Cortical stimulation mapping (CSM) has provided important insights into the neuroanatomy of language because of its high spatial and temporal resolution, and the causal relationships that can be inferred from transient disruption of specific functions. Almost all CSM studies to date have focused on word-level processes such as naming, comprehension, and repetition. In this study, we used CSM to identify sites where stimulation interfered selectively with syntactic encoding during sentence production. Fourteen patients undergoing left-hemisphere neurosurgery participated in the study. In 7 of the 14 patients, we identified nine sites where cortical stimulation interfered with syntactic encoding but did not interfere with single word processing. All nine sites were localized to the inferior frontal gyrus, mostly to the pars triangularis and opercularis. Interference with syntactic encoding took several different forms, including misassignment of arguments to grammatical roles, misassignment of nouns to verb slots, omission of function words and inflectional morphology, and various paragrammatic constructions. Our findings suggest that the left inferior frontal gyrus plays an important role in the encoding of syntactic structure during sentence production.
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http://dx.doi.org/10.1162/jocn_a_01215 | DOI Listing |
Bioengineering (Basel)
December 2024
The Bhawanipur Education Society, Kolkata 700020, India.
Disease prediction using computer-based methods is now an established area of research. The importance of technological intervention is necessary for the better management of disease, as well as to optimize use of limited resources. Various AI-based methods for disease prediction have been documented in the literature.
View Article and Find Full Text PDFTop Cogn Sci
December 2024
Department of Linguistics, University of Massachusetts Amherst.
As they process complex linguistic input, language comprehenders must maintain a mapping between lexical items (e.g., morphemes) and their syntactic position in the sentence.
View Article and Find Full Text PDFPeerJ Comput Sci
February 2024
School of Information Engineering, Fuyang Normal University, Fuyang, Anhui, China.
With the continuous advancement of deep learning technologies, neural machine translation (NMT) has emerged as a powerful tool for enhancing communication efficiency among the members of cross-language collaborative teams. Among the various available approaches, leveraging syntactic dependency relations to achieve enhanced translation performance has become a pivotal research direction. However, current studies often lack in-depth considerations of non-Euclidean spaces when exploring interword correlations and fail to effectively address the model complexity arising from dependency relation encoding.
View Article and Find Full Text PDFPeerJ Comput Sci
October 2024
Faculty of Computing, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia.
Understanding spoken language is crucial for conversational agents, with intent detection and slot filling being the primary tasks in natural language understanding (NLU). Enhancing the NLU tasks can lead to an accurate and efficient virtual assistant thereby reducing the need for human intervention and expanding their applicability in other domains. Traditionally, these tasks have been addressed individually, but recent studies have highlighted their interconnection, suggesting better results when solved together.
View Article and Find Full Text PDFbioRxiv
November 2024
Department of Neurosurgery, David Geffen School of Medicine, UCLA, Los-Angeles, California, USA.
According to psycholinguistic theories, during language processing, spoken and written words are first encoded along independent phonological and orthographic dimensions, then enter into modality-independent syntactic and semantic codes. Non-invasive brain imaging has isolated several cortical regions putatively associated with those processing stages, but lacks the resolution to identify the corresponding neural codes. Here, we describe the firing responses of over 1000 neurons, and mesoscale field potentials from over 1400 microwires and 1500 iEEG contacts in 21 awake neurosurgical patients with implanted electrodes during written and spoken sentence comprehension.
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