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Theoretical simulation of the selective stimulation of axons in different areas of a nerve bundle by multichannel near-infrared lasers

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Abstract

Damaged nerve function can be repaired by applying external stimuli, and the selective stimulation of nerve fibers is the highest goal of nerve functional repair. This paper proposes a method of using multichannel near-infrared lasers to achieve the selective stimulation of axons in different areas in a mixed nerve bundle. An exposed bullfrog sciatic nerve was considered the object of study to realize the selective stimulation. A model was established by using COMSOL Multiphysics to simulate the temperature distribution of nerves under multichannel near-infrared laser stimulation. The results of this model showed that by changing the distance between the laser fiber and the nerve (d) or the power of the 4 lasers (P), the axons at different parts of the nerve bundle may be selectively stimulated. If only the axons located in the center are selected to be activated, it is necessary to set the d and P value in the four directions to the same value. If only axons on the nerve edge are selected for activation, we can reduce the d value of the nearest laser (or increase P) and increase the d value of lasers in other directions (or decrease P). If only axons in the shallow area below the surface between the two lasers are selected for activation, it is necessary to reduce the d value of the laser in two directions close there (or increase P) and increase the d value of the laser in the other two directions (or decrease P). If only the axons of the superficial region on the coordinate axis are activated, the d value of the laser in the farthest direction can be increased (or decrease P) and the d value of the other three lasers can be reduced (or increase P). Moreover, the results of animal experiments further verify the feasibility of our method to realize selective activation of the axons.

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References

  1. Gudnason G, Bruun E, Haugland M (2000) A chip for an implantable neural stimulator. Analog Integr Circ S 22(1):81–89

    Article  Google Scholar 

  2. Richter CP, Matic AI, Well JD, Jansen ED, Walsh JT (2011) Neural stimulation with optical radiation. Laser Photonics Rev. 5(1):68–80

    Article  CAS  Google Scholar 

  3. Wells J, Kao C, Jansen ED, Konrad P, Mahadevan-Jansen A (2014) Application of infrared light for in vivo neural stimulation. J Biomed Opt. 10(6):064003

    Article  Google Scholar 

  4. Qiang S, Xueliang L, Dazong J, Changfeng T (2001) A bipolar method for selective activation of nerve fibers using biphasic rectangular pulses. Chin J Biomed Eng 20(6):533–540

    Google Scholar 

  5. Fang ZP, Mortimer JT (1991) Selective activations of small motor axons by quasitrapezoidal current pulses. IEEE T Bio-med Eng 38(2):168–174

    Article  CAS  Google Scholar 

  6. Freeman DK, Eddington DK, Rizzo J, Fried S (2010) Selective activation of neuronal targets with sinusoidal electric stimulation. J Neurophysiol 104(5):2778–2791

    Article  Google Scholar 

  7. Grill W, Norman S, Bellamkonda R (2009) Implanted neural interfaces: biochallenges and engineered solutions. Biomed Eng 11(1)

  8. Veraart C, Grill W, Mortimer J (1993) Selective control of muscle activation with a multipolar nerve cuff electrode. IEEE T Bio-med Eng 40(7):640–653

    Article  CAS  Google Scholar 

  9. Zariffa J, Nagai M, Daskalakis Z, Popovic M (2009) Influence of the number and location of recording contacts on the selectivity of a nerve cuff electrode. IEEE T Reh Eng 17(5):420–427

    Google Scholar 

  10. Butson C, Miller I, Normann R, Clark G (2011) Selective neural activation in a histologically derived model of peripheral nerve. J Neural Eng. 8(3):036009

    Article  Google Scholar 

  11. Wells J, Konrad P, Kao C, Jansen E, Mahadevan-Jansen A (2007) Pulsed laser versus electrical energy for peripheral nerve stimulation. J Neurosci Meth 163(2):326–337

