Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams

Tijl Grootswagers; Ivy Zhou; Amanda K. Robinson; Martin N. Hebart; Thomas A. Carlson

doi:10.1038/s41597-021-01102-7

Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams

Tijl Grootswagers
, Ivy Zhou
, Amanda K. Robinson
, Martin N. Hebart
, Thomas A. Carlson

Research output: Contribution to journal › Article › peer-review

64 Citations (Scopus)

Abstract

The neural basis of object recognition and semantic knowledge has been extensively studied but the high dimensionality of object space makes it challenging to develop overarching theories on how the brain organises object knowledge. To help understand how the brain allows us to recognise, categorise, and represent objects and object categories, there is a growing interest in using large-scale image databases for neuroimaging experiments. In the current paper, we present THINGS-EEG, a dataset containing human electroencephalography responses from 50 subjects to 1,854 object concepts and 22,248 images in the THINGS stimulus set, a manually curated and high-quality image database that was specifically designed for studying human vision. The THINGS-EEG dataset provides neuroimaging recordings to a systematic collection of objects and concepts and can therefore support a wide array of research to understand visual object processing in the human brain.

Original language	English
Article number	3
Number of pages	7
Journal	Scientific Data
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41597-021-01102-7
Publication status	Published - Dec 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s).

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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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10.1038/s41597-021-01102-7

Cite this

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title = "Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams",

abstract = "The neural basis of object recognition and semantic knowledge has been extensively studied but the high dimensionality of object space makes it challenging to develop overarching theories on how the brain organises object knowledge. To help understand how the brain allows us to recognise, categorise, and represent objects and object categories, there is a growing interest in using large-scale image databases for neuroimaging experiments. In the current paper, we present THINGS-EEG, a dataset containing human electroencephalography responses from 50 subjects to 1,854 object concepts and 22,248 images in the THINGS stimulus set, a manually curated and high-quality image database that was specifically designed for studying human vision. The THINGS-EEG dataset provides neuroimaging recordings to a systematic collection of objects and concepts and can therefore support a wide array of research to understand visual object processing in the human brain.",

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year = "2022",

month = dec,

doi = "10.1038/s41597-021-01102-7",

language = "English",

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AU - Grootswagers, Tijl

AU - Zhou, Ivy

AU - Robinson, Amanda K.

AU - Hebart, Martin N.

AU - Carlson, Thomas A.

PY - 2022/12

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AB - The neural basis of object recognition and semantic knowledge has been extensively studied but the high dimensionality of object space makes it challenging to develop overarching theories on how the brain organises object knowledge. To help understand how the brain allows us to recognise, categorise, and represent objects and object categories, there is a growing interest in using large-scale image databases for neuroimaging experiments. In the current paper, we present THINGS-EEG, a dataset containing human electroencephalography responses from 50 subjects to 1,854 object concepts and 22,248 images in the THINGS stimulus set, a manually curated and high-quality image database that was specifically designed for studying human vision. The THINGS-EEG dataset provides neuroimaging recordings to a systematic collection of objects and concepts and can therefore support a wide array of research to understand visual object processing in the human brain.

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Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams

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THINGS-EEG: Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts

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Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams

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THINGS-EEG: Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts

Cite this