Discover datasets

This dataset comprises whole-head functional near-infrared spectroscopy (fNIRS) recordings from 38 subjects performing spatial-attention tasks in a cocktail-party paradigm with simultaneous eye-tracking. The study includes both overt attention tasks with eye movements and covert auditory attention tasks with central fixation, along with baseline and resting-state conditions. The fNIRS system captured 1134 measurement channels (56 sources, 144 detectors) at approximately 8.99 Hz sampling rate, providing comprehensive hemodynamic measurements during naturalistic audiovisual stimulus processing.

Participants

38

Size

37.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

…True ## Tags - **Modality**: visual - **Type**: perception ## Documentation - **Description**: BigP3BCI: the largest public…

Participants

10

Channels

32 (10-10)

HED

v8.4.0

Size

1.56 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset contains EEG recordings from a flanker word/pseudoword lexical decision task collected at the NeuroCognition Laboratory in San Diego. Participants viewed four-letter real words and pseudowords flanked by identical, different, or no flanking words, while EEG was recorded to examine neural responses associated with lexical processing under flanker conditions. The dataset was collected under San Diego State University's IRB oversight.

Participants

60

Channels

32 (10-10)

Citations

1

Size

3.57 GB

Version

v1.0.0

Updated

Aug 19, 2026

…True ## Tags - **Modality**: visual - **Type**: perception ## Documentation - **Description**: BigP3BCI: the largest public…

Participants

21

Channels

16 (10-10)

HED

v8.4.0

Size

2.38 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset comprises electroencephalography (EEG) recordings from participants performing an auditory oddball task conducted at the Meditation Research Institute in Rishikesh, India. Participants completed three 13-minute sessions during which they were presented with 750 auditory stimuli consisting of standard tones (70%), oddball tones (15%), and distractor noise bursts (15%), with instructions to respond to oddball stimuli via keypad. The study was approved by the Meditation Research Institute ethical committee in India and the University of California San Diego Institutional Review Board (IRB project #090731) and represents a standardized paradigm for investigating event-related potentials and attentional processing.

Participants

13

Channels

64 (10-10)

Citations

7

HED

v8.0.0

Size

2.31 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from participants performing go-nogo categorization and detection tasks across two recording sessions. Participants viewed briefly presented images (20 ms) and responded according to task-specific rules: lifting a finger for target stimuli (go response) or maintaining button press for non-targets (nogo response). The dataset includes two complementary tasks—animal categorization and image recognition—with systematic manipulation of stimulus presentation and response requirements, providing a rich resource for investigating event-related potentials and decision-making processes.

Participants

14

Channels

31 (10-20)

Size

9.22 GB

Version

v1.0.0

Updated

Jul 10, 2026

…True Tags ---- Modality: visual Type: perception Documentation ------------- Description: BigP3BCI: the largest public…

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

1.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

…True Tags ---- Modality: visual Type: perception Documentation ------------- Description: BigP3BCI: the largest public…

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

1.49 GB

Version

v1.0.3

Updated

Aug 18, 2026

…True ## Tags - **Modality**: visual - **Type**: perception ## Documentation - **Description**: BigP3BCI: the largest public…

Participants

5

Channels

16 (10-10)

HED

v8.4.0

Size

790 MB

Version

v1.0.3

Updated

Aug 18, 2026

NOD-EEG provides electroencephalography (EEG) recordings collected from the same subjects and using the same naturalistic ImageNet stimuli as the previously published NOD-fMRI dataset, extending the Natural Object Dataset (NOD) to include temporal dynamics of visual object recognition. Combined with companion MEG data, this multimodal resource enables investigation of neural mechanisms underlying object recognition across naturalistic scenes with both high spatial and high temporal resolution. The dataset includes raw and preprocessed EEG time series and epoched data, along with detailed trial-level event metadata.

Participants

19

Channels

62 (10-10)

Citations

7

Size

24.3 GB

Version

v1.0.0

Updated

Aug 19, 2026