PseudoSorter: A self-supervised spike sorting approach applied to reveal Tau-induced reductions in neuronal activity.

ABSTRACT: Microelectrode arrays (MEAs) permit recordings with high electrode counts, thus generating complex datasets that would benefit from precise neuronal spike sorting for meaningful data extraction. Nevertheless, conventional spike sorting methods face limitations in recognizing diverse spike shapes. Here, we introduce PseudoSorter, which uses self-supervised learning techniques, a density-based pseudolabeling strategy, and an iterative fine-tuning process to enhance spike sorting accuracy. Through benchmarking, we demonstrate the superior performance of PseudoSorter compared to other spike sorting algorithms before applying PseudoSorter on MEA recordings from hippocampal neurons exposed to subneuronal concentrations of monomeric Tau as a model for Alzheimer's disease. Our results unveil that

SUBMITTER: Brockhoff M 

PROVIDER: S-EPMC11908484 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature