Academic Journal
Computational modeling of interferential stimulation of the spinal cord.
| Τίτλος: | Computational modeling of interferential stimulation of the spinal cord. |
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| Συγγραφείς: | Mohammadi F; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America.; Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America., Yearwood T; Department of Pain Management, Guy's and St Thomas' Hospitals, London, United Kingdom., Lempka SF; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America.; Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America.; Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States of America. |
| Πηγή: | Journal of neural engineering [J Neural Eng] 2026 Aug 05; Vol. 23 (4). Date of Electronic Publication: 2026 Aug 05. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Institute of Physics Pub Country of Publication: England NLM ID: 101217933 Publication Model: Electronic Cited Medium: Internet ISSN: 1741-2552 (Electronic) Linking ISSN: 17412552 NLM ISO Abbreviation: J Neural Eng Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Bristol, U.K. : Institute of Physics Pub., 2004- |
| Ιατρικοί όροι (MeSH): | Spinal Cord*/physiology , Spinal Cord Stimulation*/methods , Computer Simulation* , Models, Neurological*, Action Potentials/physiology ; Humans ; Finite Element Analysis |
| Περίληψη: | Objective.Interferential stimulation uses multiple independent groups of electrodes to apply high-frequency currents with a small-frequency offset. At a specific region(s) in space, superposition of the high-frequency currents creates low-frequency amplitude modulation that can drive neural activation. Therefore, with interferential spinal cord stimulation (IF-SCS), it may be possible to focus stimulation on target areas while avoiding stimulation of non-target areas that could produce unwanted side effects. In this study, we used a comprehensive computational modeling approach to evaluate the potential efficacy of IF-SCS to improve targeting within the spinal cord.Approach. We constructed a finite element method model of the human lower thoracic spinal cord and surrounding anatomy with two eight-contact percutaneous electrode arrays in the epidural tissue and calculated the extracellular potentials generated during IF-SCS. We applied these potential fields to multi-compartment axon models distributed throughout the spinal cord to simulate the neural response to IF-SCS. We examined how various factors, such as stimulation configuration, carrier and beat frequencies, electrode spacing, and dorsal cerebrospinal fluid (CSF) thickness, affected the neural response to IF-SCS.Main Results. IF-SCS produced different types of axonal responses, such as phasic, tonic, and quiescent. Phasic activation thresholds increased with increasing carrier and beat frequencies, electrode spacing, and dorsal CSF thickness. As we increased the stimulation amplitude, we observed that deeper regions of the dorsal columns exhibited phasic responses. Finally, a comparison of frequency-dependent and frequency-independent tissue properties revealed only minor differences in activation thresholds.Significance.Our results demonstrate that several factors affect the spatial selectivity and neural response to IF-SCS. This computational modeling study highlights the potential for IF-SCS to improve targeting within the spinal cord and supports its development into a clinically effective therapy that provides advantages over conventional SCS therapies. (Creative Commons Attribution license.) |
| Contributed Indexing: | Keywords: chronic pain; computer simulation; finite element modeling; interferential stimulation; spinal cord stimulation; temporal interference |
| Entry Date(s): | Date Created: 20260603 Date Completed: 20260805 Latest Revision: 20260805 |
| Update Code: | 20260805 |
| DOI: | 10.1088/1741-2552/ae7767 |
| PMID: | 42235552 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1741-2552 |
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| DOI: | 10.1088/1741-2552/ae7767 |