ArticleNeuroImage2022
Predicting response time variability from task and resting-state functional connectivity in the aging brain.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Using connectome-based predictive models to reveal the systems standardized tests and clinical symptoms are reflecting.Nature communications · 2026Article
- Fifteen years on: a review of the Cam-CAN study of the cognitive neuroscience of ageing.GeroScience · 2026Review
- Digital Twin Brain: Generating Multitask Behavior from Connectomes for Personalized Therapy.BME frontiers · 2026Article
- Perceptual Decision Efficiency Is Modifiable and Associated with Decreased Musculoskeletal Injury Risk Among Female College Soccer Players.Brain sciences · 2025Article
- Top-down attention and Alzheimer's pathology affect cortical selectivity during learning, influencing episodic memory in older adults.Science advances · 2025Article
- Using objective and subjective measures of mind wandering to predict progression to development of cognitive impairment and test associations with Alzheimer disease biomarkers.Journal of clinical and experimental neuropsychology · 2025Article
- Default Mode Network Functional Connectivity As a Transdiagnostic Biomarker of Cognitive Function.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Review
- Review
- Predicting response speed and age from task-evoked effective connectivity.Network neuroscience (Cambridge, Mass.) · 2025Article
- Task-specific topology of brain networks supporting working memory and inhibition.Human brain mapping · 2024Article
- Prediction of cognitive performance differences in older age from multimodal neuroimaging data.GeroScience · 2024Article
- Linking the neural signature of response time variability to Alzheimer's disease pathology and cognitive functioning.Network neuroscience (Cambridge, Mass.) · 2024Article
- Network-level enrichment provides a framework for biological interpretation of machine learning results.Network neuroscience (Cambridge, Mass.) · 2024Article
- Oxytocin enhances the triangular association among behavior, resting-state, and task-state functional connectivity.Human brain mapping · 2023Article
- Connectome-based predictive modelling of cognitive reserve using task-based functional connectivity.The European journal of neuroscience · 2023Article
- Classification and prediction of cognitive performance differences in older age based on brain network patterns using a machine learning approach.Network neuroscience (Cambridge, Mass.) · 2023Article
- TRACking health behaviors in people with Multiple Sclerosis (TRAC-MS): Study protocol and description of the study sample.Contemporary clinical trials communications · 2022Article
- Protocol for a randomized controlled trial of mindfulness-based stress reduction to improve attentional control in older adults (HealthyAgers trial).BMC geriatrics · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Aging is associated with declines in a host of cognitive functions, including attentional control, inhibitory control, episodic memory, processing speed, and executive functioning. Theoretical models attribute the age-related decline in cognitive functioning to deficits in goal maintenance and attentional inhibition. Despite these well-documented declines in executive control resources, older adults endorse fewer episodes of mind-wandering when assessed using task-embedded thought probes. Furthermore, previous work on the neural basis of mind-wandering has mostly focused on young adults with studies predominantly focusing on the activity and connectivity of a select few canonical networks. However, whole-brain functional networks associated with mind-wandering in aging have not yet been characterized. In this study, using response time variability-the trial-to-trial fluctuations in behavioral responses-as an indirect marker of mind-wandering or an "out-of-the-zone" attentional state representing suboptimal behavioral performance, we show that brain-based predictive models of response time variability can be derived from whole-brain task functional connectivity. In contrast, models derived from resting-state functional connectivity alone did not predict individual response time variability. Finally, we show that despite successful within-sample prediction of response time variability, our models did not generalize to predict response time variability in independent cohorts of older adults with resting-state connectivity. Overall, our findings provide evidence for the utility of task-based functional connectivity in predicting individual response time variability in aging. Future research is needed to derive more robust and generalizable models.
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Registered trials
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.