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Electrophysiology of Word Learning
Capacity to quickly acquire new words and learn language makes us who we are—communicating human beings. With modern brain research methodologies, we...
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Immediate word recall in cognitive assessment can predict dementia using machine learning techniques
BackgroundDementia, one of the fastest-growing public health problems, is a cognitive disorder known to increase in prevalence as age increases....
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Predicting progress in word learning for children with autism and minimal verbal skills
BackgroundApproximately 30% of children diagnosed with autism remain minimally verbal past age 5. Interventions are often effective in increasing...
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Interlinguistic conflict: Word–word Stroop with first and second language colour words
The congruency (or Stroop) effect is a standard observation of slower and less accurate colour identification to incongruent trials (e.g. “red” in...
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Electrical stimulation of the cerebellum facilitates automatic but not controlled word retrieval
Recent research has indicated that the cerebellum is engaged in language functions, yet the role of the cerebellum in lexical-semantic memory is...
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The Nonspecific Positive Actions of Direct Current Transcranial Electrical Stimulation on Novel Word Acquisition
The effects of transcranial electrical stimulation (TES) of the brain on word learning were addressed in a large-scale study in 288 people. The study...
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Irregular word reading as a marker of semantic decline in Alzheimer’s disease: implications for premorbid intellectual ability measurement
BackgroundIrregular word reading has been used to estimate premorbid intelligence in Alzheimer’s disease (AD) dementia. However, reading models...
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Habituation of Brain Activity with Repetition in Color and Picture–Word Stroop Tests
As a widely used mental task for functional near-infrared spectroscopy (fNIRS), the original color–word Stroop task has the advantage of being...
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The structure correspondence hypothesis predicts how word and sentence in language correlate with term and principle in mathematics
The association between language and mathematics is an important debated topic. Here, we proposed a structure correspondence hypothesis to explain...
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Map** the unique neural engagement in deaf individuals during picture, word, and sign language processing: fMRI study
Employing functional magnetic resonance imaging (fMRI) techniques, we conducted a comprehensive analysis of neural responses during sign language,...
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Word imageability influences the emotionality effect in episodic memory
This study examines how and to what extent imageability influences the effect of word emotionality in episodic memory. A total of 52 young adults...
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A multi-study examination of the role of repeated spaced retrieval in the word learning of children with developmental language disorder
BackgroundMany children with developmental language disorders (DLD) have well-documented weaknesses in vocabulary. In recent years, investigators...
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Big data and deep learning for RNA biology
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries....
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Motor learning and performance in schizophrenia and aging: two different patterns of decline
Psychomotor slowing has consistently been observed in schizophrenia, however research on motor learning in schizophrenia is limited. Additionally,...
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Word learning reveals white matter plasticity in preschool children
Word learning plays a central role in language development and is a key predictor for later academic success. The underlying neural basis of...
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The Role of the Human Cerebellum for Learning from and Processing of External Feedback in Non-Motor Learning: A Systematic Review
This review aimed to systematically identify and comprehensively review the role of the cerebellum in performance monitoring, focusing on learning...
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Rapid acquisition of novel written word-forms: ERP evidence
BackgroundNovel word acquisition is generally believed to be a rapid process, essential for ensuring a flexible and efficient communication system;...
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Self-supervised learning in medicine and healthcare
The development of medical applications of machine learning has required manual annotation of data, often by medical experts. Yet, the availability...
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Distinct reinforcement learning profiles distinguish between language and attentional neurodevelopmental disorders
BackgroundTheoretical models posit abnormalities in cortico-striatal pathways in two of the most common neurodevelopmental disorders (Developmental...
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A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
During the diagnostic process, clinicians leverage multimodal information, such as the chief complaint, medical images and laboratory test results....
