Brains and algorithms partially converge in natural language processing

Deep learning algorithms trained to predict masked words from large amount of text have recently been shown to generate activations similar to those of the human brain. However, what drives this similarity remains currently unknown. Here, we systematically compare a variety of deep language models t...

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Bibliographic Details
Published in:	Communications biology Vol. 5; no. 1; pp. 134 - 10
Main Authors:	Caucheteux, Charlotte, King, Jean-Rémi
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 16.02.2022 Nature Publishing Group Nature Portfolio
Subjects:	631/378/116/1925 631/378/116/2395 631/378/2649/1594 Algorithms Artificial Intelligence Biology Biomedical and Life Sciences Brain Brain - diagnostic imaging Brain - physiology Brain mapping Cognitive science Computation and Language Computational neuroscience Computer Science Deep learning Functional magnetic resonance imaging Humans Language Learning algorithms Life Sciences Machine Learning Magnetic Resonance Imaging Magnetoencephalography Natural Language Processing Neural networks Neuroimaging Neuroscience Magneto-encephalography Encoding Functional Magnetic Resonance Imaging Natural Language Processing
ISSN:	2399-3642, 2399-3642
Online Access:	Get full text
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