Chasing language through the brain: Successive parallel networks

Zheng, Weili; Reddy, Geeth Kavya Minama; Dai, Falcon Z.; Chandramani, Ayushi; Brang, David; Kohrman, Michael; Rose, Sandra; Rossi, Marvin A.; Tao, James X.; Wu, Shasha; Byrne, Richard W.; Frim, David M.; Warnke, Peter C.; Towle, Vernon L.

doi:10.1016/j.clinph.2020.10.007

Cited by 8 publications

(6 citation statements)

References 74 publications

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“…Similar superior temporal region responses to language related auditory stimuli have been described as part of work that did not utilize the response classifications described here for Sustained and Onset sites. For example, Zheng et al 2021 report iEEG data using a dynamic analytical approach to high gamma changes following auditory and other stimuli as part of a naming task 15 . They deployed a unique method of parcellating the superior temporal gyrus to elaborate cortical processing in relation to parallel language networks.…”

Section: Discussionmentioning

confidence: 99%

“…When they preceded language stimuli by 1s with a warning tone of 500ms duration, superior temporal sites responding to the warning tone were identified in the 'center' or 'middle' superior temporal gyrus. They hypothesized that this response represented "activation of the primary auditory cortex and auditory beltway areas" 15 , with activations to words being more widespread. Assuming their single word stimuli were less than 1s in duration, Zheng's procedures would not likely have distinguished Onset from Sustained activation sites.…”

Section: Discussionmentioning

confidence: 99%

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Speech-related auditory salience detection in the posterior superior temporal region

Brown

Stedelin

et al. 2021

Preprint

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Processing auditory human speech requires both detection (early and transient) and analysis (sustained). We analyzed high gamma (70-110Hz) activity of intracranial electroencephalography waveforms acquired during an auditory task that paired forward speech, reverse speech, and signal correlated noise. We identified widespread superior temporal sites with sustained activity responding only to forward and reverse speech regardless of paired order. More localized superior temporal auditory onset sites responded to all stimulus types when presented first in a pair and responded in recurrent fashion to the second paired stimulus in select conditions even in the absence of interstimulus silence; a novel finding. Auditory onset activity to a second paired sound recurred according to relative salience, with evidence of partial suppression during linguistic processing. We propose that temporal lobe auditory onset sites facilitate a salience detector function with hysteresis of 200ms and are influenced by cortico-cortical feedback loops involving linguistic processing and articulation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Speech-related auditory salience detection in the posterior superior temporal region

Brown

Stedelin

et al. 2021

Preprint

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“…However, the idea that verbs are, in general, harder to produce has been undermined in other studies where it is indicated that patients with anomic difficulties produce verbs more easily than nouns 19 , 20 . From a neurophysiological point of view, there are different opinions and theoretical proposals 21 , of which three hypotheses have been put forward regarding verb-noun storage issues within neural networks: partial separation of verbs and nouns 22 , 23 , word separation based on morphosyntax 24 , and separation between actions and objects 25 , 26 . Psycholinguistics also agree that exist, in the brain, the distinction between various grammatical categories, particularly between verbs and nouns, and propose three possible starting points or context to access the information: availability of information related to the grammatical class , a required grammatical knowledge , and the independence between the definition of grammatical class and the semantic differences 27 – 30 .…”

Section: Conceptual Frameworkmentioning

confidence: 99%

A System for Converting and Recovering Texts Managed as Structured Information

Verdesoto

Ortiz

Herrera

2022

Sci Rep

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This paper introduces a system that incorporates several strategies based on scientific models of how the brain records and recovers memories. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architecture that can be adapted to any language. A special case is studied and tested regarding the Spanish language. The applications of this proposal are vast because, in general, information such as text way, reports, emails, and web content, among others, is considered unstructured and, hence, the repositories based on SQL databases usually do not handle this kind of data correctly and efficiently. The conversion of unstructured textual information to structured one can be useful in contexts such as Natural Language Generation, Data Mining, and dynamic generation of theories, among others.

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“…However, the idea that verbs are, in general, harder to produce has been undermined in other studies where it is indicated that patients with anomic difficulties produce verbs more easily than nouns [34,35]. From a Neurophysiological point of view, there are different opinions and theoretical proposals [36], three hypotheses have been put forward regarding verb-noun storage issues within neural networks: partial separation of verbs and nouns [37,38], word separation based on morphosyntax [39], and separation between actions and objects [40,41]. Psycholinguistics also agrees that the distinction between various grammatical categories, particularly between verbs and nouns exist in the brain and proposes three possible starting points or context to access the information: availability of information related to grammatical class, required grammatical knowledge, and independence between the definition of grammatical class and the semantic differences [42][43][44][45].…”

Section: Conceptual Framework 12 Object-action Dissociation/integrationmentioning

confidence: 99%

An Abstract System for Converting and Recovering Texts like Structured Information

Verdesoto¹,

Herrera²,

Ortiz

2021

Preprint

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This paper introduces an abstract system for converting texts into structured information. The proposed architecture incorporates several strategies based on scientific models of how the brain records and recovers memories, and approaches that convert texts into structured data. The applications of this proposal are vast because, in general, the information that can be expressed like a text way, such as reports, emails, web contents, etc., is considered unstructured and, hence, the repositories based on a SQL do not capable to deal efficiently with this kind of data. The model in which was based on this proposal divides a sentence into clusters of words which in turn are transformed into members of a taxonomy of algebraic structures. The algebraic structures must comply properties of Abelian groups. Methodologically, an incremental prototyping approach has been applied to develop a satisfactory architecture that can be adapted to any language. A special case is studied, this deals with the Spanish language. The developed abstract system is a framework that permits to implements applications that convert unstructured textual information to structured information, this can be useful in contexts such as Natural Language Generation, Data Mining, dynamically generation of theories, among others.

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Chasing language through the brain: Successive parallel networks

Cited by 8 publications

References 74 publications

Speech-related auditory salience detection in the posterior superior temporal region

Speech-related auditory salience detection in the posterior superior temporal region

A System for Converting and Recovering Texts Managed as Structured Information

An Abstract System for Converting and Recovering Texts like Structured Information

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