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fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience

Title: fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience
Authors: Yücel, MA; Luke, R; Mesquita, RC; von Lühmann, A; Mehler, DMA; Lührs, M; Gemignani, J; Abdalmalak, A; Albrecht, F; de Almeida Ivo, I; Artemenko, C; Ashton, K; Augustynowicz, P; Bajracharya, A; Bannier, E; Barth, B; Bayet, L; Behrendt, J; Khani, HB; Borot, L; Borrell, JA; Brigadoi, S; Brink, K; Bulgarelli, C; Caruyer, E; Chen, HC; Copeland, C; Corouge, I; Cutini, S; Di Lorenzo, R; Dresler, T; Eggebrecht, AT; Ehlis, AC; Erdoğan, SB; Evenblij, D; Ferdous, TR; Fracalossi, V; Franzén, E; Gallagher, A; Gerloff, C; Gervain, J; Goldhamer, N; Gossé, LK; Guérin, SMR; Guevara, E; Hosseini, SH; Innes-Brown, H; Int-Veen, I; Jaffe-Dax, S; Jégou, N; Kawaguchi, H; Kelsey, C; Kent, M; Kessler, R; Kherbawy, N; Klein, F; Kochavi, N; Kolisnyk, M; Koren, Y; Kroczek, A; Kvist, A; Lin, CHP; Löw, A; Luan, S; Mao, D; Martins, GG; Middell, E; Montero-Hernandez, S; Mutlu, MC; Novi, SL; Paquette, N; Paranawithana, I; Parmet, Y; Peelle, JE; Peng, K; Peng, T; Pereira, J; Pinti, P; Pollonini, L; Jounghani, AR; Reindl, V; Ringels, W; Schopp, B; Schulte, A; Schulte-Rüther, M; Segel, A; Ala, TS; Shader, MJ; Shavit, H; Sherafati, A; Soltanlou, M; Sorger, B; Speh, E; Stubbs, KD; Stute, K; Sullivan, EF; Tak, S; Tipado, Z; Tremblay, J; Vahidi, H; Eeckhoutte, MV; Vannasing, P; Vergotte, G; Vincent, MA; Weiss, E; Yang, D; Yükselen, G; Zapała, D; Zemanek, V
Publisher Information: Nature Research
Publication Year: 2025
Collection: Liverpool John Moores University: LJMU Research Online
Subject Terms: RC1200 Sports Medicine
Description: 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.
Document Type: article in journal/newspaper
File Description: text
Language: English
ISSN: 2399-3642
Relation: https://researchonline.ljmu.ac.uk/id/eprint/27017/1/fNIRS%20reproducibility%20varies%20with%20data%20quality%20analysis%20pipelines%20and%20researcher%20experience.pdf; Yücel, MA ORCID logoorcid:0000-0002-4291-2847 , Luke, R ORCID logoorcid:0000-0002-4930-8351 , Mesquita, RC ORCID logoorcid:0000-0003-1945-6713 , von Lühmann, A ORCID logoorcid:0000-0002-4995-293X , Mehler, DMA, Lührs, M, Gemignani, J, Abdalmalak, A, Albrecht, F, de Almeida Ivo, I, Artemenko, C ORCID logoorcid:0000-0001-5947-7960 , Ashton, K, Augustynowicz, P, Bajracharya, A ORCID logoorcid:0000-0002-7361-6020 , Bannier, E ORCID logoorcid:0000-0002-8942-7486 , Barth, B, Bayet, L ORCID logoorcid:0000-0002-0323-7949 , Behrendt, J, Khani, HB ORCID logoorcid:0000-0001-5495-3964 , Borot, L, Borrell, JA, Brigadoi, S, Brink, K, Bulgarelli, C, Caruyer, E, Chen, HC, Copeland, C, Corouge, I, Cutini, S, Di Lorenzo, R ORCID logoorcid:0000-0001-6040-3926 , Dresler, T, Eggebrecht, AT ORCID logoorcid:0000-0002-6320-2676 , Ehlis, AC, Erdoğan, SB, Evenblij, D, Ferdous, TR, Fracalossi, V, Franzén, E, Gallagher, A, Gerloff, C, Gervain, J, Goldhamer, N ORCID logoorcid:0009-0007-3147-2843 , Gossé, LK, Guérin, SMR, Guevara, E ORCID logoorcid:0000-0002-2313-2810 , Hosseini, SH ORCID logoorcid:0000-0001-5186-7008 , Innes-Brown, H, Int-Veen, I, Jaffe-Dax, S ORCID logoorcid:0000-0002-8759-6980 , Jégou, N, Kawaguchi, H, Kelsey, C, Kent, M, Kessler, R ORCID logoorcid:0000-0003-4154-7451 , Kherbawy, N, Klein, F, Kochavi, N, Kolisnyk, M, Koren, Y ORCID logoorcid:0000-0002-3287-279X , Kroczek, A, Kvist, A ORCID logoorcid:0000-0001-7431-2144 , Lin, CHP ORCID logoorcid:0000-0002-5038-0262 , Löw, A, Luan, S ORCID logoorcid:0000-0002-6861-7010 , Mao, D ORCID logoorcid:0000-0003-4077-2710 , Martins, GG, Middell, E, Montero-Hernandez, S, Mutlu, MC ORCID logoorcid:0000-0003-2933-6985 , Novi, SL, Paquette, N, Paranawithana, I ORCID logoorcid:0000-0001-6509-9687 , Parmet, Y, Peelle, JE ORCID logoorcid:0000-0001-9194-854X , Peng, K, Peng, T, Pereira, J, Pinti, P, Pollonini, L, Jounghani, AR, Reindl, V, Ringels, W, Schopp, B, Schulte, A ORCID logoorcid:0000-0003-0131-1030 , Schulte-Rüther, M, Segel, A, Ala, TS, Shader, MJ ORCID logoorcid:0000-0002-4284-2738 , Shavit, H, Sherafati, A, Soltanlou, M, Sorger, B ORCID logoorcid:0000-0003-1393-3144 , Speh, E, Stubbs, KD ORCID logoorcid:0000-0002-1630-8427 , Stute, K ORCID logoorcid:0000-0002-5302-8512 , Sullivan, EF ORCID logoorcid:0000-0002-5949-2850 , Tak, S ORCID logoorcid:0000-0002-3836-0082 , Tipado, Z, Tremblay, J, Vahidi, H, Eeckhoutte, MV, Vannasing, P, Vergotte, G, Vincent, MA, Weiss, E, Yang, D, Yükselen, G, Zapała, D and Zemanek, V (2025) fNIRS reproducibility varies with data quality, analysis pipelines, and researcher experience. Communications Biology, 8 (1). ISSN 2399-3642
DOI: 10.1038/s42003-025-08412-1
Availability: https://researchonline.ljmu.ac.uk/id/eprint/27017/; https://researchonline.ljmu.ac.uk/id/eprint/27017/1/fNIRS%20reproducibility%20varies%20with%20data%20quality%20analysis%20pipelines%20and%20researcher%20experience.pdf; https://doi.org/10.1038/s42003-025-08412-1
Rights: cc_by
Accession Number: edsbas.1EE74F24
Database: BASE