    Article  Google Scholar 

  12. Wells J, Kao C, Konrad P, Milner T, Kim J, Mahadevan-Jansen A et al (2007) Biophysical mechanisms of transientoptical stimulation of peripheral nerve. Biophys J 93(7):2567–2580

    Article  CAS  Google Scholar 

  13. Cayce J, Kao C, Malphrus J, Konrad P, Mahadevan-Jansen A, Jansen E (2010) Infrared neural stimulation of thalamocortical brain slices. IEEE J Sel Top Quant 16(3):565–572

    Article  CAS  Google Scholar 

  14. Cayce J, Friedman R, Jansen E, Mahavaden-Jansen A, Roe A (2011) Pulsed infrared light alters neural activity in rat somatosensory cortex in vivo. Neuroimage 57(1):155–166

    Article  Google Scholar 

  15. Teudt I, Nevel A, Izzo A, Walsh J, Richter C, Richter C (2007) Optical stimulation of the facial nerve- a new monitoring technique. Laryngoscope 117(9):1641–1647

    Article  Google Scholar 

  16. Izzo A, Walsh J, Ralph H, Webb J, Bendett M, Wells J et al (2008) Laser stimulation of auditory neurons: effect of shorter pulse duration and penetration depth. Biophys J 94(8):3159–3166

    Article  CAS  Google Scholar 

  17. Izzo A, Walsh J, Jansen E, Bendett M, Webb J, Ralph H et al (2007) Optical parameter variability in laser nerve stimulation: a study of pulse duration, repetition rate, and wavelength. IEEE Trans Bio-med Eng 54(6):1108–1114

    Article  Google Scholar 

  18. Richter C, Bayon R, Izzo A, Otting M, Suh E, Goyal S et al (2008) Optical stimulation of auditory neurons: effects of acute and chronic deafening. Hearing Res 242(1–2):42–51

    Article  Google Scholar 

  19. Rajguru SM, Rabbitt RR, Matic AI, Highstein SM, Richter CP (2010) Inhibitory and excitatory vestibular afferent responses induced by infrared light stimulation of hair cells, 33rd Midwinter Meeting. Association for Research in Otolaryngology, Anaheim, CA

  20. Chung H, Chung E (2019) Optical stimulation and pacing of the embryonic chicken heart via thulium laser irradiation. Curr Opt Photon 3(1):1–7

    CAS  Google Scholar 

  21. Shapiro MG, Homma K, Villarreal S, Richter CP, Bezanilla F (2012) Infrared light excites cells by changing their electrical capacitance. Nat Commun 3:736

    Article  Google Scholar 

  22. Plaksin M, Kimmel E, Shoham S (2017) Thermal transients excite neurons through universal intramembrane mechano-electrical effects. bioRxiv 111724

  23. Rachael TR, Michael RI, Alexander CT, Andrew KW, James BF (2020) Optical stimulation of neural tissue. Healthc Technol Lett 7(3):58–65

    Article  Google Scholar 

  24. Barrett JN, Rincon S, Singh J, Matthewman C, Pasos J, Barrett EF et al (2018) Pulsed infrared releases Ca2þ from the endoplasmic reticulum of cultured spiral ganglion. Neurons 120:509–524

    CAS  Google Scholar 

  25. Eom K, Kim J, Choi J, Kang T, Chang J, Byun K et al (2014) Enhanced infrared neural stimulation using localized surface plasmon resonance of gold nanorods. Small 10(19):3853–3857

    Article  CAS  Google Scholar 

  26. Wang Y, Guo L (2016) Nanomaterial-enabled neural stimulation. Front Neurosci 10:69

    PubMed  PubMed Central  Google Scholar 

  27. Ren Y, Qi H, Chen Q, Ruan L (2017) Thermal dosage investigation for optimal temperature distribution in gold nanoparticle enhanced photothermal therapy. Int J Heat Mass Tran 106:212–221

