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1
Predicting Semantic Similarity Between Clinical Sentence Pairs Using Transformer Models: Evaluation and Representational Analysis
In: JMIR Med Inform (2021)
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2
Perceptual and Semantic Representations at Encoding Contribute to True and False Recognition of Objects
In: J Neurosci (2021)
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3
Perceptual and semantic representations at encoding contribute to true and false recognition of objects
Naspi, Loris; Hoffman, Paul; Devereux, Barry; Morcom, Alexa. - : Society for Neuroscience, 2021
Abstract: When encoding new episodic memories, visual and semantic processing are proposed to make distinct contributions to accurate memory and memory distortions. Here, we used functional magnetic resonance imaging (fMRI) and preregistered representational similarity analysis (RSA) to uncover the representations that predict true and false recognition of unfamiliar objects. Two semantic models captured coarse-grained taxonomic categories and specific object features, respectively, while two perceptual models embodied low-level visual properties. Twenty-eight female and male participants encoded images of objects during fMRI scanning, and later had to discriminate studied objects from similar lures and novel objects in a recognition memory test. Both perceptual and semantic models predicted true memory. When studied objects were later identified correctly, neural patterns corresponded to low-level visual representations of these object images in the early visual cortex, lingual, and fusiform gyri. In a similar fashion, alignment of neural patterns with fine-grained semantic feature representations in the fusiform gyrus also predicted true recognition. However, emphasis on coarser taxonomic representations predicted forgetting more anteriorly in the anterior ventral temporal cortex, left inferior frontal gyrus and, in an exploratory analysis, left perirhinal cortex. In contrast, false recognition of similar lure objects was associated with weaker visual analysis posteriorly in early visual and left occipitotemporal cortex. The results implicate multiple perceptual and semantic representations in successful memory encoding and suggest that fine-grained semantic as well as visual analysis contributes to accurate later recognition, while processing visual image detail is critical for avoiding false recognition errors.
URL: http://sro.sussex.ac.uk/id/eprint/101101/
http://sro.sussex.ac.uk/id/eprint/101101/1/MORCOM_Journal_of_Neuroscience_JUL_2021.pdf
https://doi.org/10.1523/JNEUROSCI.0677-21.2021
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4
Eliciting semantic properties: methods and applications [<Journal>]
Chaigneau, Sergio E. [Verfasser]; Canessa, Enrique [Verfasser]; Lenci, Alessandro [Verfasser].
DNB Subject Category Language
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5
Feature2Vec: Distributional semantic modelling of human property knowledge ...
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6
Balancing Prediction and Sensory Input in Speech Comprehension: The Spatiotemporal Dynamics of Word Recognition in Context. ...
Klimovich-Gray, Anastasia; Tyler, Lorraine; Randall, Billi. - : Apollo - University of Cambridge Repository, 2019
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7
Balancing Prediction and Sensory Input in Speech Comprehension: The Spatiotemporal Dynamics of Word Recognition in Context.
Klimovich-Gray, Anastasia; Tyler, Lorraine; Randall, Billi. - : Society for Neuroscience, 2019. : J Neurosci, 2019
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8
Balancing Prediction and Sensory Input in Speech Comprehension: The Spatiotemporal Dynamics of Word Recognition in Context
Klimovich-Gray, Anastasia; Tyler, Lorraine K.; Randall, Billi. - : Society for Neuroscience, 2019
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9
Integrated deep visual and semantic attractor neural networks predict fMRI pattern-information along the ventral object processing pathway
Devereux, Barry J.; Clarke, Alex; Tyler, Lorraine K.. - : Nature Research, 2018
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10
Oscillatory Dynamics of Perceptual to Conceptual Transformations in the Ventral Visual Pathway
Clarke, Alex; Devereux, Barry J.; Tyler, Lorraine K.. - : Massachusetts Institute of Technology Press, 2018
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11
Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge ...
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12
Integrated deep visual and semantic attractor neural networks predict fMRI pattern-information along the ventral object processing pathway
Devereux, Barry J.; Clarke, Alex; Tyler, Lorraine K.. - : Nature Publishing Group UK, 2018
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13
Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics. ...
Zhuang, Jie; Devereux, Barry J. - : Apollo - University of Cambridge Repository, 2017
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14
Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics.
Zhuang, Jie; Devereux, Barry J. - : Taylor & Francis, 2017. : Language, Cognition and Neuroscience, 2017
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15
From Perception to Conception: How Meaningful Objects Are Processed over Time
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16
Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics
Zhuang, Jie; Devereux, Barry J.. - : Routledge, 2017
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17
Decoding the Cortical Dynamics of Sound-Meaning Mapping
Kocagoncu, Ece; Clarke, Alex; Devereux, Barry J.. - : Society for Neuroscience, 2017
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18
Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.
Devereux, Barry J; Taylor, Kirsten I; Randall, Billi. - : Wiley, 2016. : Cogn Sci, 2016
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19
Predicting the Time Course of Individual Objects with MEG
Clarke, Alex; Devereux, Barry J.; Randall, Billi. - : Oxford University Press, 2015
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20
Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing
Devereux, Barry J.; Taylor, Kirsten I.; Randall, Billi. - : John Wiley and Sons Inc., 2015
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