moabb.datasets.EPFLP300#

class moabb.datasets.EPFLP300(subjects=None, sessions=None, *, return_all_modalities=False)[source]#

Bases: BaseDataset

[source]

Dataset Snapshot

EPFLP300

P300 / ERP, 2 classes (Target vs NonTarget)

AuthorsUlrich Hoffmann, Jean-Marc Vesin, Touradj Ebrahimi, Karin Diserens

🇨🇭 Ecole Polytechnique Fédérale de Lausanne, CH·2008·ulrich.hoffmann@epfl.ch

P300 / ERP Code: EPFLP300 8 subjects 4 sessions 32 ch 2048 Hz 2 classes 1.0 s trials Unknown

Class Labels: Target, NonTarget

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Overview

P300 dataset from Hoffmann et al 2008.

Dataset from the paper

Dataset Description

In the present work a six-choice P300 paradigm is tested using a population of five disabled and four able-bodied subjects. Six different images were flashed in random order with a stimulus interval of 400 ms. Users were facing a laptop screen on which six im- ages were displayed. The images showed a television, a telephone, a lamp, a door, a window, and a radio.

The images were flashed in random sequences, one image at a time. Each flash of an image lasted for 100 ms and during the following 300 ms none of the images was flashed, i.e. the interstimulus interval was 400 ms. The EEG was recorded at 2048 Hz sampling rate from 32 electrodes placed at the standard positions of the 10-20 international system. The system was tested with five disabled and four healthy subjects. The disabled subjects were all wheelchair-bound but had varying communication and limb muscle control abilities (Subjects 1 to 5). In particular, Subject 5 was only able to perform extremely slow and relatively uncontrolled movements with hands and arms. Due to a severe hypophony and large fluctuations in the level of alertness, communication with subject 5 was very difficult, which is why its data is not available in this dataset. Subjects 6 to 9 were PhD students recruited from our laboratory (all male, age 30 ± 2.3).

Each subject completed four recording sessions. The first two sessions were performed on one day and the last two sessions on another day. For all subjects the time between the first and the last session was less than two weeks. Each of the sessions consisted of six runs, one run for each of the six images. The duration of one run was approximately one minute and the duration of one session including setup of electrodes and short breaks between runs was approximately 30 minutes. One session comprised on average 810 trials, and the whole data for one subject consisted on average of 3240 trials.

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Benchmark Context

WithinSession

Included in 1 MOABB benchmark table(s). Scores are across available pipelines (WithinSession accuracy).

Sample frame: 8 subjects × 4 sessions

ERP/P300 all classes 5 pipelinesMax 84.29 · Median 71.97 · Mean 74.78 · Std 8.94

Citation & Impact

Paper DOI10.1016/j.jneumeth.2007.03.005
CitationsLoading…
Public APICrossref | OpenAlex
MOABB tables1 (WithinSession)
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30d: 28 · all-time: 354
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Updated: 2026-03-18 UTC

Stimulus Protocol

1s task window per trial · 2-class p300 / erp paradigm · 6 runs/session across 4 sessions

HED Event Tags

HED tags2/2 events annotated

Source: MOABB BIDS HED annotation mapping.

Experimental-stimulus

2

Sensory-event

2

Visual-presentation

2

Non-target

1

Target

1

Target

Sensory-eventExperimental-stimulusVisual-presentationTarget

NonTarget

Sensory-eventExperimental-stimulusVisual-presentationNon-target

HED tree view

Tree · Target

├─ Sensory-event
├─ Experimental-stimulus
├─ Visual-presentation
└─ Target

Tree · NonTarget

├─ Sensory-event
├─ Experimental-stimulus
├─ Visual-presentation
└─ Non-target

Channel Summary

Total channels32

EEG32 (active)

MISC2

Montagestandard_1020

Sampling2048 Hz

Notch / line50 Hz

This diagram is automatically generated from MOABB metadata. Please consult the original publication to confirm the experimental protocol details.

Overview

P300 dataset from Hoffmann et al 2008.

Dataset from the paper [1].

Dataset Description

In the present work a six-choice P300 paradigm is tested using a population of five disabled and four able-bodied subjects. Six different images were flashed in random order with a stimulus interval of 400 ms. Users were facing a laptop screen on which six im- ages were displayed. The images showed a television, a telephone, a lamp, a door, a window, and a radio.

