A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.

A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.

Brain decoding-the process of inferring a person's momentary cognitive state from their brain activity-has enormous potential in the field of human-computer interaction. In this study we propose a zero-shot EEG-to-image brain decoding approach which makes use of state-of-the-art EEG preprocessi...

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Main Authors: Ben McCartney, Jesus Martinez-Del-Rincon, Barry Devereux, Brian Murphy
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0214342
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spelling doaj-03b1f6956e854310ab6de97e8e423f922021-03-03T19:51:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01149e021434210.1371/journal.pone.0214342A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.Ben McCartneyJesus Martinez-Del-RinconBarry DevereuxBrian MurphyBrain decoding-the process of inferring a person's momentary cognitive state from their brain activity-has enormous potential in the field of human-computer interaction. In this study we propose a zero-shot EEG-to-image brain decoding approach which makes use of state-of-the-art EEG preprocessing and feature selection methods, and which maps EEG activity to biologically inspired computer vision and linguistic models. We apply this approach to solve the problem of identifying viewed images from recorded brain activity in a reliable and scalable way. We demonstrate competitive decoding accuracies across two EEG datasets, using a zero-shot learning framework more applicable to real-world image retrieval than traditional classification techniques.https://doi.org/10.1371/journal.pone.0214342
collection DOAJ
language English
format Article
sources DOAJ
author Ben McCartney
Jesus Martinez-Del-Rincon
Barry Devereux
Brian Murphy
spellingShingle Ben McCartney
Jesus Martinez-Del-Rincon
Barry Devereux
Brian Murphy
A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
PLoS ONE
author_facet Ben McCartney
Jesus Martinez-Del-Rincon
Barry Devereux
Brian Murphy
author_sort Ben McCartney
title A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
title_short A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
title_full A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
title_fullStr A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
title_full_unstemmed A zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
title_sort zero-shot learning approach to the development of brain-computer interfaces for image retrieval.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description Brain decoding-the process of inferring a person's momentary cognitive state from their brain activity-has enormous potential in the field of human-computer interaction. In this study we propose a zero-shot EEG-to-image brain decoding approach which makes use of state-of-the-art EEG preprocessing and feature selection methods, and which maps EEG activity to biologically inspired computer vision and linguistic models. We apply this approach to solve the problem of identifying viewed images from recorded brain activity in a reliable and scalable way. We demonstrate competitive decoding accuracies across two EEG datasets, using a zero-shot learning framework more applicable to real-world image retrieval than traditional classification techniques.
url https://doi.org/10.1371/journal.pone.0214342
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