Spike Sorting Multivariate
Extending waveform sorting across multichannel neuronal recordings
Automated classification of waveforms is an important method used across neuroscience, biomedical engineering, and related fields. This work demonstrated spike sorting for multichannel electrode arrays using correlation principles and data-driven references.
A new Monte Carlo method for estimating the number of k-means clusters was introduced. Performance was validated on generated signals mimicking multichannel recordings of extra-cellular neuronal activity.
Larionov, P., Juergens, T. & Schanze, T. (2019). Correlation-based spike sorting of multivariate data. Current Directions in Biomedical Engineering, 5(1), pp. 113-116.
Role
Main author, developer, and project leader.
Context
Co-created with Tom Jurgens. Institute of Biomedical Technology (IBMT), University of Applied Sciences, scientific group of Prof. Dr. Thomas Schanze (2019). Presented at the "Current Directions in Biomedical Engineering" conference.