Collateral Inhibition of Transcallosal Activity Facilitates Functional Brain Asymmetry

The corpus callosum is the largest connection between the functionally asymmetric cerebral hemispheres. The objective of this study was to measure functional activity of callosal fiber tracts during speech processing. We analyzed the regional glucose metabolism of the corpus callosum and of speech-relevant cortical areas in 10 normal individuals at rest and during word repetition. We used three-dimensionally registered magnetic resonance imaging to visualize the individual brain morphology and high-resolution positron emission tomography for metabolic measurements. The task-induced metabolic changes of the callosal midbody and isthmus had a significant negative correlation with key regions of language processing in the left inferior frontal cortex (Brodmann's area 44) and in the right superior temporal cortex (Brodmann's area 22) (e.g., correlation of metabolic changes in the surface aspects of the right Brodmann's area 22 and the callosal midbody/isthmus: r = −0.91, P < 0.001). The study indicates that language processing in asymmetrically organized cortical areas inhibits the reciprocal transcallosal information exchange in favor of the lateralized mental operation. Our data agree with anatomic, electrophysiologic, and pharmacologic experiments that point to the important role of collateral inhibition for the transcallosal information exchange.

Download Full-text

Task-Dependent Modulation of Regions in the Left Inferior Frontal Cortex during Semantic Processing

Journal of Cognitive Neuroscience ◽

10.1162/08989290152541485 ◽

2001 ◽

Vol 13 (6) ◽

pp. 829-843 ◽

Cited By ~ 177

Author(s):

A. L. Roskies ◽

J. A. Fiez ◽

D. A. Balota ◽

M. E. Raichle ◽

S. E. Petersen

Keyword(s):

Frontal Cortex ◽

Language Processing ◽

Semantic Processing ◽

Semantic Analysis ◽

Lexical Processing ◽

Temporal Cortex ◽

Dependent Manner ◽

Inferior Frontal Cortex ◽

Semantic Judgment ◽

The Right

To distinguish areas involved in the processing of word meaning (semantics) from other regions involved in lexical processing more generally, subjects were scanned with positron emission tomography (PET) while performing lexical tasks, three of which required varying degrees of semantic analysis and one that required phonological analysis. Three closely apposed regions in the left inferior frontal cortex and one in the right cerebellum were significantly active above baseline in the semantic tasks, but not in the nonsemantic task. The activity in two of the frontal regions was modulated by the difficulty of the semantic judgment. Other regions, including some in the left temporal cortex and the cerebellum, were active across all four language tasks. Thus, in addition to a number of regions known to be active during language processing, regions in the left inferior frontal cortex were specifically recruited during semantic processing in a task-dependent manner. A region in the right cerebellum may be functionally related to those in the left inferior frontal cortex. Discussion focuses on the implications of these results for current views regarding neural substrates of semantic processing.

Download Full-text

Language in the Right Cerebral Hemisphere: Contributions from Reading Studies

Physiology ◽

10.1152/nips.01454.2003 ◽

2003 ◽

Vol 18 (6) ◽

pp. 257-261 ◽

Cited By ~ 2

Author(s):

Kirsten I. Taylor ◽

Marianne Regard

Keyword(s):

Corpus Callosum ◽

Language Processing ◽

Epileptic Seizure ◽

Cerebral Hemisphere ◽

Word Meaning ◽

Half Century ◽

Right Cerebral Hemisphere ◽

The Right ◽

Cortical Functions

Evidence for a right hemispheric involvement in language processing, in particular at the level of word meaning, has emerged within the last half century. Hemispheric functional specializations are dynamic; right hemispheric language participation significantly increases under certain conditions, such as during an epileptic seizure and during recovery from stroke. Interhemispheric connections via the corpus callosum critically mediate these and other higher cortical functions.

Download Full-text

The Brain Basis of Language Processing: From Structure to Function

Physiological Reviews ◽

10.1152/physrev.00006.2011 ◽

2011 ◽

Vol 91 (4) ◽

pp. 1357-1392 ◽

Cited By ~ 734

Author(s):

Angela D. Friederici

Keyword(s):

