Igor TETKO
Institute of Bioorganic and Petroleum Chemistry of NAS of Ukraine,
Kyiv, UKRAINE;
Institute for Bioinformatics, Ingolstraedter Lanstrasse 1,
D-85764, Neuherberg, GERMANY
E-mail: itetko@vvclab.org
Symmetry analysis in spikes (bursts) recognition and classifications
Abstract:
The present study introduces an approach for automatic classification
of extracellularly recorded action potentials of neurons based on geometrical
approach. Neuronal spikes (bursts) are considered as geometrical objects,
namely trajectories in phase space. It is shown that for spikes, generated
by the same neuron, it is possible to find such symmetry transformation
under which their trajectories are invariant in phase space. On the other
hand, the phase trajectories of spikes generated by other neurons change
significantly under action of that transformation. Thus it is possible
to define a special symmetry transformation (including Lie symmetry) that
only typifies the spikes of the given neuron. The proposed algorithm
is explained and an overview of the mathematical background is given. The
method was tested on simulated data and showed good results in real experiments.
New problems and applications are also discussed.