Search

Disrupted sleep is common following combat deployment. Contributors to risk include posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI); however, the mechanisms linking PTSD, mTBI, and sleep are unclear. Both PTSD and mTBI affect frontolimbic white matter tracts, such as the uncinate fasciculus. The current study examined the relationship between PTSD symptom presentation, lateralized uncinate fasciculus integrity, and sleep quality.Participants include 42 combat veterans with and without PTSD and mTBI. Freesurfer and Tracula were used to establish specific white matter ROI integrity via 3-T MRI. The Pittsburgh Sleep Quality Index and PTSD Checklist were used to assess sleep quality and PTSD symptoms.Decreased fractional anisotropy in the right uncinate fasciculus (β = -1.11, SE = 0.47,Both right uncinate integrity and hyperarousal symptom severity are associated withsleep quality in combat veterans. The right uncinate is a key regulator of limbic behavior and sympathetic nervous system reactivity, a core component of hyperarousal. Damage to this pathway may be one mechanism by which mTBI and/or PTSD could create vulnerability for sleep problems following combat deployment.

Objective In stroke survivors, a treatment-resistant problem is inability to volitionally differentiate upper limb wrist extension versus flexion. When one intends to extend the wrist, the opposite occurs, wrist flexion, rendering the limb non-functional. Conventional therapeutic approaches have had limited success in achieving functional recovery of patients with chronic and severe upper extremity impairments. Functional magnetic resonance imaging (fMRI) neurofeedback is an emerging strategy that has shown potential for stroke rehabilitation. There is a lack of information regarding unique blood-oxygenation-level dependent (BOLD) cortical activations uniquely controlling execution of wrist extension versus uniquely controlling wrist flexion. Therefore, a first step in providing accurate neural feedback and training to the stroke survivor is to determine the feasibility of classifying (or differentiating) brain activity uniquely associated with wrist extension from that of wrist flexion, first in healthy adults. Approach We studied brain signal of 10 healthy adults, who performed wrist extension and wrist flexion during fMRI data acquisition. We selected four types of analyses to study the feasibility of differentiating brain signal driving wrist extension versus wrist flexion, as follows: 1) general linear model (GLM) analysis; 2) support vector machine (SVM) classification; 3) ‘Winner Take All’; and 4) Relative Dominance. Results With these four methods and our data, we found that few voxels were uniquely active during either wrist extension or wrist flexion. SVM resulted in only minimal classification accuracies. There was no significant difference in activation magnitude between wrist extension versus flexion; however, clusters of voxels showed extension signal > flexion signal and other clusters vice versa. Spatial patterns of activation differed among subjects. Significance We encountered a number of obstacles to obtaining clear group results in healthy adults. These obstacles included the following: high variability across healthy adults in all measures studied; close proximity of uniquely active voxels to voxels that were common to both the extension and flexion movements; in general, higher magnitude of signal for the voxels common to both movements versus the magnitude of any given uniquely active voxel for one type of movement. Our results indicate that greater precision in imaging will be required to develop a truly effective method for differentiating wrist extension versus wrist flexion from fMRI data.

Objective Pilot testing of real time functional magnetic resonance imaging (rt-fMRI) and real time functional near infrared spectroscopy (rt-fNIRS) as brain computer interface (BCI) neural feedback systems combined with motor learning for motor recovery in chronic severely impaired stroke survivors. Approach We enrolled a four-case series and administered three sequential rt-fMRI and ten rt-fNIRS neural feedback sessions interleaved with motor learning sessions. Measures were: Arm Motor Assessment Tool, functional domain (AMAT-F; 13 complex functional tasks), Fugl-Meyer arm coordination scale (FM); active wrist extension range of motion (ROM); volume of activation (fMRI); and fNIRS HbO concentration. Performance during neural feedback was assessed, in part, using percent successful brain modulations during rt-fNIRS. Main results Pre-/post-treatment mean clinically significant improvement in AMAT-F (.49 ± 0.22) and FM (10.0 ± 3.3); active wrist ROM improvement ranged from 20° to 50°. Baseline to follow-up change in brain signal was as follows: fMRI volume of activation was reduced in almost all ROIs for three subjects, and for one subject there was an increase or no change; fNIRS HbO was within normal range, except for one subject who increased beyond normal at post-treatment. During rt-fNIRS neural feedback training, there was successful brain signal modulation (42%–78%). Significance Severely impaired stroke survivors successfully engaged in spatially focused BCI systems, rt-fMRI and rt-fNIRS, to clinically significantly improve motor function. At the least, equivalency in motor recovery was demonstrated with prior long-duration motor learning studies (without neural feedback), indicating that no loss of motor improvement resulted from substituting neural feedback sessions for motor learning sessions. Given that the current neural feedback protocol did not prevent the motor improvements observed in other long duration studies, even in the presence of fewer sessions of motor learning in the current work, the results support further study of neural feedback and its potential for recovery of motor function in stroke survivors. In future work, expanding the sophistication of either or both rt-fMRI and rt-fNIRS could hold the potential for further reducing the number of hours of training needed and/or the degree of recovery. ClinicalTrials.gov ID: NCT02856035.