Language Processing ◽

Right Hemisphere ◽

Structural Connectivity ◽

Temporal Cortex ◽

Brain Regions ◽

Posterior Portion ◽

Language Functions ◽

Marker Studies ◽

The Right ◽

The Brain

Language processing is a trait of human species. The knowledge about its neurobiological basis has been increased considerably over the past decades. Different brain regions in the left and right hemisphere have been identified to support particular language functions. Networks involving the temporal cortex and the inferior frontal cortex with a clear left lateralization were shown to support syntactic processes, whereas less lateralized temporo-frontal networks subserve semantic processes. These networks have been substantiated both by functional as well as by structural connectivity data. Electrophysiological measures indicate that within these networks syntactic processes of local structure building precede the assignment of grammatical and semantic relations in a sentence. Suprasegmental prosodic information overtly available in the acoustic language input is processed predominantly in a temporo-frontal network in the right hemisphere associated with a clear electrophysiological marker. Studies with patients suffering from lesions in the corpus callosum reveal that the posterior portion of this structure plays a crucial role in the interaction of syntactic and prosodic information during language processing.

Download Full-text

Artificial Grammar Learning and Its Neurobiology in Relation to Language Processing and Development

The Oxford Handbook of Psycholinguistics ◽

10.1093/oxfordhb/9780198786825.013.33 ◽

2018 ◽

pp. 754-783

Author(s):

Julia Uddén ◽

Claudia Männel

Keyword(s):

Language Acquisition ◽

Language Processing ◽

Temporal Cortex ◽

Systematic Investigation ◽

Artificial Grammar Learning ◽

Artificial Grammar ◽

Complex Syntax ◽

Grammar Learning ◽

Frontal Operculum ◽

The Right

The artificial grammar learning (AGL) paradigm enables systematic investigation of the acquisition of linguistically relevant structures. It is a paradigm of interest for language processing research, interfacing with theoretical linguistics, and for comparative research on language acquisition and evolution. This chapter presents a key for understanding major variants of the paradigm. An unbiased summary of neuroimaging findings of AGL is presented, using meta-analytic methods, pointing to the crucial involvement of the bilateral frontal operculum and regions in the right lateral hemisphere. Against a background of robust posterior temporal cortex involvement in processing complex syntax, the evidence for involvement of the posterior temporal cortex in AGL is reviewed. Infant AGL studies testing for neural substrates are reviewed, covering the acquisition of adjacent and non-adjacent dependencies as well as algebraic rules. The language acquisition data suggest that comparisons of learnability of complex grammars performed with adults may now also be possible with children.

Download Full-text

Artifical grammar learning and its neurobiology in relation to language processing and development

10.31234/osf.io/fdt69 ◽

2017 ◽

Author(s):

Julia Udden ◽

Claudia Männel

Keyword(s):

Language Acquisition ◽

Language Processing ◽

Comparative Research ◽

Temporal Cortex ◽

Neural Substrates ◽

Systematic Investigation ◽

Complex Syntax ◽

Grammar Learning ◽

Frontal Operculum ◽

The Right

The artificial grammar learning (AGL) paradigm enables systematic investigation of the acquisition of linguistically relevant structures. It is a paradigm of interest for language processing research, interfacing with theoretical linguistics, and for comparative research on language acquisition and evolution. We present a key for understanding major variants of the paradigm. An unbiased summary of neuroimaging findings of AGL is presented, using meta-analytic methods, pointing to the crucial involvement of the bilateral frontal operculum and regions in the right lateral hemisphere. Against a background of robust posterior temporal cortex involvement in processing complex syntax, we review the evidence for involvement of the posterior temporal cortex in AGL. Infant AGL studies testing for neural substrates are reviewed, covering the acquisition of adjacent and non-adjacent dependencies as well as algebraic rules. The language acquisition data suggest that comparisons of learnability of complex grammars performed with adults may now also be possible with children.

Download Full-text

A Tracer Study of ICT Graduate Students at Mzuzu University, Malawi

Mousaion ◽

10.25159/2663-659x/5227 ◽

2019 ◽

Vol 36 (3) ◽

Author(s):

Chimango Nyasulu ◽

Winner Chawinga ◽

George Chipeta

Keyword(s):

