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  1. Neural classification maps for distinct word combinations in Broca’s area.Marianne Schell, Angela D. Friederici & Emiliano Zaccarella - 2022 - Frontiers in Human Neuroscience 16:930849.
    Humans are equipped with the remarkable ability to comprehend an infinite number of utterances. Relations between grammatical categories restrict the way words combine into phrases and sentences. How the brain recognizes different word combinations remains largely unknown, although this is a necessary condition for combinatorial unboundedness in language. Here, we used functional magnetic resonance imaging and multivariate pattern analysis to explore whether distinct neural populations of a known language network hub—Broca’s area—are specialized for recognizing distinct simple word combinations. The phrases (...)
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  • Merge-Generability as the Key Concept of Human Language: Evidence From Neuroscience.Kyohei Tanaka, Isso Nakamura, Shinri Ohta, Naoki Fukui, Mihoko Zushi, Hiroki Narita & Kuniyoshi L. Sakai - 2019 - Frontiers in Psychology 10.
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  • Social Interaction Affects Neural Outcomes of Sign Language Learning As a Foreign Language in Adults.Noriaki Yusa, Jungho Kim, Masatoshi Koizumi, Motoaki Sugiura & Ryuta Kawashima - 2017 - Frontiers in Human Neuroscience 11.
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  • Systems Underlying Human and Old World Monkey Communication: One, Two, or Infinite.Shigeru Miyagawa & Esther Clarke - 2019 - Frontiers in Psychology 10:469108.
    Using artificially synthesized stimuli, previous research has shown that cotton-top tamarin monkeys easily learn simple AB grammar sequences, but not the more complex AnBn sequences that require hierarchical structure. Humans have no trouble learning AnBn combinations. A more recent study, using similar artificially created stimuli, showed that there is a neuroanatomical difference in the brain between these two kinds of arrays. While the simpler AB sequences recruit the frontal operculum, the AnBn array recruits the phylogenetically newer Broca’s area. We propose (...)
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  • Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation.Julia Uddén, Mauricio Jesus Dias Martins, Willem Zuidema & W. Tecumseh Fitch - 2020 - Topics in Cognitive Science 12 (3):910-924.
    Spoken language consists of a linear sequence of units, from which the existence of particular underlying hierarchical processing mechanisms is inferred. Uddén et al. use graph theory to provide a framework for describing the possible structural relationships that may underlie a linear output sequence. Being more explicit in defining different structures can help identifying and testing for such structures in AGL experiments, as well as help showing how behavioral and neuroimaging data reveals signatures of hierarchical processing in humans.
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  • Online neurostimulation of Broca’s area does not interfere with syntactic predictions: A combined TMS-EEG approach to basic linguistic combination.Matteo Maran, Ole Numssen, Gesa Hartwigsen & Emiliano Zaccarella - 2022 - Frontiers in Psychology 13.
    Categorical predictions have been proposed as the key mechanism supporting the fast pace of syntactic composition in language. Accordingly, grammar-based expectations are formed—e.g., the determiner “a” triggers the prediction for a noun—and facilitate the analysis of incoming syntactic information, which is then checked against a single or few other word categories. Previous functional neuroimaging studies point towards Broca’s area in the left inferior frontal gyrus as one fundamental cortical region involved in categorical prediction during incremental language processing. Causal evidence for (...)
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  • Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation.Julia Uddén, Mauricio de Jesus Dias Martins, Willem Zuidema & W. Tecumseh Fitch - 2020 - Topics in Cognitive Science 12 (3):910-924.
    Spoken language consists of a linear sequence of units, from which the existence of particular underlying hierarchical processing mechanisms is inferred. Uddén et al. use graph theory to provide a framework for describing the possible structural relationships that may underlie a linear output sequence. Being more explicit in defining different structures can help identifying and testing for such structures in AGL experiments, as well as help showing how behavioral and neuroimaging data reveals signatures of hierarchical processing in humans.
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