HF-SEF dataset#

This example looks at high-frequency SEF responses.

# Author: Jussi Nurminen (jnu@iki.fi)
#
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import os

import mne
from mne.datasets import hf_sef

fname_evoked = os.path.join(hf_sef.data_path(), "MEG/subject_b/hf_sef_15min-ave.fif")

print(__doc__)

Read evoked data

    Found the data of interest:
        t =     -50.00 ...     250.00 ms (SEF)
        0 CTF compensation matrices available
        nave = 2790 - aspect type = 100
No projector specified for this dataset. Please consider the method self.add_proj.

Create a highpass filtered version

evoked_hp = evoked.copy()
evoked_hp.filter(l_freq=300, h_freq=None)
Setting up high-pass filter at 3e+02 Hz

FIR filter parameters
---------------------
Designing a one-pass, zero-phase, non-causal highpass filter:
- Windowed time-domain design (firwin) method
- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation
- Lower passband edge: 300.00
- Lower transition bandwidth: 75.00 Hz (-6 dB cutoff frequency: 262.50 Hz)
- Filter length: 133 samples (0.044 s)

[Parallel(n_jobs=1)]: Done  17 tasks      | elapsed:    0.0s
[Parallel(n_jobs=1)]: Done  71 tasks      | elapsed:    0.0s
[Parallel(n_jobs=1)]: Done 161 tasks      | elapsed:    0.1s
[Parallel(n_jobs=1)]: Done 287 tasks      | elapsed:    0.1s
General
Filename(s) hf_sef_15min-ave.fif
MNE object type Evoked
Measurement date 1970-01-01 at 00:00:00 UTC
Participant Unknown
Experimenter Jussi Nurminen (jussi)
Acquisition
Aggregation average of 2790 epochs
Condition SEF
Time range -0.050 – 0.250 s
Baseline off
Sampling frequency 3000.00 Hz
Time points 901
Channels
Magnetometers
Gradiometers
Head & sensor digitization 93 points
Filters
Highpass 300.00 Hz
Lowpass 990.00 Hz


Compare high-pass filtered and unfiltered data on a single channel

ch = "MEG0443"
pick = evoked.ch_names.index(ch)
edi = {"HF": evoked_hp, "Regular": evoked}
mne.viz.plot_compare_evokeds(edi, picks=pick)
MEG0443

Total running time of the script: (0 minutes 1.204 seconds)

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