Computational Neuroscience
Head: Eduard Kuriščák, MD., Ph.D.
Neural coding, mathematical modeling, computer simulations
Our working group studies the brain functions using the approaches of mathematical modeling, information theory and computer simulations. We are dealing with the problems of neuronal coding in central and peripheral nervous system. Our research approach and object of interest are neuromorphic simulations powered by detailed multicompartmental neuronal models. We analyze propagation of electrical signals (postsynaptic potentials, action potentials) along the dendritic trees and axons of various morphology and membrane properties. Our focus ranges from sub-milisecond time resolution (we focus on capabilities of neurons to generate precise “temporal neural coding”) to phenomena lasting seconds and minutes, underlying various forms of synaptic plasticity, learning, memory and its retrieval).
We use and work with the following theoretical and technical approaches:
- Information theory – a branch of applied mathematics dealing with the quantification of transmission, encoding and processing of information
- Multicompartmental modeling – approach of computational neuroscience facilitating the formulation and assembly of complex cable models. It helps us to study electrical behavior of detailed 3D structures of neurons and neuronal circuits
- Matlab software – powerful and universal tool for modeling, simulation and processing of experimental simulation data
- Genesis – GEneral NEural SImulation Software, a tool specialized to build and prototype compartmental model of neurons and neuronal circuits
Selected Publications:
Kuriscak E, Marsalek P, Stroffek J, Toth PG. Biological context of Hebb learning in artificial neural networks, a review. Neurocomputing 152, 27-35. 2015
Kuriscak E, Marsalek P, Stroffek J, Wünsch Z. The effect of neural noise on spike time precision in a detailed CA3 neuron model.Comput Math Methods Med. 2012;2012:595398. doi: 10.1155/2012/595398. Epub 2012 Jun 24
Kuriščák E, Trojan S, Wünsch Z. Model of spike propagation reliability along the myelinated axon corrupted by axonal intrinsic noise sources. Physiol. Res 51, 205-215.2002.