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Linear regression with short source-detector separation channels (S-channels) as references is an efficient way to overcome significant physiological interference from the superficial layer for functional nearinfrared spectroscopy (fNIRS). However, the co-located configuration of Schannels and long source-detector separation channels (L-channels) is difficult to achieve in practice. In this study, we recorded superficial interference with S-channels in multiple scalp regions. We found that superficial interference has overall frequency-specific and globally symmetrical patterns. The performance of linear regression is also dependent on these patterns, indicating the possibility of simplifying the Schannel configurations for multiregional fNIRS imaging.

Accumulating evidence has revealed that the resting-state functional connectivity (RSFC) is frequency specific and functional system dependent. Determination of dominant frequency of RSFC (RSFCdf) within a functional system, therefore, is of importance for further understanding the brain interaction and accurately assessing the RSFC within the system. Given the unique advantages over other imaging techniques, functional near-infrared spectroscopy (fNIRS) holds distinct merits for RSFCdf determination. However, an obstacle that hinders fNIRS from potential RSFCdf investigation is the interference of various global noises in fNIRS data which could bring spurious connectivity at the frequencies unrelated to spontaneous neural activity. In this study, we first quantitatively evaluated the interferences of multiple systemic physiological noises and the motion artifact by using simulated data. We then proposed a functional system dependent and frequency specific analysis method to solve the problem by introducing anatomical priori information on the functional system of interest. Both the simulated and real resting-state fNIRS experiments showed that the proposed method outperforms the traditional one by effectively eliminating the negative effects of the global noises and significantly improving the accuracy of the RSFCdf estimation. The present study thus provides an effective approach to RSFCdf determination for its further potential applications in basic and clinical neurosciences.

Perception and evaluation of environmental hazards are vital for human beings to avoid potential hazard. This study used event-related potentials to explore the neural temporal features in the human brain during the processing of environmental hazard presented by picture stimuli, and we found two stages involved in processing pictures with environmental hazard: the relatively early automatic hazard perception stage indicated by P200 and the later hazard evaluation stage indicated by late positive potential. It provided certain evidence for the hazard perception two-stage model. The results indicated consistency between neural processing toward word and picture stimuli in the hazard evaluation tasks.