ArticlePLoS computational biology2024
Controlling target brain regions by optimal selection of input nodes.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Control of cortical population activity with patterned microstimulation.bioRxiv : the preprint server for biology · 2026Article
- Controlling the human connectome with spatially diffuse input signals.Communications biology · 2026Article
- Optimal stochastic tracking control for brain network dynamics.Communications biology · 2025Article
- Towards model-based design of causal manipulations of brain circuits with high spatiotemporal precision.bioRxiv : the preprint server for biology · 2025Article
- Mapping effective connectivity by virtually perturbing a surrogate brain.Nature methods · 2025Article
- Towards model-based design of causal manipulations of brain circuits with high spatiotemporal precision.ArXiv · 2025Article
- Network control theory applied to the human connectome: A study on variability and discriminability of fMRI connectomic features under normal and defective sensorineural conditions.Network neuroscience (Cambridge, Mass.) · 2025Article
- Controlling the human connectome with spatially diffuse input signals.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
9 authors.
Funding
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Abstract
The network control theory framework holds great potential to inform neurostimulation experiments aimed at inducing desired activity states in the brain. However, the current applicability of the framework is limited by inappropriate modeling of brain dynamics, and an overly ambitious focus on whole-brain activity control. In this work, we leverage recent progress in linear modeling of brain dynamics (effective connectivity) and we exploit the concept of target controllability to focus on the control of a single region or a small subnetwork of nodes. We discuss when control may be possible with a reasonably low energy cost and few stimulation loci, and give general predictions on where to stimulate depending on the subset of regions one wishes to control. Importantly, using the robustly asymmetric effective connectome instead of the symmetric structural connectome (as in previous research), we highlight the fundamentally different roles in- and out-hubs have in the control problem, and the relevance of inhibitory connections. The large degree of inter-individual variation in the effective connectome implies that the control problem is best formulated at the individual level, but we discuss to what extent group results may still prove useful.
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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.