5.26]; 6 month OR = 2.04 [95% CI: 1.18-3.42]). Patients with TBI with polytrauma are at greater risk for 3- and 6-month disability compared with those with isolated TBI. Methodological improvements in assessing TBI-specific disability, versus disability attributable to all systemic injuries, will generate better TBI outcomes assessment tools.

Pre-injury Comorbidities Are Associated With Functional Impairment and Post-concussive Symptoms at 3- and 6-Months After Mild Traumatic Brain Injury: A TRACK-TBI Study.

Introduction: Over 70% of traumatic brain injuries (TBI) are classified as mild (mTBI), which present heterogeneously. Associations between pre-injury comorbidities and outcomes are not well-understood, and understanding their status as risk factors may improve mTBI management and prognostication. Methods: mTBI subjects (GCS 13-15) from TRACK-TBI Pilot completing 3- and 6-month functional [Glasgow Outcome Scale-Extended (GOSE)] and post-concussive outcomes [Acute Concussion Evaluation (ACE) physical/cognitive/sleep/emotional subdomains] were extracted. Pre-injury comorbidities >10% incidence were included in regressions for functional disability (GOSE ≤ 6) and post-concussive symptoms by subdomain. Odds ratios (OR) and mean differences (B) were reported. Significance was assessed at p < 0.0083 (Bonferroni correction). Results: In 260 subjects sustaining blunt mTBI, mean age was 44.0-years and 70.4% were male. Baseline comorbidities >10% incidence included psychiatric-30.0%, cardiac (hypertension)-23.8%, cardiac (structural/valvular/ischemic)-20.4%, gastrointestinal-15.8%, pulmonary-15.0%, and headache/migraine-11.5%. At 3- and 6-months separately, 30.8% had GOSE ≤ 6. At 3-months, psychiatric (GOSE ≤ 6: OR = 2.75, 95% CI [1.44-5.27]; ACE-physical: B = 1.06 [0.38-1.73]; ACE-cognitive: B = 0.72 [0.26-1.17]; ACE-sleep: B = 0.46 [0.17-0.75]; ACE-emotional: B = 0.64 [0.25-1.03]), headache/migraine (GOSE ≤ 6: OR = 4.10 [1.67-10.07]; ACE-sleep: B = 0.57 [0.15-1.00]; ACE-emotional: B = 0.92 [0.35-1.49]), and gastrointestinal history (ACE-physical: B = 1.25 [0.41-2.10]) were multivariable predictors of worse outcomes. At 6-months, psychiatric (GOSE ≤ 6: OR = 2.57 [1.38-4.77]; ACE-physical: B = 1.38 [0.68-2.09]; ACE-cognitive: B = 0.74 [0.28-1.20]; ACE-sleep: B = 0.51 [0.20-0.83]; ACE-emotional: B = 0.93 [0.53-1.33]), and headache/migraine history (ACE-physical: B = 1.81 [0.79-2.84]) predicted worse outcomes. Conclusions: Pre-injury psychiatric and pre-injury headache/migraine symptoms are risk factors for worse functional and post-concussive outcomes at 3- and 6-months post-mTBI. mTBI patients presenting to acute care should be evaluated for psychiatric and headache/migraine history, with lower thresholds for providing TBI education/resources, surveillance, and follow-up/referrals. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT01565551.

Sleep disturbances precede depressive symptomatology following traumatic brain injury.

The purpose of the present study was to evaluate the impact of sleep disturbances on subsequent depressive symptomatology among a representative sample of patients following traumatic brain injury (TBI). Within a retrospective cohort design, our sample included 305 individuals from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot; NINDS-OD09-004) database. At 3-months post-TBI, symptoms of insomnia were reported by 34% of patients, and symptoms of hypersomnia were reported by 39% of patients. For the vast majority of individuals, sleep complaints were likely to persist through 6-month follow-up. Symptoms of hypersomnia but not insomnia at three months were associated with worsened depressive symptomatology at six months. These results highlight the importance of sleep disturbances in recovery from TBI and suggest targeted sleep treatments as a pathway to improve outcomes and quality of life following TBI.