Bispectral analysis of visual interactions in humans

Bispectral analysis of visual interactions in humans
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DOI:
10.1016/0013-4694(95)00230-8
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发表时间:
1996-02-01
期刊:
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY
影响因子:
--
通讯作者:
Stecker, MM
Stecker, MM
中科院分区:
其他
文献类型:
--
作者:
Shils, JL;Litt, M;Stecker, MM

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先前的电生理学研究已经证明了在视觉空间中的相同位置呈现的双视视觉刺激之间的相互作用。在这项研究中,我们使用非线性谱分析,特别是双谱,研究刺激左右视野引起的脑电活动之间的相互作用。刺激由两个方块组成,每个视野中一个,以不同的频率闪烁。计算了8名受试者单眼观察视觉刺激的双谱、双相干和双相。制作相位与频率和双相与频率图,以确定从刺激施加到EEG电极中出现信号的加权时间延迟。双谱分析揭示了视野之间的非线性相互作用,其加权延迟时间为410 +/-58 msec,而非相互作用分量传播的加权延迟时间为202 +/-39 msec。根据各种模型的预测评估这些结果,我们可以得出结论,这种相互作用不会发生在retinal.These结果说明如何双谱分析可以是一个强大的工具,在分析复杂系统中的神经网络的连接。它允许不同的神经元系统被标记为特定频率的刺激,其连接可以使用头皮EEG的频率分析来追踪。
Previous electrophysiological studies have demonstrated interactions between dichoptic visual stimuli presented to the same location in visual space. In this study, we used non-linear spectral analysis, in particular the bispectrum, to study interactions between the electrocerebral activity resulting from stimulation of the left and right visual fields. The stimulus consisted of two squares, one in each visual field, flickering at different frequencies. Bispectra, bicoherence and biphase were calculated for 8 subjects monocularly observing a visual stimulus. Both phase vs. frequency and biphase vs. frequency plots were made to determine weighted time delays from stimulus application to signal appearance in the EEG electrodes. Bispectral analysis reveals non-linear interactions between visual fields occurring with weighted delay times of 410 +/- 58 msec while non-interactive components propagated with weighted time delays of 202 +/- 39 msec. Evaluating these results in light of the predictions of various models, we were able conclude that this interaction does not occur in the retina.These results illustrate how bispectral analysis can be a powerful tool in analyzing the connectivity of neural networks in complex systems. It allows different neuronal systems to be labeled with stimuli at specific frequencies, whose connections can be traced using frequency analysis of the scalp EEG.