drop-nondata-channels

name	drop_nondata_channels
description	Remove non-data channels (markers/triggers, misc, optionally physiological refs)
layer	L3
group	channel
metadata	{"tags":["operator","channels","marker","trigger","stim","clean","nondata"],"modalities":["eeg","seeg","ecog","meg"],"step_string":"drop_nondata_channels","analysis_goal_allowed":["classification","source_localization","feature_extraction","clinical_screening","exploratory","generic","online_inference"],"analysis_goal_forbidden":["connectivity","phase_amplitude_coupling"]}

Drop Non-Data Channels

Function

Removes channels that are not target neural signal — pure marker/trigger channels (STI / Trigger / Status / Event / DC), and optionally misc and physiological-reference channels (EOG/EMG/ECG). Classification comes from channel_classifier (MNE ch_types first, channel-name regex as fallback).

This is different from drop_bads: drop_bads removes broken data channels (flat/noisy); this removes non-data channels that were never meant to be analyzed.

Parameter Format

drop_nondata_channels:{mode}

mode	Drops	Keeps
markers_only (default)	marker/trigger channels	data + physio + misc
markers_and_misc	marker + misc	data + physio
data_only	marker + misc + physio	data only

drop_nondata_channels with no param == markers_only.

When to Use

• Almost always early in the pipeline when inspect_data's channel_summary.must_drop is non-empty — marker channels pollute CAR, ICA, and filtering.
• Use markers_only by default.
• Use markers_and_misc if misc channels are clearly junk.
• Use data_only only when you are sure EOG/ECG are not needed for ICA artifact rejection later. If ICA-with-EOG-reference is planned, keep physio.

Goal-conditional output cleanup (Phase 1+)

After ICA, the codegen layer (_enforce_clean_output in tools/neural_processing/codegen/generator.py) decides whether to append a second drop_nondata_channels:data_only step before save, based on the analysis_goal declared at propose_pipeline time. The decision table is the single source of truth in improved_docs/plans/goal-driven-preprocessing/02-phase1-goal-first.md §1.3:

analysis_goal	Post-ICA data_only cleanup	Rationale
classification	✅ append	downstream classifier wants pure brain channels
feature_extraction	✅ append	features should not mix in EOG/ECG
clinical_screening	✅ append	screening models trained on data-only montages
generic	✅ append	conservative default for unknown downstream
source_localization	❌ skip (intentional)	source modelling consumes physio refs / full montage
exploratory	❌ skip	exploration phase wants the original physical channels visible

This is a design choice, not a bug. The skill writer does NOT need to hand-add a trailing drop_nondata_channels:data_only; codegen handles it.

When NOT to Use

• Spike/unit data — no channel-type concept; operator is a no-op.
• MEG ref_meg channels are classified as data and never dropped here.

Ordering

Place before referencing (CAR/bipolar), ICA, and filtering. Recommended: right after inspect/load, before notch/bandpass.

Evidence / Reporting

Dropped channel names are recorded in meta.dropped_channels and surfaced in the CONFIRM display and mini-repo reasoning so the user sees exactly what was removed and why.