Search

Subconcussive blast exposure has been shown to alter neurological functioning. However, the extent to which neurological dysfunction persists after blast exposure is unknown. This longitudinal study examined the potential short- and long-term effects of repeated subconcussive blast exposure on neuromotor performance from heavy weapons training in military personnel. A total of 214 participants were assessed; 137 were exposed to repeated subconcussive blasts and 77 were not exposed to blasts (controls). Participants completed a short stepping-in-place task while an Android smartphone app placed on their thigh recorded movement kinematics. We showed acute suppression of neuromotor variability 6 h after subconcussive blast exposure, followed by a rebound to levels not different from baseline at the 72 h, 2-week, and 3-month post-tests. It is postulated that this suppression of neuromotor variability results from a reduction in the functional degrees of freedom from the subconcussive neurological insult. It is important to note that this change in behavior is short-lived, with a return to pre-blast exposure movement kinematics within 72 h.

Abstract Background Subconcussive blast exposure during military training has been the subject of both anecdotal concerns and reports in the medical literature, but prior studies have often been small and have used inconsistent methods. Methods This paper presents the methodology employed in INVestigating traIning assoCiated blasT pAthology (INVICTA) to assess a wide range of aspects of brain function, including immediate and delayed recall, gait and balance, audiologic and oculomotor function, cerebral blood flow, brain electrical activity and neuroimaging and blood biomarkers. Results A number of the methods employed in INVICTA are relatively easy to reproducibly utilize, and can be completed efficiently, while other measures require greater technical expertise, take longer to complete, or may have logistical challenges. Conclusions This presentation of methods used to assess the impact of blast exposure on the brain is intended to facilitate greater uniformity of data collection in this setting, which would enable comparison between different types of blast exposure and environmental circumstances, as well as to facilitate meta-analyses and syntheses across studies.

Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

Mild traumatic brain injury (mTBI) has been firmly associated with disrupted white matter integrity due to induced white matter damage and degeneration. However, comparatively less is known about the changes of the intrinsic functional connectivity mediated via neural synchronization in the brain after mTBI. Moreover, despite the presumed link between structural and functional connectivity, no existing studies in mTBI have demonstrated clear association between the structural abnormality of white matter axons and the disruption of neural synchronization. To investigate these questions, we recorded resting state EEG and diffusion tensor imaging (DTI) from a cohort of military service members. A newly developed synchronization measure, the weighted phase lag index was applied on the EEG data for estimating neural synchronization. Fractional anisotropy was computed from the DTI data for estimating white matter integrity. Fifteen service members with a history of mTBI within the past 3 years were compared to 22 demographically similar controls who reported no history of head injury. We observed that synchronization at low-gamma frequency band (25–40 Hz) across scalp regions was significantly decreased in mTBI cases compared with controls. The synchronization in theta (4–7 Hz), alpha (8–13 Hz), and beta (15–23 Hz) frequency bands were not significantly different between the two groups. In addition, we found that across mTBI cases, the disrupted synchronization at low-gamma frequency was significantly correlated with the white matter integrity of the inferior cerebellar peduncle, which was also significantly reduced in the mTBI group. These findings demonstrate an initial correlation between the impairment of white matter integrity and alterations in EEG synchronization in the brain after mTBI. The results also suggest that disruption of intrinsic neural synchronization at low-gamma frequency may be a characteristic functional pathology following mTBI and may prove useful for developing better methods of diagnosis and treatment.

The objective of this research project is the identification of a physiological prodrome of post-traumatic stress disorder (PTSD) that has a reliability that could justify preemptive treatment in the sub-syndromal state. Because abnormalities in event-related potentials (ERPs) have been observed in fully expressed PTSD, the possible utility of abnormal ERPs in predicting delayed-onset PTSD was investigated. ERPs were recorded from military service members recently returned from Iraq or Afghanistan who did not meet PTSD diagnostic criteria at the time of ERP acquisition. Participants (n = 65) were followed for up to 1 year, and 7.7% of the cohorts (n = 5) were PTSD-positive at follow-up. The initial analysis of the receiver operating characteristic (ROC) curve constructed using ERP metrics was encouraging. The average amplitude to target stimuli gave an area under the ROC curve of greater than 0.8. Classification based on the Youden index, which is determined from the ROC, gave positive results. Using average target amplitude at electrode Cz yielded Sensitivity = 0.80 and Specificity = 0.87. A more systematic statistical analysis of the ERP data indicated that the ROC results may simply represent a fortuitous consequence of small sample size. Predicted error rates based on the distribution of target ERP amplitudes approached those of random classification. A leave-one-out cross validation using a Gaussian likelihood classifier with Bayesian priors gave lower values of sensitivity and specificity. In contrast with the ROC results, the leave-one-out classification at Cz gave Sensitivity = 0.65 and Specificity = 0.60. A bootstrap calculation, again using the Gaussian likelihood classifier at Cz, gave Sensitivity = 0.59 and Specificity = 0.68. Two provisional conclusions can be offered. First, the results can only be considered preliminary due to the small sample size, and a much larger study will be required to assess definitively the utility of ERP prodromes of PTSD. Second, it may be necessary to combine ERPs with other biomarkers in a multivariate metric to produce a prodrome that can justify preemptive treatment.

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions:1. Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. 2. ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are nondisclosing. 3. The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including nonlinear dynamical analysis, complexity measures, analysis of causal interactions, graph theory and information dynamics. 4. and 5. are too long to include here

Psychophysiological investigations of traumatic brain injury (TBI) are being conducted for several reasons, including the objective of learning more about the underlying physiological mechanisms of the pathological processes that can be initiated by a head injury. Additional goals include the development of objective physiologically based measures that can be used to monitor the response to treatment and to identify minimally symptomatic individuals who are at risk of delayed onset neuropsychiatric disorders following injury. Research programs studying TBI search for relationships between psychophysiological measures, particularly ERP component properties (e.g. timing, amplitude, scalp distribution), and a participant’s clinical condition. Moreover, the complex relationships between brain injury and psychiatric disorders are receiving increased research attention, and ERP technologies are making contributions to this effort. This review has two objectives supporting such research efforts. The first is to review evidence indicating that traumatic brain injury is a significant risk factor for post-injury neuropsychiatric disorders. The second objective is to introduce ERP researchers who are not familiar with neuropsychiatric assessment to the instruments that are available for characterizing traumatic brain injury, post-concussion syndrome, and psychiatric disorders. Specific recommendations within this very large literature are made. We have proceeded on the assumption that, as is typically the case in an ERP laboratory, the investigators are not clinically qualified and that they will not have access to participant medical records.