Institut de Pharmacologie Moléculaire et Céllulaire (IPMC)

At IPMC, Hélène Marie/Jacques Barik's team is a long-term expert in mechanisms of synaptic and neuronal plasticity associated to learning using whole-cell patch clamping on the one hand (e.g., Marie et al., 2005; Middei et al., 2013) and spatial organism-level learning using rodent behavioral tasks (e.g., Tse et al., 2007; Bethus et al. 2010) on the other hand, but no experimental links currently exist within the team between these two levels (purpose of the new IPMC platform proposed here). Massimo Mantegazza's team is expert in neuron excitability investigations at the single cell level by whole-cell recordings and in studies of neuronal activity by EEG recordings in rodents (Heidrich et al., 2014; Cestele et al 2013; Liautard et al., 2013, 2014). Both Hélène Marie/Jacques Barik and Massimo Mantegazza teams will provide knowledge on biological mechanisms of brain circuits in healthy and disease conditions (Alzheimer, epilepsy) (eg. Marchetti et al. 2011; Guerrini et al. 2014).

Institut de Biologie de Valrose (IBV)

At IBV, Michele Studer's team will provide knowledge on cortical circuit development and assembly (Alfano et al., 2014; Harb et al., 2016) and is currently developing microcircuit analysis ex vivo using multi-electrode arrays (MEA) in collaboration with LJAD and I3S.

Laboratoire d’Informatique, Signaux et Systèmes de Sophia Antipolis (I3S)

At I3S, Alexandre Muzy's project recently extended (theoretically and experimentally) the theory of sequential machines using a new kind of algorithms correlating the activity of structure-based components with the whole network behavior (Muzy & Zeigler, 2014a, 2014b) but lacking theoretical proofs for complex network structures.
Alexandre Muzy's project, Modélisation, Simulation & Neurocognition (MS&N) (I3S and LJAD), emerged from previous project Bio-info at I3S.

Laboratoire Jean-Alexandre Dieudonné (LJAD)

At LJAD, in NeuroStatMod, researchers have expertise in sequential learning and optimization (Devaine et al., 2013), which allows comparing theoretically learning algorithms but lacks network structures. Besides, several statistical methods have been developed to analyze neuronal activity, notably for single unit recording (Tuleau-Malot et al., 2014; Reynaud-Bouret et al., 2014; Albert et al., 2015; 2016). These methods will require renewed efforts in order to be applied on massive recordings, as MEA and secondarily for single unit recording on freely moving animals. Other approaches will be pursued in order to develop new statistical methods for spike sorting and LFP/single unit recordings correlations. ComputaBrain will also collaborate with LJAD through the proposal “Factorisation de matrices pour le traitement de données biomédicales” submitted to the IDEX AAP Data Sciences, for spike sorting and neuronal graph reconstruction.

Institut national de recherche en sciences et technologies du numérique (Inria)

At INRIA, deterministic models are developed from synapses to learning of sequences of items in memory, and multilevel statistical analysis is well established. Network dynamics is also an area of expertise, in close collaboration with LJAD researchers (equivariant and heteroclinic dynamics (Chossat et al., 2016), slow-fast systems (Desroches et al., 2016)).

Bases, corpus, langage (BCL)

At BCL, human behavior and cognitive processes are investigated experimentally and modeled by biologically inspired networks of the cerebral cortex (Brunel & Lavigne, 2009; Lavigne et al., 2011). However, cognitive modeling still lacks statistical models of the data and also biological data on synaptic learning. The collaboration between partners aims at filling all these gaps.