Abstract
Recent technical advancements in neural engineering allow for precise recording and control of neural circuits simultaneously, opening up new opportunities for closed-loop neural control. In this work, a rapid spike sorting system was developed based on template matching to rapidly calculate instantaneous firing rates for each neuron in a multi-unit extracellular recording setting. Cluster templates were first generated by a desktop computer using a non-parameter spike sorting algorithm (Super-paramagnetic clustering) and then transferred to a field-programmable gate array digital circuit for rapid sorting through template matching. Two different matching techniques–Euclidean distance (ED) and correlational matching (CM)–were compared for the accuracy of sorting and the performance of calculating firing rates. The performance of the system was first verified using publicly available artificial data and was further confirmed with pre-recorded neural spikes from an anesthetized Mongolian gerbil. Real-time recording and sorting from an awake mouse were also conducted to confirm the system performance in a typical behavioral neuroscience experimental setting. Experimental results indicated that high sorting accuracies were achieved for both template-matching methods, but CM can better handle spikes with non-Gaussian spike distributions, making it more robust for in vivo recording. The technique was also compared to several other off-line spike sorting algorithms and the results indicated that the sorting accuracy is comparable but sorting time is significantly shorter than these other techniques. A low sorting latency of under 2 ms and a maximum spike sorting rate of 941 spikes/second have been achieved with our hybrid hardware/software system. The low sorting latency and fast sorting rate allow future system developments of neural circuit modulation through analyzing neural activities in real-time.
Highlights
Recording action potentials from neurons in the brain gives neuroscientists the ability to study neural circuits with single cell accuracy [1,2,3,4,5,6] Typically neural spikes are recorded extracellularly with a metal or glass electrode inserted into the brain of an animal or a human patient [7,8]
The maximum spike sorting rate was measured by monotonically reducing the temporal difference between the peaks of two spikes until the field programmable gate array (FPGA) module can no longer differentiate the second spike from the first spike
Low-latency real-time neural spike sorting system were padded in the gap space, and if the spacing was less than the span, the data points of the overlapping space were averaged between the two spikes
Summary
Recording action potentials from neurons in the brain gives neuroscientists the ability to study neural circuits with single cell accuracy [1,2,3,4,5,6] Typically neural spikes (or action potentials) are recorded extracellularly with a metal or glass electrode inserted into the brain of an animal or a human patient [7,8]. Electrodes are typically placed within the extracellular space between neurons to capture neural spikes extracellularly In this extracellular configuration, neural spikes generated from several adjacent neurons are often captured by the electrode at the same time, hereafter referred to as multi-units, making it challenging to determine the activity patterns of single neurons included in the recording. Neural spikes generated from several adjacent neurons are often captured by the electrode at the same time, hereafter referred to as multi-units, making it challenging to determine the activity patterns of single neurons included in the recording These multi-unit recordings are especially common when signals are measured from brain areas densely packed with neurons. The temporal profiles of these neural spikes are dependent on the impedance of the extracellular fluid between the neurons and the electrode, the currents produced by each neuron, as well as the cell membrane area from which the ionic currents can reach the metal electrode [1,7,8]
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