According to prediction-based accounts of language comprehension, incoming contextual information is constantly used to guide the pre-activation of the most probable continuations to the unfolding sentences. However, there is still scarce evidence of the build-up of these predictions during sentence comprehension. Using event-related brain potentials, we investigated sustained processes associated to semantic prediction during online sentence comprehension. To address this, participants read sentences with varying levels of contextual constraint one word at a time. A 1000 ms interval preceded the final word, which could be congruent or incongruent. A slow sustained negativity developed gradually over the course of sentences, showing differences across conditions, with increasingly larger amplitudes for high than low levels of constraint. The effect was maximal in the interval preceding the closing word. This interval elicited a left-dominant slow negative potential with a graded amplitude modulation to contextual constraint, replicating previous results in speech comprehension. We argue that these slow potentials index the engagement of cognitive operations associated to semantic prediction. In addition, we replicated the finding of an earlier onset of the N400 effect (incongruent minus congruent) for high relative to low contextual constraint, suggesting facilitated processing for contextually-supported and highly expected words. Altogether, these results are consistent with prediction-based models of language comprehension and they also strengthen the value of investigating slow components as potential indices of mechanisms linked to language prediction.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.neuroimage.2019.01.005 | DOI Listing |
Diabetes Metab Res Rev
January 2025
Rush Alzheimer's Disease Centre, Rush University Medical Center, Chicago, Illinois, USA.
Diabetes increases the risk of dementia, and insulin resistance (IR) has emerged as a potential unifying feature. Here, we review published findings over the past 2 decades on the relation of diabetes and IR to brain health, including those related to cognition and neuropathology, in the Religious Orders Study, the Rush Memory and Aging Project, and the Minority Aging Research Study (ROS/MAP/MARS), three harmonised cohort studies of ageing and dementia at the Rush Alzheimer's Disease Center (RADC). A wide range of participant data, including information on medical conditions such as diabetes and neuropsychological tests, as well as other clinical and laboratory-based data collected annually.
View Article and Find Full Text PDFMult Scler
January 2025
Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
The past 25 years have brought extraordinary advances in our understanding of MS pathogenesis and the subsequent development of effective therapies. Collaborative genetics efforts have uncovered the association of 236 common DNA variants with disease susceptibility and the first association with disease severity, paving the way to more effective therapies, particularly for progressive forms of the disease. In parallel, and in addition to established environmental disease triggers or modifiers, new collaborative work has revealed new associations with components of the gut microbiome.
View Article and Find Full Text PDFBehav Res Methods
January 2025
CogNosco Lab, Department of Psychology and Cognitive Sciences, University of Trento, Trento, Italy.
We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically validated lexicons for detecting the eight emotions in Plutchik's theory. We show that EmoAtlas can match or surpass transformer-based natural language processing techniques, BERT or large language models like ChatGPT 3.
View Article and Find Full Text PDFSci Rep
January 2025
Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE, Minzu University of China, Beijing, 100081, China.
Aspect Category Sentiment Analysis (ACSA) is a fine-grained sentiment analysis task aimed at predicting the sentiment polarity associated with aspect categories within a sentence.Most existing ACSA methods are based on a given aspect category to locate sentiment words related to it. When irrelevant sentiment words have semantic meaning for the given aspect category, it may cause the problem that sentiment words cannot be matched with aspect categories.
View Article and Find Full Text PDFJ Gerontol B Psychol Sci Soc Sci
January 2025
Herbert and Jacqueline Krieger Klein Alzheimer's Research Center, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
Objectives: The oldest old adults (90+) constitute the fastest growing demographic at highest dementia risk among older adults. Depression, a common risk factor, inherently presents with heterogeneous clinical manifestations. Here, we explored the associations of the predominant depression dimensions with cognition in the LifeAfter90 study.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!