Multi-neuron extracellular recordings with multichannel microelectrodes, like tetrodes or heptodes, are used to get insights in the neuronal information processing in the brain. Spike sorting is the detection and classification of extracellular action potentials (spikes) recorded with these electrodes. Here we report on the improvement of spike sorting performance when using heptodes rather than tetrodes by simulating tetrode/heptode recordings and analysing them automatically with our spike sorting algorithm. Simulation of signals is performed via a simple model of neurons and electrodes that has the ability to emulate preferably realistic recording conditions without too much complexity. Results indicate that spike sorting performance is better when heptodes instead of tetrodes are used to record from highly active local clusters consisting of many neurons and when the signals have a low signal-to-noise ratio.
展开▼
