Understanding the brain with attention: A survey of transformers in brain sciences
Abstract Owing to their superior capabilities and advanced achievements, Transformers have gradually attracted attention with regard to understanding complex brain processing mechanisms. This study aims to comprehensively review and discuss the applications of Transformers in brain sciences. First,...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-09-01
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| Series: | Brain-X |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/brx2.29 |
| _version_ | 1797231268593664000 |
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| author | Cheng Chen Huilin Wang Yunqing Chen Zihan Yin Xinye Yang Huansheng Ning Qian Zhang Weiguang Li Ruoxiu Xiao Jizong Zhao |
| author_facet | Cheng Chen Huilin Wang Yunqing Chen Zihan Yin Xinye Yang Huansheng Ning Qian Zhang Weiguang Li Ruoxiu Xiao Jizong Zhao |
| author_sort | Cheng Chen |
| collection | DOAJ |
| description | Abstract Owing to their superior capabilities and advanced achievements, Transformers have gradually attracted attention with regard to understanding complex brain processing mechanisms. This study aims to comprehensively review and discuss the applications of Transformers in brain sciences. First, we present a brief introduction of the critical architecture of Transformers. Then, we overview and analyze their most relevant applications in brain sciences, including brain disease diagnosis, brain age prediction, brain anomaly detection, semantic segmentation, multi‐modal registration, functional Magnetic Resonance Imaging (fMRI) modeling, Electroencephalogram (EEG) processing, and multi‐task collaboration. We organize the model details and open sources for reference and replication. In addition, we discuss the quantitative assessments, model complexity, and optimization of Transformers, which are topics of great concern in the field. Finally, we explore possible future challenges and opportunities, exploiting some concrete and recent cases to provoke discussion and innovation. We hope that this review will stimulate interest in further research on Transformers in the context of brain sciences. |
| first_indexed | 2024-04-24T15:41:41Z |
| format | Article |
| id | doaj.art-58d50a28d5a340a8a057d3bc379faf24 |
| institution | Directory Open Access Journal |
| issn | 2835-3153 |
| language | English |
| last_indexed | 2024-04-24T15:41:41Z |
| publishDate | 2023-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Brain-X |
| spelling | doaj.art-58d50a28d5a340a8a057d3bc379faf242024-04-01T19:00:07ZengWileyBrain-X2835-31532023-09-0113n/an/a10.1002/brx2.29Understanding the brain with attention: A survey of transformers in brain sciencesCheng Chen0Huilin Wang1Yunqing Chen2Zihan Yin3Xinye Yang4Huansheng Ning5Qian Zhang6Weiguang Li7Ruoxiu Xiao8Jizong Zhao9School of Computer and Communication Engineering University of Science and Technology Beijing Beijing ChinaSchool of Computer and Communication Engineering University of Science and Technology Beijing Beijing ChinaSchool of Computer and Communication Engineering University of Science and Technology Beijing Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital Capital Medical University Beijing ChinaSchool of Computer and Communication Engineering University of Science and Technology Beijing Beijing ChinaSchool of Computer and Communication Engineering University of Science and Technology Beijing Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital Capital Medical University Beijing ChinaDepartment of Health Technology and Informatics Hong Kong Polytechnic University Hong Kong SAR ChinaSchool of Computer and Communication Engineering University of Science and Technology Beijing Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital Capital Medical University Beijing ChinaAbstract Owing to their superior capabilities and advanced achievements, Transformers have gradually attracted attention with regard to understanding complex brain processing mechanisms. This study aims to comprehensively review and discuss the applications of Transformers in brain sciences. First, we present a brief introduction of the critical architecture of Transformers. Then, we overview and analyze their most relevant applications in brain sciences, including brain disease diagnosis, brain age prediction, brain anomaly detection, semantic segmentation, multi‐modal registration, functional Magnetic Resonance Imaging (fMRI) modeling, Electroencephalogram (EEG) processing, and multi‐task collaboration. We organize the model details and open sources for reference and replication. In addition, we discuss the quantitative assessments, model complexity, and optimization of Transformers, which are topics of great concern in the field. Finally, we explore possible future challenges and opportunities, exploiting some concrete and recent cases to provoke discussion and innovation. We hope that this review will stimulate interest in further research on Transformers in the context of brain sciences.https://doi.org/10.1002/brx2.29brain scienceEEGfMRIMRItransformer |
| spellingShingle | Cheng Chen Huilin Wang Yunqing Chen Zihan Yin Xinye Yang Huansheng Ning Qian Zhang Weiguang Li Ruoxiu Xiao Jizong Zhao Understanding the brain with attention: A survey of transformers in brain sciences Brain-X brain science EEG fMRI MRI transformer |
| title | Understanding the brain with attention: A survey of transformers in brain sciences |
| title_full | Understanding the brain with attention: A survey of transformers in brain sciences |
| title_fullStr | Understanding the brain with attention: A survey of transformers in brain sciences |
| title_full_unstemmed | Understanding the brain with attention: A survey of transformers in brain sciences |
| title_short | Understanding the brain with attention: A survey of transformers in brain sciences |
| title_sort | understanding the brain with attention a survey of transformers in brain sciences |
| topic | brain science EEG fMRI MRI transformer |
| url | https://doi.org/10.1002/brx2.29 |
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