    Article  CAS  Google Scholar 

  28. Yan C, Yanxiong N, Fang T, Huichai Y, Chu Z, Nan J et al (2007) Numerical simulation of the optical-thermal interaction in vivo layered skin-tissue by Laser. Appl Laser 27(5):382–386

    Google Scholar 

  29. Rickard Vitkaya AY, Seker SS (2016) Study of temperature distribution in light-tissue interaction using the FEM. Turk J Electr Eng Co 24:807–819

    Article  Google Scholar 

  30. Mengxian Y, Zongxia M (2017) Model study of combined electrical and near-infrared neural stimulation on the bullfrog sciatic nerve. Lasers Medl Sci 32(5):1163–1172

    Article  Google Scholar 

  31. Yucel A, Ersen A, Sahin M, Al-Smadi Y (2013) FEA modeling of temperature elevation in neural tissue illuminated by a laser: Transient effects. 6th Annual International IEEE/EMBS Conference on Neural Engineering, pp 1112–1114

  32. Urzova J, Jelinek M (2018) Heat transfer modelling of pulsed laser-tissue interaction. Laser Phys 28(3):036001

    Article  Google Scholar 

  33. Li X (2014) Numerical analysis and experimental research on laser induced thermal effect in bio-tissues. Tianjin University Press, Tianjin, pp 32–40

    Google Scholar 

  34. Mobley J, Vo-Dinh T (2003) Optical properties of tissue. In: Vo-Dinh T (ed) Biomedical photonics handbook. CRC Press, Boca Raton, pp 2-1-2–70

    Google Scholar 

  35. You MX, Mou ZX (2019) Selective stimulation of bullfrog sciatic nerve by gold nanorod assisted combined electrical and near-infrared stimulation. Biomed Microdevice 21:76

    Article  Google Scholar 

  36. Castoro M, Yoo P, Hincapie J, Hamann J, Ruble S, Wolf P et al (2010) Excitation properties of the right cervical vagus nerve in adult dogs. Exp Neurol 227(1):62–68

    Article  Google Scholar 

  37. Stewart J (2003) Peripheral nerve fascicles: anatomy and clinical relevance. Muscle Nerve 28(5):525–541

    Article  Google Scholar 

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Funding

This work was supported by the Nature Science Foundation of China Grant (No. 31500796).

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Correspondence to Zongxia Mou or Xing Wang.

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Appendix

Appendix

According to Beer-Lambert Law,

$$AU=\mathrm{lg}(1/T)=KCl,$$
(8)

Where,

T:

the transmittance (the ratio of transmitted light intensity to incident light intensity).

K :

the extinction coefficient of the solution (L/g/cm).

C :

the concentration of the solution (g/L).

l :

the optical path of the solution (cm).

In this paper, μα = 1/lα.

μα:

the absorption coefficient (1/cm).

l α :

the absorption length (cm).

l α :

is also the optical path when T = 1/e, where AUα = lg(1/T) = lge = 0.43429448. According to Formula (8), AUα = KClα, then

$${\mu }_{\alpha }=1/{l}_{\alpha }=KC/{AU}_{\alpha }.$$
(9)

From the measurement results we can see that AU is about 2 at λ = 808 nm, where C = 3e-5 g/l, and l = 1 cm. So according to Formula (8),

$$AU=KCl=2.$$
(10)

Where,

K and C is equal to those in Formula (9) and l is the equal the thickness of the cuvette (l = 1 cm). Then solve formulas (9) and (10), μα = 4.6 (1/cm) = 460 (1/m).

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Zhou, R., Mou, Z., Yang, D. et al. Theoretical simulation of the selective stimulation of axons in different areas of a nerve bundle by multichannel near-infrared lasers. Med Biol Eng Comput 60, 205–220 (2022). https://doi.org/10.1007/s11517-021-02475-y

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  • DOI: https://doi.org/10.1007/s11517-021-02475-y

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