Posttraumatic stress disorder (PTSD) is prevalent among veterans with a history of traumatic brain injury (TBI); however, the relationship between TBI and PTSD is not well understood. We present the case of a 31-year-old male veteran with PTSD who reported TBI before entering the military. The reported injury appeared to be mild: He was struck on the head by a baseball, losing consciousness for ∼10 seconds. Years later, he developed severe PTSD after combat exposure. He was not receiving clinical services for these issues but was encountered in the context of a research study. We conducted cognitive, autonomic, and MRI assessments to assess brain function, structure, and neurophysiology. Next, we compared amygdala volume, uncinate fasciculus diffusion, functional connectivity, facial affect recognition, and baroreceptor coherence with those of a control group of combat veterans (n = 23). Our veteran's MRI revealed a large right medial-orbital prefrontal lesion with surrounding atrophy, which the study neuroradiologist interpreted as likely caused by traumatic injury. Comparison with controls indicated disrupted structural and functional connectivity of prefrontal-limbic structures and impaired emotional, cognitive, and autonomic responses. Detection of this injury before combat would have been unlikely in a clinical context because our veteran had reported a phenomenologically mild injury, and PTSD is a simple explanation for substance abuse, sleep impairment, and psychosocial distress. However, it may be that right prefrontal-limbic disruption imparted vulnerability for the development of PTSD and exacerbated our veteran's emotional response to, and recovery from, PTSD.

Background After stroke, wrist extension dyscoordination precludes functional arm/hand. We developed a more spatially precise brain signal for use in brain computer interface (BCI's) for stroke survivors. New method Combination BCI protocol of real-time functional magnetic resonance imaging (rt-fMRI) sequentially followed by functional near infrared spectroscopy (rt-fNIRS) neurofeedback, interleaved with motor learning sessions without neural feedback. Custom Matlab and Python code was developed to provide rt-fNIRS-based feedback to the chronic stroke survivor, system user. Results The user achieved a maximum of 71 % brain signal accuracy during rt-fNIRS neural training; progressive focus of brain activation across rt-fMRI neural training; increasing trend of brain signal amplitude during wrist extension across rt-fNIRS training; and clinically significant recovery of arm coordination and active wrist extension. Comparison with existing methods Neurorehabilitation, peripherally directed, shows limited efficacy, as do EEG-based BCIs, for motor recovery of moderate/severely impaired stroke survivors. EEG-based BCIs are based on electrophysiological signal; whereas, rt-fMRI and rt-fNIRS are based on neurovascular signal. Conclusion The system functioned well during user testing. Methods are detailed for others' use. The system user successfully engaged rt-fMRI and rt-fNIRS neurofeedback systems, modulated brain signal during rt-fMRI and rt-fNIRS training, according to volume of brain activation and intensity of signal, respectively, and clinically significantly improved limb coordination and active wrist extension. fNIRS use in this case demonstrates a feasible/practical BCI system for further study with regard to use in chronic stroke rehab, and fMRI worked in concept, but cost and some patient-use issues make it less feasible for clinical practice.

BACKGROUND: Alcohol use disorder (AUD) is prevalent among individuals diagnosed with human immunodeficiency virus (HIV), and both HIV and alcohol use have been shown to negatively affect the integrity of white matter pathways in the brain. Behavioral, functional, and anatomical impairments have been linked independently to HIV and alcohol use, and these impairments have bases in specific frontally-mediated pathways within the brain. METHODS: Magnetic Resonance Imaging (MRI) data were acquired for 37 HIV+ participants without dementia or hepatitis C. Imaging data were processed through the FreeSurfer and TraCULA pipelines to obtain four bilateral frontal white matter tracts for each participant. Diffusion metrics of white matter integrity along the highest probability pathway for each tract were analyzed with respect to demographics, disease-specific variables, and reported substance use. RESULTS: Significantly increased Axial Diffusivity (AD; decreased axonal integrity) and a trending increase in Mean Diffusivity (MD) were observed along the Anterior Thalamic Radiation (ATR) in participants with a history of AUD. A diagnosis of AUD explained over 36% of the variance in diffusivity along the Anterior Thalamic Radiation overall when accounting for clinical variables including Nadir CD4 and age-adjusted HIV infection length. CONCLUSIONS: The present study provides evidence of HIV-related associations between alcohol use and indicators of axonal integrity loss along the ATR, a frontal pathway involved in the inhibition of addictive or unwanted behaviors. Reduced axonal integrity of this pathway was greatest in HIV+ participants with an AUD, even when considering the effect of age-adjusted disease length and severity (Nadir CD4). This finding implicates a potential biological mechanism linking reduced integrity of frontal white matter to the high prevalence of AUD in an HIV+ population without dementia or hepatitis C.