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Evaluation of neural information content from the phase component of a 32-channel frequency-domain fNIRS system

机译:从32通道频域Fnirs系统的相位分量评估神经信息内容

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We present a 32-transmitter. 32-receiver dual-wavelength frequency-domain (FD) fNIRS system comprised of commercially available avalanche photodiodes. laser drivers and laser mounts. The custom frequency domain (FD) fNIRS system is used to interrogate cerebral tissue with optodes positioned at the posterior occipital region of the head. Data are collected from human subjects watching movie scenes with no sound. We applied cross-validated PCA to identify the number of dimensions retained in the neural signal recorded using FD-fNIRS for the magnitude, phase, and FD (magnitude and phase combined) components of the recorded signal. Importantly, a comparison of the cross-validation error for each signal allows us quantify the dimensionality of the linear subspace spanned by each data type. The number of principal components producing the minimum cross-validation error for the held-out test runs represents the number of orthogonal signal dimensions preserved across training and held-out test data runs. We find that the FD signal captures a higher dimensional space compared to the magnitude or phase signals in isolation. Previous theoretical and empirical work suggest that signals extracted using FD-fNIRS contain higher fidelity neural information than CW-fNIRS in isolation. The findings reported here further support this hypothesis and extend beyond the findings reported in the literature, demonstrating that a higher dimension linear subspace is covered by FD-fNIRS above and beyond the baseline signal captured using traditional CW-fNIRS. assuming other optical performance metrics such as optical dynamic range, noise-equivalent power and cross-talk are comparable. This work was funded by a research contract under Facebook's Sponsored Academic Research Agreement.
机译:我们提供了一个32变送器。 32-接收器双波长频域(FD)FNIRS系统由市售的雪崩光电二极管组成。激光驱动器和激光架。定制频域(FD)Fnirs系统用于与位于头部后枕区位于头部的光电的脑组织。从人类受试者收集数据,观看没有声音的电影场景。我们应用交叉验证的PCA以识别使用FD-FNIR为记录信号的幅度,相位和FD(幅度和相位组合)组件记录的神经信号中保留的尺寸的数量。重要的是,每个信号的交叉验证误差的比较允许我们量化每种数据类型跨越的线性子空间的维度。为保持测试运行的最小交叉验证误差产生的主组件数表示跨越训练和保持测试数据的正交信号尺寸的数量。我们发现FD信号与隔离的幅度或相位信号相比捕获更高的尺寸空间。以前的理论和经验工作表明,使用FD-FNIR提取的信号在隔离中包含比CW-FNIR更高的保真神经信息。这里报告的调查结果进一步支持了这一假设,并延伸到文献中报告的调查结果,表明更高的尺寸线性子空间由上方的FD-FNIR覆盖,超出使用传统CW-Fnirs捕获的基线信号。假设其他光学性能度量如光学动态范围,噪声等效功率和串扰是可比的。这项工作由Facebook赞助的学术研究协议下的研究合同提供资金。

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