ArticleBiological cybernetics2021
Leveraging deep learning to control neural oscillators.
Article in Biological cybernetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Data-Driven Pattern Formation in Oscillator Networks Using Partial Observations.Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control · 2025Article
- Optimal control for stochastic neural oscillators.Biological cybernetics · 2025Article
- Magnitude-constrained optimal chaotic desynchronization of neural populations.Frontiers in network physiology · 2025Article
- A feasibility study on AI-controlled closed-loop electrical stimulation implants.Scientific reports · 2023Article
- Data-Driven Control of Neuronal Networks with Population-Level Measurement.Research square · 2023Article
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Authors and funding
2 authors.
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Abstract
Modulation of the firing times of neural oscillators has long been an important control objective, with applications including Parkinson's disease, Tourette's syndrome, epilepsy, and learning. One common goal for such modulation is desynchronization, wherein two or more oscillators are stimulated to transition from firing in phase with each other to firing out of phase. The optimization of such stimuli has been well studied, but this typically relies on either a reduction of the dimensionality of the system or complete knowledge of the parameters and state of the system. This limits the applicability of results to real problems in neural control. Here, we present a trained artificial neural network capable of accurately estimating the effects of square-wave stimuli on neurons using minimal output information from the neuron. We then apply the results of this network to solve several related control problems in desynchronization, including desynchronizing pairs of neurons and achieving clustered subpopulations of neurons in the presence of coupling and noise.
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33909165What OpenQuestion holds
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.