ArticleCortex; a journal devoted to the study of the nervous system and behavior2016
Resting-state low-frequency fluctuations reflect individual differences in spoken language learning.
Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 55 citations in OpenAlex.
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- Brain connectivity patterns associated with individual differences in the access to experience-near personal semantics: a resting-state fMRI study.Cognitive, affective & behavioral neuroscience · 2024Article
- Functional connectivity across the human subcortical auditory system using an autoregressive matrix-Gaussian copula graphical model approach with partial correlations.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Greater neural pattern similarity to the native language is associated with better novel word learning.Frontiers in psychology · 2024Article
- Resting-state functional alterations in patients with brain arteriovenous malformations involving language areas.Human brain mapping · 2023Article
- Intrinsic hippocampal connectivity is associated with individual differences in retrospective duration processing.Brain structure & function · 2023Article
- The Hong Kong Grocery Shopping Dialog Task (HK-GSDT): A Quick Screening Test for Neurocognitive Disorders.International journal of environmental research and public health · 2022Article
- Altered Cerebellum Spontaneous Activity in Juvenile Autism Spectrum Disorders Associated with Clinical Traits.Journal of autism and developmental disorders · 2022Article
- Language and nonlanguage factors in foreign language learning: evidence for the learning condition hypothesis.NPJ science of learning · 2021Article
- Neural Fingerprints Underlying Individual Language Learning Profiles.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Task-induced brain functional connectivity as a representation of schema for mediating unsupervised and supervised learning dynamics in language acquisition.Brain and behavior · 2021Article
- Emerging native-similar neural representations underlie non-native speech category learning success.Neurobiology of language (Cambridge, Mass.) · 2021Article
- Examining Individual Differences in Language Learning: A Neurocognitive Model of Language Aptitude.Neurobiology of language (Cambridge, Mass.) · 2021Article
- Abnormal Static and Dynamic Local-Neural Activity in COPD and Its Relationship With Pulmonary Function and Cognitive Impairments.Frontiers in human neuroscience · 2020Article
- A machine learning investigation of volumetric and functional MRI abnormalities in adults born preterm.Human brain mapping · 2019Article
- The development of brain functional connectivity networks revealed by resting-state functional magnetic resonance imaging.Neural regeneration research · 2019Article
- Time-evolving dynamics in brain networks forecast responses to health messaging.Network neuroscience (Cambridge, Mass.) · 2019Article
- Multimodal cortical and hippocampal prediction of episodic-memory plasticity in young and older adults.Human brain mapping · 2018Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
A major challenge in language learning studies is to identify objective, pre-training predictors of success. Variation in the low-frequency fluctuations (LFFs) of spontaneous brain activity measured by resting-state functional magnetic resonance imaging (RS-fMRI) has been found to reflect individual differences in cognitive measures. In the present study, we aimed to investigate the extent to which initial spontaneous brain activity is related to individual differences in spoken language learning. We acquired RS-fMRI data and subsequently trained participants on a sound-to-word learning paradigm in which they learned to use foreign pitch patterns (from Mandarin Chinese) to signal word meaning. We performed amplitude of spontaneous low-frequency fluctuation (ALFF) analysis, graph theory-based analysis, and independent component analysis (ICA) to identify functional components of the LFFs in the resting-state. First, we examined the ALFF as a regional measure and showed that regional ALFFs in the left superior temporal gyrus were positively correlated with learning performance, whereas ALFFs in the default mode network (DMN) regions were negatively correlated with learning performance. Furthermore, the graph theory-based analysis indicated that the degree and local efficiency of the left superior temporal gyrus were positively correlated with learning performance. Finally, the default mode network and several task-positive resting-state networks (RSNs) were identified via the ICA. The "competition" (i.e., negative correlation) between the DMN and the dorsal attention network was negatively correlated with learning performance. Our results demonstrate that a) spontaneous brain activity can predict future language learning outcome without prior hypotheses (e.g., selection of regions of interest--ROIs) and b) both regional dynamics and network-level interactions in the resting brain can account for individual differences in future spoken language learning success.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.