Background techniques for neurophysics: dynamical system theory, statistical physics, wavelet analysis

Ioffe' PTI, SPbU
Anton Chizhov
A. Chizhov, S.V. Bozhokin, A.V. Gorbatyuk, R.R. Aliev
Minimal requirements: 
Students are expected to have basic knowledge of mathematics and physics on the level of technical universities as well as an understanding of electrical properties of excitable membranes.

Course will be held in Auditorium 90, Faculty of Biology and Soil Science of SPbU  

17.30-22.00  September, 14-17, 2011 

Language: Russian

Contact person: Anton Chizhov, A.F.Ioffe Physical-Technical Institute of RAS,

 Deadline for registration - 4.09.2011  


The models of computational neuroscience borrow ideas and methodology from physics and mathematics. Current course gives some introduction into the dynamical system theory, statistical physics, wavelet analysis and gives examples of application of these techniques for the analysis of single neuron models and derivation of neuronal population models.

Lecture 1 “Introduction into the models of single neurons and neuronal populations” (A.V. Chizhov)

Lectures 2-4 “Introduction into the dynamical system theory” (A.V. Gorbatyuk) 

Lectures 5-6 “Introduction into nonequilibrium statistical physics” (S.V.Bozhokin) 

Lectures 7-8 "From thermodynamics to a nonlinear distributed neural tissue" (R.R.Aliev)  

Lecture 9 “Model of single neuronal population” (A.V.Chizhov) 

Lectures 10 “Introduction to wavelets” (R.R.Aliev) 

Lectures 11-12 “Wavelet analysis” (S.V.Bozhokin)

Learning outcomes: 
Students will learn about the basic techniques applied in the dynamical system theory, statistical physics and wavelet analysis, which may provide a base for their future development of the theory of brain modeling.
SPbU with participation of IPTI

Signups closed for this Modular course