Presentation

Pollock
 

Modélisation, Simulation & Neurocognition (MS&N) is common to the laboratory of Computer Science, Signals and Systems in Sophia Antipolis (I3S) and to the Mathematics laboratory J.-A. Dieudonné (JAD), which belong to both Centre National de la Recherche Scientifique (CNRS) and Université Nice Sophia Antipolis (UNS).

MS&N aims at integrating models from computer science, mathematics and biology.

The study of neurocognition is characterized by sparse and small fragments of observations. Then, the question that cognitivists and neuroscientists ask to modelers is not: how the system behaves really? They ask: Is this hypothesis of behavior/structure acceptable or worth? To answer this question, the problem of the modeler is then how to implement and in/validate an hypothesis? At MS&N, to solve this problem we provide: a multilevel methodology from the minimal formal transcription of the biological system to its efficent simulation, using abstraction to validate the links between the different description levels. Furthermore, to choose and "navigate" between the different abstractions of the systems framed by the hypothesis, our conviction is that activity is a good guide.
 
Research areas
  • Probability and statistics: dependence detection, models of interaction graphs, estimation in those models and tests on real biological data (goodness-of-fit)
  • Abstract models and formal analysis/synthesis of general, reactive and discrete-event systems, algebraic semantics, category theory
  • Formal modeling, formal prototyping using synchronous programming languages
  • Computer-aided proofs of behavioral properties
  • In silico experiments
 
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