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Quantitative Biology > Neurons and Cognition

arXiv:2404.05553 (q-bio)
[Submitted on 8 Apr 2024 (v1), last revised 14 May 2024 (this version, v3)]

Title:Alljoined1 -- A dataset for EEG-to-Image decoding

Authors:Jonathan Xu, Bruno Aristimunha, Max Emanuel Feucht, Emma Qian, Charles Liu, Tazik Shahjahan, Martyna Spyra, Steven Zifan Zhang, Nicholas Short, Jioh Kim, Paula Perdomo, Ricky Renfeng Mao, Yashvir Sabharwal, Michael Ahedor Moaz Shoura, Adrian Nestor
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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. We publicly release the dataset and all code at this https URL.
Comments: 8 Pages, 6 Figures
Subjects: Neurons and Cognition (q-bio.NC); Artificial Intelligence (cs.AI)
ACM classes: I.5.1; I.6.3; I.2.6; K.3.2
Cite as: arXiv:2404.05553 [q-bio.NC]
  (or arXiv:2404.05553v3 [q-bio.NC] for this version)
  https://doi.org/10.48550/arXiv.2404.05553

Submission history

From: Tazik Shahjahan [view email]
[v1] Mon, 8 Apr 2024 14:21:34 UTC (8,438 KB)
[v2] Thu, 9 May 2024 07:34:20 UTC (8,439 KB)
[v3] Tue, 14 May 2024 04:47:45 UTC (8,439 KB)
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