The Experts below are selected from a list of 171 Experts worldwide ranked by ideXlab platform
Rik Vandenberghe - One of the best experts on this subject based on the ideXlab platform.
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cross modal representation of spoken and written word meaning in left pars triangularis
NeuroImage, 2017Co-Authors: Antonietta Gabriella Liuzzi, Katarzyna Adamczuk, Emmanuel Keuleers, Simon De Deyne, Ronald R Peeters, Gerrit Storms, Rose Bruffaerts, Patrick Dupont, Rik VandenbergheAbstract:The correspondence in meaning extracted from written versus spoken input remains to be fully understood neurobiologically. Here, in a total of 38 subjects, the functional anatomy of cross-modal semantic Similarity for concrete words was determined based on a dual criterion: First, a voxelwise univariate analysis had to show significant activation during a semantic task (property verification) performed with written and spoken concrete words compared to the perceptually matched control condition. Second, in an independent dataset, in these clusters, the Similarity in fMRI response pattern to two distinct entities, one presented as a written and the other as a spoken word, had to correlate with the Similarity in meaning between these entities. The left ventral occipitotemporal transition zone and ventromedial temporal cortex, retrosplenial cortex, pars orbitalis bilaterally, and the left pars triangularis were all activated in the univariate contrast. Only the left pars triangularis showed a cross-modal semantic Similarity effect. There was no effect of phonological nor Orthographic Similarity in this region. The cross-modal semantic Similarity effect was confirmed by a secondary analysis in the cytoarchitectonically defined BA45. A semantic Similarity effect was also present in the ventral occipital regions but only within the visual modality, and in the anterior superior temporal cortex only within the auditory modality. This study provides direct evidence for the coding of word meaning in BA45 and positions its contribution to semantic processing at the confluence of input-modality specific pathways that code for meaning within the respective input modalities.
Cynthia S Q Siew - One of the best experts on this subject based on the ideXlab platform.
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the phonographic language network using network science to investigate the phonological and Orthographic Similarity structure of language
Journal of Experimental Psychology: General, 2019Co-Authors: Cynthia S Q Siew, Michael S VitevitchAbstract:Orthographic effects in spoken word recognition and phonological effects in visual word recognition have been observed in a variety of experimental tasks, strongly suggesting that a close interrelationship exists between phonology and orthography. However, the metrics used to investigate these effects, such as consistency and neighborhood size, fail to generalize to words of various lengths or syllable structures, and do not take into account the more global Similarity structure that exists between phonological and Orthographic representations in the language. To address these limitations, the tools of Network Science were used to simultaneously characterize the phonological as well as Orthographic Similarity structure of words in English. In the phonographic network of language, links are placed between words that are both phonologically and Orthographically similar to each other (e.g., words such as pant (/paent/) and punt (/pʌnt/)). Conventional psycholinguistic experiments (auditory naming and auditory lexical decision) and an archival analysis of the English Lexicon Project (visual naming and visual lexical decision) were conducted to investigate the influence of 2 network science metrics derived from the phonographic network-phonographic degree and phonographic clustering coefficient-on spoken and visual word recognition. Results indicated a facilitatory effect of phonographic degree on visual word recognition, and a facilitatory effect of phonographic clustering coefficient on spoken word recognition. Implications of the present findings for theoretical models of spoken and visual word recognition are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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the Orthographic Similarity structure of english words insights from network science
Applied Network Science, 2018Co-Authors: Cynthia S Q SiewAbstract:Network science has been applied to study the structure of the mental lexicon, the part of long-term memory where all the words a person knows are stored. Here the tools of network science are used to study the organization of Orthographic word-forms in the mental lexicon and how that might influence visual word recognition. An Orthographic Similarity network of the English language was constructed such that each node represented an English word, and undirected, unweighted edges were placed between words that differed by an edit distance of 1, a commonly used operationalization of Orthographic Similarity in psycholinguistics. The largest connected component of the Orthographic language network had a small-world structure and a long-tailed degree distribution. Additional analyses were conducted using behavioral data obtained from a psycholinguistic database to determine if network science measures obtained from the Orthographic language network could be used to predict how quickly and accurately people process written words. The present findings show that the structure of the mental lexicon influences lexical access in visual word recognition.
Antonietta Gabriella Liuzzi - One of the best experts on this subject based on the ideXlab platform.
