Brain Regions That Represent Amodal Conceptual Knowledge

Fairhall, Scott L.; Caramazza, Alfonso

doi:10.1523/jneurosci.0051-13.2013

Cited by 249 publications

(257 citation statements)

References 38 publications

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“…According to this visual word processing model, the ventral occipitotemporal posterior-anterior progression from word identification to word association is similar to progression proposed by Suzuki and Naya (2014) for visual objects, from object identification to associative coding between objects. As far as our data allow us to tell, at the left perirhinal stage there is convergence between written word and visual object modality (Fairhall and Caramazza, 2013) but not between written and auditory input modality. Within the "Lichtheim-2" dual-pathway framework (Ueno et al, 2011) this would mean that apart from a dorsal and a ventral, lateral temporal auditory word processing pathway, a third ventromedial temporal pathway exists for visual word input.…”

Section: Visual Word Processing Modelmentioning

confidence: 63%

“…Perirhinal cortex is also involved in explicit semantic tasks with written words. For instance, during a typicality judgment for written words and pictures, RSA revealed a crossmodal effect both for written words and for pictures in left ventral temporal cortex, encompassing among other areas the perirhinal cortex (-33, -29, -23) (Fairhall and Caramazza, 2013). In another study, an associative-semantic judgment with written words activated ventromedial temporal cortex comprising among other areas perirhinal cortex (Visser et al, 2010a).…”

Section: Extracting Meaning From Printed Wordsmentioning

confidence: 90%

“…The semantic similarity effect in perirhinal cortex was subsequently confirmed by Clarke and Tyler (2014) during overt naming of pictures of animate and inanimate items. A third research group independently found crossmodal semantic effects for written words and pictures in left ventral temporal cortex, encompassing left perirhinal cortex among other areas (Fairhall and Caramazza, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…An ever increasing number of studies have succeeded in detecting patterns of brain activity that reflect the identity or the semantic category of pictures (Haxby et al, 2001;Hanson et al, 2004;Shinkareva et al, 2008;Connolly et al, 2012;Mur et al, 2012;Bruffaerts et al, 2013a), written words Just et al, 2010), written words and pictures (Shinkareva et al, 2011;Simanova et al, 2012;Bruffaerts et al, 2013b;Devereux et al, 2013;Fairhall and Caramazza, 2013), written and spoken words (Akama et al, 2012;Simanova et al, 2012) as well as natural sounds (Simanova et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Left perirhinal cortex is one of the regions that has come out of a number of MVPA studies of this kind in a relatively consistent manner (Bruffaerts et al, 2013b;Fairhall and Caramazza, 2013;Clarke and Tyler, 2014;Mur, 2014). For written words, semantic similarity between concrete animate entities is reflected by the cosine similarity between fMRI response patterns in perirhinal cortex (Bruffaerts et al, 2013b).…”

Section: Introductionmentioning

confidence: 99%

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Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

et al. 2015

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This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Neuropsychologia following peer review. The definitive publisher-authenticated version (Liuzzi A.G., Bruffaerts R., Dupont P., Adamczuk K., Peeters R., De Deyne S., Storms G., Vandenberghe R. AbstractLeft perirhinal cortex has been previously implicated in associative coding. According to a recent experiment, the similarity of perirhinal fMRI response patterns to written concrete words is higher for words which are more similar in their meaning. If left perirhinal cortex functions as an amodal semantic hub, one would predict that this semantic similarity effect would extend to the spoken modality. We conducted an event-related fMRI experiment and evaluated whether a same semantic similarity effect could be obtained for spoken as for written words. Twenty healthy subjects performed a property verification task in either the written or the spoken modality. Words corresponded to concrete animate entities for which extensive feature generation was available from more than 1000 subjects. From these feature generation data, a concept-feature matrix was derived which formed the basis of a cosine similarity matrix between the entities reflecting their similarity in meaning (called the "semantic cossimilarity matrix"). Independently, we calculated a cosine similarity matrix between the left perirhinal fMRI activity patterns evoked by the words (called the "fMRI cossimilarity matrix"). Next, the similarity was determined between the semantic cossimilarity matrix and the fMRI cossimilarity matrix. This was done for written and spoken words pooled, for written words only, for spoken words only, as well as for crossmodal pairs. Only for written words did the fMRI cossimilarity matrix correlate with the semantic cossimilarity matrix. Contrary to our prediction, we did not find any such effect for auditory word input nor did we find cross-modal effects in perirhinal cortex between written and auditory words. Our findings situate the contribution of left perirhinal cortex to word processing at the top of the visual processing pathway, rather than at an amodal stage where visual and auditory word processing pathways have already converged.

