scholarly journals P.066 Hemispheric Reorganization of Functional Language Networks Following Neonatal Stroke Supports Language Outcome

2021 ◽  
Vol 48 (s3) ◽  
pp. S38-S38
Author(s):  
Z Emami ◽  
BT Dunkley ◽  
A Robertson ◽  
R Westmacott ◽  
P Krishnan ◽  
...  
Keyword(s):  
Language Processing ◽  
Time Window ◽  
Cross Sectional Study ◽  
Functional Language ◽  
Arterial Ischemic Stroke ◽  
Cross Sectional ◽  
Language Outcome ◽  
Classical Language ◽  
Language Areas ◽  
Language Network

Background: Neonatal Arterial Ischemic Stroke (NAIS) is a common form of paediatric stroke often affecting classical language areas. The post-stroke reorganization of functional language networks may provide insight into later-emerging language deficits and may help to identify at-risk children with NAIS. Methods: A cross-sectional study of fourteen children with left (n=8; 2M; 11.1±2.2 years) or right (n=6; 3M; 12.4±4 years) middle cerebral artery (MCA) NAIS, as well as seven neurotypical children (5M; 13.4±2.7 years), was conducted. Children listened to correct/incorrect syntactic sentences while MEG was recorded, and task-related functional connectivity in the time window and frequency band of interest was determined. Language outcomes were assessed using a battery of neuropsychological tests. Results: A network-based analysis of syntactic language processing (4-7 Hz, 1.2-1.4s) revealed a dysfunctional bilateral frontal-temporal network involving language areas in patients (p=0.01). Patients with right-MCA stroke exhibited a positive correlation between left hemispheric connectivity and measures of language skill (p<0.01), resembling the neurotypical children. In left-MCA stroke patients, greater bilateral connectivity or right laterality in the language network is correlated with good outcome (p<0.05). Conclusions: Depending on the hemispheric location of stroke, certain patterns of language network reorganization may account for impairments in a bilateral frontal-temporal language subnetwork and support language outcome.

scholarly journals Sentence Reading: A Functional MRI Study at 4 Tesla

1997 ◽  
Vol 9 (5) ◽  
pp. 664-686 ◽  
Author(s):  
D. Bavelier ◽  
D. Corina ◽  
P. Jezzard ◽  
S. Padmanabhan ◽  
V. P. Clark ◽  
...  
Keyword(s):  
Language Processing ◽  
Word Processing ◽  
Blood Oxygenation ◽  
Anterior Portion ◽  
Individual Subject ◽  
Sentence Reading ◽  
Wernicke’S Area ◽  
Classical Language ◽  
Mri Study ◽  
Language Areas

In this study, changes in blood oxygenation and volume were monitored while monolingual right-handed subjects read English sentences. Our results confirm the role of the left peri-sylvian cortex in language processing. Interestingly, individual subject analyses reveal a pattern of activation characterized by several small, limited patches rather than a few large, anatomically well-circumscribed centers. Between-subject analyses confirm a lateralized pattern of activation and reveal active classical language areas including Broca's area, Wernicke's area, and the angular gyms. In addition they point to areas only more recently considered as language-relevant including the anterior portion of the superior temporal sulcus. This area has not been reliably observed in imaging studies of isolated word processing. This raises the hypothesis that activation in this area is dependent on processes specific to sentence reading.

Evaluation of macrolinguistic aspects of the oral discourse in patients with Alzheimer’s disease

2018 ◽  
Vol 31 (9) ◽  
pp. 1343-1353 ◽  
Author(s):  
Juliana Onofre de Lira ◽  
Thaís Soares Cianciarullo Minett ◽  
Paulo Henrique Ferreira Bertolucci ◽  
Karin Zazo Ortiz
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Language Processing ◽  
Cross Sectional Study ◽  
Oral Discourse ◽  
Cross Sectional ◽  
Cohesive Devices ◽  
Global Coherence ◽  
Comparison Groups ◽  
Study Setting

ABSTRACTIntroduction:Alzheimer’s disease (AD) is a degenerative syndrome that impairs cognitive functioning, including speech and language. Discourse can be used to analyze language processing, which is organized into microlinguistic and macrolinguistic dimensions.Objectives:To identify the occurrence of changes in the macrolinguistic dimension of oral discourse in AD patients. Design: This was developed as a cross-sectional study. Setting: Outpatient clinic of the Behavioural Neurology Division of São Paulo Federal University.Participants:121 elderly patients, with ≥ 4 years of education, divided into AD and comparison groups.Measurements:The subjects were asked to create a narrative based on seven figures that made up a story. The macrolinguistic aspects of the narratives were analyzed.Results:The performance of the AD group was inferior to that of the comparison group on content-related, no-content-related complete and incomplete propositions as well as macropropositions, main information units, appropriated local and global coherence, cohesive devices and all subtypes, cohesive errors and some of their subtypes. Global coherence, macropropositions and ellipsis subtype of cohesive devices were the variables that best differentiated the groups.Conclusions:Changes were observed in most aspects of the macrolinguistic dimension of oral discourse in patients with AD.