The images were flashed in random sequences, one image at a time. Each flash of an image lasted for 100 ms and during the following 300 ms none of the images was flashed, i.e. the interstimulus interval was 400 ms. The EEG was recorded at 2048 Hz sampling rate from 32 electrodes placed at the standard positions of the 10-20 international system. The system was tested with five disabled and four healthy subjects. The disabled subjects were all wheelchair-bound but had varying communication and limb muscle control abilities (Subjects 1 to 5). In particular, Subject 5 was only able to perform extremely slow and relatively uncontrolled movements with hands and arms. Due to a severe hypophony and large fluctuations in the level of alertness, communication with subject 5 was very difficult, which is why its data is not available in this dataset. Subjects 6 to 9 were PhD students recruited from our laboratory (all male, age 30 ± 2.3).

Each subject completed four recording sessions. The first two sessions were performed on one day and the last two sessions on another day. For all subjects the time between the first and the last session was less than two weeks. Each of the sessions consisted of six runs, one run for each of the six images. The duration of one run was approximately one minute and the duration of one session including setup of electrodes and short breaks between runs was approximately 30 minutes. One session comprised on average 810 trials, and the whole data for one subject consisted on average of 3240 trials.

References

[1]

Hoffmann, U., Vesin, J-M., Ebrahimi, T., Diserens, K., 2008. An efficient P300-based brain-computer interfacefor disabled subjects. Journal of Neuroscience Methods . https://doi.org/10.1016/j.jneumeth.2007.03.005

Code Examples

from moabb.datasets import EPFLP300
dataset = EPFLP300()
data = dataset.get_data(subjects=[1])
print(data[1])

Metadata

Dataset summary

#Subj	8
#Chan	32
#Trials / class	2753 NT / 551 T
Trials length	1 s
Freq	2048 Hz
#Sessions	4

Participants

Population: mixed
Clinical population: 4 disabled (cerebral palsy, multiple sclerosis, late-stage amyotrophic lateral sclerosis, traumatic brain and spinal-cord injury C4 level), 4 able-bodied
Age: 38.4 (range: 30-56) years
BCI experience: no training required

Equipment

Amplifier: Biosemi ActiveTwo
Electrodes: active
Montage: standard_1020

Preprocessing

Data state: raw

Data Access

DOI: 10.1016/j.jneumeth.2007.03.005
Repository: http://bci.epfl.ch/p300

Experimental Protocol

Paradigm: p300
Feedback: none
Stimulus: image_flash

__init__(subjects=None, sessions=None, *, return_all_modalities=False)[source]#: Initialize function for the BaseDataset.

property all_subjects#: Full list of subjects available in this dataset (unfiltered).

convert_to_bids(path=None, subjects=None, overwrite=False, format='EDF', verbose=None, generate_figures=False)[source]#

Convert the dataset to BIDS format.

Saves the raw EEG data in a BIDS-compliant directory structure. Unlike the caching mechanism (see CacheConfig), the files produced here do not contain a processing-pipeline hash (desc-<hash>) in their names, making the output a clean, shareable BIDS dataset.

Parameters:

path (str | Path | None) – Directory under which the BIDS dataset will be written. If None the default MNE data directory is used (same default as the rest of MOABB).
subjects (list of int | None) – Subject numbers to convert. If None, all subjects in subject_list are converted.
overwrite (bool) – If True, existing BIDS files for a subject are removed before saving. Default is False.
format (str) – The file format for the raw EEG data. Supported values are "EDF" (default), "BrainVision", and "EEGLAB".
verbose (str | None) – Verbosity level forwarded to MNE/MNE-BIDS.
generate_figures (bool) – If True, generate interactive neural signature HTML figures in {bids_root}/derivatives/neural_signatures/. Requires plotly (pip install moabb[interactive]). Default is False.

Returns:

bids_root – Path to the root of the written BIDS dataset.

Return type:

pathlib.Path

Examples

>>> from moabb.datasets import AlexMI
>>> dataset = AlexMI()
>>> bids_root = dataset.convert_to_bids(path='/tmp/bids', subjects=[1])