ArticleNeuroImage2022
Deep neural networks reveal topic-level representations of sentences in medial prefrontal cortex, lateral anterior temporal lobe, precuneus, and angular gyrus.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Boston NamingTest performance in mild cognitive impairment: a meta-analysis.BMC neurology · 2026Pooled it
- Neural Coding of Multiple Linguistic Components During Reading Comprehension Across Development.Neurobiology of language (Cambridge, Mass.) · 2026Article
- Reading experience reveals shared and idiosyncratic neural patterns during text comprehension.NPJ science of learning · 2025Article
- Semantic Representational Strength in the Precuneus and Lateral ATL Predicts Successful Factual Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Association of magnetic resonance imaging glymphatic function with gray matter volume loss and cognitive impairment in Alzheimer's disease: a diffusion tensor image analysis along the perivascular space (DTI-ALPS) study.Quantitative imaging in medicine and surgery · 2025Article
- Neural mechanisms for the attention-mediated propagation of conceptual information in the human brain.PLoS biology · 2025Article
- The role of variation in phonological and semantic working memory capacities in sentence comprehension: neural evidence from healthy and brain-damaged individuals.Cognitive, affective & behavioral neuroscience · 2025Review
- How the intrinsic functional connectivity patterns of the semantic network support semantic processing.Brain imaging and behavior · 2024Article
- Predicting the next sentence (not word) in large language models: What model-brain alignment tells us about discourse comprehension.Science advances · 2024Article
- How does the "default mode" network contribute to semantic cognition?Brain and language · 2024Review
- An exploration of distinguishing subjective cognitive decline and mild cognitive impairment based on resting-state prefrontal functional connectivity assessed by functional near-infrared spectroscopy.Frontiers in aging neuroscience · 2024Article
- The neuroconnectionist research programme.Nature reviews. Neuroscience · 2023Review
- Prediction of Early Postoperative Language Function by Quantitative Evaluation with Visual and Auditory Naming Tasks during Awake Craniotomy for Brain Tumor Resection: Significance of Auditory Naming Task.Neurologia medico-chirurgica · 2023Article
- Recruitment of Control and Representational Components of the Semantic System during Successful and Unsuccessful Access to Complex Factual Knowledge.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
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3 authors.
Funding
Abstract
When reading a sentence, individual words can be combined to create more complex meaning. In this study, we sought to uncover brain regions that reflect the representation of the meaning of sentences at the topic level, as opposed to the meaning of their individual constituent words when considered irrespective of their context. Using fMRI, we recorded the neural activity of participants while reading sentences. We constructed a topic-level sentence representations using the final layer of a convolutional neural network (CNN) trained to classify Wikipedia sentences into broad semantic categories. This model was contrasted with word-level sentence representations constructed using the average of the word embeddings constituting the sentence. Using representational similarity analysis, we found that the medial prefrontal cortex, lateral anterior temporal lobe, precuneus, and angular gyrus more strongly represent sentence topic-level, compared to word-level, meaning, uncovering the important role of these semantic system regions in the representation of topic-level meaning. Results were comparable when sentence meaning was modelled with a multilayer perceptron that was not sensitive to word order within a sentence, suggesting that the learning objective, in the terms of the topic being modelled, is the critical factor in capturing these neural representational spaces.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.