ArticleNature communications2019
Dynamic network coding of working-memory domains and working-memory processes.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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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
26 citing papers in PubMed.
- Synchronization patterns reveal neuronal coding of working memory content.Cell reports · 2021Trial
- Prioritizing flexible working memory representations relies on the involvement of the parahippocampal-insula network during memory reactivation.Communications biology · 2025Article
- Ultrafast fMRI reveals serial queuing of information processing during multitasking in the human brain.Nature communications · 2025Article
- Infraslow Dynamic Patterns in Human Cortical Networks Track a Spectrum of External to Internal Attention.Human brain mapping · 2025Article
- Explaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis.Journal of neurology · 2025Article
- Changes in memory and cognition during the SARS-CoV-2 human challenge study.EClinicalMedicine · 2024Article
- Dynamic layer-specific processing in the prefrontal cortex during working memory.Communications biology · 2024Article
- GABAergic inhibition shapes behavior and neural dynamics in human visual working memory.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Role of articulatory motor networks in perceptual categorization of speech signals: a 7T fMRI study.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Planning ahead: Predictable switching recruits task-active and resting-state networks.Human brain mapping · 2023Article
- Spectrotemporal content of human auditory working memory represented in functional connectivity patterns.Communications biology · 2023Article
- Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy.Science advances · 2022Article
- Cortical connectivity gradients and local timescales during cognitive states are modulated by cognitive loads.Brain structure & function · 2022Article
- Do sparse brain activity patterns underlie human cognition?NeuroImage · 2022Article
- Abnormal Dynamic Functional Connectivity in Patients With End-Stage Renal Disease.Frontiers in neuroscience · 2022Article
- A Bayesian optimization approach for rapidly mapping residual network function in stroke.Brain : a journal of neurology · 2021Article
- Dynamic functional connectivity changes in the triple networks and its association with cognitive impairment in hemodialysis patients.Brain and behavior · 2021Article
- Neuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance.Nature communications · 2021Article
- Alterations in Neural Networks During Working Memory Encoding Related to Cognitive Impairment in Temporal Lobe Epilepsy.Frontiers in human neuroscience · 2021Article
- Activity in the fronto-parietal multiple-demand network is robustly associated with individual differences in working memory and fluid intelligence.Cortex; a journal devoted to the study of the nervous system and behavior · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The classic mapping of distinct aspects of working memory (WM) to mutually exclusive brain areas is at odds with the distributed processing mechanisms proposed by contemporary network science theory. Here, we use machine-learning to determine how aspects of WM are dynamically coded in the human brain. Using cross-validation across independent fMRI studies, we demonstrate that stimulus domains (spatial, number and fractal) and WM processes (encode, maintain, probe) are classifiable with high accuracy from the patterns of network activity and connectivity that they evoke. This is the case even when focusing on 'multiple demands' brain regions, which are active across all WM conditions. Contrary to early neuropsychological perspectives, these aspects of WM do not map exclusively to brain areas or processing streams; however, the mappings from that literature form salient features within the corresponding multivariate connectivity patterns. Furthermore, connectivity patterns provide the most precise basis for classification and become fine-tuned as maintenance load increases. These results accord with a network-coding mechanism, where the same brain regions support diverse WM demands by adopting different connectivity states.
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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.