ArticleNetwork neuroscience (Cambridge, Mass.)2019
Adaptive frequency-based modeling of whole-brain oscillations: Predicting regional vulnerability and hazardousness rates.
Article in Network neuroscience (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Macroscopic resting state model predicts theta burst stimulation response: A randomized trial.PLoS computational biology · 2023Trial
- Transient destabilization of whole brain dynamics induced by N,N-Dimethyltryptamine (DMT).Communications biology · 2025Article
- Digital twin brain simulator for real-time consciousness monitoring and virtual intervention using primate electrocorticogram data.NPJ digital medicine · 2025Article
- Preparatory activity of anterior insula predicts conflict errors: integrating convolutional neural networks and neural mass models.Scientific reports · 2024Article
- The Hopf whole-brain model and its linear approximation.Scientific reports · 2024Article
- Parkinson's disease is characterized by sub-second resting-state spatio-oscillatory patterns: A contribution from deep convolutional neural network.NeuroImage. Clinical · 2022Article
- Whole-Brain Modelling: Past, Present, and Future.Advances in experimental medicine and biology · 2022Article
- Acquired olfactory loss alters functional connectivity and morphology.Scientific reports · 2021Article
- A unified approach for characterizing static/dynamic connectivity frequency profiles using filter banks.Network neuroscience (Cambridge, Mass.) · 2021Article
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Authors and funding
3 authors.
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Abstract
Whole-brain computational modeling based on structural connectivity has shown great promise in successfully simulating fMRI BOLD signals with temporal coactivation patterns that are highly similar to empirical functional connectivity patterns during resting state. Importantly, previous studies have shown that spontaneous fluctuations in coactivation patterns of distributed brain regions have an inherent dynamic nature with regard to the frequency spectrum of intrinsic brain oscillations. In this modeling study, we introduced frequency dynamics into a system of coupled oscillators, where each oscillator represents the local mean-field model of a brain region. We first showed that the collective behavior of interacting oscillators reproduces previously shown features of brain dynamics. Second, we examined the effect of simulated lesions in gray matter by applying an in silico perturbation protocol to the brain model. We present a new approach to map the effects of vulnerability in brain networks and introduce a measure of regional hazardousness based on mapping of the degree of divergence in a feature space.
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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 Socratic graph.