AECuration: automated event curation for spike sorting

Objective. This paper discusses a novel method for automating the curation of neural spike events detected from neural recordings using spike sorting methods. Spike sorting seeks to identify isolated neural events from extracellular recordings. This is critical for interpretation of electrophysiology recordings in neuroscience studies. Spike sorting analysis is vulnerable to errors because of non-neural events, such as experimental artifacts or electrical interference. To improve the specificity of spike sorting results, a manual postprocessing curation is typically used to examine the detected events and identify neural spikes based on their specific features. However, this manual curation process is subjective, prone to human errors and not scalable, especially for large datasets.Approach. To address these challenges, we introduce AECuration, a novel automatic curation method based on an autoencoder model trained on features of simulated extracellular spike waveforms. Using reconstruction error as a performance metric, our method classifies neural and non-neural events in experimental electrophysiology datasets.Main results. This paper demonstrates that AECuration can classify neural events with 97.46% accuracy on synthetic datasets. Moreover, our method can improve the sensitivity of different spike sorting pipelines on datasets with ground-truth recordings by up to 20%. The ratio of clustered units with low interspike interval violation rates is improved from 55.3% to 85.5% as demonstrated using our in-house experimental dataset.Significance. AEcuration is a time-domain evaluation method that automates the analysis of extracellular recordings based on learned time-domain features. Once trained on a synthetic dataset, this method can be applied to real extracellular datasets without the need for re-training. This highlights the generalizability of AECuration. It can be readily integrated with existing spike sorting pipelines as a preprocessing filtering or a postprocessing curation step to improve the overall accuracy and efficiency.