1,933 research outputs found

    Bidirectional syntactic priming across cognitive domains: from arithmetic to language and back

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    Scheepers et al. (2011) showed that the structure of a correctly solved mathematical equation affects how people subsequently complete sentences containing high vs. low relative-clause attachment ambiguities. Here we investigated whether such effects generalise to different structures and tasks, and importantly, whether they also hold in the reverse direction (i.e., from linguistic to mathematical processing). In a questionnaire-based experiment, participants had to solve structurally left- or right-branching equations (e.g., 5 × 2 + 7 versus 5 + 2 × 7) and to provide sensicality ratings for structurally left- or right-branching adjective-noun-noun compounds (e.g., alien monster movie versus lengthy monster movie). In the first version of the experiment, the equations were used as primes and the linguistic expressions as targets (investigating structural priming from maths to language). In the second version, the order was reversed (language-to-maths priming). Both versions of the experiment showed clear structural priming effects, conceptually replicating and extending the findings from Scheepers et al. (2011). Most crucially, the observed bi-directionality of cross-domain structural priming strongly supports the notion of shared syntactic representations (or recursive procedures to generate and parse them) between arithmetic and language

    Age differences in encoding-related alpha power reflect sentence comprehension difficulties

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    When sentence processing taxes verbal working memory, comprehension difficulties arise. This is specifically the case when processing resources decline with advancing adult age. Such decline likely affects the encoding of sentences into working memory, which constitutes the basis for successful comprehension. To assess age differences in encoding-related electrophysiological activity, we recorded the electroencephalogram from three age groups (24, 43, and 65 years). Using an auditory sentence comprehension task, age differences in encoding-related oscillatory power were examined with respect to the accuracy of the given response. That is, the difference in oscillatory power between correctly and incorrectly encoded sentences, yielding subsequent memory effects (SME), was compared across age groups. Across age groups, we observed an age-related SME inversion in the alpha band from a power decrease in younger adults to a power increase in older adults. We suggest that this SME inversion underlies age-related comprehension difficulties. With alpha being commonly linked to inhibitory processes, this shift may reflect a change in the cortical inhibition–disinhibition balance. A cortical disinhibition may imply enriched sentence encoding in younger adults. In contrast, resource limitations in older adults may necessitate an increase in cortical inhibition during sentence encoding to avoid an information overload. Overall, our findings tentatively suggest that age-related comprehension difficulties are associated with alterations to the electrophysiological dynamics subserving general higher cognitive functions

    Towards a neural basis of auditory sentence processing

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    AbstractFunctional dissociations within the neural basis of auditory sentence processing are difficult to specify because phonological, syntactic and semantic information are all involved when sentences are perceived. In this review I argue that sentence processing is supported by a temporo–frontal network. Within this network, temporal regions subserve aspects of identification and frontal regions the building of syntactic and semantic relations. Temporal analyses of brain activation within this network support syntax-first models because they reveal that building of syntactic structure precedes semantic processes and that these interact only during a later stage

    Differential task effects on semantic and syntactic processes as revealed by ERPs

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    Two experiments investigated the time-course of semantic and syntactic processes in auditory language comprehension as well as their possible functional dependencies, using event-related brain potentials (ERPs). Participants listened to sentences which were either correct, semantically incorrect, syntactically incorrect, or both semantically and syntactically incorrect. In experiment 1, participants judged the overall correctness of these sentences. The semantic violation elicited an N400 whereas the syntactic phrase structure violation elicited an early anterior negativity followed by a P600. Sentences in which the critical element violated both semantic and syntactic constraints elicited the same pattern of ERPs as the syntactic violation alone, not evoking an N400. In experiment 2, participants judged the same sentences for semantic coherence, required to ignore syntactic violations. Again, an early anterior negativity was elicited for those sentences containing phrase-structure errors. In contrast to experiment 1, however, combined violations elicited both an early negativity and an N400. Together, the results suggest that the N400 associated with semantic aspects of sentence comprehension reflects controlled processes whereas initial parsing processes associated with the early anterior negativity are independent of semantic constraints and task requirements

    The neural basis of sign language processing in deaf signers: An activation likelihood estimation meta-analysis

