OPTIMAL LOCATION OF ACTION POTENTIAL GENERATION BASED ON ACTIVATION FUNCTION USING COMPUTATIONAL MODELLING

Yıl 2023, Cilt: 11 Sayı: 3, 801 - 811, 01.09.2023

Enver Salkım

https://doi.org/10.36306/konjes.1240153

Öz

Transcutaneous electrical nerve stimulation is used to elevate health-related disorders. This technology is now an important therapeutic system for medical science. In this system, the electrical current pulse is applied over the skin through the inner layers via electrodes to activate excitable tissue layers. Activating other excitable tissue layers may cause discomfort. Thus, it is vital to design electrode configuration arrangements to activate the target anatomical layers without affecting the neighboring ones. A device for primary headaches showed mixed results. This may be related to the electrode position that requires higher stimulus current levels to activate target nerve fibers. This may stimulate neighboring nerve fibers which resulted in the discomfort of patients. A feasible solution is to identify the optimal electrode configuration based on the activation function which is the second derivative of the electric potential along an axon. This may guide to estimate of the possibility of action potential generation on the neural tissue layer using a specified electrode arrangement. In this study, the multilayered human head was developed based on MRI data set using pre and post-processing. Then multi-electrode arrangements were developed to examine the possible nerve activation location. Results showed that the nerve fibers were activated at the same location of the trajectory for the anodal and cathodal stimulation. This may be proof that the activation function can be used to define the optimal location of nerve activation. This may lead to lower thresholds for similar therapeutic benefits in transcutaneous electrical nerve stimulation with decreased power consumption.

Anahtar Kelimeler

Action Potential, Activation Function, Extracellular Potential, Finite Element Simulation

