ArticleNeuroImage2018
Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation.
Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed.
- Knocking at the Doors of Perception: Relating LSD Effects on Low‐Frequency Fluctuations and Regional Homogeneity to Receptor Densities in fMRI.The European journal of neuroscience · 2025Article
- How the intrinsic functional connectivity patterns of the semantic network support semantic processing.Brain imaging and behavior · 2024Article
- Encoding Manual Dexterity through Modulation of Intrinsic α Band Connectivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Decreased integration of default-mode network during a working memory task in schizophrenia with severe attention deficits.Frontiers in cellular neuroscience · 2022Article
- Efficient Brain Connectivity Reconfiguration Predicts Higher Marital Quality and Lower Depression.Social cognitive and affective neuroscience · 2021Article
- Evaluation of denoising strategies for task-based functional connectivity: Equalizing residual motion artifacts between rest and cognitively demanding tasks.Human brain mapping · 2021Article
- Brain Connectivity Changes after Osteopathic Manipulative Treatment: A Randomized Manual Placebo-Controlled Trial.Brain sciences · 2020Article
- Task-evoked reconfiguration of the fronto-parietal network is associated with cognitive performance in brain tumor patients.Brain imaging and behavior · 2020Article
- Aberrant insular cortex connectivity in abstinent alcohol-dependent rats is reversed by dopamine D3 receptor blockade.Addiction biology · 2020Article
- Brain Network Modularity During a Sustained Working-Memory Task.Frontiers in physiology · 2020Article
- Metastable States of Multiscale Brain Networks Are Keys to Crack the Timing Problem.Frontiers in computational neuroscience · 2018Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.
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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.