eelbrain.load.mne.sensor_dim

eelbrain.load.mne.sensor_dim(info, picks=None, sysname=None, connectivity=None)

Create a Sensor dimension from an mne.Info object.

Parameters:

  • info (Info) – Measurement info dictionary (or mne-python object that has a .info attribute that contains measurement info).

  • picks (ndarray) – Channel picks (integer array, as used in mne-python). By default all MEG and EEG channels are included.

  • sysname (str) – Name of the sensor system to load sensor connectivity (e.g. ‘neuromag’, inferred automatically for KIT data converted with a recent version of MNE-Python).

  • connectivity (str | list of (str, str) | array of int, (n_edges, 2)) –

    Sensor connectivity (adjacency graph). Can be specified as:

    • "none" for no connections

    • list of connections (e.g., [('OZ', 'O1'), ('OZ', 'O2'), ...])

    • numpy.ndarray of int, shape (n_edges, 2), to specify connections in terms of indices. Each row should specify one connection [i, j] with i < j. If the array’s dtype is uint32, property checks are disabled to improve efficiency.

    • "grid" to use adjacency in the sensor names

    If unspecified, it is inferred from sysname if possible.

Returns:

sensor_dim – Sensor dimension object.

Return type:

Sensor