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72 results for "neuromarketing" · page 5 of 8 · ranked by relevance

nm000272
Romani et al. 2025 — BrainForm: a Serious Game for BCI Training and Data Collection (P300 ERP, University of Trento)

EEG

BrainForm is a P300 event-related potential (ERP) EEG dataset collected from 22 participants using a gamified brain-computer interface (BCI) designed for scalable data collection with consumer hardware. Participants completed repeated runs of a P300 spelling/selection task within a serious game paradigm, enabling investigation of BCI skill acquisition across sessions and the effects of different visual stimulation textures on perceptual and performance outcomes.

Size

132 MB

Updated

Jun 8, 2026

by Michele Romani et al.
ds006648
Poetry Assessment EEG Dataset 1

EEG

Participants

47

by Soma Chaudhuri et al.
ds004563
Vicarious touch: overlapping neural patterns between seeing and feeling touch

EEG

Participants

40

by Sophie Smit et al.
nm000277
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study G)

EEG

BigP3BCI Study G is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 checkerboard visual speller task. This derivative dataset is Study G of 20 studies in the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects total. The data were acquired at 256 Hz using 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.

Size

327 MB

Updated

Jun 3, 2026

by Boyla Mainsah et al.
ds006801
Resting-state EEG before and after different study methods

EEG

Participants

21

by Paloma Victoria de Sales Alves et al.
nm000132
ERP CORE

EEG

Size

17.5 GB

Updated

May 18, 2026

by Emily S. Kappenman et al.
nm000264
Vaineau, Barachant & Andreev 2013 — Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset (BI2013a)

EEG

This dataset comprises electroencephalographic recordings from 24 healthy subjects performing a visual P300 brain-computer interface task based on the Brain Invaders video game paradigm. The study compares adaptive versus non-adaptive calibration approaches using Riemannian geometry for classifier training. EEG data were acquired using 16 electrodes at 512 Hz sampling rate during sessions conducted at GIPSA-lab, Grenoble, France in 2013.

Size

1.71 GB

Updated

Jun 3, 2026

by E. Vaineau et al.
ds005811
NOD-EEG

EEG

Participants

19

by Guohao Zhang et al.
on003194
Neuroepo multisession

EEG

Imported from OpenNeuro ds003194

Size

189 MB

Updated

May 23, 2026

by Maria Luisa Bringas Vega et al. OpenNeuro ds003194
nm000326
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study C)

EEG

BigP3BCI Study C is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects performing a visual speller task using a 6x6 checkerboard paradigm. The dataset contains single-session recordings with 32-channel EEG data sampled at 256 Hz, annotated with target and non-target event labels. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset, and is formatted according to BIDS standards with HED event annotations for machine learning applications.

Size

1.22 GB

Updated

Jun 3, 2026

by Boyla Mainsah et al.