ArticleBrain structure & function2023
Using modular connectome-based predictive modeling to reveal brain-behavior relationships of individual differences in working memory.
Article in Brain structure & function, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Connectome-based predictive modelling predicts frailty levels in older adults.bioRxiv : the preprint server for biology · 2025Article
- Connectome-based predictive modeling of grip strength: a marker of physical frailty.Frontiers in neuroscience · 2025Article
- Exploring anterior thalamus functional connectivity with cortical regions in prospective memory with ultra-high-field functional MRI.Brain communications · 2025Article
- GenCPM: a toolbox for generalized connectome-based predictive modeling.Frontiers in neuroscience · 2025Article
- Functional MRI of imprinting memory in awake newborn domestic chicks.Communications biology · 2024Article
- Stimulus shapes strategy: Effects of stimulus characteristics and individual differences in academic achievement on the neural mechanisms engaged during the N-back task.Developmental cognitive neuroscience · 2024Article
- Cognitive Functions following Trigeminal Neuromodulation.Biomedicines · 2023Review
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Working memory plays a crucial role in our daily lives, and brain imaging has been used to predict working memory performance. Here, we present an improved connectome-based predictive modeling approach for building a predictive model of individual working memory performance from whole-brain functional connectivity. The model was built using n-back task-based fMRI and resting-state fMRI data from the Human Connectome Project. Compared to prior models, our model was more interpretable, demonstrated a closer connection to the known anatomical and functional network. The model also demonstrates strong generalization on nine other cognitive behaviors from the HCP database and can well predict the working memory performance of healthy individuals in external datasets. By comparing the differences in prediction effects of different brain networks and anatomical feature analysis on n-back tasks, we found the essential role of some networks in differentiating between high and low working memory loads conditions.
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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.