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Section: Visual Word Processing Modelmentioning

confidence: 63%

Section: Extracting Meaning From Printed Wordsmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

et al. 2015

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Neural correlates of association strength and categorical relatedness in youths with autism spectrum disorder

2019

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Impaired language and communication are commonly observed in youths with autism spectrum disorders (ASDs). However, the organization of semantic knowledge in youths with ASD remains unclear compared to typically developing (TD) youths. The present study addresses this issue by using functional magnetic resonance imaging (fMRI) to examine the distinction between association strength and categorical relatedness of semantic knowledge. A sample of 31 male youths with ASD (mean age = 12.1 years, SD = 1.2) and 38 TD youths (mean age = 11.9 years, SD = 1.0) was recruited with matched age, gender, and handedness. Participants decided if two visually presented Chinese characters were semantically related during fMRI scanning. For weaker association strength, the ASD group showed greater left cuneus activation, which was positively correlated with the picture completion for visual perception, whereas the TD group showed greater middle temporal gyrus and inferior frontal gyrus activation. For higher categorical relatedness, the TD group showed greater activation than the ASD group in the occipitotemporal cortex and left precuneus, which was positively correlated with the similarities for concept formulation. Findings imply that the ASD group may use lower‐level visual information for both association strength and categorical relatedness. The TD group showed higher‐level controlled processes of more elaborate semantic representations for association strength and more elaborate features of categorical knowledge for semantic selection and integration. Autism Res 2019, 12: 1484–1494. © 2019 International Society for Autism Research, Wiley Periodicals, Inc.Lay SummaryIndividuals with autism spectrum disorder (ASD) often present language/communication impairments. Exploring the difference of semantic processing between youths with ASD and typically developing (TD) youths is crucial for understanding the organization of semantic knowledge. We found different neural substrates of semantic knowledge between these two groups. ASD youths may rely more on lower‐level visual information during semantic judgments, whereas TD youths showed higher‐level controlled processes of more elaborate semantic representations for selection and integration of words, phrases, and sentences.

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Lipreading a naturalistic narrative in a female population: Neural characteristics shared with listening and reading

et al. 2022

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Introduction: Few of us are skilled lipreaders while most struggle with the task. Neural substrates that enable comprehension of connected natural speech via lipreading are not yet well understood. Methods:We used a data-driven approach to identify brain areas underlying the lipreading of an 8-min narrative with participants whose lipreading skills varied extensively (range 6-100%, mean = 50.7%). The participants also listened to and read the same narrative. The similarity between individual participants' brain activity during the whole narrative, within and between conditions, was estimated by a voxel-wise comparison of the Blood Oxygenation Level Dependent (BOLD) signal time courses.Results: Inter-subject correlation (ISC) of the time courses revealed that lipreading, listening to, and reading the narrative were largely supported by the same brain areas in the temporal, parietal and frontal cortices, precuneus, and cerebellum. Additionally, listening to and reading connected naturalistic speech particularly activated higherlevel linguistic processing in the parietal and frontal cortices more consistently than lipreading, probably paralleling the limited understanding obtained via lip-reading. Importantly, higher lipreading test score and subjective estimate of comprehension of the lipread narrative was associated with activity in the superior and middle temporal cortex. Conclusions:Our new data illustrates that findings from prior studies using wellcontrolled repetitive speech stimuli and stimulus-driven data analyses are also valid for naturalistic connected speech. Our results might suggest an efficient use of brain areas dealing with phonological processing in skilled lipreaders.

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Brain Regions That Represent Amodal Conceptual Knowledge

Cited by 249 publications

References 38 publications

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

Neural correlates of association strength and categorical relatedness in youths with autism spectrum disorder

Lipreading a naturalistic narrative in a female population: Neural characteristics shared with listening and reading

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