on003519
EEG: Visual Working Memory + Cabergoline Challenge
EEG
Visual Working Memory. Mostly unpublished! Beh data published here: 10.3758/s13415…
- Participants
- 27
- Channels
- 64 (10-10)
- Size
- 8.96 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "verbal memory encoding" · page 8 of 10 · ranked by relevance
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- on007629
ROAMM
BEH EEGROAMM is a large-scale multimodal neuroimaging dataset combining simultaneous EEG and eye-tracking recordings from 44 participants during naturalistic reading of standardized articles. The dataset includes span-level mind-wandering annotations, reading comprehension assessments, and linguistic stimulus information, providing a benchmark resource for mind-wandering detection and EEG-based language decoding in naturalistic contexts.
- Participants
- 1
- Channels
- 64 (10-10)
- Size
- 46.6 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005932
PWIe
EEG…lightweight headset to record their verbal responses. They were instructed to watch…
- Participants
- 29
- Channels
- 32 (10-10)
- Size
- 2.28 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000259
Speier et al. 2017 — A comparison of stimulus types in online classification of the P300 speller using language models
EEGThis dataset comprises EEG recordings from 10 healthy participants performing a P300 speller task using a 6×6 character matrix. The study compares two stimulus conditions—famous faces and inverting—to evaluate their effects on online P300 classification performance using language models. Data were collected across 2 sessions per subject with 3 runs per session, sampled at 256 Hz from 32 EEG channels.
- Participants
- 10
- Channels
- 32 (10-10)
- Citations
- 28
- HED
- v8.4.0
- Size
- 288 MB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- on006647
Poetry Assessment EEG Dataset 2
EEGThis dataset comprises 64-channel EEG recordings and behavioral ratings from 4 participants (P105, P141, P142, P146; anonymized as sub-001 to sub-004 in BIDS format) who evaluated 210 short English-language texts (70 Haiku, 70 Senryu, and 70 control texts) on five subjective dimensions: Aesthetic Appeal, Vivid Imagery, Being Moved, Originality, and Creativity. IMPORTANT: These 4 participants were EXCLUDED from primary analyses due to segmented EEG recordings acquired in multiple sessions and subsequently concatenated during preprocessing, which introduced potential artifacts. This is a companion dataset to Poetry Assessment EEG Dataset 1 (47 participants with validated continuous recordings used in primary analyses). Poetry Assessment EEG Dataset 2 is included for completeness and transparency, enabling users to apply their own quality control pipelines if desired. The dataset includes resting-state EEG (trigger codes: 65285, 65286 for pre-experiment; 65287, 65288 for post-experiment), trial-by-trial behavioral ratings, and psychometric responses (PANAS, Openness, Curiosity, VVIQ, AVIQ, MAAS, AReA), enabling investigation of neural correlates of aesthetic and creative cognition during poetic language processing. All preprocessing steps, event markers, and metadata structures were applied identically across both Poetry Assessment EEG datasets.
- Participants
- 4
- Channels
- 64 (10-10)
- Size
- 4.29 GB
- Version
- v1.0.0
- Updated
- Jul 22, 2026
- on006142
Essex EEG Movie Memory dataset
EEG…nemar.on006142) # Essex EEG Movie Memory Dataset Authors: Ana Matran-Fernandez and…
- Participants
- 27
- Channels
- 64 (10-10)
- Size
- 24.3 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004703
sEEG Passive listening to natural speech
ANAT iEEG…passages of conversational speech and verbally answered a 2AC content question after…
- Participants
- 10
- Size
- 13.0 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000199
Learning from label proportions for a visual matrix speller (ERP)
EEG- Participants
- 13
- Citations
- 46
- HED
- v8.4.0
- Size
- 5.14 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000351
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study P)
EEGBigP3BCI Study P is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects across 2 sessions each, using a 9x8 character grid spelling paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 montage, annotated with target and non-target visual stimulus events. This derivative dataset is part of the largest public P300 BCI dataset collection, and is optimized for machine learning applications in BCI research.
- Participants
- 19
- Channels
- 32 (10-10)
- HED
- v8.4.0
- Size
- 1.46 GB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- on003421
HD-EEGtask(Dataset 2)
EEG…naming, auditory naming and working memory tasks). All participants provided a written…
- Participants
- 20
- Channels
- 257 (egi-geodesic)
- Size
- 76.8 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026