Add neuropixels-analysis skill for extracellular electrophysiology

Adds comprehensive toolkit for analyzing Neuropixels high-density neural
recordings using SpikeInterface, Allen Institute, and IBL best practices.

Features:
- Data loading from SpikeGLX, Open Ephys, and NWB formats
- Preprocessing pipelines (filtering, phase shift, CAR, bad channel detection)
- Motion/drift estimation and correction
- Spike sorting integration (Kilosort4, SpykingCircus2, Mountainsort5)
- Quality metrics computation (SNR, ISI violations, presence ratio)
- Automated curation using Allen/IBL criteria
- AI-assisted visual curation for uncertain units
- Export to Phy and NWB formats

Supports Neuropixels 1.0 and 2.0 probes.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

scientific-skills/neuropixels-analysis/scripts/preprocess_recording.py

@@ -0,0 +1,122 @@
+#!/usr/bin/env python
+"""
+Preprocess Neuropixels recording.
+
+Usage:
+    python preprocess_recording.py /path/to/data --output preprocessed/ --format spikeglx
+"""
+
+import argparse
+from pathlib import Path
+
+import spikeinterface.full as si
+
+
+def preprocess_recording(
+    input_path: str,
+    output_dir: str,
+    format: str = 'auto',
+    stream_id: str = None,
+    freq_min: float = 300,
+    freq_max: float = 6000,
+    phase_shift: bool = True,
+    common_ref: bool = True,
+    detect_bad: bool = True,
+    n_jobs: int = -1,
+):
+    """Preprocess a Neuropixels recording."""
+
+    print(f"Loading recording from: {input_path}")
+
+    # Load recording
+    if format == 'spikeglx' or (format == 'auto' and 'imec' in str(input_path).lower()):
+        recording = si.read_spikeglx(input_path, stream_id=stream_id or 'imec0.ap')
+    elif format == 'openephys':
+        recording = si.read_openephys(input_path)
+    elif format == 'nwb':
+        recording = si.read_nwb(input_path)
+    else:
+        # Try auto-detection
+        try:
+            recording = si.read_spikeglx(input_path, stream_id=stream_id or 'imec0.ap')
+        except:
+            recording = si.load_extractor(input_path)
+
+    print(f"Recording: {recording.get_num_channels()} channels, {recording.get_total_duration():.1f}s")
+
+    # Preprocessing chain
+    rec = recording
+
+    # Bandpass filter
+    print(f"Applying bandpass filter ({freq_min}-{freq_max} Hz)...")
+    rec = si.bandpass_filter(rec, freq_min=freq_min, freq_max=freq_max)
+
+    # Phase shift correction (for Neuropixels ADC)
+    if phase_shift:
+        print("Applying phase shift correction...")
+        rec = si.phase_shift(rec)
+
+    # Bad channel detection
+    if detect_bad:
+        print("Detecting bad channels...")
+        bad_channel_ids, bad_labels = si.detect_bad_channels(rec)
+        if len(bad_channel_ids) > 0:
+            print(f"  Removing {len(bad_channel_ids)} bad channels: {bad_channel_ids[:10]}...")
+            rec = rec.remove_channels(bad_channel_ids)
+
+    # Common median reference
+    if common_ref:
+        print("Applying common median reference...")
+        rec = si.common_reference(rec, operator='median', reference='global')
+
+    # Save preprocessed
+    output_path = Path(output_dir)
+    output_path.mkdir(parents=True, exist_ok=True)
+
+    print(f"Saving preprocessed recording to: {output_path}")
+    rec.save(folder=output_path / 'preprocessed', n_jobs=n_jobs)
+
+    # Save probe info
+    probe = rec.get_probe()
+    if probe is not None:
+        from probeinterface import write_probeinterface
+        write_probeinterface(output_path / 'probe.json', probe)
+
+    print("Done!")
+    print(f"  Output channels: {rec.get_num_channels()}")
+    print(f"  Output duration: {rec.get_total_duration():.1f}s")
+
+    return rec
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Preprocess Neuropixels recording')
+    parser.add_argument('input', help='Path to input recording')
+    parser.add_argument('--output', '-o', default='preprocessed/', help='Output directory')
+    parser.add_argument('--format', '-f', default='auto', choices=['auto', 'spikeglx', 'openephys', 'nwb'])
+    parser.add_argument('--stream-id', default=None, help='Stream ID for multi-probe recordings')
+    parser.add_argument('--freq-min', type=float, default=300, help='Highpass cutoff (Hz)')
+    parser.add_argument('--freq-max', type=float, default=6000, help='Lowpass cutoff (Hz)')
+    parser.add_argument('--no-phase-shift', action='store_true', help='Skip phase shift correction')
+    parser.add_argument('--no-cmr', action='store_true', help='Skip common median reference')
+    parser.add_argument('--no-bad-channel', action='store_true', help='Skip bad channel detection')
+    parser.add_argument('--n-jobs', type=int, default=-1, help='Number of parallel jobs')
+
+    args = parser.parse_args()
+
+    preprocess_recording(
+        args.input,
+        args.output,
+        format=args.format,
+        stream_id=args.stream_id,
+        freq_min=args.freq_min,
+        freq_max=args.freq_max,
+        phase_shift=not args.no_phase_shift,
+        common_ref=not args.no_cmr,
+        detect_bad=not args.no_bad_channel,
+        n_jobs=args.n_jobs,
+    )
+
+
+if __name__ == '__main__':
+    main()