Enhancing reproducibility and validation of automated spike sorting workflows

Year of award: 2018


  • Dr Matthias Hennig

    University of Edinburgh

Project summary

Spike sorting is the assignment of events detected in extracellular recordings to individual neurons. It is a complex task and multiple sources of error and bias can affect the interpretation of data. High-density extracellular micro-electrode arrays (MEAs) are used to record from hundreds to thousands of channels. 

We will create an open-source library for reproducible quality control of spike-sorted units. We will organise a workshop to bring together experts in the field, which will provide a forum to establish spike-sorting standards. It will include training sessions for software and an introduction to novel methods of spike sorting. We will develop a curated resource to collect and summarise information on methods, software packages and ground truth datasets available for modern MEAs.

This project will enhance trust in published findings, facilitate re-use of existing data and empower researchers and educators with free standardised tools for high-volume neural recordings.