1.     Marino, C. (§), Gemignani, J. (§), Peña, M., Martinez-Alvarez, A., Bonadies, L., Baraldi, E. and Gervain, J. “Do newborns detect prosodic violations in an unfamiliar language at birth?”, Brain and Language (§: co-first authors, accepted Sept 7th 2025), https://doi.org/10.1016/j.bandl.2025.105640

2.   Yücel, M. et al. (2025) “fNIRS Reproducibility Varies with Data Quality, Analysis Pipelines, and Researcher Experience", Communications Biology 8, 1149, https://doi.org/10.1038/s42003-025-08412-1

3.     Stute, K., et al. (2025) "The fNIRS glossary project: a consensus-based resource for functional near-infrared spectroscopy terminology." Neurophotonics 12.2 027801-027801 https://doi.org/10.1117/1.NPh.12.2.027801

4.     Aydın, Z.,, Colavolpe, B., Gemignani, J., Gervain, J., Lucarini, G., Marino, C., Nallet, C., Polver, S., Turconi, M., in press. (2025) “Speech Perception”. In Scott Johnson (ed.): Oxford Handbook of Perceptual Development. Oxford: Oxford University Press. [authors appear in alphabetical order]

5.     Monciatti A., Lapini M., Gemignani J., Frediani G., Carpi F. (2025) “Unpleasant odors compared to pleasant ones cause higher cortical activations detectable by fNIRS and observable mostly in females”, APL Bioengineering. 1 March 2025; 9 (1): 016101. https://doi.org/10.1063/5.0231217

6.     Casetta, I., Crepaldi, A., Laudisi, M., Baroni, A., Gemignani, J., Straudi, S., Manfredini, F., Lamberti, N. (2024) “Variations of cortical oxygenation by near-infrared spectroscopy according to head positioning after an acute stroke: an observational study”, Journal of Clinical Medicine, 13, 3914, DOI: 10.3390/jcm13133914

7.     Gemignani, J. (*), Gervain, J. (2024) “A Within-Subject Multimodal NIRS-EEG Classifier for Infant Data”, Sensors, 24, 4161, DOI: 10.3390/s24134161 (*corresponding author)

8.     Deroche, M., Wolfe, J., Neumann, S., Manning, J., Hanna, L., Towler, W., Wilson, C., Bien, A., Miller, S., Schafer, E., Gemignani, J., Alemi, R., Muthuraman, M., Koirala, N. & Gracco, V.L. (2024) “Cross-modal plasticity in children with cochlear implant: converging evidence from EEG and fNIRS”, Brain Communications, fcae175, DOI:10.1093/braincomms/fcae175

9.     Gemignani, J.*, and Gervain, J. (2024) “Brain responses to repetition-based rule-learning do not exhibit sex differences: an aggregated analysis of infant fNIRS studies”, Scientific Reports 14, 2611, DOI: 10.1038/s41598-024-53092-2 (*corresponding author)

10.  Alemi, R., Wolfe, J., Neumann, S., Manning, J., Hanna, L., Towler, W., Wilson, C., Bien, A., Miller, S., Schafer, E., Gemignani J., Koirala, N., Gracco, V.L. and De Roche, M. (2024) “Motor Processing in Children with Cochlear Implants: Studying Brain Activation with Functional Near-Infrared Spectroscopy (fNIRS)”, Perceptual and Motor Skills: 00315125231213167, DOI: 10.1177/00315125231213167

11.  Gemignani J.*, de la Cruz-Pavia I., Martinez A., Nallet, C., Pasquini A., Lucarini G., Cavicchiolo F., Gervain J. (2023) "Reproducibility of infant fNIRS studies: a meta-analytic approach". Neurophotonics 10(2), 023518, DOI: 10.1117/1.NPh.10.2.023518 (* corresponding author)

12.  Stibbs-Eaton, L., Hodgson, C., Kolade, A., Crowell, J., Gemignani, J., Hope, H., Pierce, M., Elmadih, A., Zhao, C., Downey, D., Elliott, E. & Abel, K. M. (2022). Vocal brain development in infants of mothers with serious mental illness (CAPRI-Voc): study protocol. BMJ open, 12(3), e053598, DOI: 10.1136/bmjopen-2021-053598

13.  Gemignani, J.*, & Gervain, J. (2021). Comparing different pre-processing routines for infant fNIRS data. Developmental cognitive neuroscience, 48, 100943, DOI: 10.1016/j.dcn.2021.100943 (*corresponding author)

14.  Riccardi, A., Gemignani, J., Fernández-Navarro, F., & Heffernan, A. (2021). Optimisation of non-pharmaceutical measures in COVID-19 growth via neural networks. IEEE Transactions on Emerging Topics in Computational Intelligence, 5(1), 79-91, DOI: 10.1109/TETCI.2020.3046012.

15.  Gemignani J.*, Middell E., Barbour R.L., Graber H.L., Blankertz B., Improving the analysis of near-infrared spectroscopy data with multivariate classification of hemodynamic patterns: A theoretical formulation and validation (2018), Journal of Neural Engineering, 15(4), DOI: 10.1088/1741-2552/aabb7c (*corresponding author)

16.  Fisher, S. P., Cui, N., McKillop, L. E., Gemignani, J., Bannerman, D. M., Oliver, P. L., Peirson S.N and Vyazovskiy, V. V. (2016). Stereotypic wheel running decreases cortical activity in mice. Nature communications, 7, 13138, DOI: 10.1038/ncomms13138

17.  Carpi, F., Frediani, G., Gerboni, C., Gemignani, J., & De Rossi, D. (2014). Enabling variable-stiffness hand rehabilitation orthoses with dielectric elastomer transducers. Medical engineering and physics, 36(2), 205-211. DOI: 10.1016/j.medengphy.2013.10.015

1.   Gemignani, J (2021): Classification of fNIRS data with LDA and SVM: a proof-of-concept for application in infant studies. In Engineering in Medicine and Biology Society (EMBC), 2021 43rd Annual International Conference of the IEEE (pp. 824-827). IEEE. DOI: 10.1109/EMBC46164.2021.9629951

2.   Gemignani, J* and Gervain , J. (2021): A practical guide for synthetic fNIRS data generation. In Engineering in Medicine and Biology Society (EMBC), 2021 43rd Annual International Conference of the IEEE (pp. 828-831). IEEE. DOI: 10.1109/EMBC46164.2021.9631014 (* corresponding author)

3.   Gemignani, J.*, Bayet, L., Kabdebon, C., Blankertz, B., Pugh, K. R., & Aslin, R. N. (2018, July). Classifying the mental representation of word meaning in children with Multivariate Pattern Analysis of fNIRS. In Engineering in Medicine and Biology Society (EMBC) 2018 40th Annual International Conference of the IEEE (pp. 295-298). IEEE. DOI: 10.1109/EMBC.2018.8512209 (*corresponding author)

4.   Gemignani, J.*, Gheysens, T., & Summerer, L. (2015, August). Beyond astronaut's capabilities: The current state of the art. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (pp. 3615-3618). IEEE. DOI: 10.1109/EMBC.2015.7319175 (*corresponding author)

5.   Gemignani, J.*, Agrimi, J., Cheli, E., Gemignani, A., Laurino, M., Allegrini, P., Landi A. and Menicucci, D. (2015, August). Pattern recognition with adaptive-thresholds for sleep spindle in high density EEG signals. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (pp. 594-597). IEEE. DOI: 10.1109/EMBC.2015.7318432 (*corresponding author)