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Impact of head modeling and sensor types in localizing human gamma-band oscillations

机译:头部建模和传感器类型对人类伽马波段振荡的定位影响

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An effective mechanism in neuronal communication is oscillatory neuronal synchronization. The neuronal gamma-band (30–100 Hz) synchronization is associated with attention which is induced by a certain visual stimuli. Numerous studies have shown that the gamma-band activity is observed in the visual cortex. However, impact of different head modeling techniques and sensor types to localize gamma-band activity have not yet been reported. To do this, the brain activity was recorded using 306 magnetoencephalography (MEG) sensors, consisting of 102 magnetometers and 102 pairs of planar gradiometers (one measuring the derivative of the magnetic field along the latitude and the other along the longitude), and the data were analyzed with respect to time, frequency, and location of the strongest response. The spherical head models with a single-shell and overlapping spheres (local sphere) have been used as a forward model for calculating the external magnetic fields generated from the gamma-band activity. For each sensor type, the subject-specific frequency range of the gamma-band activity was obtained from the spectral analysis. The identified frequency range of interest with the highest gamma-band activity is then localized using a spatial-filtering technique known as dynamic imaging of coherent sources (DICS). The source analysis for all the subjects revealed that the gradiometer sensors which measure the derivative along the longitude, showed sources close to the visual cortex (cuneus) as compared to the other gradiometer sensors which measure the derivative along the latitude. However, using the magnetometer sensors, it was not possible to localize the sources in the region of interest. When comparing the two head models, the local-sphere model helps in localizing the source more focally as compared to the single-shell head model.
机译:神经元沟通的有效机制是振荡神经元同步。神经元的伽马波段(30-100 Hz)同步与某些视觉刺激引起的注意力相关。大量研究表明,在视觉皮层中观察到了伽玛带活动。但是,尚未报道使用不同的头部建模技术和传感器类型来定位伽马波段活动的影响。为此,使用306个脑磁图(MEG)传感器记录了大脑的活动,该传感器由102个磁力仪和102对平面梯度仪组成(一个沿纬度测量磁场的导数,另一个沿经度测量磁场的导数),并记录数据就时间,频率和响应最强的位置进行了分析。具有单壳和重叠球体(局部球体)的球形头模型已被用作正向模型,用于计算由伽马带活动产生的外部磁场。对于每种传感器类型,可以从光谱分析中获得特定对象的伽马波段活动频率范围。然后使用被称为相干源动态成像(DICS)的空间滤波技术,对确定的具有最高伽玛带活动性的感兴趣频率范围进行定位。对所有受试者的源分析表明,与沿纬度测量导数的其他梯度计传感器相比,沿经度测量导数的梯度计传感器显示的源靠近视觉皮层(cuneus)。但是,使用磁力计传感器无法将源定位在感兴趣的区域中。比较两个头部模型时,与单壳头部模型相比,局部球体模型有助于更集中地定位源。

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