scholarly journals Science, healthcare system, and government effectiveness perception and COVID-19 vaccination acceptance and hesitancy in a global sample: an analytical cross-sectional analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e049716
Author(s):  
Timothy D Dye ◽  
Monica Barbosu ◽  
Shazia Siddiqi ◽  
José G Pérez Ramos ◽  
Hannah Murphy ◽  
...  
Keyword(s):  
Language Processing ◽  
Public Perception ◽  
Strong Predictor ◽  
Cross Sectional Study ◽  
Amazon Mechanical Turk ◽  
Cross Sectional ◽  
Vaccine Acceptance ◽  
Vaccination Acceptance ◽  
Sectional Analysis

BackgroundDeterminants of COVID-19 vaccine acceptance are complex; how perceptions of the effectiveness of science, healthcare and government impact personal COVID-19 vaccine acceptance is unclear, despite all three domains providing critical roles in development, funding and provision, and distribution of COVID-19 vaccine.ObjectiveTo estimate impact of perception of science, healthcare systems, and government along with sociodemographic, psychosocial, and cultural characteristics on vaccine acceptance.DesignWe conducted a global nested analytical cross-sectional study of how the perceptions of healthcare, government and science systems have impacted COVID-19 on vaccine acceptance.SettingGlobal Facebook, Instagram and Amazon Mechanical Turk (mTurk) users from 173 countries.Participants7411 people aged 18 years or over, and able to read English, Spanish, Italian, or French.MeasurementsWe used Χ2 analysis and logistic regression-derived adjusted Odds Ratios (aORs) and 95% CIs to evaluate the relationship between effectiveness perceptions and vaccine acceptance controlling for other factors. We used natural language processing and thematic analysis to analyse the role of vaccine-related narratives in open-ended explanations of effectiveness.ResultsAfter controlling for confounding, attitude toward science was a strong predictor of vaccine acceptance, more so than other attitudes, demographic, psychosocial or COVID-19-related variables (aOR: 2.1; 95% CI: 1.8 to 2.5). The rationale for science effectiveness was dominated by vaccine narratives, which were uncommon in other domains.LimitationsThis study did not include participants from countries where Facebook and Amazon mTurk are not available, and vaccine acceptance reflected intention rather than actual behaviour.ConclusionsAs our findings show, vaccine-related issues dominate public perception of science’s impact around COVID-19, and this perception of science relates strongly to the decision to obtain vaccination once available.

scholarly journals Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter

2020 ◽  
pp. 1-8
Author(s):  
Sameh N. Saleh ◽  
Christoph U. Lehmann ◽  
Samuel A. McDonald ◽  
Mujeeb A. Basit ◽  
Richard J. Medford
Keyword(s):  
Language Processing ◽  
Public Perception ◽  
Large Scale ◽  
Community Support ◽  
Cross Sectional Study ◽  
Public Understanding ◽  
Cross Sectional ◽  
Social Distancing ◽  
English Only ◽  
Twitter Users

Abstract Objective: Social distancing policies are key in curtailing severe acute respiratory coronavirus virus 2 (SARS-CoV-2) spread, but their effectiveness is heavily contingent on public understanding and collective adherence. We studied public perception of social distancing through organic, large-scale discussion on Twitter. Design: Retrospective cross-sectional study. Methods: Between March 27 and April 10, 2020, we retrieved English-only tweets matching two trending social distancing hashtags, #socialdistancing and #stayathome. We analyzed the tweets using natural language processing and machine-learning models, and we conducted a sentiment analysis to identify emotions and polarity. We evaluated the subjectivity of tweets and estimated the frequency of discussion of social distancing rules. We then identified clusters of discussion using topic modeling and associated sentiments. Results: We studied a sample of 574,903 tweets. For both hashtags, polarity was positive (mean, 0.148; SD, 0.290); only 15% of tweets had negative polarity. Tweets were more likely to be objective (median, 0.40; IQR, 0–0.6) with ~30% of tweets labeled as completely objective (labeled as 0 in range from 0 to 1). Approximately half of tweets (50.4%) primarily expressed joy and one-fifth expressed fear and surprise. Each correlated well with topic clusters identified by frequency including leisure and community support (ie, joy), concerns about food insecurity and quarantine effects (ie, fear), and unpredictability of coronavirus disease 2019 (COVID-19) and its implications (ie, surprise). Conclusions: Considering the positive sentiment, preponderance of objective tweets, and topics supporting coping mechanisms, we concluded that Twitter users generally supported social distancing in the early stages of their implementation.

