Alljoined1 -A dataset for EEG-to-Image decoding - A&O (Apprentissage et Optimisation)
Conference Papers Year : 2024

Alljoined1 -A dataset for EEG-to-Image decoding

Abstract

We present Alljoined1, a dataset built specifically for EEG-to-Image decoding. Recognizing that an extensive and unbiased sampling of neural responses to visual stimuli is crucial for image reconstruction efforts, we collected data from 8 participants looking at 10,000 natural images each. We have currently gathered 46,080 epochs of brain responses recorded with a 64-channel EEG headset. The dataset combines response-based stimulus timing, repetition between blocks and sessions, and diverse image classes with the goal of improving signal quality. For transparency, we also provide data quality scores.

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hal-04743819 , version 1 (18-10-2024)

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Jonathan Xu, Bruno Aristimunha, Max Emanuel Feucht, Emma Qian, Charles Liu, et al.. Alljoined1 -A dataset for EEG-to-Image decoding. Workshop Data Curation and Augmentation in Medical Imaging at 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, May 2024, Settle, United States. ⟨10.48550/arXiv.2404.05553⟩. ⟨hal-04743819⟩
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