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    The neurophysiological response during processing of sign language (SL) has been studied since the advent of Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI). Nevertheless, the neural substrates of SL remain subject to debate, especially with regard to involvement and relative lateralization of SL processing without production in (left) inferior frontal gyrus (IFG; e.g., Campbell, MacSweeney, & Waters, 2007; Emmorey, 2006, 2015). Our present contribution is the first to address these questions meta-analytically, by exploring functional convergence on the whole-brain level using previous fMRI and PET studies of SL processing in deaf signers. We screened 163 records in PubMed and Web of Science to identify studies of SL processing in deaf signers conducted with fMRI or PET that reported foci data for one of the two whole-brain contrasts: (1) “SL processing vs. control” or (2) “SL processing vs. low-level baseline”. This resulted in a total of 21 studies reporting 23 experiments matching our selection criteria. We manually extracted foci data and performed a coordinate-based Activation Likelihood Estimation (ALE) analysis using GingerALE (Eickhoff et al., 2009). Our selection criteria and the ALE method allow us to identify regions that are consistently involved in processing SL across studies and tasks. Our analysis reveals that processing of SL stimuli of varying linguistic complexity engages widely distributed bilateral fronto-occipito-temporal networks in deaf signers. We find significant clusters in both hemispheres, with the largest cluster (5240 mm3) being located in left IFG, spanning Broca’s region (posterior BA 45 and the dorsal portion of BA 44). Other clusters are located in right middle and inferior temporal gyrus (BA 37), right IFG (BA 45), left middle occipital gyrus (BA 19), right superior temporal gyrus (BA 22), left precentral and middle frontal gyrus (BA 6 and 8), as well as left insula (BA 13). On these clusters, we calculated lateralization indices using hemispheric and anatomical masks: SL comprehension is slightly left-lateralized globally, and strongly left-lateralized in Broca’s region. Sub-regionally, left-lateralization is strongest in BA 44 (Table 1). Next, we performed a contrast analysis between SL and an independent dataset of action observation in hearing non-signers (Papitto, Friederici, & Zaccarella, 2019) to determine which regions are associated with processing of human actions and movements irrespective of the presence of linguistic information. Only studies of observation of non-linguistic manual actions were included in the final set (n = 26), for example, excluding the handling of objects. Significant clusters involved in the linguistic aspects of SL comprehension were found in left Broca’s region (centered in dorsal BA 44), right superior temporal gyrus (BA 22), and left middle frontal and precentral gyrus (BA 6 and 8; Figure 1A, B, D and E). Meta-analytic connectivity modelling for the surviving cluster in Broca’s region using the BrainMap database then revealed that it is co-activated with the classical language network and functionally primarily associated with cognition and language processing (Figure 1C and D). In line with studies of spoken and written language processing (Zaccarella, Schell, & Friederici, 2017; Friederici, Chomsky, Berwick, Moro, & Bolhuis, 2017), our meta-analysis points to Broca’s region and especially left BA 44 as a hub in the language network that is involved in language processing independent of modality. Right IFG activity is not language-specific but may be specific to the visuo-gestural modality (Campbell et al., 2007). References Amunts, K., Schleicher, A., Bürgel, U., Mohlberg, H., Uylings, H. B., & Zilles, K. (1999). Broca’s region revisited: Cytoarchitecture and intersubject variability. The Journal of Comparative Neurology, 412(2), 319-341. Campbell, R., MacSweeney, M., & Waters, D. (2007). Sign language and the brain: A review. Journal of Deaf Studies and Deaf Education, 13(1), 3-20. doi: 10.1093/deafed/enm035 Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009). Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Human Brain Mapping, 30(9), 2907-2926. doi: 10.1002/hbm.20718 Emmorey, K. (2006). The role of Broca’s area in sign language. In Y. Grodzinsky & K. Amunts (Eds.), Broca’s region (p. 169-184). Oxford, England: Oxford UP. Emmorey, K. (2015). The neurobiology of sign language. In A. W. Toga, P. Bandettini, P. Thompson, & K. Friston (Eds.), Brain mapping: An encyclopedic reference (Vol. 3, p. 475-479). London, England: Academic Press. doi: 10.1016/B978-0-12-397025-1.00272-4 Friederici, A. D., Chomsky, N., Berwick, R. C., Moro, A., & Bolhuis, J. J. (2017). Language, mind and brain. Nature Human Behaviour. doi: 10.1038/s41562-017-0184-4 Matsuo, K., Chen, S.-H. A., & Tseng, W.-Y. I. (2012). AveLI: A robust lateralization index in functional magnetic resonance imaging using unbiased threshold-free computation. Journal of Neuroscience Methods, 205(1), 119-129. doi: 10.1016/j.jneumeth.2011.12.020 Papitto, G., Friederici, A. D., & Zaccarella, E. (2019). A neuroanatomical comparison of action domains using Activation Likelihood Estimation meta-analysis [Unpublished Manuscript, Max Planck Institute for Human Cognitive & Brain Sciences]. Leipzig, Germany. Zaccarella, E., Schell, M., & Friederici, A. D. (2017). Reviewing the functional basis of the syntactic Merge mechanism for language: A coordinate-based activation likelihood estimation meta-analysis. Neuroscience & Biobehavioral Reviews, 80, 646-656. doi: 10.1016/j.neubiorev.2017.06.01
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