scholarly journals Phonological awareness and sinusoidal amplitude modulation in phonological dislexia

2016 ◽  
Vol 74 (4) ◽  
pp. 293-298
Author(s):  
Yolanda Peñaloza-López ◽  
Aline Herrera-Rangel ◽  
Santiago J. Pérez-Ruiz ◽  
Adrián Poblano
Keyword(s):  
Phonological Awareness ◽  
Language Processing ◽  
Amplitude Modulation ◽  
Cross Sectional Study ◽  
Control Group ◽  
Regression Equations ◽  
Cross Sectional ◽  
Learning To Read ◽  
The Mean ◽  
Sinusoidal Amplitude Modulation

ABSTRACT Objective Dyslexia is the difficulty of children in learning to read and write as results of neurological deficiencies. The objective was to test the Phonological awareness (PA) and Sinusoidal amplitude modulation (SAM) threshold in children with Phonological dyslexia (PD). Methods We performed a case-control, analytic, cross sectional study. We studied 14 children with PD and 14 control children from 7 to 11 years of age, by means of PA measurement and by SAM test. The mean age of dyslexic children was 8.39 years and in the control group was 8.15. Results Children with PD exhibited inadequate skills in PA, and SAM. We found significant correlations between PA and SAM at 4 Hertz frequency, and calculated regression equations that predicts between one-fourth and one-third of variance of measurements. Conclusion Alterations in PA and SAM found can help to explain basis of deficient language processing exhibited by children with PD.

scholarly journals Extracting Clinical Features From Dictated Ambulatory Consult Notes Using a Commercially Available Natural Language Processing Tool: Pilot, Retrospective, Cross-Sectional Validation Study (Preprint)

2018 ◽  
Author(s):  
Jeremy Petch ◽  
Jane Batt ◽  
Joshua Murray ◽  
Muhammad Mamdani
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Clinical Features ◽  
Language Processing ◽  
A Priori ◽  
Cross Sectional Study ◽  
Free Text ◽  
Cross Sectional ◽  
Text Data ◽  
Complex Features

BACKGROUND The increasing adoption of electronic health records (EHRs) in clinical practice holds the promise of improving care and advancing research by serving as a rich source of data, but most EHRs allow clinicians to enter data in a text format without much structure. Natural language processing (NLP) may reduce reliance on manual abstraction of these text data by extracting clinical features directly from unstructured clinical digital text data and converting them into structured data. OBJECTIVE This study aimed to assess the performance of a commercially available NLP tool for extracting clinical features from free-text consult notes. METHODS We conducted a pilot, retrospective, cross-sectional study of the accuracy of NLP from dictated consult notes from our tuberculosis clinic with manual chart abstraction as the reference standard. Consult notes for 130 patients were extracted and processed using NLP. We extracted 15 clinical features from these consult notes and grouped them a priori into categories of simple, moderate, and complex for analysis. RESULTS For the primary outcome of overall accuracy, NLP performed best for features classified as simple, achieving an overall accuracy of 96% (95% CI 94.3-97.6). Performance was slightly lower for features of moderate clinical and linguistic complexity at 93% (95% CI 91.1-94.4), and lowest for complex features at 91% (95% CI 87.3-93.1). CONCLUSIONS The findings of this study support the use of NLP for extracting clinical features from dictated consult notes in the setting of a tuberculosis clinic. Further research is needed to fully establish the validity of NLP for this and other purposes.

scholarly journals Early Crowdfunding Response to the COVID-19 Pandemic: Cross-sectional Study (Preprint)

2020 ◽  
Author(s):  
Sameh Nagui Saleh ◽  
Christoph U Lehmann ◽  
Richard J Medford
Keyword(s):  
United States ◽  
Language Processing ◽  
Early Stage ◽  
Affective Response ◽  
The United States ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Web Based ◽  
Early Signal ◽  
Acute Distress

