Learned regulation of the limbic network via combined EEG and fMRI
Learned regulation of the limbic network via combined EEG and fMRI
批准号:
8464276
负责人:
JOHN GABRIELI
金额:
$23.11万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-05-01 至 2015-02-28
关键词:
AddressAdverse effectsAffectiveAmygdaloid structureAnteriorAnxietyBrainBrain regionClinicalCognitiveDataDiseaseEffectivenessElectroencephalographyEmotionalEmotionsFaceFeedbackFrequenciesFunctional Magnetic Resonance ImagingFunctional disorderGoalsHigh PrevalenceIndividualLeadLearningLogicMachine LearningMagnetic Resonance ImagingMental DepressionMental disordersMethodsMood DisordersNeurosciencesOutcomePainPatternPerceptionPerformancePhysiologicalPlacebosPopulationPost-Traumatic Stress DisordersProceduresProcessPsyche structurePsychiatric therapeutic procedurePsychopathologyRegulationResearchResolutionSelf-control as a personality traitSignal TransductionSourceSpecificityStimulusStructureSyndromeSystemTechniquesTestingTherapeutic InterventionTimeTrainingValidationWorkbasechronic painclinically relevantclinically significantcommon treatmentcostdepressive symptomsdrug developmentemotion regulationimprovedinnovationmental stateneurofeedbackneuropsychiatrynovelpsychologicresearch studyresilienceresponsesocialsuccesstherapy developmenttoolyoung adult
中文摘要
描述(由申请人提供):本项目旨在开发一种新的潜在治疗常见神经精神疾病的方法,特别是慢性疼痛综合征和情感障碍,包括抑郁、焦虑和创伤后应激障碍(PTSD)。我们之前已经证明,实时功能磁共振成像(rt-fMRI)可以提供反馈信号(神经反馈),使人们获得对吻侧前扣带(rACC)激活的习得性自愿控制,从而改变疼痛感知。在这里,
英文摘要
DESCRIPTION (provided by applicant): This project aims to develop a novel potential treatment for common neuropsychiatric disorders, specifically chronic pain syndrome and affective disorders including depression, anxiety, and post-traumatic stress disorder (PTSD). We have previously shown that real-time functional magnetic resonance imaging (rt-fMRI) can provide a feedback signal (neurofeedback) that allows people to gain learned voluntary control of activation in the rostral anterior cingulate (rACC), which in turn alters pain perception. Here,
we aim to develop a brain-validated electroencephalography (EEG) neurofeedback method that involves simultaneous EEG and fMRI recordings. This system will then be used to determine EEG signatures reflective of regulation of rACC and of the amygdala. Multiple psychiatric states (e.g., depressive, anxious) are associated with an inability to regulate emotion and appear to be characterized by dysfunction of the limbic circuit including the ACC and amygdala. However, current psychiatric treatment approaches typically lack specificity regarding brain networks and mechanisms. Based on research studies indicating that individuals can be trained to regulate their own mental and physiological responses through online feedback, the proposed study aims to develop a novel tool for enhancing physiological resilience through psychological training using brain signals as the basis for such feedback. Thus, neurofeedback can provide a potential, complementary/alternate approach for treatment of neuropsychiatric disturbances. The combination of simultaneously acquired high spatial-resolution fMRI data and high temporal-resolution EEG data together with advanced statistical learning approaches provide a plausible way to infer and generate a robust and effective EEG neurofeedback signals that can target even deep brain structures such as the rACC or amygdala as the source of feedback. Given the high prevalence of psychopathology and the non-specific targeting of current treatments, the development of a robust method for learned regulation of specific limbic regions is important. Specifically, the new EEG-neurofeedback tool could be a novel, rational, neuroscience-based therapeutic intervention that could become a portable, easy-to-use, and low-cost clinical tool for improving self-control over brain working. In the long-term such a technique could be useful in alleviating chronic pain and regulating emotional instability and agony in cases of depression and anxiety syndromes.
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会议论文
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批准号:9763085
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财政年份:2012
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Learned regulation of the limbic network via combined EEG and fMRI
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批准号:8302045
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Brain Bases of Language Deficits in SLI and ASD
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财政年份:2011
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负责人:JOHN GABRIELI
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依托单位:
Brain Bases of Language Deficits in SLI and ASD
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资助金额:$61.42万
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财政年份:2011
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负责人:JOHN GABRIELI
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依托单位:
Brain Bases of Language Deficits in SLI and ASD
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财政年份:2011
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Brain Bases of Language Deficits in SLI and ASD
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Using Cognitive Neuroscience to Predict Dyslexia among Kindergarden Children
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Using Cognitive Neuroscience to Predict Dyslexia among Kindergarden Children
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Using Cognitive Neuroscience to Predict Dyslexia among Kindergarden Children
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项目类别:
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资助金额:$58.2万
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依托单位:
Using Cognitive Neuroscience to Predict Dyslexia among Kindergarden Children
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资助金额:$67.75万
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Brain Bases of Language Deficits in SLI and ASD
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依托单位:
Using Cognitive Neuroscience to Predict Dyslexia among Kindergarden Children
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项目类别:
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Developmental Cognitive Neuroscience
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负责人:JOHN GABRIELI
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依托单位:
Developmental Cognitive Neuroscience
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负责人:JOHN GABRIELI
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依托单位:
海外基金