Mathematical models of neurodynamics

Lobachevsky NNSU
Susanna Gordleeva
V. Kazantsev, S. Lobov, A. Pimashkin
Minimal requirements: 
PhD students, master students

The course "Mathematical models of neurodynamics" in Lobachevsky State University of Nizhny Novgorod, February 19-20

Module 1. Mathematical models of neuron-glial systems - 3 lectures

VB Kazantsev, D.Sc., Head. of NDNB

The aims of the course are:

  • to provide PhD students the knowledge about modern approaches to modelling the processes of generation and signal spreading in neuronal and glial brain systems;
  • to form theoretical ideas about the possibilities of mathematical modelling and mathematical models based on experimental data;
  • to study of the effects of nonlinear dynamics in the mathematical models of neuron-glial systems.

Objectives of the course are:

  •  to give information on methodologies for constructing mathematical models of neurons, glial cells and neuron-glial networks;
  •  to give information about the interpretation of the model effects in the biophysical mechanisms of signal generation;
  •  to earn basic nonlinear effects of signal generation  in the models;
  •  to familiarize graduate students with the basic mathematical tools of research models, reduction techniques to simplified models.

Module 2. Modelling plasticity and learning in neural networks of the brain - 2 lectures

SA Lobov, PhD, Research IAP

The aim of the course:

The purpose of the course is introducing graduate students with modern concepts of learning in neural networks, the main approaches to the modelling of neuronal plasticity and ability to work with the program-simulation of neural networks. These goals are achieved through the study of mathematical models of various forms of plasticity, designing neural networks of different configurations, and computer modelling of neural activity.

Module 3. Analysis of neurophysiological data - 2 lectures

AS Pimashkin, Ph.D., Researcher IAP

The aim of the course:

The aim of the course is to develop a holistic view about the basic techniques of recording and analysis of bioelectric signals in neural networks of the brain, forming the ability to understand and develop methods of statistical analysis of experimental data, to develop methods to analyse the data in order to identify significant characteristics of the signals to generalize the results and explain them in the set of hypotheses.

The main objectives of the course are: 1) design a holistic view of the statistical and mathematical analysis of various experimental data obtained in the experiments, studies of brain activity, particularly in experiments with rat brain slices and cultures of hippocampal neurons 2) basics of electrical signals in the experiments, recording and stimulation of neural networks 3) development of methods for the analysis of data in different programming environments.

We are waiting for applications to participate in the course from post-graduate students and master students till 14 February 2013. Please, send a motivation letter (containing information about your current position, your research interests and why you need to listen to this course) to the course coordinator Susanna Gordleeva gordleeva at neuro dot nnov dot ru

The decision on admission to the course will be announced on February 15, 2013.

Learning outcomes: 
Forming in graduate students the theoretical knowledge and practical skills in: mathematical modelling of the processes of generation and signal spreading in neuronal and glial brain systems mathematical modelling of neuronal plasticity and learning mathematical and statistical analysis of experimental data of registration of cellular neuronal activity
ННГУ им Лобачевского

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