Subspace Learning with Interval-Censored Likelihoods for Dequantizing Percept PC LFP Snapshots
Read the original on arXiv Statistics ML →The paper addresses the problem of quantization artifacts in spectral data from the Medtronic Percept PC deep brain stimulation device, which stores local field potential amplitudes as 16‑bit integers. By treating dequantization as an interval‑censored subspace estimation problem, the authors evaluate five correction methods and find that quantized probabilistic PCA most effectively reduces spurious spectral peaks while preserving true peaks and maintaining a low noise floor. The study demonstrates that over 20% of detected peaks in clinical spectra are artifacts, highlighting the need for accurate dequantization in biomarker pipelines.
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