BSc Thesis Project

OData support
Dr. Antal Péter
Department of Measurement and Information Systems

Measurement of neural currents constitutes an important tool in cognitive neuroscience. The purpose of this thesis was to devise a new CSD-reconstruction method capable of determining the membrane currents of a single neuron from extracellular potential data. This task is essentially equivalent to solving an ill-posed Poisson-type inverse problem. The algorithm is based on a previous method called spike CSD, which employs a priori knowledge about the currents of a spiking neuron to solve the problem of CSD-reconstruction. The new algorithm aims to improve the abilities of its predecessor by using ideas borrowed from super-resolution approaches developed for image processing. Testing with simulated data indicated an improvement in the algorithm's parameter-estimation on idealized potential-patterns. Surprisingly, this did not lead to an increase in the accuracy of the reconstructed current-source densities. Suitability of the new solution was demonstrated by testing on real-world data.


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