RT-Sort: An action potential propagationbased algorithm for real time spike detection and sorting with millisecond latencies

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 realtime 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.

Publication Details

Journal
Repository for Publications and Research Data (ETH Zurich)
Published
2024-12-01
DOI
https://doi.org/10.3929/ethz-b-000711238
Primary Topic
Advanced Image and Video Retrieval Techniques
Type
article
Field-Weighted Citation Impact
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article

RT-Sort: An action potential propagationbased algorithm for real time spike detection and sorting with millisecond latencies

Repository for Publications and Research Data (ETH Zurich)
Advanced Image and Video Retrieval Techniques
article

RT-Sort: An action potential propagationbased algorithm for real time spike detection and sorting with millisecond latencies

article en

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 realtime 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.

Repository for Publications and Research Data (ETH Zurich)
Openalex Percentile: Top 62%
Advanced Image and Video Retrieval Techniques
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