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cross modal representation of spoken and written word meaning in left pars triangularis
NeuroImage, 2017Co-Authors: Antonietta Gabriella Liuzzi, Katarzyna Adamczuk, Emmanuel Keuleers, Simon De Deyne, Ronald R Peeters, Gerrit Storms, Rose Bruffaerts, Patrick Dupont, Rik VandenbergheAbstract:The correspondence in meaning extracted from written versus spoken input remains to be fully understood neurobiologically. Here, in a total of 38 subjects, the functional anatomy of cross-modal semantic Similarity for concrete words was determined based on a dual criterion: First, a voxelwise univariate analysis had to show significant activation during a semantic task (property verification) performed with written and spoken concrete words compared to the perceptually matched control condition. Second, in an independent dataset, in these clusters, the Similarity in fMRI response pattern to two distinct entities, one presented as a written and the other as a spoken word, had to correlate with the Similarity in meaning between these entities. The left ventral occipitotemporal transition zone and ventromedial temporal cortex, retrosplenial cortex, pars orbitalis bilaterally, and the left pars triangularis were all activated in the univariate contrast. Only the left pars triangularis showed a cross-modal semantic Similarity effect. There was no effect of phonological nor Orthographic Similarity in this region. The cross-modal semantic Similarity effect was confirmed by a secondary analysis in the cytoarchitectonically defined BA45. A semantic Similarity effect was also present in the ventral occipital regions but only within the visual modality, and in the anterior superior temporal cortex only within the auditory modality. This study provides direct evidence for the coding of word meaning in BA45 and positions its contribution to semantic processing at the confluence of input-modality specific pathways that code for meaning within the respective input modalities.
Michael S Vitevitch - One of the best experts on this subject based on the ideXlab platform.
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the phonographic language network using network science to investigate the phonological and Orthographic Similarity structure of language
Journal of Experimental Psychology: General, 2019Co-Authors: Cynthia S Q Siew, Michael S VitevitchAbstract:Orthographic effects in spoken word recognition and phonological effects in visual word recognition have been observed in a variety of experimental tasks, strongly suggesting that a close interrelationship exists between phonology and orthography. However, the metrics used to investigate these effects, such as consistency and neighborhood size, fail to generalize to words of various lengths or syllable structures, and do not take into account the more global Similarity structure that exists between phonological and Orthographic representations in the language. To address these limitations, the tools of Network Science were used to simultaneously characterize the phonological as well as Orthographic Similarity structure of words in English. In the phonographic network of language, links are placed between words that are both phonologically and Orthographically similar to each other (e.g., words such as pant (/paent/) and punt (/pʌnt/)). Conventional psycholinguistic experiments (auditory naming and auditory lexical decision) and an archival analysis of the English Lexicon Project (visual naming and visual lexical decision) were conducted to investigate the influence of 2 network science metrics derived from the phonographic network-phonographic degree and phonographic clustering coefficient-on spoken and visual word recognition. Results indicated a facilitatory effect of phonographic degree on visual word recognition, and a facilitatory effect of phonographic clustering coefficient on spoken word recognition. Implications of the present findings for theoretical models of spoken and visual word recognition are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Sascha Schroeder - One of the best experts on this subject based on the ideXlab platform.
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Orthographic networks in the developing mental lexicon insights from graph theory and implications for the study of language processing
Frontiers in Psychology, 2018Co-Authors: Jutta Trautwein, Sascha SchroederAbstract:In this study, we examine the development of Orthographic networks in the mental lexicon using graph theory. According to this view, words are represented by nodes in a network and connected as a function of their Orthographic Similarity. With a sampling approach based on a language corpus for German school children, we were able to simulate lexical development for children from Grade 1 to 8. By sampling different lexicon sizes from the corpus, we were able to analyze the content of the Orthographic lexicon at different time points and examined network characteristics using graph theory. Results show that, similar to semantic and phonological networks, Orthographic networks possess small-word characteristics defined by short average path lengths between nodes and strong local clustering. Moreover, the interconnectivity of the network decreases with growth. Implications for the study of the effect of network measures on language processing are discussed.
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the developmental lexicon project a behavioral database to investigate visual word recognition across the lifespan
Behavior Research Methods, 2017Co-Authors: Pauline Schroter, Sascha SchroederAbstract:With the Developmental Lexicon Project (DeveL), we present a large-scale study that was conducted to collect data on visual word recognition in German across the lifespan. A total of 800 children from Grades 1 to 6, as well as two groups of younger and older adults, participated in the study and completed a lexical decision and a naming task. We provide a database for 1,152 German words, comprising behavioral data from seven different stages of reading development, along with sublexical and lexical characteristics for all stimuli. The present article describes our motivation for this project, explains the methods we used to collect the data, and reports analyses on the reliability of our results. In addition, we explored developmental changes in three marker effects in psycholinguistic research: word length, word frequency, and Orthographic Similarity. The database is available online.
