ArticleHuman brain mapping2023
A computational study on the optimization of transcranial temporal interfering stimulation with high-definition electrodes using unsupervised neural networks.
Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- [Progresses on temporal interference electromagnetic stimulation for non-invasive deep brain function modulation].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Pooled it
- Temporal interference stimulation for deep brain neuromodulation in humans.Nature biomedical engineering · 2026Review
- On the feasibility of temporal interference stimulation of human brains using two arrays of electrodes.bioRxiv : the preprint server for biology · 2026Article
- Transcranial Temporal Interference Stimulation: A Brief Review of Architectures, Circuits, and Application Challenges.IEEE open journal of engineering in medicine and biology · 2026Article
- Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment.The journal of ECT · 2025Article
- Review
- On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability.bioRxiv : the preprint server for biology · 2025Article
- Beyond the surface: a review of transcranial temporal interference stimulation for deep brain modulation.Frontiers in neurology · 2025Review
- Pilot study of using transcranial temporal interfering theta-burst stimulation for modulating motor excitability in rat.Journal of neuroengineering and rehabilitation · 2024Article
- A computational study on the optimization of transcranial temporal interfering stimulation with high-definition electrodes using unsupervised neural networks.Human brain mapping · 2023Article
- A mini-review: recent advancements in temporal interference stimulation in modulating brain function and behavior.Frontiers in human neuroscience · 2023Review
- On the need of individually optimizing temporal interference stimulation of human brains due to inter-individual variability.Brain stimulationArticle
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Authors and funding
3 authors.
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Abstract
Transcranial temporal interfering stimulation (tTIS) can focally stimulate deep parts of the brain related to specific functions using beats at two high frequencies that do not individually affect the human brain. However, the complexity and nonlinearity of the simulation limit it in terms of calculation time and optimization precision. We propose a method to quickly optimize the interfering current value of high-definition electrodes, which can finely stimulate the deep part of the brain, using an unsupervised neural network (USNN) for tTIS. We linked a network that generates the values of electrode currents to another network, which is constructed to compute the interference exposure, for optimization by comparing the generated stimulus with the target stimulus. Further, a computational study was conducted using 16 realistic head models. We also compared tTIS with transcranial alternating current stimulation (tACS), in terms of performance and characteristics. The proposed method generated the strongest stimulation at the target, even when targeting deep areas or performing multi-target stimulation. The high-definition tTISl was less affected than tACS by target depth, and mis-stimulation was reduced compared with the case of using two-pair inferential stimulation in deep region. The optimization of the electrode currents for the target stimulus could be performed in 3 min. Using the proposed USNN for tTIS, we demonstrated that the electrode currents of tTIS can be optimized quickly and accurately. Moreover, we confirmed the possibility of precisely stimulating the deep parts of the brain via transcranial electrical stimulation.
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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 OpenQuestion graph.