ArticleJournal of neural engineering2017
An improved genetic algorithm for designing optimal temporal patterns of neural stimulation.
Article in Journal of neural engineering, 2017. 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.
- The optimization of neuroprosthetic interfaces relying on biophysical and surrogate digital twins.npj biomedical innovations · 2026Review
- Mitigating Neural Habituation in Insect Bio-Bots: A Dual-Timescale Adaptive Control Approach.Biomimetics (Basel, Switzerland) · 2025Article
- NRV: An open framework for in silico evaluation of peripheral nerve electrical stimulation strategies.PLoS computational biology · 2024Article
- Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity.Journal of neural engineering · 2024Article
- NRV: An open framework forbioRxiv : the preprint server for biology · 2024Article
- Optimized monophasic pulses with equivalent electric field for rapid-rate transcranial magnetic stimulation.Journal of neural engineering · 2023Article
- Measuring and modeling the effects of vagus nerve stimulation on heart rate and laryngeal muscles.Bioelectronic medicine · 2023Article
- Towards personalized and optimized fitting of cochlear implants.Frontiers in neuroscience · 2023Article
- Exploratory evaluation of spinal cord stimulation with dynamic pulse patterns: a promising approach to improve stimulation sensation, coverage of pain areas, and expected pain relief.Frontiers in pain research (Lausanne, Switzerland) · 2023Article
- Deep brain-machine interfaces: sensing and modulating the human deep brain.National science review · 2022Review
- Adjust Neuronal Reactions to Pulses of High-Frequency Stimulation with Designed Inter-Pulse-Intervals in Rat Hippocampus In Vivo.Brain sciences · 2021Article
- Technology of deep brain stimulation: current status and future directions.Nature reviews. Neurology · 2021Review
- Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies.Frontiers in human neuroscience · 2021Article
- Time-dynamic pulse modulation of spinal cord stimulation reduces mechanical hypersensitivity and spontaneous pain in rats.Scientific reports · 2020Article
- Small Changes in Inter-Pulse-Intervals Can Cause Synchronized Neuronal Firing During High-Frequency Stimulations in Rat Hippocampus.Frontiers in neuroscience · 2019Article
- Temporal Pattern of Electrical Stimulation is a New Dimension of Therapeutic Innovation.Current opinion in biomedical engineering · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
objectiveElectrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. APPROACH: We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. MAIN
resultsThe proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. SIGNIFICANCE: The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.
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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.