Build vneurotk data from different recordings¶

vtk.read() accepts any path object and returns a BaseData with lazy-loaded neural data.

MEG (MNE-BIDS)¶

import mne
import numpy as np
import pandas as pd
import vneurotk as vtk
from vneurotk.io import MNEPath, VTKPath

mne_path = MNEPath(root=..., subject="01", session="ImageNet01",
                   task="ImageNet", run="01", suffix="meg_clean", extension=".fif")

data: vtk.BaseData = vtk.read(mne_path)
# BaseData(ntime=80000, nchan=273, n_trials=0, configured=False, neuro=<lazy>)

Configure trial structure — binds stimulus IDs, onset samples, time window, and image database:

raw = mne.io.read_raw(mne_path.fpath, preload=False, verbose=False)
vision_onsets = vtk.utils.get_event_samples(raw, event_name="stim_on")

data.configure(
    vision_onsets=vision_onsets,   # (n_trials,) sample indices
    stim_ids=stim_ids,             # (n_trials,) stimulus IDs
    vision_db={sid: path, ...},    # {stim_id: image path / ndarray / PIL.Image}
    trial_window=[-0.2, 0.8],      # seconds (float) or samples (int)
)

Access neural views — data.neuro triggers lazy load:

neuro = data.neuro                 # NeuroData (np.ndarray subclass)
neuro.epochs                       # (n_trials, n_timebins, nchan)
neuro.continuous                   # (total_samples, nchan)

Save and reload:

data.save(VTKPath(SAVE_ROOT, subject="01", session="ImageNet01", task="ImageNet", run="01"))

loaded = vtk.read(save_path)
# vision.db becomes LazyH5Dict — images decoded on demand

Ephys¶

All ephys types are pre-configured on load; no configure() call needed.

from vneurotk.io import EphysPath

# Trial-level spike raster — data_mode='epochs', shape (n_trials, n_timebins, n_units)
bd = vtk.read(EphysPath(root=EPHYS_ROOT, session_id=SES, dtype="TrialRaster"))
bd.neuro.shape  # (50932, 350, 333)

# Trial-level mean firing rate — shape (n_trials, n_units)
bd = vtk.read(EphysPath(root=EPHYS_ROOT, session_id=SES, dtype="MeanFr"))

# Stimulus-level channel firing rate — shape (n_stimuli, n_channels)
bd = vtk.read(EphysPath(root=EPHYS_ROOT, session_id=SES, dtype="ChStimFr"))

trial_meta (from TrialRecord.csv) is automatically attached and accessible as data.trial_meta.