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Neural organization of spoken language revealed by lesion-symptom mapping.

Mirman D, Chen Q, Zhang Y, Wang Z, Faseyitan OK, Coslett HB, Schwartz MF - Nat Commun (2015)

Bottom Line: In this study, we combine high-quality structural neuroimaging analysis techniques and extensive behavioural assessment of patients with persistent acquired language deficits to study the neural basis of language.Phonological form deficits are associated with lesions in peri-Sylvian regions, whereas semantic production and recognition deficits are associated with damage to the left anterior temporal lobe and white matter connectivity with frontal cortex, respectively.These findings provide a novel synthesis of traditional and contemporary views of the cognitive and neural architecture of language processing, emphasizing dual routes for speech processing and convergence of white matter tracts for semantic control and/or integration.

View Article: PubMed Central - PubMed

Affiliation: 1] Moss Rehabilitation Research Institute, 50 Township Line Road, Elkins Park, Pennsylvania 19027, USA [2] Department of Psychology, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19104, USA.

ABSTRACT
Studies of patients with acquired cognitive deficits following brain damage and studies using contemporary neuroimaging techniques form two distinct streams of research on the neural basis of cognition. In this study, we combine high-quality structural neuroimaging analysis techniques and extensive behavioural assessment of patients with persistent acquired language deficits to study the neural basis of language. Our results reveal two major divisions within the language system-meaning versus form and recognition versus production-and their instantiation in the brain. Phonological form deficits are associated with lesions in peri-Sylvian regions, whereas semantic production and recognition deficits are associated with damage to the left anterior temporal lobe and white matter connectivity with frontal cortex, respectively. These findings provide a novel synthesis of traditional and contemporary views of the cognitive and neural architecture of language processing, emphasizing dual routes for speech processing and convergence of white matter tracts for semantic control and/or integration.

No MeSH data available.


Related in: MedlinePlus

Factor analysis resultsEach panel shows the factor loadings of each test on the named factor. Longer and more saturated bars correspond to stronger loadings with blue indicating positive loading and red indicating negative loading. See Methods for detailed descriptions of the tests and performance measures.
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Figure 1: Factor analysis resultsEach panel shows the factor loadings of each test on the named factor. Longer and more saturated bars correspond to stronger loadings with blue indicating positive loading and red indicating negative loading. See Methods for detailed descriptions of the tests and performance measures.

Mentions: We used factor analysis with varimax rotation to identify key dimensions of variability on 17 measures of language function in 99 individuals with chronic language deficits following left hemisphere stroke. Three factors had eigenvalues above 1.0, passing the Kaiser threshold for inclusion in exploratory factor analysis. The first factor had high loadings from tests that require recognition of semantic relationships or matches, including verbal comprehension (word-to-picture matching, synonym judgments) and non-verbal comprehension (picture association judgments). These tests all require extracting task-appropriate semantic content from pictures or words but do not require substantial additional processing, as might be necessary for categorical inference or semantically-driven word production, so we call this factor “Semantic Recognition”. The second factor had high positive loadings from tests of word and nonword repetition and negative loading from production of phonological errors in picture naming. These tests capture phonological/articulatory encoding for speech production, so we call this factor “Speech Production”. The third factor had high loadings from auditory lexical decision and phoneme discrimination tests and moderate loadings from rhyme discrimination and word and nonword repetition tests. These tests capture auditory-phonological perception, so we call this factor “Speech Recognition”. The fourth factor had eigenvalue just below 1.0 (0.947), but had only one high loading: semantic errors in picture naming. Semantic error production was only moderately correlated with deficits on measures of semantic recognition (all Kendall rank correlations: τ < 0.25) and, in a three-factor solution, this behavioral score did not load strongly on any of the factors (all loadings less than 0.4), suggesting that it is relatively independent of the other factors. Semantic errors in naming were previously analyzed in a subset of the present group17,18 and they provide a potentially important comparison for the first factor, so this factor was also retained (we will refer to it as “Semantic Errors”). The resulting four-factor solution captured 76% of the variance in the original data and the loadings are shown in Fig. 1.


