Verification of Temporal Properties of Neuronal Archetypes Modeled as Synchronous Reactive Systems
There exists many ways to connect two, three or more neurons together to form different graphs. We call archetypes only the graphs whose properties can be associated with specific classes of biologically relevant structures and behaviors. These archetypes are supposed to be the basis of typical instances of neuronal information processing. To model different representative archetypes and express their temporal properties, we use a synchronous programming language dedicated to reactive systems (Lustre). The properties are then automatically validated thanks to several model checkers supporting data types. The respective results are compared and depend on their underlying abstraction methods.
- 1.Luke webpage. http://www.it.uu.se/edu/course/homepage/pins/vt11/lustre
- 2.Nuxmv webpage. https://nuxmv.fbk.eu/
- 5.De Maria, E., Muzy, A., Gaffé, D., Ressouche, A., Grammont, F.: Verification of Temporal Properties of Neuronal Archetypes Using Synchronous Models. Research report 8937, UCA, Inria; UCA, I3S; UCA, LEAT; UCA, LJAD, July 2016. https://hal.inria.fr/hal-01349019
- 8.Hagen, G., Tinelli, C.: Scaling up the formal verification of lustre programs with SMT-based techniques. In: Formal Methods in Computer-Aided Design, FMCAD 2008, Portland, Oregon, USA, pp. 1–9, 17–20 November 2008Google Scholar
- 14.Maréchal, A., Fouilhé, A., King, T., Monniaux, D., Périn, M.: Polyhedral approximation of multivariate polynomials using Handelman’s theorem. In: Jobstmann, B., Leino, K.R.M. (eds.) Verification, Model Checking, and Abstract Interpretation. LNCS, vol. 9583, pp. 166–184. Springer, Heidelberg (2016)CrossRefGoogle Scholar