Short separation regression improves statistical significance and better localizes the hemodynamic response obtained by near-infrared spectroscopy for tasks with differing autonomic responses

短时分离回归提高了统计显著性,并能更好地定位近红外光谱法测得的不同自主神经反应任务的血流动力学响应。

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Abstract

Autonomic nervous system response is known to be highly task-dependent. The sensitivity of near-infrared spectroscopy (NIRS) measurements to superficial layers, particularly to the scalp, makes it highly susceptible to systemic physiological changes. Thus, one critical step in NIRS data processing is to remove the contribution of superficial layers to the NIRS signal and to obtain the actual brain response. This can be achieved using short separation channels that are sensitive only to the hemodynamics in the scalp. We investigated the contribution of hemodynamic fluctuations due to autonomous nervous system activation during various tasks. Our results provide clear demonstrations of the critical role of using short separation channels in NIRS measurements to disentangle differing autonomic responses from the brain activation signal of interest.

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