ReviewNeurobiology of language (Cambridge, Mass.)2025
From Multimodal Sensorimotor Integration to Semantic Networks: A Phylogenetic Perspective on Speech and Language Evolution.
Review in Neurobiology of language (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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2 authors.
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Abstract
This integrative perspective article delves into the crucial role of the superior temporal sulcus (STS) and adjacent perisylvian regions in multimodal integration and semantic cognition. Drawing from a wide range of neuroscientific evidence, including studies on nonhuman primates and human brain evolution, the article highlights the significance of the STS in linking auditory and visual modalities, particularly in the establishment of associative links between auditory inputs and visual stimuli. Furthermore, it explores the expansion of the human temporal lobe and its implications for the amplification of multisensory regions, emphasizing the role of these regions in the development of word-related concepts and semantic networks. We propose a posteroanterior gradient organization in the human temporal lobe, from low-level sensorimotor integration in posterior regions to higher-order, transmodal semantic control in anterior portions, particularly in the anterior temporal lobe. Overall, this perspective provides a comprehensive overview of the functional and evolutionary aspects of the STS and adjacent regions in multimodal integration and semantic cognition, offering valuable insights for future research in this field.
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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.