Author
Listed:
- Tjitse van der Molen
- Max Lim
- Julian Bartram
- Zhuowei Cheng
- Ash Robbins
- David F Parks
- Linda R Petzold
- Andreas Hierlemann
- David Haussler
- Paul K Hansma
- Kenneth R Tovar
- Kenneth S Kosik
Abstract
With the use of high-density multi-electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high-fidelity sequential activations on adjacent electrodes, together with a convolutional neural network-based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations.
Suggested Citation
Tjitse van der Molen & Max Lim & Julian Bartram & Zhuowei Cheng & Ash Robbins & David F Parks & Linda R Petzold & Andreas Hierlemann & David Haussler & Paul K Hansma & Kenneth R Tovar & Kenneth S Kosi, 2024.
"RT-Sort: An action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies,"
PLOS ONE, Public Library of Science, vol. 19(12), pages 1-36, December.
Handle:
RePEc:plo:pone00:0312438
DOI: 10.1371/journal.pone.0312438
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