Kaynakça

• N. Ravichandran, M. Y. Teo, K. Aw, and A. McDaid, “Design of Transcutaneous Stimulation Electrodes for Wearable Neuroprostheses,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 7, pp. 1651–1660, Jul. 2020, doi: 10.1109/TNSRE.2020.2994900.
• B. A. Karamian et al., “The role of electrical stimulation for rehabilitation and regeneration after spinal cord injury,” Journal of Orthopaedics and Traumatology, vol. 23, no. 1. Springer Science and Business Media Deutschland GmbH, Dec. 01, 2022. doi: 10.1186/s10195-021-00623-6.
• A. Gupta, N. Vardalakis, and F. B. Wagner, “Neuroprosthetics: from sensorimotor to cognitive disorders,” Communications biology, vol. 6, no. 1. NLM (Medline), p. 14, Dec. 01, 2023. doi: 10.1038/s42003-022-04390-w.
• E. Salkim, A. Shiraz, and A. Demosthenous, “Impact of neuroanatomical variations and electrode orientation on stimulus current in a device for migraine: A computational study,” J Neural Eng, vol. 17, no. 1, 2020, doi: 10.1088/1741-2552/ab3d94.
• E. Salkim, A. Shiraz, and A. Demosthenous, “Influence of cellular structures of skin on fiber activation thresholds and computation cost In fl uence of cellular structures of skin on fi ber activation thresholds and computation cost,” Biomed Phys Eng Express, vol. 5, no. 1, p. 015015, 2018.
• S. Joucla, A. Glière, and B. Yvert, “Current approaches to model extracellular electrical neural microstimulation,” Front Comput Neurosci, vol. 8, no. February, pp. 1–12, 2014, doi: 10.3389/fncom.2014.00013.
• S. F. Cogan, “Neural Stimulation and Recording Electrodes,” Annu Rev Biomed Eng, vol. 10, no. 1, pp. 275–309, 2008, doi: 10.1146/annurev.bioeng.10.061807.160518.
• A. Kuhn, T. Keller, M. Lawrence, and M. Morari, “The influence of electrode size on selectivity and comfort in transcutaneous electrical stimulation of the forearm,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 18, no. 3, pp. 255–262, Jun. 2010, doi: 10.1109/TNSRE.2009.2039807.
• A. Patriciu, K. Yoshida, J. J. Struijk, T. P. DeMonte, M. L. G. Joy, and H. Stoødkilde-Joørgensen, “Current density imaging and electrically induced skin burns under surface electrodes,” IEEE Trans Biomed Eng, vol. 52, no. 12, pp. 2024–2031, Dec. 2005, doi: 10.1109/TBME.2005.857677.
• D. Magis, S. Sava, T. S. d’Elia, R. Baschi, and J. Schoenen, “Safety and patients’ satisfaction of transcutaneous supraorbital neurostimulation (tSNS) with the Cefaly® device in headache treatment: a survey of 2,313 headache sufferers in the general population.,” J Headache Pain, vol. 14, p. 95, 2013, doi: 10.1186/1129-2377-14-95.
• J. Schoenen et al., “Migraine prevention with a supraorbital transcutaneous stimulator: A randomized controlled trial,” Neurology, vol. 80, no. 8, pp. 697–704, 2013, doi: 10.1212/WNL.0b013e3182825055.
• E. Salkim, “Electrode Array Position Guiding in Cochlea Based on Impedance Variation : Computational Study,” Muş Alparslan Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 1, no. 1, pp. 64–71, 2020.
• A. Fellner, A. Heshmat, P. Werginz, and F. Rattay, “A finite element method framework to model extracellular neural stimulation,” J Neural Eng, vol. 19, no. 2, Apr. 2022, doi: 10.1088/1741-2552/ac6060.
• F. Rattay, S. M. Danner, U. S. Hofstoetter, and K. Minassian, “Finite Element Modeling for Extracellular Stimulation,” in Encyclopedia of Computational Neuroscience, Springer New York, 2014, pp. 1–12. doi: 10.1007/978-1-4614-7320-6_593-5.
• S. Joucla and B. Yvert, “Modeling extracellular electrical neural stimulation: From basic understanding to MEA-based applications,” Journal of Physiology-Paris, vol. 106, no. 3–4, pp. 146–158, 2012, doi: 10.1016/j.jphysparis.2011.10.003.
• H. Ye, “Finding the Location of Axonal Activation by a Miniature Magnetic Coil,” Front Comput Neurosci, vol. 16, Jun. 2022, doi: 10.3389/fncom.2022.932615.
• D. N. Anderson, G. Duffley, J. Vorwerk, A. D. Dorval, and C. R. Butson, “Anodic stimulation misunderstood: Preferential activation of fiber orientations with anodic waveforms in deep brain stimulation,” J Neural Eng, vol. 16, no. 1, Feb. 2019, doi: 10.1088/1741-2552/aae590.
• K. N. Christensen, N. Lachman, W. Pawlina, and C. L. Baum, “Cutaneous Depth of the Supraorbital Nerve,” Dermatologic Surgery, vol. 40, no. 12, pp. 1342–1348, 2014, doi: 10.1097/DSS.0000000000000174.
• Y.-C. Gil, K.-J. Shin, S.-H. Lee, W.-C. Song, K.-S. Koh, and H. J. Shin, “Topography of the supraorbital nerve with reference to the lacrimal caruncle: danger zone for direct browplasty,” British Journal of Ophthalmology, vol. 101, no. 7, pp. 940–945, 2017, doi: 10.1136/bjophthalmol-2016-309332.
• “OVERVIEW » IT’IS Foundation.” https://itis.swiss/virtual-population/regional-human-models/overview/ (accessed Jan. 20, 2023).
• A. K. D. Harold Ellis, Bari M Logan, Human Sectional Anatomy, Third Edit. London: Hodder Arnold, 2009.
• M. Z. Siemionow, “The Face as a Sensory Organ,” in The Know-How of Face Transplantation, M. Siemionow, Ed., Springer, 2011, pp. 207–212. doi: 10.1007/978-0-85729-253-7.
• F. Rattay, “Analysis of models for extracellular fiber stimulation.pdf,” IEEE Trans. Biomed. Eng., vol. 36, no. 7, pp. 676–682, 1989.
• A. Fellner, A. Heshmat, P. Werginz, and F. Rattay, “A finite element method framework to model extracellular neural stimulation,” J Neural Eng, vol. 19, no. 2, Apr. 2022, doi: 10.1088/1741-2552/ac6060.
• “Low Frequency (Conductivity) » IT’IS Foundation.” https://itis.swiss/virtual-population/tissue-properties/database/low-frequency-conductivity/ (accessed May 20, 2019).
• E. Salkim, “Optimisation of a Wearable Neuromodulator for Migraine Using Computational Methods.”
• E. Salkim, “Analysis of tissue electrical properties on bio-impedance variation of upper limps”, doi: 10.3906/elk-1300-0632.3908.
• T. F. Oostendorp, J. Delbeke, and D. F. Stegeman, “The conductivity of the human skull: Results of in vivo and in vitro measurements,” IEEE Trans Biomed Eng, vol. 47, no. 11, pp. 1487–1492, Nov. 2000, doi: 10.1109/TBME.2000.880100.