Modeling neuronal cell and networks
Coordination: David Holcman, Biology Department, ENS
Format: Hours: 45h. One course per week. Beginning: October (during around 4 months)
Crédit : 6 ECTS
Semester : 1st semestre
Number of students:
Présentation:
Themes:
Part I: Diffusion in microdomains: modeling, analysis, stochastic
processes, MFPT, see Bionewmetrics
Part II: Modeling neuronal cells and network:
1-Introduction of the HH-model for neuronal excitability.
2-Mean field model of synaptic depression.
3- Modeling and simulations of a neural network that generates a clock:
example of the PreBotz complex.
4- Method to extract synaptic connectivity from the statistics of time
series (electrophysiological recordings).
5-Diffusion during synaptic transmission
5a- Computing the probability of vesicular release.
5b- Asymptotic computations.
Part III: Modeling phototransduction
1-Model of rhodopsin activation/ deactivation.
2-Markov chains for the dynamics of PDE molecules.
3-Computing the rate of cGMP hydrolysis.
4-Mode of diffusion including the geometry of the outersegment.
5-Simulations of the full photoresponse.
6-Open questions in fly photoreceptors, olfaction, hair cells.
Teaching team: David Holcman (ENS, Paris)
Exams: small projects, with a report and oral presentation (30 minutes).