plexon

name	plexon
description	Plexon (.plx / .pl2) — NHP electrophysiology + behavior synchronization
layer	L0
group	spike_ephys
metadata	{"tags":["io","plexon","plx","pl2","nhp","behavior_sync"],"formats":[".plx",".pl2"],"modalities":["spike","lfp"]}

Plexon

Format Overview

Plexon Inc. (now part of NeuralCorp) acquisition hardware writes .plx (legacy) and .pl2 (current) files. Common in NHP labs running behavioral experiments with synchronized neural + behavioral channels.

File Manifest

session.plx          # legacy ~32 ch
session.pl2          # current; up to 256 ch + 8 wideband + 16 analog

Metadata Schema

Header carries: per-channel name, gain, filter cut-offs, sample rate (per channel; mixed rates supported), event channel definitions.

Loader Library Map

Priority	Library	Lazy install
Primary	neo.io.PlexonIO (or Pl2RawIO for pl2)	neo==0.13.4 via io.plexon.
Secondary	pypl2 (Plexon-provided)	pip install pypl2.

Modality Coverage

Spike (sorted online by Plexon), LFP, NI-DAQ-style analog channels.

Common Pitfalls

• .plx vs .pl2 reader path differ in neo. Use Pl2RawIO for .pl2; PlexonIO for .plx.
• Mixed sample rates. Spike channels at 40 kHz; LFP at 1 kHz; analog at variable rates. Verify per-stream.
• Online-sort spikes embedded. Like Blackrock NEV, the .plx carries Plexon Sort Client-classified spikes — re-sort offline for publication-grade analysis.

Reference Implementation

Standalone

import numpy as np
import neo


def load_plexon(path: str, stream: str = "spike") -> dict:
    reader = neo.io.PlexonIO(filename=path) if path.endswith(".plx") else neo.rawio.PlexonRawIO(filename=path)
    reader.parse_header()
    return {"sfreq": float(reader.get_signal_sampling_rate(0)),
            "n_channels": int(reader.signal_channels_count())}

EasyBCI-Adapted

from typing import Any, Dict


def operator_load_plexon(
    data_dict: Dict[str, Any], *, path: str, stream: str = "spike",
) -> Dict[str, Any]:
    """EasyBCI-adapted Plexon loader.

    Parameters
    ----------
    data_dict : dict
    path : str
    stream : str

    Returns
    -------
    dict — populated OperatorIO.

    Raises
    ------
    EasyBCIOperatorError
        recoverable=False on missing file.

    Modality coverage
    -----------------
    Spike / LFP (NHP): yes.

    References
    ----------
    Plexon DataWarehouse spec; neo.rawio docs.

    Notes
    -----
    L0 IO operator (CODE_STANDARD Rule 12 exempt).
    """
    import time
    # easybci-allow: file-io  # L0 IO operator
    from easybci_lib.tools.neural_processing.operator_errors import EasyBCIOperatorError
    if not path:
        raise EasyBCIOperatorError(
            operator="load_plexon", reason="path required", recoverable=False,
        )
    t0 = time.monotonic()
    try:
        import neo
        reader = neo.rawio.PlexonRawIO(filename=path)
        reader.parse_header()
        sfreq = float(reader.get_signal_sampling_rate(stream_index=0))
        sig = reader.get_analogsignal_chunk(block_index=0, seg_index=0, channel_indexes=None)
        import numpy as np
        gains = reader.header["signal_channels"]["gain"].astype(np.float32)
        offsets = reader.header["signal_channels"]["offset"].astype(np.float32)
        data = sig.astype(np.float32).T * gains[:, None] + offsets[:, None]
    except Exception as exc:
        raise EasyBCIOperatorError(
            operator="load_plexon", reason=f"load failed: {exc}", recoverable=False,
        ) from exc
    elapsed = time.monotonic() - t0
    n_t = data.shape[1]
    return {
        "data": data, "channels": [f"ch{i}" for i in range(data.shape[0])],
        "frequency": sfreq, "duration": n_t / sfreq, "elapsed_s": elapsed,
        "meta": {"modality": "spike" if sfreq >= 20000 else "lfp",
                 "load_plexon": {"path": path, "stream": stream}},
    }

References

1. Garcia, S. et al. (2014). Neo: an object model for handling electrophysiology data. Frontiers in Neuroinformatics 8: 10. doi:10.3389/fninf.2014.00010.
2. Plexon Documentation (proprietary). https://www.plexon.com/

Boundary with Related Formats

• blackrock: clinical UEA; Plexon = NHP research.
• nwb: archived deposit; Plexon = vendor working format.
• openephys / spikeglx: alternative research acquisition stacks.