Informed Analysis

Informed Analysis is the third pillar of Informed Electrophysiology. When the analysis pipeline knows the quality profile of the input data, it can make better decisions about processing.

Why it matters: Standard spike sorting treats all channels equally — spending the same compute on high-quality channels and garbage channels, then requiring manual curation to discard unreliable results. Informed Analysis provides channel-level quality scores to the sorting algorithm, enabling quality-aware confidence weighting, focused computation on high-quality time windows, and automatic flagging of results from marginal channels.

Key insight: The researcher no longer discovers quality problems during analysis. They already know — because the acquisition system reported during the session and the curation system confirmed during triage. Analysis becomes what it should be: extracting scientific results from data whose quality is already understood.

Implementation: Radiens Videre and RadiensPy provide quality-aware analysis workflows. The Python API (RadiensPy) enables reproducible, scriptable analysis pipelines that consume quality metadata.