Supervised Spike Sorting Feasibility of Noisy Single-Electrode Extracellular Recordings: Systematic Study of Human C-Nociceptors recorded via Microneurography

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Sorting spikes from noisy single-channel in-vivo extracellular recordings is challenging, particularly due to the lack of ground truth data. Microneurography, an electrophysiological technique for studying peripheral sensory systems, employs experimental protocols that time-lock a subset of spikes. Stable propagation speed of nerve signals enables reliable sorting of these spikes. Leveraging this property, we established ground truth labels for data collected in two European laboratories and designed a proof-of-concept open-source pipeline to process data across diverse hardware and software systems. Using the labels derived from the time-locked spikes, we employed a supervised approach instead of the unsupervised methods typically used in spike sorting. We evaluated multiple low-dimensional representations of spikes and found that raw signal features outperformed more complex approaches, which are effective in brain recordings. However, the choice of the optimal features remained dataset-specific, influenced by the similarity of average spike shapes and the number of fibers contributing to the signal. Based on our findings, we recommend tailoring lightweight algorithms to individual recordings and assessing the “sortability feasibility” based on achieved accuracy and the research question before proceeding with sorting of non-time-locked spikes in future projects.

Authors 8

1. Alina Troglio corresponding Aachen

   Universitätsklinikum Aachen

   Affiliation as printed

   Universitatsklinikum Aachen;

   Universitatsklinikum Aachen

2. Peter Konradi Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat;

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat

3. Andrea Fiebig Aachen

   Universitätsklinikum Aachen

   Affiliation as printed

   Universitatsklinikum Aachen;

   Universitatsklinikum Aachen

4. Ariadna Pérez Garriga Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat;

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat

5. Rainer Röhrig Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat;

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat

6. James Philip Dunham

   University of Bristol

   Affiliation as printed

   University of Bristol School of Physiology Pharmacology and Neuroscience;

   University of Bristol School of Physiology Pharmacology and Neuroscience

7. Ekaterina Kutafina

   University of Cologne

   Affiliation as printed

   Universitat zu Koln Medizinische Fakultat

8. Barbara Namer Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat;

   Rheinisch-Westfalische Technische Hochschule Aachen Medizinische Fakultat