BACKGROUND As the number of COVID-19 cases increased precipitously in the United States, policy makers and health officials marshalled their pandemic responses. As the economic impacts multiplied, anecdotal reports noted the increased use of web-based crowdfunding to defray these costs. OBJECTIVE We examined the web-based crowdfunding response in the early stage of the COVID-19 pandemic in the United States to understand the incidence of initiation of COVID-19–related campaigns and compare them to non–COVID-19–related campaigns. METHODS On May 16, 2020, we extracted all available data available on US campaigns that contained narratives and were created between January 1 and May 10, 2020, on GoFundMe. We identified the subset of COVID-19–related campaigns using keywords relevant to the COVID-19 pandemic. We explored the incidence of COVID-19–related campaigns by geography, by category, and over time, and we compared the characteristics of the campaigns to those of non–COVID-19–related campaigns after March 11, when the pandemic was declared. We then used a natural language processing algorithm to cluster campaigns by narrative content using overlapping keywords. RESULTS We found that there was a substantial increase in overall GoFundMe web-based crowdfunding campaigns in March, largely attributable to COVID-19–related campaigns. However, as the COVID-19 pandemic persisted and progressed, the number of campaigns per COVID-19 case declined more than tenfold across all states. The states with the earliest disease burden had the fewest campaigns per case, indicating a lack of a case-dependent response. COVID-19–related campaigns raised more money, had a longer narrative description, and were more likely to be shared on Facebook than other campaigns in the study period. CONCLUSIONS Web-based crowdfunding appears to be a stopgap for only a minority of campaigners. The novelty of an emergency likely impacts both campaign initiation and crowdfunding success, as it reflects the affective response of a community. Crowdfunding activity likely serves as an early signal for emerging needs and societal sentiment for communities in acute distress that could be used by governments and aid organizations to guide disaster relief and policy.

Examining second language development using event-related potentials

2013 ◽  
Vol 3 (2) ◽  
pp. 213-232 ◽  
Author(s):  
Alison Gabriele ◽  
Robert Fiorentino ◽  
José Alemán Bañón
Keyword(s):  
Second Language ◽  
Language Processing ◽  
Event Related Potentials ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Second Language Processing ◽  
Advanced Learners ◽  
Number Agreement ◽  
Related Potentials ◽  
Structural Distance

This cross-sectional study examines the role of L1-L2 differences and structural distance in the processing of gender and number agreement by English-speaking learners of Spanish at three different levels of proficiency. Preliminary results show that differences between the L1 and L2 impact L2 development, as sensitivity to gender agreement violations, as opposed to number agreement violations, emerges only in learners at advanced levels of proficiency. Results also show that the establishment of agreement dependencies is impacted by the structural distance between the agreeing elements for native speakers and for learners at intermediate and advanced levels of proficiency but not for low proficiency. The overall pattern of results suggests that the linguistic factors examined here impact development but do not constrain ultimate attainment; for advanced learners, results suggest that second language processing is qualitatively similar to native processing.

scholarly journals Composition is the Core Driver of the Language-selective Network

2020 ◽  
Vol 1 (1) ◽  
pp. 104-134 ◽  
Author(s):  
Francis Mollica ◽  
Matthew Siegelman ◽  
Evgeniia Diachek ◽  
Steven T. Piantadosi ◽  
Zachary Mineroff ◽  
...  
Keyword(s):  
Language Processing ◽  
Word Order ◽  
Blood Oxygen Level Dependent ◽  
Blood Oxygen Level ◽  
Total N ◽  
The Core ◽  
Sentence Level ◽  
Linguistic Input ◽  
Language Areas ◽  
Language Network

The frontotemporal language network responds robustly and selectively to sentences. But the features of linguistic input that drive this response and the computations that these language areas support remain debated. Two key features of sentences are typically confounded in natural linguistic input: words in sentences (a) are semantically and syntactically combinable into phrase- and clause-level meanings, and (b) occur in an order licensed by the language’s grammar. Inspired by recent psycholinguistic work establishing that language processing is robust to word order violations, we hypothesized that the core linguistic computation is composition, and, thus, can take place even when the word order violates the grammatical constraints of the language. This hypothesis predicts that a linguistic string should elicit a sentence-level response in the language network provided that the words in that string can enter into dependency relationships as in typical sentences. We tested this prediction across two fMRI experiments (total N = 47) by introducing a varying number of local word swaps into naturalistic sentences, leading to progressively less syntactically well-formed strings. Critically, local dependency relationships were preserved because combinable words remained close to each other. As predicted, word order degradation did not decrease the magnitude of the blood oxygen level–dependent response in the language network, except when combinable words were so far apart that composition among nearby words was highly unlikely. This finding demonstrates that composition is robust to word order violations, and that the language regions respond as strongly as they do to naturalistic linguistic input, providing that composition can take place.

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