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中文摘要
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描述(由申请人提供):这项建议的目标是通过表征人类癫痫网络在广泛的时空尺度上的电生理活动来定位人类癫痫网络。几十年来,临床颅内脑电(IEEG)使用有限的空间(厘米尺度)和时间(~0.5-100赫兹)带宽,更多地基于传统,而不是现代神经科学,在癫痫手术评估期间,令寻找离散的、可切除的“电信号病变”的癫痫专家受挫。同样,最近在充分确定癫痫发作可以在标准临床大电极上检测到之后,应用直接脑刺激来终止癫痫发作的努力,到目前为止只取得了部分成功。我们假设,提高临床颅内脑电的空间和时间分辨率可以提高癫痫手术和反应性脑刺激控制癫痫发作的效果。人类癫痫网络产生的病理活动范围从立方厘米脑组织产生的癫痫发作和尖峰,到发生在亚毫米尺度上的高频振荡。最近的证据表明,这些信号的重要成分是在标准临床iEEG检测不到的频率上发现的。使用微线阵列和临床大电极的同时iEEG记录,我们的团队已经开始表征致痫大脑的两个潜在特征:高频振荡和“微癫痫”,这两个特征超出了传统临床iEEG的分辨率。在这一应用中,我们建议对从微线阵列和临床大电极同时记录的连续、高分辨率、宽带iEEG进行分析,以定位人类癫痫网络。我们将在一组接受癫痫手术评估的患者中,前瞻性地将我们的发现与手术结果相关联。这项工作建立在我们在翻译神经工程学方面的既定努力基础上,融合了最先进的癫痫护理和尖端研究。
英文摘要
DESCRIPTION (provided by applicant): The goal of this proposal is to localize human epileptic networks by characterizing their electrophysiological activity over a wide range of spatiotemporal scales. Decades of clinical intracranial EEG (IEEG) using restricted spatial (centimeter scale) and temporal (~0.5-100 Hz) bandwidth, based more on tradition than modern neuroscience, have frustrated epileptologists looking for discrete, resectable "electrographic lesions" during evaluation for epilepsy surgery. Similarly, recent efforts to apply direct brain stimulation to abort seizures after they are sufficiently established to be detected on standard clinical macroelectrodes have, so far, met with only partial success. We hypothesize that enhancing the spatial and temporal resolution of clinical intracranial EEG can improve the efficacy of epilepsy surgery and responsive brain stimulation to control seizures. Human epileptic networks produce pathological activity that ranges from seizures and spikes, generated by cubic centimeters of brain tissue, to high frequency oscillations that occur on sub-millimeter dimensions. Recent evidence suggests that important components of these signals are found at frequencies not detected by standard clinical IEEG. Using simultaneous IEEG recordings from microwire arrays and clinical macroelectrodes, our group has begun to characterize two potential signatures of epileptogenic brain, high frequency oscillations and "micro-seizures," that are outside the resolution of conventional clinical IEEG. In this application, we propose analysis of continuous, high-resolution, wide- bandwidth IEEG recorded simultaneously from microwire arrays and clinical macroelectrodes in order to localize human epileptic networks. We will correlate our findings with surgical outcome, prospectively, in a cohort of patients undergoing evaluation for epilepsy surgery. This work builds upon our established effort in Translational Neuroengineering melding state of the art epilepsy care with cutting-edge research.
期刊论文(35)
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会议论文
DOI: 10.2217/bmm.11.74
发表时间: 2011-10
期刊: Biomarkers in medicine
影响因子: 2.2
作者: [Worrell G, Gotman J]
通讯作者: Gotman J
DOI: 10.1001/jamaneurol.2013.209
发表时间: 2013-08
期刊: JAMA NEUROLOGY
影响因子: 29
作者: [Noe, Katherine, Sulc, Vlastimil, Wong-Kisiel, Lily, Wirrell, Elaine, Van Gompel, Jamie J., Wetjen, Nicholas, Britton, Jeffrey, So, Elson, Cascino, Gregory D., Marsh, W. Richard, Meyer, Fredric, Horinek, Daniel, Giannini, Caterina, Watson, Robert, Brinkmann, Benjamin H., Stead, Matt, Worrell, Gregory A.]
通讯作者: Worrell, Gregory A.
DOI: 10.3171/2010.12.jns10846
发表时间: 2011-04
期刊: Journal of neurosurgery
影响因子: 4.1
作者: [Van Gompel JJ, Koeller KK, Meyer FB, Marsh WR, Burger PC, Roncaroli F, Worrell GA, Giannini C]
通讯作者: Giannini C
DOI: 10.1016/j.cobme.2017.09.006
发表时间: 2017-12
期刊: Current opinion in biomedical engineering
影响因子: 3.9
作者: [Khadjevand F, Cimbalnik J, Worrell GA]
通讯作者: Worrell GA
共 15 条
    Reliable Seizure Prediction Using Physiological Signals and Machine Learning
    • 批准号:
      10518240
    • 项目类别:
    • 资助金额:
      $56.46万
    • 财政年份:
      2022
    • 负责人:
      Gregory A Worrell
    • 依托单位:
    Reliable Seizure Prediction Using Physiological Signals and Machine Learning
    • 批准号:
      10629373
    • 项目类别:
    • 资助金额:
      $58.68万
    • 财政年份:
      2022
    • 负责人:
      Gregory A Worrell
    • 依托单位:
    Reliable Seizure Prediction Using Physiological Signals and Machine Learning
    • 批准号:
      9445497
    • 项目类别:
    • 资助金额:
      $60.76万
    • 财政年份:
      2015
    • 负责人:
      Gregory A Worrell
    • 依托单位:
    Neurophysiologically Based Brain State Tracking & Modulation in Focal Epilepsy
    • 批准号:
      9921573
    • 项目类别:
    • 资助金额:
      $143.77万
    • 财政年份:
      2015
    • 负责人:
      Gregory A Worrell
    • 依托单位:
    海外基金