Passive electrical neurofeedback treatment of mTBI: MEG and Behavioral Outcomes
mTBI 的被动电神经反馈治疗:MEG 和行为结果
基本信息
- 批准号:10383148
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-01-01 至 2022-09-30
- 项目状态:已结题
- 来源:
- 关键词:AcuteAddressAftercareBehavioralBlast InjuriesBrain InjuriesChemosensitizationChronicChronic PhaseCognitiveCombined Modality TherapyDatabasesDiagnosisDiagnostic ImagingDouble-Blind MethodElectric StimulationElectroencephalographyEmotionalFunctional disorderGeneral PopulationGenerationsGoalsImageImaging TechniquesImaging technologyIndividualInjuryInvestigationMagnetic Resonance ImagingMagnetoencephalographyMeasuresMemoryMilitary PersonnelMonitorNeurobiologyNeuronal InjuryNeuronal PlasticityNeuronsNeuropsychological TestsNeuropsychologyPhotophobiaPhysiologic pulsePhysiologicalPlacebo ControlPlacebosPost-Concussion SyndromePost-Traumatic HeadachesPost-Traumatic Stress DisordersResearchRestSiteSleep disturbancesSourceSymptomsTBI PatientsTBI treatmentTechniquesTestingTherapeuticTherapeutic InterventionTimeValidationVeteransVisitWakefulnessbasebehavior measurementbehavioral outcomecognitive functioncombatcomorbiditydesigneffective therapyfollow-uphealingimaging approachimaging biomarkerimprovedinterestmild traumatic brain injuryneurofeedbackneuroimagingneuromechanismnon-invasive imagingperformance testsplacebo grouprehabilitation strategyrelating to nervous systemsuccesstreatment group
项目摘要
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 noninvasive imaging 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 potentiation 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.
轻度创伤性脑损伤(mTBI)是导致持续的身体、认知、情感和精神疾病的主要原因
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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MINGXIONG HUANG其他文献
MINGXIONG HUANG的其他文献
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{{ truncateString('MINGXIONG HUANG', 18)}}的其他基金
Diagnostic Machine Learning Algorithm to Identify MEG Features of Mild TBI and Comorbid PTSD
用于识别轻度 TBI 和共病 PTSD 的 MEG 特征的诊断机器学习算法
- 批准号:
10651625 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Diagnostic Machine Learning Algorithm to Identify MEG Features of Mild TBI and Comorbid PTSD
用于识别轻度 TBI 和共病 PTSD 的 MEG 特征的诊断机器学习算法
- 批准号:
10398791 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Diagnostic Machine Learning Algorithm to Identify MEG Features of Mild TBI and Comorbid PTSD
用于识别轻度 TBI 和共病 PTSD 的 MEG 特征的诊断机器学习算法
- 批准号:
9888520 - 财政年份:2020
- 资助金额:
-- - 项目类别:
Passive electrical neurofeedback treatment of mTBI: MEG and Behavioral Outcomes
mTBI 的被动电神经反馈治疗:MEG 和行为结果
- 批准号:
9911992 - 财政年份:2018
- 资助金额:
-- - 项目类别:
Passive electrical neurofeedback treatment of mTBI: MEG and Behavioral Outcomes
mTBI 的被动电神经反馈治疗:MEG 和行为结果
- 批准号:
10189733 - 财政年份:2018
- 资助金额:
-- - 项目类别:
Neuroimaging Investigation of mTBI and its Potentiation of PTSD in Veterans
mTBI 的神经影像学研究及其对退伍军人 PTSD 的增强作用
- 批准号:
9486873 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Diagnosing Mild TBI in VA and Active Duty Military Patients using MEG and DTI
使用 MEG 和 DTI 诊断 VA 和现役军人患者的轻度 TBI
- 批准号:
8391100 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Diagnosing Mild TBI in VA and Active Duty Military Patients using MEG and DTI
使用 MEG 和 DTI 诊断 VA 和现役军人患者的轻度 TBI
- 批准号:
8142261 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Diagnosing Mild TBI in VA and Active Duty Military Patients using MEG and DTI
使用 MEG 和 DTI 诊断 VA 和现役军人患者的轻度 TBI
- 批准号:
8590197 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Neuroimaging Investigation of mTBI and its Potentiation of PTSD in Veterans
mTBI 的神经影像学研究及其对退伍军人 PTSD 的增强作用
- 批准号:
8923101 - 财政年份:2011
- 资助金额:
-- - 项目类别:
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