Language Processing ◽

Mobile Application ◽

First Century ◽

Application Development ◽

Job Requirements ◽

Level Of Satisfaction ◽

Information And Communication ◽

Quantitative Design ◽

The Right ◽

The University

Governments the world over are increasingly challenging universities to produce human resources with the right skills sets and knowledge required to drive their economies in this twenty-first century. It therefore becomes important for universities to produce graduates that bring tangible and meaningful contributions to the economies. Graduate tracer studies are hailed to be one of the ways in which universities can respond and reposition themselves to the actual needs of the industry. It is against this background that this study was conducted to establish the relevance of the Department of Information and Communication Technology at Mzuzu University to the Malawian economy by systematically investigating occupations of its former students after graduating from the University. The study adopted a quantitative design by distributing an online-based questionnaire with predominantly closed-ended questions. The study focused on three key objectives: to identify key employing sectors of ICT graduates, to gauge the relevance of the ICT programme to its former students’ jobs and businesses, and to establish the level of satisfaction of the ICT curriculum from the perspectives of former ICT graduates. The key findings from the study are that the ICT programme is relevant to the industry. However, some respondents were of the view that the curriculum should be strengthened by revising it through an addition of courses such as Mobile Application Development, Machine Learning, Natural Language Processing, Data Mining, and LINUX Administration to keep abreast with the ever-changing ICT trends and job requirements. The study strongly recommends the need for regular reviews of the curriculum so that it is continually responding to and matches the needs of the industry.

Download Full-text

A Machine Learning Application for Raising WASH Awareness in the Times of COVID-19 Pandemic (Preprint)

10.2196/preprints.25320 ◽

2020 ◽

Cited By ~ 1

Author(s):

Rohan Pandey ◽

Vaibhav Gautam ◽

Ridam Pal ◽

Harsh Bandhey ◽

Lovedeep Singh Dhingra ◽

...

Keyword(s):

Machine Learning ◽

Natural Language Processing ◽

Natural Language ◽

Machine Translation ◽

Language Processing ◽

User Feedback ◽

Who Guidelines ◽

The Times ◽

The Right ◽

Local Languages

BACKGROUND The COVID-19 pandemic has uncovered the potential of digital misinformation in shaping the health of nations. The deluge of unverified information that spreads faster than the epidemic itself is an unprecedented phenomenon that has put millions of lives in danger. Mitigating this ‘Infodemic’ requires strong health messaging systems that are engaging, vernacular, scalable, effective and continuously learn the new patterns of misinformation. OBJECTIVE We created WashKaro, a multi-pronged intervention for mitigating misinformation through conversational AI, machine translation and natural language processing. WashKaro provides the right information matched against WHO guidelines through AI, and delivers it in the right format in local languages. METHODS We theorize (i) an NLP based AI engine that could continuously incorporate user feedback to improve relevance of information, (ii) bite sized audio in the local language to improve penetrance in a country with skewed gender literacy ratios, and (iii) conversational but interactive AI engagement with users towards an increased health awareness in the community. RESULTS A total of 5026 people who downloaded the app during the study window, among those 1545 were active users. Our study shows that 3.4 times more females engaged with the App in Hindi as compared to males, the relevance of AI-filtered news content doubled within 45 days of continuous machine learning, and the prudence of integrated AI chatbot “Satya” increased thus proving the usefulness of an mHealth platform to mitigate health misinformation. CONCLUSIONS We conclude that a multi-pronged machine learning application delivering vernacular bite-sized audios and conversational AI is an effective approach to mitigate health misinformation. CLINICALTRIAL Not Applicable

Download Full-text

Auditory cortical micro-networks show differential connectivity during voice and speech processing in humans

Communications Biology ◽

10.1038/s42003-021-02328-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Florence Steiner ◽

Marine Bobin ◽

Sascha Frühholz

Keyword(s):

Speech Processing ◽

Neural Circuits ◽

Brain Activity ◽

Inhibitory Pathways ◽

Ac Networks ◽

Directional Connectivity ◽

The Right ◽

Voice Processing ◽

Differential Connectivity ◽

Voice And Speech

AbstractThe temporal voice areas (TVAs) in bilateral auditory cortex (AC) appear specialized for voice processing. Previous research assumed a uniform functional profile for the TVAs which are broadly spread along the bilateral AC. Alternatively, the TVAs might comprise separate AC nodes controlling differential neural functions for voice and speech decoding, organized as local micro-circuits. To investigate micro-circuits, we modeled the directional connectivity between TVA nodes during voice processing in humans while acquiring brain activity using neuroimaging. Results show several bilateral AC nodes for general voice decoding (speech and non-speech voices) and for speech decoding in particular. Furthermore, non-hierarchical and differential bilateral AC networks manifest distinct excitatory and inhibitory pathways for voice and speech processing. Finally, while voice and speech processing seem to have distinctive but integrated neural circuits in the left AC, the right AC reveals disintegrated neural circuits for both sounds. Altogether, we demonstrate a functional heterogeneity in the TVAs for voice decoding based on local micro-circuits.

Download Full-text