Neural organization of spoken language revealed by lesion-symptom mapping.

Mirman D, Chen Q, Zhang Y, Wang Z, Faseyitan OK, Coslett HB, Schwartz MF - Nat Commun (2015)

Factor analysis resultsEach panel shows the factor loadings of each test on the named factor. Longer and more saturated bars correspond to stronger loadings with blue indicating positive loading and red indicating negative loading. See Methods for detailed descriptions of the tests and performance measures.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4400840&req=5

Figure 1: Factor analysis resultsEach panel shows the factor loadings of each test on the named factor. Longer and more saturated bars correspond to stronger loadings with blue indicating positive loading and red indicating negative loading. See Methods for detailed descriptions of the tests and performance measures.
Mentions: We used factor analysis with varimax rotation to identify key dimensions of variability on 17 measures of language function in 99 individuals with chronic language deficits following left hemisphere stroke. Three factors had eigenvalues above 1.0, passing the Kaiser threshold for inclusion in exploratory factor analysis. The first factor had high loadings from tests that require recognition of semantic relationships or matches, including verbal comprehension (word-to-picture matching, synonym judgments) and non-verbal comprehension (picture association judgments). These tests all require extracting task-appropriate semantic content from pictures or words but do not require substantial additional processing, as might be necessary for categorical inference or semantically-driven word production, so we call this factor “Semantic Recognition”. The second factor had high positive loadings from tests of word and nonword repetition and negative loading from production of phonological errors in picture naming. These tests capture phonological/articulatory encoding for speech production, so we call this factor “Speech Production”. The third factor had high loadings from auditory lexical decision and phoneme discrimination tests and moderate loadings from rhyme discrimination and word and nonword repetition tests. These tests capture auditory-phonological perception, so we call this factor “Speech Recognition”. The fourth factor had eigenvalue just below 1.0 (0.947), but had only one high loading: semantic errors in picture naming. Semantic error production was only moderately correlated with deficits on measures of semantic recognition (all Kendall rank correlations: τ < 0.25) and, in a three-factor solution, this behavioral score did not load strongly on any of the factors (all loadings less than 0.4), suggesting that it is relatively independent of the other factors. Semantic errors in naming were previously analyzed in a subset of the present group17,18 and they provide a potentially important comparison for the first factor, so this factor was also retained (we will refer to it as “Semantic Errors”). The resulting four-factor solution captured 76% of the variance in the original data and the loadings are shown in Fig. 1.

Bottom Line: In this study, we combine high-quality structural neuroimaging analysis techniques and extensive behavioural assessment of patients with persistent acquired language deficits to study the neural basis of language.Phonological form deficits are associated with lesions in peri-Sylvian regions, whereas semantic production and recognition deficits are associated with damage to the left anterior temporal lobe and white matter connectivity with frontal cortex, respectively.These findings provide a novel synthesis of traditional and contemporary views of the cognitive and neural architecture of language processing, emphasizing dual routes for speech processing and convergence of white matter tracts for semantic control and/or integration.

View Article: PubMed Central - PubMed

Affiliation: 1] Moss Rehabilitation Research Institute, 50 Township Line Road, Elkins Park, Pennsylvania 19027, USA [2] Department of Psychology, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19104, USA.

ABSTRACT
Studies of patients with acquired cognitive deficits following brain damage and studies using contemporary neuroimaging techniques form two distinct streams of research on the neural basis of cognition. In this study, we combine high-quality structural neuroimaging analysis techniques and extensive behavioural assessment of patients with persistent acquired language deficits to study the neural basis of language. Our results reveal two major divisions within the language system-meaning versus form and recognition versus production-and their instantiation in the brain. Phonological form deficits are associated with lesions in peri-Sylvian regions, whereas semantic production and recognition deficits are associated with damage to the left anterior temporal lobe and white matter connectivity with frontal cortex, respectively. These findings provide a novel synthesis of traditional and contemporary views of the cognitive and neural architecture of language processing, emphasizing dual routes for speech processing and convergence of white matter tracts for semantic control and/or integration.

No MeSH data available.


Related in: MedlinePlus