Group of Data Modeling, Computational Biology and Predictive Medicine
IBENS

Axe 2 : Approches quantitatives à l'exploration du comportement et de la cognition

Axe 3 : Réseaux neuronaux, modélisation et intelligence artificielle
Exploring the multi-scale interactions of neural processes.
Our team investigates multiscale interactions of neuronal processes from molecules to brain regions using mathematical modeling, AI, and simulations. We develop real-time algorithms to predict brain states during anesthesia or coma and decode activation pathways in neural networks. We also study the impact of stochastic processes on brain responses.
We develop computational methods and algorithms to analyze and simulate brain activity from molecular to the system level. We study receptor trajectories, calcium to EEG time series, we model ionic interactions and to quantify spatial organization. This includes applications to analyzing calcium dynamics, voltage in nanodomains, cell migration patterns, communication dynamics, and complex interactions within neural networks.
Mathematical modeling, artificial intelligence, data analysis, and numerical simulations.
Major publications
Perochon, T., Krsnik, Z., Massimo, M. et al…D. Holcman, Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics. Nat Commun 16, 1577 (2025). https://doi.org/10.1038/s41467-025-56560-z
Zonca L, Bellier FC, Milior G, Aymard P, Visser J, Rancillac A, Rouach N, Holcman D. Commun Biol. 2025 Jan 24;8(1):114. doi: 10.1038/s42003-024-07390-0. PMID: 39856404 Unveiling the functional connectivity of astrocytic networks with AstroNet, a graph reconstruction algorithm coupled to image processing.
Loison V, Voskobiynyk Y, Lindquist B, Necula D, Longrois D, Paz J, Holcman D. Neuroimage. 2024 Jan;285:120498. doi: 10.1016/j.neuroimage.2023.120498. Epub 2023 Dec 20. PMID: 38135170 Mapping general anesthesia states based on electro-encephalogram transition phases.
Mc Hugh J, Makarchuk S, Mozheiko D, Fernandez-Villegas A, Kaminski Schierle GS, Kaminski CF, Keyser UF, Holcman* D, Rouach* N. Nanoscale. 2023 Jul 27;15(29):12245-12254. doi: 10.1039/d2nr03475a. PMID: 37455621 Diversity of dynamic voltage patterns in neuronal dendrites revealed by nanopipette electrophysiology.
Basnayake K, Mazaud D, Kushnireva L, Bemelmans A, Rouach N, Korkotian E, Holcman D. Sci Adv. 2021 Sep 17;7(38):eabh1376. doi: 10.1126/sciadv.abh1376. Epub 2021 Sep 15. PMID: 34524854 Nanoscale molecular architecture controls calcium diffusion and ER replenishment in dendritic spines.
46 Rue d'Ulm, 75005, Paris
Team leader :
Holcman David
Name of co-team leader :
Administrative Contact Name :
Website : Cliquez ici
Key words : #Modélisation neuronale multi-échelle #Intelligence artificielle en neurosciences #Processus stochastiques dans la dynamique cérébrale #Algorithmes prédictifs en temps réel #Simulations de réseaux neuronaux #Multiscale Neuronal Modeling #Artificial Intelligence in Neuroscience #Stochastic Processes in Brain Dynamics Real-Time #Predictive Algorithms Neural #Network reconstruction