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Models of Neural Systems

PhD Theses

Adaptive and Blind Array Processing Techniques for Extracellular Electrode Recordings
Citation key Natora2011
Author Michal Natora
Year 2011
School Technische Universität Berlin
Abstract Electrophysiological recordings with electrodes, or more generally, with arrays of multi-electrodes, are key for recording neural activity data from the central nervous system. This technique delivers high temporal and spatial resolution, as well as enables neuron stimulation by current injection. The neuronal activity encoded by action potentials (simply called "spikes") of individual neurons, however, is not recorded directly; rather the measurement contains a mixture of spike trains from several neurons and additional noise. To determine the spiking times of a neuron and to determine a spike's originating neuron, spike detection and spike sorting algorithms are needed. The main focus of this thesis is the development of such algorithms. The system consisting of neurons emitting spike trains, their mixture and corruption by noise, and of the process of recording these data with several electrodes channels, is modelled as a linear time-invariant multiple input, multiple output system. The problem of spike detection/sorting can then be regarded as a blind equalisation and source separation task. We use finite impulse response filters for equalisation and source separation throughout the thesis, and therefore, we first start with analysing some properties of these filters. Amongst others, their performance in terms of detection probability and false alarm probability is studied in the case when the spike waveform is perfectly known, and when it is estimated from the data themselves. The subsequently presented spike detection and sorting algorithms are two stage algorithms, consisting of a system identification phase and the following equalisation/separation. Common to them is that both stages can be performed with minimal human supervision although the spatial mixing and temporal distortion are unknown, and the ability to adapt to changing waveforms during the equalisation/separation stage. As such they can be termed as adaptive and blind array processing techniques. Finally, we also propose an unsupervised control algorithm for electrodes, which allows to move them to favourable recording sites. This closes the loop, as the system can now perform spike detection/sorting at any position and decides by itself whether to move the electrode to a more promising position or whether current quality of data is sufficient.
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