Neural Encoding and Decoding With Distributed Sentence Representations

Building computational models to account for the cortical representation of language plays an important role in understanding the human linguistic system. Recent progress in distributed semantic models (DSMs), especially transformer-based methods, has driven advances in many language understanding t...

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Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 32; no. 2; pp. 589 - 603
Main Authors:	Sun, Jingyuan, Wang, Shaonan, Zhang, Jiajun, Zong, Chengqing
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.02.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Ablation Algorithms Artificial neural networks Brain Brain - diagnostic imaging Brain mapping Brain modeling Brain-Computer Interfaces Brain–machine interfaces Cerebral Cortex - anatomy & histology Cerebral Cortex - physiology Coders Computational neuroscience Computer Simulation Decoding Deep Learning distributed semantic representations Encoding Functional magnetic resonance imaging Humans Image Processing, Computer-Assisted Interfaces Language Linguistics Machine learning Magnetic Resonance Imaging Model accuracy Natural Language Processing Neural coding neural decoding neural encoding Neural networks Neural Networks, Computer Neuroimaging Occipital Lobe - diagnostic imaging Reading Representations Reproducibility of Results Selectivity Semantics Sentences Stimuli Task analysis Temporal gyrus Temporal Lobe - diagnostic imaging Transformers
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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