As data analysis pipelines grow more complex in brain imaging research, understanding how methodological choices affect results is essential for ensuring reproducibility and transparency. This is especially relevant for functional Near-Infrared Spectroscopy (fNIRS), a rapidly growing technique for assessing brain function in naturalistic settings and across the lifespan, yet one that still lacks standardized analysis approaches. In the fNIRS Reproducibility Study Hub (FRESH) initiative, we asked 38 research teams worldwide to independently analyze the same two fNIRS datasets. Despite using different pipelines, nearly 80% of teams agreed on group-level results, particularly when hypotheses were strongly supported by literature. Teams with higher self-reported analysis confidence, which correlated with years of fNIRS experience, showed greater agreement. At the individual level, agreement was lower but improved with better data quality. The main sources of variability were related to how poor-quality data were handled, how responses were modeled, and how statistical analyses were conducted. These findings suggest that while flexible analytical tools are valuable, clearer methodological and reporting standards could greatly enhance reproducibility. By identifying key drivers of variability, this study highlights current challenges and offers direction for improving transparency and reliability in fNIRS research.

Numerous studies have reported the beneficial effects of acute exercise on executive functions. Less is known, however, about the effects of exercise on working memory as one subcomponent of executive functions and about its effects on older adults. We investigated the effects of acute moderate-intensity exercise on working memory performance, the respective cortical hemodynamic activation patterns, and the development and persistence of such effects in healthy older adults. Forty-four participants (M: 69.18 years ± 3.92; 21 females) performed a letter 2-back task before and at three time points after (post 15 min, post 30 min, and post 45 min) either listening to an audiobook or exercising (15 min; 50% VO₂-peak). Functional near-infrared spectroscopy (fNIRS) was used to assess cortical hemodynamic activation and brain-behavior correlations in the fronto-parietal working memory network. Overall, we found no group differences for working memory performance. However, only within the experimental group, 2-back performance was enhanced 15 min and 45 min post-exercise. Furthermore, 15 min post-exercise frontal activation predicted working memory performance, regardless of group. In sum, our results indicate slight beneficial effects of acute moderate-intensity exercise on working memory performance in healthy older adults. Findings are discussed in light of the cognitive aging process and moderators affecting the exercise-cognition relationship.

SignificanceA shared understanding of terminology is essential for clear scientific communication and minimizing misconceptions. This is particularly challenging in rapidly expanding, interdisciplinary domains that utilize functional near-infrared spectroscopy (fNIRS), where researchers come from diverse backgrounds and apply their expertise in fields such as engineering, neuroscience, and psychology.AimThe fNIRS Glossary Project was established to develop a community-sourced glossary covering key fNIRS terms, including those related to the continuous-wave (CW), frequency-domain (FD), and time-domain (TD) NIRS techniques.ApproachThe glossary was collaboratively developed by a diverse group of 76 fNIRS researchers, representing a wide range of career stages (from PhD students to experts) and disciplines. This collaborative process, structured across five phases, ensured the glossary’s depth and comprehensiveness.ResultsThe glossary features over 300 terms categorized into six key domains: analysis, experimental design, hardware, neuroscience, mathematics, and physics. It also includes abbreviations, symbols, synonyms, references, alternative definitions, and figures where relevant.ConclusionsThe fNIRS glossary provides a community-sourced resource that facilitates education and effective scientific communication within the fNIRS community and related fields. By lowering barriers to learning and engaging with fNIRS, the glossary is poised to benefit a broad spectrum of researchers, including those with limited access to educational resources.

In neuroimaging research, efforts to enhance replication and reproducibility have increased the focus on improving transparency, particularly in the complex data analysis processes. We conducted a multi-lab collaborative study involving 38 international teams that analyzed two functional Near-Infrared Spectroscopy (fNIRS) datasets. These teams tested seven group-level and forty individual-level hypotheses, and they submitted detailed reports on their analysis pipelines and testing outcomes. The results showed significant variability in hypothesis testing outcomes due to differences in analytical approaches. There was greater consensus in group-level analyses compared to individual-level analyses. Factors such as the pruning method, hemodynamic response function model and estimation, and statistical analysis space partly account for the variability in hypothesis testing outcomes. Additionally, we have found higher similarity in hypothesis testing outcomes across the researchers who reported higher confidence in their analysis skills. This study underscores the importance of complying with best practices in fNIRS analysis methodologies and the need for standardized analysis protocols to improve reliability and credibility.

Significance: The expansion of fNIRS methodology and analysis tools give rise to various design and analytical decisions researchers have to make. Several recent efforts have developed guidelines for preprocessing, analyzing, and reporting practices. For the planning stage of fNIRS studies, similar guidance would be desirable. Study preregistration helps researchers to transparently document study protocols before conducting the study - including materials, methods and analyses - and thus others to verify, understand, and reproduce a study. Preregistration can thus serve as a useful tool for transparent, careful and comprehensive fNIRS study design. Aim: We aim to create a guide about the design and analysis steps involved in fNIRS studies and provide a preregistration template specified for fNIRS studies.Approach: The presented preregistration guide has a strong focus on fNIRS specific requirements, and the associated template provides examples based on continuous-wave fNIRS studies conducted in humans. These can, however, be extended to other types of fNIRS studies. Results: On a step-by-step basis, we walk the fNIRS user through key methodological and analysis-related aspects central to a comprehensive fNIRS study design. These include items specific to the design of continuous-wave, task-based fNIRS studies, but also sections that are of general importance, including an in-depth elaboration on sample size planning. Conclusions: Our guide introduces these open science tools to the fNIRS community, providing researchers with an overview of key design aspects and specification recommendations for comprehensive study planning. As such it can be used as a template to preregister fNIRS studies or merely as a tool for transparent fNIRS study design.