ReviewComputational and structural biotechnology journal2023
Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling.
Review in Computational and structural biotechnology journal, 2023. 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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Who cites it
18 citing papers in PubMed, 40 citations in OpenAlex.
- Perturbations of whole-brain model reveal critical areas related to relapse of early psychosis.Network neuroscience (Cambridge, Mass.) · 2026Article
- Optimal stochastic tracking control for brain network dynamics.Communications biology · 2025Article
- Perturbing whole-brain models of brain hierarchy: An application for depression following pharmacological treatment.Annals of the New York Academy of Sciences · 2025Article
- Network control energy reductions under DMT relate to serotonin receptors, signal diversity, and subjective experience.Communications biology · 2025Article
- Impaired brain ability of older adults to transit and persist to latent states with well-organized structures at wakeful rest.GeroScience · 2025Article
- Whole-brain turbulent dynamics predict responsiveness to pharmacological treatment in major depressive disorder.Molecular psychiatry · 2025Article
- Atypical attentional network dynamics in adolescent depression during emotional movie viewing.Social cognitive and affective neuroscience · 2025Article
- Human brain dynamics are shaped by rare long-range connections over and above cortical geometry.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder.Entropy (Basel, Switzerland) · 2024Article
- Whole brain modelling for simulating pharmacological interventions on patients with disorders of consciousness.Communications biology · 2024Article
- Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation.PLoS computational biology · 2024Article
- A synergetic turn in cognitive neuroscience of brain diseases.Trends in cognitive sciences · 2024Review
- Brain dynamics predictive of response to psilocybin for treatment-resistant depression.Brain communications · 2024Article
- Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients.Brain communications · 2024Article
- The unique neural signature of your trip: Functional connectome fingerprints of subjective psilocybin experience.Network neuroscience (Cambridge, Mass.) · 2024Article
- Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks.Progress in neurobiology · 2023Review
- Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness.NeuroImage · 2023Article
- Effects of θ High Definition-Transcranial Alternating Current Stimulation in the Anterior Cingulate Cortex on the Dominance of Attention Focus in Standing Postural Control.Behavioral sciences (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditionally, in neuroimaging, model-free analyses are used to find significant differences between brain states via signal detection theory. Depending on the a priori assumptions about the underlying data, different spatio-temporal features can be analysed. Alternatively, model-based techniques infer features from the data and compare significance from model parameters. However, to assess transitions from one brain state to another remains a challenge in current paradigms. Here, we introduce a "Dynamic Sensitivity Analysis" framework that quantifies transitions between brain states in terms of stimulation ability to rebalance spatio-temporal brain activity towards a target state such as healthy brain dynamics. In practice, it means building a whole-brain model fitted to the spatio-temporal description of brain dynamics, and applying systematic stimulations in-silico to assess the optimal strategy to drive brain dynamics towards a target state. Further, we show how Dynamic Sensitivity Analysis extends to various brain stimulation paradigms, ultimately contributing to improving the efficacy of personalised clinical interventions.
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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.