Grants per year
Personal profile
Education/Academic qualification
Neuroscience, PhD, Lille 2 University of Health and Law
… → 2014
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Dive into the research topics where Pierre Alain Besson is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Northwestern Alzheimer's Disease Research Center
Vassar, R. J., Avery, R. J., Besson, P. A., Castellani, R. J., Disterhoft, J. F., Flanagan, M. E., Gate, D., Gefen, T. D., Geula, C., Kiskinis, E., Kurani, A., Mao, Q., Martersteck, A., Mesulam, M., Morhardt, D. J., Parrish, T. B., Rogalski, E., Wang, L., Wehbe, F., Weintraub, S., Zhang, H., Bonakdarpour, B. & Grant, I. M.
8/15/21 → 6/30/26
Project: Research project
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Rogalski - Core G
Avery, R. J., Besson, P. A., Kurani, A., Martersteck, A., Parrish, T. B. & Rogalski, E.
8/15/21 → 6/30/26
Project: Research project
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Surface based deep learning to define HIV-related brain aging. Included investigators
Bandt, K., Besson, P. A. & Ragin, A.
University of Washington, National Institute on Aging
5/1/21 → 4/30/22
Project: Research project
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A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction
Wu, Y., Besson, P., Azcona, E. A., Bandt, S. K., Parrish, T. B., Breiter, H. C. & Katsaggelos, A. K., Dec 2022, In: Scientific reports. 12, 1, 17760.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations -
Automatic segmentation of deep grey nuclei using a high-resolution 7T magnetic resonance imaging atlas—Quantification of T1 values in healthy volunteers
Brun, G., Testud, B., Girard, O. M., Lehmann, P., de Rochefort, L., Besson, P., Massire, A., Ridley, B., Girard, N., Guye, M., Ranjeva, J. P. & Le Troter, A., Jan 2022, In: European Journal of Neuroscience. 55, 2, p. 438-460 23 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Geometric deep learning reveals a structuro-temporal understanding of healthy and pathologic brain aging
Besson, P., Rogalski, E., Gill, N. P., Zhang, H., Martersteck, A. & Bandt, S. K., Aug 23 2022, In: Frontiers in Aging Neuroscience. 14, 895535.Research output: Contribution to journal › Article › peer-review
Open Access -
Reconstruction of Resting State FMRI Using LSTM Variational Auto-Encoder on Subcortical Surface to Detect Epilepsy
Wu, Y., Besson, P., Azcona, E. A., Kathleen Bandt, S., Parrish, T. B. & Katsaggelos, A. K., 2022, ISBI 2022 - Proceedings: 2022 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, (Proceedings - International Symposium on Biomedical Imaging; vol. 2022-March).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Geometric deep learning on brain shape predicts sex and age
Besson, P., Parrish, T., Katsaggelos, A. K. & Bandt, S. K., Jul 2021, In: Computerized Medical Imaging and Graphics. 91, 101939.Research output: Contribution to journal › Article › peer-review
6 Scopus citations
Datasets
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Structural constraints of functional connectivity drive cognitive impairment in the early stages of multiple sclerosis
Koubiyr, I. (Creator), Deloire, M. (Creator), Brochet, B. (Creator), Besson, P. A. (Creator), Charré-Morin, J. (Creator), Saubusse, A. (Creator), Tourdias, T. (Creator) & Ruet, A. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.c.5233278.v1, https://sage.figshare.com/collections/Structural_constraints_of_functional_connectivity_drive_cognitive_impairment_in_the_early_stages_of_multiple_sclerosis/5233278/1
Dataset