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Analog Tetrode Spikes Detection
Keywords: spikes detection, analog hardware realization, tetrode
Measuring, analyzing and interpreting the activity of individual brain cells are essential rudiments to studying brain function. Most brain cells communicate by firing action potentials (spikes). Brain information is thought to be encoded in the timing between successive spikes. While extracellular recordings were first done with single electrodes, the technique of multiple simultaneous recordings from the same local area by means of tetrodes has become widespread. Detecting spikes and identifying the firing times of a specific neuron require analyzing the signals from the four tetrode conductors simultaneously and filtering useful information from any background noise. Among all existing techniques for detecting action potentials buried in noise, the computational simplicity of voltage thresholding makes it the most common method. It also requires minimal hardware and often satisfies experimental demands. Nevertheless, it is not straightforward to apply the technique to several channels simultaneously. A new algorithm is proposed for combining the four tetrode signals and comparing the result against an adaptive voltage threshold. The signals are combined using an analog signal multiplication that emphasizes times when all four signals are spiking simultaneously. The adaptive threshold is set to be proportional to a real-time estimate of the background noise level. For implanted circuitry, an analog hardware realization is advantageous over a digital realization because it has lower power consumption and it is smaller in size. Thus, the entire system is being adapted for an all-analog VLSI implementation. This technique has been demonstrated in Matlab simulation using real tetrode data. The algorithm has shown to provide a good tradeoff between detected spikes and false alarms in data where spike times of a neuron are precisely known.
Nadia Barakat, Student
Temple University
Philadelphia, PA

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