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中文摘要
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 描述(由申请人提供): 目前还没有成像技术能够以毫秒和毫米分辨率检测整个人脑中的神经元活动。我们建议评估开发一种新的非侵入性方法,声电断层扫描(SET),能够直接成像在整个人脑的电生理活动,这样的分辨率的可能性。在该方法中,传统的头皮脑电图(EEG)被用来测量电活动。产生EEG信号的活动组织的每个位置根据EEG信号中的标记的US签名来确定。该信息可用于非侵入性地构建神经元电流的断层图像。为了发展这种技术,我们将评估三种候选机制:(1)组织电阻率的声电(AE)调制,(2)等效电流偶极子源的机械振动 在活性组织中,和(3)膜性质的调节。目前,这仍然是未知的,这些机制可以用来实现SET。我们将首先在大鼠体内评估这些机制。在目标1中,我们将对大鼠桶皮质的一个区域应用聚焦US,并基于每种机制测试SET的灵敏度。一个桶柱将通过单须刺激激活,并分析大脑或头皮上产生的局部场电位(LFP)。最可行的US编码方案将根据LFP中的US签名来确定。目标2将与目标1非常相似,不同之处在于,将应用US频率沿着变化的单个线性US射束来产生神经元活动的一维图像。目标1和2将建立有效和安全的机制,以开发供人类使用的SET。在目标3中,将用经皮电刺激来刺激手的五个手指,以激活区域3b中的手指区域。线性US束将被应用于区域3b中的每个投影区域。将分析区域3b中的头皮EEG信号,以确定每个投影部位特定的US频率下是否存在EEG信号。这将识别每个活动站点。我们将测试这种方法是否可以识别多种活性组织。或者,我们将首先使用全脑MEG和/或EEG识别活动组织,然后使用US测试每个预测部位的活动存在。这些测试将确定开发真正的全脑美国活动映射(USAmapping)技术的可行性和最佳方向。
英文摘要
 DESCRIPTION (provided by applicant): Presently there is no imaging technology capable of detecting neuronal activity in the entire human brain with millisecond and millimeter resolution. We propose to evaluate the possibility of developing a novel noninvasive method, sonoelectric tomography (SET), capable of directly imaging electrophysiological activity in the entire human brain with such resolution. In this method, conventional scalp electroencephalography (EEG) is used to measure the electrical activity. Each location of active tissue giving rise to the EEG signals is determined from the tagged US signature in the EEG signals. This information can be used to noninvasively construct a tomographic image of neuronal currents. In order to develop such a technique, we will evaluate three candidate mechanisms: (1) acousto-electric (AE) modulation of tissue resistivity, (2) mechanical vibration of the equivalent current dipole sources in active tissue, and (3) modulation of membrane properties. At present, it is still unknown which of these mechanisms can be used to implement the SET. We will first evaluate these mechanisms in rats in vivo. In Aim 1, we will apply a focused US to one region of the barrel cortex of the rat and test the sensitivity of the SET based on each mechanism. One barrel column will be activated by single whisker stimulation and the resulting local field potentials (LFPs) on the brain or scalp will be analyzed. The most viable US-encoding scheme will be determined from the US signatures in the LFPs. Aim 2 will be very similar to Aim 1, except a single linear US beam varying in US frequency along the beam will be applied to produce a one-dimensional image of neuronal activity. Aims 1 and 2 will establish the effective and safe mechanism for developing SET for human use. In Aim 3, the five digits of a hand will be stimulated with transcutaneous electrical stimulation to activate the finger areas in areas 3b. A linear US beam will be applied to each projection area in area 3b. The scalp EEG signals in area 3b will be analyzed for presence of EEG signals at the US frequency specific for each projection site. This will identify each active site. We will test to see if this method can identiy multiple active tissues. Alternatively, we will first identify the active tissues using a whole-hea MEG and/or EEG and then use the US to test the presence of activity at each predicted site. These tests will determine the feasibility and the best direction for developing a truly whole-brai US-based Activity mapping (USAmapping) technique.
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Integrating Electromagnetic Multifocal Brain Stimulation and Recording Technologies
  • 批准号:
    10038182
  • 项目类别:
  • 资助金额:
    $26.21万
  • 财政年份:
    2020
  • 负责人:
    MATTI HAMALAINEN
  • 依托单位:
Integrating Electromagnetic Multifocal Brain Stimulation and Recording Technologies
  • 批准号:
    10224853
  • 项目类别:
  • 资助金额:
    $25.68万
  • 财政年份:
    2020
  • 负责人:
    MATTI HAMALAINEN
  • 依托单位:
Scalable Software for Distributed Processing and Visualization of Multi-Site MEG/EEG Datasets
  • 批准号:
    10175064
  • 项目类别:
  • 资助金额:
    $54.4万
  • 财政年份:
    2018
  • 负责人:
    MATTI HAMALAINEN
  • 依托单位:
Scalable Software for Distributed Processing and Visualization of Multi-Site MEG/EEG Datasets
  • 批准号:
    9750274
  • 项目类别:
  • 资助金额:
    $54.4万
  • 财政年份:
    2018
  • 负责人:
    MATTI HAMALAINEN
  • 依托单位:
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