scholarly journals The language system in the human mind and brain

2020 ◽  
Vol 19 (2) ◽  
pp. 1-4
Author(s):  
Paloma Batista Cardoso

In this text, we review the conference given by Evelina Fedorenko, entitled "The language system in the human mind and brain", given on May 6th, 2020 as part of the activities of the Abralin live event - linguists online. In her speech, the referred researcher discusses language processing, considering its physiological and cognitive aspects. Fedorenko defends the existence of the language network, which encompasses the surface of the frontal, temporal and parietal cortex; which function is language processing. This region of the brain responds, with a major or minor degree of intensity; to semantic and syntactic stimuli to compose meanings that are acceptable to speakers.

Author(s):  
Jack M. Gorman

Some scientists now argue that humans are really not superior to other species, including our nearest genetic neighbors, chimpanzees and bonobos. Indeed, those animals seem capable of many things previously thought to be uniquely human, including a sense of the future, empathy, depression, and theory of mind. However, it is clear that humans alone produce speech, dominate the globe, and have several brain diseases like schizophrenia. There are three possible sources within the brain for these differences in brain function: in the structure of the brain, in genes coding for proteins in the brain, and in the level of expression of genes in the brain. There is evidence that all three are the case, giving us a place to look for the intersection of the human mind and brain: the expression of genes within neurons of the prefrontal cortex.


2009 ◽  
Vol 63 (2) ◽  
pp. 102-115
Author(s):  
Luco van den Brom

Developments in medical technology summon the image of a novel ‘bionic’ humanity of the cyborg. Is it possible to entirely reproduce human beings and retain their identity? This technological enhancement aims at improving the physical make-up of the human phenomenon as an individual. Mankind thus assumes control over their mental evolution, creating a techno-sapiens. This prompts the question whether religious faith, emotion, intention or responsibility are physiological reproducible. Experiments with a ‘God Machine’ seem to evoke religious impressions and to deny the individual meaning of God and the human mind. Hick’s dualism of mind and brain as dancing partners is unsuccessful by actually personalizing the brain. This article proposes to describe mental and brain functions as complementary instead of tracing their physiological origin. Then, religious faith is not reduced to fides quae, as merely physiological reproducible information, but remains an existential attitude to life, as fides qua, by itself within the context of a community of believers.


1968 ◽  
Vol 1 ◽  
pp. 160-180
Author(s):  
R. J. Hirst

Life Science Library now claims to examine ‘the most complex of all biological organs: the human mind’, and scientists quite commonly make no distinction between mind and brain — they delight in talking about the brain classifying, decoding, perceiving, deciding or giving orders. And while resisting the conceptual muddle involved in talking of the brain doing what persons do, the identity hypothesis tries to provide a philosophically respectable basis for the equation of mind and brain, maintaining that ‘mind’ is just a term for a group of activities and dispositions, and that these in turn are in some sense to be identified with brain activities or traces. On the other hand, from the point of view of religion and traditional philosophy the suggestion is completely unplausible — creative or inventive thought, and aesthetic, moral or religious experiences seem so far removed from mechanical or physiological processes that a good deal of softening up is necessary if any kind of identity theory is to get a fair hearing. This softening up is best carried out by considering the difficulties in the main rival philosophical view, interactionism.


2017 ◽  
Vol 29 (10) ◽  
pp. 1755-1765 ◽  
Author(s):  
Andrew C. Papanicolaou ◽  
Marina Kilintari ◽  
Roozbeh Rezaie ◽  
Shalini Narayana ◽  
Abbas Babajani-Feremi

The results of this magnetoencephalography study challenge two long-standing assumptions regarding the brain mechanisms of language processing: First, that linguistic processing proper follows sensory feature processing effected by bilateral activation of the primary sensory cortices that lasts about 100 msec from stimulus onset. Second, that subsequent linguistic processing is effected by left hemisphere networks outside the primary sensory areas, including Broca's and Wernicke's association cortices. Here we present evidence that linguistic analysis begins almost synchronously with sensory, prelinguistic verbal input analysis and that the primary cortices are also engaged in these linguistic analyses and become, consequently, part of the left hemisphere language network during language tasks. These findings call for extensive revision of our conception of linguistic processing in the brain.


