Alljoined1 -- A dataset for EEG-to-Image decoding
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909201470586880 |
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| author | Xu, Jonathan Aristimunha, Bruno Feucht, Max Emanuel Qian, Emma Liu, Charles Shahjahan, Tazik Spyra, Martyna Zhang, Steven Zifan Short, Nicholas Kim, Jioh Perdomo, Paula Mao, Ricky Renfeng Sabharwal, Yashvir Shoura, Michael Ahedor Moaz Nestor, Adrian |
| author_facet | Xu, Jonathan Aristimunha, Bruno Feucht, Max Emanuel Qian, Emma Liu, Charles Shahjahan, Tazik Spyra, Martyna Zhang, Steven Zifan Short, Nicholas Kim, Jioh Perdomo, Paula Mao, Ricky Renfeng Sabharwal, Yashvir Shoura, Michael Ahedor Moaz Nestor, Adrian |
| contents | 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 https://linktr.ee/alljoined1. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_05553 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Alljoined1 -- A dataset for EEG-to-Image decoding Xu, Jonathan Aristimunha, Bruno Feucht, Max Emanuel Qian, Emma Liu, Charles Shahjahan, Tazik Spyra, Martyna Zhang, Steven Zifan Short, Nicholas Kim, Jioh Perdomo, Paula Mao, Ricky Renfeng Sabharwal, Yashvir Shoura, Michael Ahedor Moaz Nestor, Adrian Neurons and Cognition Artificial Intelligence I.5.1; I.6.3; I.2.6; K.3.2 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 https://linktr.ee/alljoined1. |
| title | Alljoined1 -- A dataset for EEG-to-Image decoding |
| topic | Neurons and Cognition Artificial Intelligence I.5.1; I.6.3; I.2.6; K.3.2 |
| url | https://arxiv.org/abs/2404.05553 |