As a promising non-invasive neuroimaging technique, functional near-infrared spectroscopy (fNIRS) has seen increasing use in neuroscientific studies over the last decades.^{1 – 3} Compared to other neuroimaging techniques, fNIRS has several specific advantages: acceptable spatial resolution; lower cost, silent, higher temporal resolution, lower sensitivity to head motion, and fewer physical constraints compared to functional magnetic resonance imaging (fMRI); portability/mobility and few restrictions on use location. These advantages make it an ideal alternative for detecting human brain activity in both healthy people (from newborns to the elderly) and patients with neurological or psychiatric conditions, in both laboratory and natural contexts. Validation studies using simultaneous fNIRS and fMRI scanning have shown fNIRS to be effective for both task-driven activation detection^{4 – 8} and resting-state brain function research.^9,10 FNIRS has been successfully applied to various neuroscience domains, including areas such as motor-related studies with large bodily movements, social cognitive neuroscience, and neurodevelopment.^{11 – 15} In addition to task-evoked activation studies, fNIRS has also seen increasing use in detecting spontaneous brain activity absent of external stimuli during resting state,^{16 – 20} which is particularly useful for several special populations who cannot perform complicated tasks, such as infants and patients with certain deficits.

Backgrounds: Decision-making deficits have been reported as trans-diagnostic characteristics of vulnerability to suicidal behaviors, independent of co-existing psychiatric disorders. Individuals with suicidal behaviors often regret their decision to attempt suicide and may have impairments in future-oriented processing. However, it is not clear how people with suicidal dispositions use future-oriented cognition and past experience of regret to guide decision-making. Here, we examined the processes of regret anticipation and experience in subclinical youth with and without suicidal ideation during value-based decision-making.Methods: In total, 80 young adults with suicidal ideation and 79 healthy controls completed a computational counterfactual thinking task and self-reported measures of suicidal behaviors, depression, anxiety, impulsivity, rumination, hopelessness, and childhood maltreatment.Results: Individuals with suicidal ideation showed a reduced ability to anticipate regret compared to healthy controls. Specifically, suicidal ideators’ experience of regret/relief was significantly different from that of healthy controls upon obtained outcomes, while their disappointment/pleasure experience was not significantly different from healthy controls.Conclusion: These findings suggest that young adults with suicidal ideation have difficulty predicting the consequences or the future value of their behavior. Individuals with suicidal ideation showed impairments in value comparison and flat affect to retrospective rewards, whereas individuals with high suicidality showed blunted affect to immediate rewards. Identifying the counterfactual decision-making characteristics of at-risk suicidal individuals may help to elucidate measurable markers of suicidal vulnerability and identify future intervention targets.

The development of the construction industry has generated a large amount of construction waste, and resource utilization of construction waste is an effective means of recycling. However, such recycled construction waste products still lack market competitiveness and recognition. Consumers’ psychological activities are often influenced by emotions, and the sense of awe plays an important role in green consumption. This study aims to investigate how the sense of awe affects consumers’ willingness to pay for construction waste recycled products. The study used functional near-infrared spectroscopy (fNIRS) with a willingness-to-pay task paradigm for experiments, which aims to reveal how different types of awe affect willingness to pay for construction waste recycled products. The behavioral results showed that two conditions effectively induced awe and enhanced consumers’ willingness to pay, but the difference between nature awe and social awe was not significant. The neural activation results showed significant activation in the inferior prefrontal gyrus and dorsolateral prefrontal cortex. In particular, dorsolateral prefrontal cortex activity was significantly enhanced in the social awe condition. The functional connectivity results showed that, compared to the control condition experiment, the awe condition experiment triggered stronger functional connectivity. Therefore, exploring the effect of awe on the willingness to pay for construction waste recycled products can provide a basis reference for companies to develop marketing strategies and corporate pricing and promote the promotion and application of construction waste recycled products in the market.

Functional near-infrared spectroscopy (fNIRS) -based hyperscanning is a popular new technology in the field of social neuroscience research. In recent years, studying human social interaction from the perspective of inter-brain networks has received increasing attention. In the present study, we proposed a new approach named the hyper-brain independent component analysis (HB-ICA) for detecting the inter-brain networks from fNIRS-hyperscanning data. HB-ICA is an ICA-based, data-driven method, and can be used to search the inter-brain networks of social interacting groups containing multiple participants. We validated the method by using both simulated data and in vivo fNIRS-hyperscanning data. The results showed that the HB-ICA had good performance in detecting the inter-brain networks in both simulation and in-vivo experiments. Our approach provided a promising tool for studying the neural mechanism of human social interactions.

Functional connectivity analysis is widely used to characterize large-scale brain networks in fNIRS, but conventional approaches rely on pairwise interactions and may overlook multiregional coordination. Here, we propose a higher-order functional connectivity and topological analysis framework for multichannel fNIRS data, based on triangle-level co-fluctuations and weighted simplicial-complex representations. Using resting-state fNIRS data, we evaluated the reliability of higher-order connectivity metrics. Triangle-based higher-order connectivity showed consistent spatial-pattern reliability ( r = 0.572 intra-session; r = 0.280 inter-session) and moderate feature-wise reliability (single-measure ICC ≈ 0.31-0.32), comparable to pairwise connectivity and higher than edge-centric measures, while topological scaffold features exhibited lower reliability. As an exploratory application, higher-order connectivity demonstrated robust individual identifiability ( I _diff = 0.053), exceeding pairwise (0.044) and edge-centric connectivity (0.041), with rank-based identification performance above chance (AUC = 0.58). Scaffold features showed lower I _diff but remained above-chance rank-based identification performance. Overall, these findings demonstrate that higher-order and topological features can be reliably derived from fNIRS data and provide complementary information beyond pairwise connectivity. The proposed framework establishes a methodological foundation for investigating higher-order functional networks in fNIRS.