Author(s):  
Morten H. Christiansen ◽  
Nick Chater

AbstractMemory is fleeting. New material rapidly obliterates previous material. How, then, can the brain deal successfully with the continual deluge of linguistic input? We argue that, to deal with this “Now-or-Never” bottleneck, the brain must compress and recode linguistic input as rapidly as possible. This observation has strong implications for the nature of language processing: (1) the language system must “eagerly” recode and compress linguistic input; (2) as the bottleneck recurs at each new representational level, the language system must build a multilevel linguistic representation; and (3) the language system must deploy all available information predictively to ensure that local linguistic ambiguities are dealt with “Right-First-Time”; once the original input is lost, there is no way for the language system to recover. This is “Chunk-and-Pass” processing. Similarly, language learning must also occur in the here and now, which implies that language acquisition is learning to process, rather than inducing, a grammar. Moreover, this perspective provides a cognitive foundation for grammaticalization and other aspects of language change. Chunk-and-Pass processing also helps explain a variety of core properties of language, including its multilevel representational structure and duality of patterning. This approach promises to create a direct relationship between psycholinguistics and linguistic theory. More generally, we outline a framework within which to integrate often disconnected inquiries into language processing, language acquisition, and language change and evolution.


2020 ◽  
Author(s):  
Aniketh Janardhan Reddy ◽  
Leila Wehbe

AbstractWe are far from having a complete mechanistic understanding of the brain computations involved in language processing and of the role that syntax plays in those computations. Most language studies do not computationally model syntactic structure, and most studies that do model syntactic processing use effort-based metrics. These metrics capture the effort needed to process the syntactic information given by every word [9, 10, 25]. They can reveal where in the brain syntactic processing occurs, but not what features of syntax are processed by different brain regions. Here, we move beyond effort-based metrics and propose explicit features capturing the syntactic structure that is incrementally built while a sentence is being read. Using these features and functional Magnetic Resonance Imaging (fMRI) recordings of participants reading a natural text, we study the brain representation of syntax. We find that our syntactic structure-based features are better than effort-based metrics at predicting brain activity in various parts of the language system. We show evidence of the brain representation of complex syntactic information such as phrase and clause structures. We see that regions well-predicted by syntactic features are distributed in the language system and are not distinguishable from those processing semantics. Our results call for a shift in the approach used for studying syntactic processing.


2021 ◽  
Vol 75 (1) ◽  
pp. 66-71
Author(s):  
Zh. Ibrayeva ◽  

The use of two or more languages is common in most countries of the world. However, until recently, bilingualism was considered as a factor that complicates the processing of speech, cognition and the brain. In the past 25 years there have been a surge in research on bilingualism, including the study, mastery and processing of languages, their cognitive and neural foundations, and the lifelong implications of bilingualism for cognition and the brain. Contrary to the belief that bilingualism complicates the language system, new research demonstrates that all known and used languages ​​become part of the same language system. The interactions that occur when using the two languages ​​have consequences for mind and the brain and indeed for language processing itself but these implications are not additive. Thus, bilingualism helps to uncover the fundamental architecture and language processing mechanisms that locates differently in monolingual speakers.


2020 ◽  
Author(s):  
Micha Heilbron ◽  
Kristijan Armeni ◽  
Jan-Mathijs Schoffelen ◽  
Peter Hagoort ◽  
Floris P. de Lange

AbstractUnderstanding spoken language requires transforming ambiguous stimulus streams into a hierarchy of increasingly abstract representations, ranging from speech sounds to meaning. It has been suggested that the brain uses predictive computations to guide the interpretation of incoming information. However, the exact role of prediction in language understanding remains unclear, with widespread disagreement about both the ubiquity of prediction, and the level of representation at which predictions unfold. Here, we address both issues by analysing brain recordings of participants listening to audiobooks, and using a state-of-the-art deep neural network (GPT-2) to quantify predictions in a fine-grained, contextual fashion. First, we establish clear evidence for predictive processing, confirming that brain responses to words are modulated by probabilistic predictions. Next, we factorised the model-based predictions into distinct linguistic dimensions, revealing dissociable neural signatures of syntactic, phonemic and semantic predictions. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting theories of hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, and demonstrate that linguistic prediction is not implemented by a single system but occurs throughout the language network, forming a hierarchy of linguistic predictions across all levels of analysis.


2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.


Author(s):  
Riitta Salmelin ◽  
Jan Kujala ◽  
Mia Liljeström

When seeking to uncover the brain correlates of language processing, timing and location are of the essence. Magnetoencephalography (MEG) offers them both, with the highest sensitivity to cortical activity. MEG has shown its worth in revealing cortical dynamics of reading, speech perception, and speech production in adults and children, in unimpaired language processing as well as developmental and acquired language disorders. The MEG signals, once recorded, provide an extensive selection of measures for examination of neural processing. Like all other neuroimaging tools, MEG has its own strengths and limitations of which the user should be aware in order to make the best possible use of this powerful method and to generate meaningful and reliable scientific data. This chapter reviews MEG methodology and how MEG has been used to study the cortical dynamics of language.


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