ArticlePLoS computational biology2018
Design of optimal nonlinear network controllers for Alzheimer's disease.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 29 citations in OpenAlex.
- Longitudinal changes in control energy of brain networks in older adults at familial risk for Alzheimer's disease.bioRxiv : the preprint server for biology · 2026Article
- Brain energetic landscapes shape state dysregulation in major depressive disorder: a morphological network controllability perspective.Translational psychiatry · 2026Article
- Disrupted Energetic and Entropic Landscape in Individuals With Mild Cognitive Impairment: Insights From Network Control Theory.Human brain mapping · 2025Article
- Data-driven modeling of amyloid-β targeted antibodies for Alzheimer's disease.NPJ systems biology and applications · 2025Article
- Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms.Translational psychiatry · 2024Review
- Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease.Communications biology · 2024Article
- Development of the brain network control theory and its implications.Psychoradiology · 2024Review
- In-vivo neuronal dysfunction by Aβ and tau overlaps with brain-wide inflammatory mechanisms in Alzheimer's disease.Frontiers in aging neuroscience · 2024Article
- Alzheimer's Disease: Insights from Large-Scale Brain Dynamics Models.Brain sciences · 2023Review
- Revealing the combined roles of Aβ and tau in Alzheimer's disease via a pathophysiological activity decoder.bioRxiv : the preprint server for biology · 2023Article
- Extracting electrophysiological correlates of functional magnetic resonance imaging data using the canonical polyadic decomposition.Human brain mapping · 2022Article
- Prevalence and scalable control of localized networks.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Toward noninvasive brain stimulation 2.0 in Alzheimer's disease.Ageing research reviews · 2022Review
- Communicability distance reveals hidden patterns of Alzheimer's disease.Network neuroscience (Cambridge, Mass.) · 2020Article
- Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3.Frontiers in neuroinformatics · 2019Article
- Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification.Frontiers in neuroscience · 2018Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
Brain stimulation can modulate the activity of neural circuits impaired by Alzheimer's disease (AD), having promising clinical benefit. However, all individuals with the same condition currently receive identical brain stimulation, with limited theoretical basis for this generic approach. In this study, we introduce a control theory framework for obtaining exogenous signals that revert pathological electroencephalographic activity in AD at a minimal energetic cost, while reflecting patients' biological variability. We used anatomical networks obtained from diffusion magnetic resonance images acquired by the Alzheimer's Disease Neuroimaging Initiative (ADNI) as mediators for the interaction between Duffing oscillators. The nonlinear nature of the brain dynamics is preserved, given that we extend the so-called state-dependent Riccati equation control to reflect the stimulation objective in the high-dimensional neural system. By considering nonlinearities in our model, we identified regions for which control inputs fail to correct abnormal activity. There are changes to the way stimulated regions are ranked in terms of the energetic cost of controlling the entire network, from a linear to a nonlinear approach. We also found that limbic system and basal ganglia structures constitute the top target locations for stimulation in AD. Patients with highly integrated anatomical networks-namely, networks having low average shortest path length, high global efficiency-are the most suitable candidates for the propagation of stimuli and consequent success on the control task. Other diseases associated with alterations in brain dynamics and the self-control mechanisms of the brain can be addressed through our framework.
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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.