AN91-- research service - MEG analysis

BACKGROUND: Mild traumatic brain injury (mTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral deficits in OEF/OIF/OND Veterans and the general public. However, the underlying pathophysiology is not completely understood, and there are few effective treatments for post-concussive symptoms (PCS). In addition, there are substantial overlaps between PCS and post-traumatic stress disorder (PTSD) symptoms in mTBI. IASIS is among a class of passive neurofeedback treatments that combine low-intensity pulses for transcranial electrical stimulation (LIP-tES) with electroencephalography (EEG) monitoring. LIP-tES techniques have shown promising results in alleviating PCS individuals with TBI. However, the neural mechanisms underlying the effects of LIP-tES treatment in TBI are unknown, owing to the dearth of neuroimaging investigations of this therapeutic intervention. Conventional neuroimaging techniques such as MRI and CT have limited sensitivity in detecting physiological abnormalities caused by mTBI, or in assessing the efficacy of mTBI treatments. In acute and chronic phases, CT and MRI are typically negative even in mTBI patients with persistent PCS. In contrast, evidence is mounting in support of resting-state magnetoencephalography (rs-MEG) slow-wave source imaging (delta-band, 1-4 Hz) as a marker for neuronal abnormalities in mTBI. The primary goal of the present application is to use rs-MEG to identify the neural underpinnings of behavioral changes associated with IASIS treatment in Veterans with mTBI. Using a double-blind placebo controlled design, we will study changes in abnormal MEG slow-waves before and after IASIS treatment (relative to a sham treatment group) in Veterans with mTBI. In addition, we will examine treatment-related changes in PCS, PTSD symptoms, neuropsychological test performances, and their association with changes in MEG slow-waves. We for the first time will address a fundamental question about the mechanism of slow-waves in brain injury, namely whether slow-wave generation in wakefulness is merely a negative consequence of neuronal injury or if it is a signature of ongoing neuronal rearrangement and healing that occurs at the site of the injury. Specific Aim 1 will detect the loci of injury in Veterans with mTBI and assess the mechanisms underlying functional neuroimaging changes related to IASIS treatment using rs-MEG slow-wave source imaging. We hypothesize that MEG slow-wave source imaging will show significantly higher sensitivity than conventional MRI in identifying the loci of injury on a single-subject basis. We also hypothesize that in wakefulness, slow-wave generation is a signature of ongoing neural rearrangement / healing, rather than a negative consequence of neuronal injury. Furthermore, we hypothesize IASIS will ultimately reduce abnormal MEG slow-wave generation in mTBI by the end of the treatment course, owing to the accomplishment of neural rearrangement / healing. Specific Aim 2 will examine treatment-related changes in PCS and PTSD symptoms in Veterans with mTBI. We hypothesize that compared with the sham group, mTBI Veterans in the IASIS treatment group will show significantly greater decreases in PCS and PTSD symptoms between baseline and post-treatment assessments. Specific Aim 3 will study the relationship among IASIS treatment-related changes in rs-MEG slow-wave imaging, PCS, and neuropsychological measures in Veterans with mTBI. We hypothesize that Reduced MEG slow-wave generation will correlate with reduced total PCS score, individual PCS scores (e.g., sleep disturbance, post-traumatic headache, photophobia, and memory problem symptoms), and improved neuropsychological exam scores between post-IASIS and baseline exams. The success of the proposed research will for the first time confirm that facilitation of slow-wave generation in wakefulness leads to significant therapeutic benefits in mTBI, including an ultimate reduction of abnormal slow-waves accompanied by an improvement in PCS and cognitive functioning.

The Contractor shall provide services in support of Dr. Huang s VA Research Study, H170033, Passive Electrical Neurofeedback Treatment of MTBI: MEG and Behavioral outcomes MEG Level 2 Analysis Hours will be used for advanced MEG data analysis including but not limited to Utilization of Matlab Software and Dr. Huang s Patented Software fast-vestal, programming of the software applications pertinent to the subject populations and higher order statistical analysis, and assistance with new study design and provide service in support of Dr. Huang s VA IRB Study, H170033, Passive Electrical Neurofeedback Treatment of MTBI: MEG and behavioral outcomes may Level 1 analysis hours will be used for the management of data quality activities, provide basic level of data pre-processing including utilization of MEG data analysis software including Neuromag Software and Freesurfer, and Basic Statistical Analysis of MEG data.

SPECIFIC TASKS:

MEG Level 1 Analysis Hours

- Management of data quality activities

- Provide basic level of data pre-processing including utilization of MEG data analysis software including Neuromag software and Freesurfer

- Basic statistical analysis of MEG data

MEG Level 2 Analysis Hours

- Advanced MEG data anaylsis including but not limited to utilization of Matlab software and Dr. Mingxiong Huang s patented software Fast-VESTAL

- Programming of software applications pertinent to the subject populations and higher order statistical analysis

- Assistance with new study design

PERFORMANCE MONITORING:

The PI, Dr. Mingxiong Huang, will be checking the quality of performance when MEG analysis hours are used for both Level 1 and Level 2 MEG Analysis.

PLACE OF PERFORMANCE: UCSD RIL: 3510 Dunhill Street, San Diego, CA 92121