.. _overview: Overview ======== SpikeSift is a high-performance spike sorting algorithm designed for high-density extracellular recordings. It delivers **state-of-the-art** accuracy while running in **real time on a single CPU core**. How Does SpikeSift Work? ------------------------ SpikeSift extracts and tracks individual neuron activity from raw extracellular recordings. It includes: - Filtering and segmenting the signal based on drift-aware heuristics - Iteratively detecting and clustering spikes within each segment - Merging matching clusters across segments to produce globally aligned spike trains The result is a drift-corrected, neuron-by-neuron reconstruction of spiking activity across time. Why Use SpikeSift? ------------------ SpikeSift is built for speed, robustness, and clean integration into any workflow: - **Extremely fast** --- sorts thousands of channels in real time on a single CPU core - **Drift-resilient** --- handles both gradual and abrupt electrode drift - **Clean and non-intrusive** --- no data copying, no file modifications, no clutter - **Modular** --- sort in parallel, split or merge segments, track transients - **Drop-in ready** --- works out of the box on most datasets - **Session-aware** --- merge across files, append sessions, or sort progressively - **Reliable on short recordings** --- maintains accuracy even with limited data These features make SpikeSift ideal for real-time pipelines, high-throughput labs, and large-scale sorting tasks --- even on resource-constrained systems. What the Documentation Covers ----------------------------- The rest of this documentation includes: - :ref:`installation` --- how to install and get started - :ref:`user_guide` --- how to sort data and interpret the results - :ref:`example_usage` --- real-world workflows and advanced use cases - :ref:`performance` --- benchmarks and key efficiency advantages - :ref:`implementation` --- algorithmic insights and design principles - :ref:`api_reference` --- complete API for all user-facing functions For a quick start, see the :ref:`user_guide`. To explore practical workflows, head to :ref:`example_usage`. .. note:: SpikeSift is under active development and continues to improve in accuracy and flexibility. For more details or citations, see the upcoming preprint: - `SpikeSift: A Computationally Efficient and Drift-Resilient Spike Sorting Algorithm `__