Krätzig, F.*, Mei, J.*, Rebaliha, M., Rampanjato, Z., Ranaivoson, R., Razafinjato, J., De Neve, J. W., Franke, M., Muller, N., & Emmrich, J. V. (2024). Proportion of foetal and placental abnormalities in Madagascar: a cross-sectional study of 35,919 women at public-sector primary healthcare facilities in central and southern Madagascar, 2017-2020. In press.

Meshkinnejad, R., Mei, J., Lizotte, D., & Mohsenzadeh, Y. (2024). Look-ahead selective plasticity for continual learning of visual tasks. Proceedings of UniReps: the Second Workshop on Unifying Representations in Neural Models. NeurIPS 2024.
doi.org/10.48550/arXiv.2311.01617

Mei, J., & Nagai, Y. (2024). Understanding context dependency in time perception in autism spectrum disorders: a computational study. 2024 IEEE International Conference on Development and Learning (ICDL) (pp. 1-7). IEEE.
doi.org/10.1109/ICDL61372.2024.10645025
 

Wen, W., Mei, J.*, Aktas, H.*, Chang. A., Takada, K., Suzuishi, Y., & Kasahara, S. (2024). Control over self and others’ face: Exploitation and exploration.

Scientific Reports 14 (1), 15473.

doi.org/10.1038/s41598-024-66316-2

Mei, J., Meshkinnejad, R., & Mohsenzadeh, Y. (2023). Effects of neuromodulation-inspired mechanisms on the performance of deep neural networks in a spatial learning task. iScience, 26(2).
doi.org/10.1016/j.isci.2023.106026

Mei, J., Muller, E., & Ramaswamy, S. (2022). Informing deep neural networks by multiscale principles of neuromodulatory systems. Trends in Neurosciences, 45(3), 237-250.
doi.org/10.1016/j.tins.2021.12.008

Nasim, M. Q., Maiti, T., Srivastava, A., Singh, T., & Mei, J. (2022). Seismic facies analysis: a deep domain adaptation approach. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-16.
doi.org/10.1109/TGRS.2022.3151883

Bussiere, N., Mei, J., Lévesque-Boissonneault, C., Blais, M., Carazo, S., Gros-Louis., F., Laforce, R., De Serres, G., Dupré, N., & Frasnelli, J. (2022). Persisting chemosensory impairments in 366 healthcare workers following COVID-19: An 11-month follow-up. Chemical Senses, 47, bjac010.
doi.org/10.1093/chemse/bjac010

Ali, J., Ngo, D. Q., Bhattacharjee, A., Maiti, T., Singh, T., & Mei, J. (2022). Depression detection: text augmentation for robustness to label noise in self-reports. Digital Humanism: A Human-Centric Approach to Digital Technologies (pp. 81-103). Cham: Springer International Publishing.
doi.org/10.1007/978-3-030-97054-3_6

Kohler, J., Mei, J., Banneke, S., Winter, Y., Endres, M. and Emmrich, J. (2022) Assessing spatial learning and memory in mice: classic radial maze versus a new animal-friendly automated radial maze allowing free access and not requiring food deprivation. Frontiers in Behavioral Neuroscience, 16, 1013624.
doi.org/10.3389/fnbeh.2022.1013624

Bussiere, N., Mei, J., Lévesque-Boissonneault, C., Blais, M., Carazo, S., Gros-Louis., F., De Serres, G., Dupré, N., & Frasnelli, J. (2021). Chemosensory dysfunctions induced by COVID-19 can persist up to 7 months: A study of over 700 healthcare workers. Chemical senses, 46, bjab038.
doi.org/10.1093/chemse/bjab038

Mei, J., Desrosiers, C., & Frasnelli, J. (2021). Machine learning for the diagnosis of Parkinson's disease: a review of literature. Frontiers in aging neuroscience, 13, 633752.
doi.org/10.3389/fnagi.2021.633752

Mei, J., Tremblay, C., Stikov N., Desrosiers, C., & Frasnelli, J. (2021). Differentiation of Parkinson’s disease and non-Parkinsonian olfactory dysfunction with structural MRI data. Medical Imaging 2021: Computer-Aided Diagnosis (Vol. 11597, pp. 320-327). SPIE.
doi.org/10.1117/12.2581233

Kang, W., Pineda Hernández, S., & Mei, J. (2020). Neural Mechanisms of Observational Learning: A neural working model. Frontiers in human neuroscience, 14, 609312.
doi.org/10.3389/fnhum.2020.609312

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Tremblay, C., Mei, J., & Frasnelli, J. (2020). Olfactory bulb surroundings can help to distinguish Parkinson’s disease from non-parkinsonian olfactory dysfunction. NeuroImage: Clinical, 28, 102457.
doi.org/10.1016/j.nicl.2020.102457

Shen, J., Mei, J., Walldén, M., & Ino, F. (2020). Integrating GPU support for FreeSurfer with OpenACC. 2020 IEEE 6th International Conference on Computer and Communications (ICCC) (pp. 1622-1628). IEEE. 
doi.org/10.1109/ICCC51575.2020.9345102

Akgun, O. C., & Mei, J. (2019). An energy efficient time-mode digit classification neural network implementation. Philosophical Transactions of the Royal Society A, 378(2164), 20190163.
doi.org/10.1098/rsta.2019.0163

 

Mei, J., Kohler, J., Winter, Y., Spies, C., Endres, M., Banneke, S., & Emmrich, J. V. (2019). Automated radial 8-arm maze: A voluntary and stress-free behavior test to assess spatial learning and memory in mice.  Behavioural Brain Research, 381, 112352.

doi.org/10.1016/j.bbr.2019.112352

Mei, J., Banneke, S., Lips, J., Kuffner, M. T., Hoffmann, C. J., Dirnagl, U., ... & Emmrich, J. V. (2019). Refining Humane Endpoints in Mouse Models of Disease by Systematic Review and Machine Learning-Based Endpoint Definition. ALTEX: Alternatives to Animal Experimentation, 36.
doi.org/10.14573/altex.1812231

Mei, J., Riedel, N., Grittner, U., Endres, M., Banneke, S., & Emmrich, J. V. (2018).

Body temperature measurement in mice during acute illness: implantable temperature transponder versus surface infrared thermometry. Scientific reports, 8(1), 3526.
doi.org/10.1038/s41598-018-22020-6

Mei, J., & Singh, T. (2018). Intra-thalamic and thalamocortical connectivity: potential implication for deep learning. Proceedings of the 1st International Workshop on Software Engineering for Cognitive Services (pp. 9-14).
doi.org/10.1145/3195555.3195556

Jarmolowska, J., Turconi, M. M., Busan, P., Mei, J., & Battaglini, P. P. (2013). A multimenu system based on the P300 component as a time saving procedure for communication with a brain-computer interface. Frontiers in neuroscience, 7, 35988.
doi.org/10.3389/fnins.2013.00039