Isao Nambu, Takuya Ozawa, Takanori Sato, Takatsugu Aihara, Yusuke Fujiwara, Yohei Otaka, Rieko Osu, Jun Izawa, Yasuhiro Wada
Journal of Biomedical Optics, Vol. 22, Issue 03, 035008, (March 2017) https://doi.org/10.1117/1.JBO.22.3.035008
TOPICS: Hemodynamics, Sensors, Signal to noise ratio, Lithium, Statistical analysis, Brain, Principal component analysis, Near infrared spectroscopy, Neuroimaging, Data modeling
Functional near-infrared spectroscopy (fNIRS) is a widely utilized neuroimaging tool in fundamental neuroscience research and clinical investigation. Previous research has revealed that task-evoked systemic artifacts mainly originating from the superficial-tissue may preclude the identification of cerebral activation during a given task. We examined the influence of such artifacts on event-related brain activity during a brisk squeezing movement. We estimated task-evoked superficial-tissue hemodynamics from short source–detector distance channels (15 mm) by applying principal component analysis. The estimated superficial-tissue hemodynamics exhibited temporal profiles similar to the canonical cerebral hemodynamic model. Importantly, this task-evoked profile was also observed in data from a block design motor experiment, suggesting a transient increase in superficial-tissue hemodynamics occurs following motor behavior, irrespective of task design. We also confirmed that estimation of event-related cerebral hemodynamics was improved by a simple superficial-tissue hemodynamic artifact removal process using 15-mm short distance channels, compared to the results when no artifact removal was applied. Thus, our results elucidate task design-independent characteristics of superficial-tissue hemodynamics and highlight the need for the application of superficial-tissue hemodynamic artifact removal methods when analyzing fNIRS data obtained during event-related motor tasks.