Topic: SpikeInterface

The NeuralNet minischool combines theory with practical work on participants’ laptops to develop skills in extracting and interpreting neuronal spikes. Spike-sorting sessions introduce available methods and the SpikeInterface framework, then cover preprocessing, running sorters, postprocessing, automatic and manual curation, and visualization. Participants can bring their own data for supervised analysis. The final morning addresses spike-train methods, including firing rates, population representations, waveform and cell-type analysis, connectivity through cross-correlograms, and decoding, wi

This webinar will focus on spike sorting analysis with SpikeInterface, an open-source framework for the analysis of extracellular electrophysiology data. After a brief introduction of the project (~30 mins) highlighting the basics of the SpikeInterface software and advanced features (e.g., data compression, quality metrics, drift correction, cloud visualization), we will have an extensive hands-on tutorial (~90 mins) showing how to use SpikeInterface in a real-world scenario. After attending the webinar, you will: (1) have a global overview of the different steps involved in a processing pipe

Much development has been directed toward improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and