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Arora Y, Walia P, Hayashibe M, et al. Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans. PLoS Comput Biol. 2021;17(10):e1009386doi: 10.1371/journal.pcbi.1009386.
Arora, Y., Walia, P., Hayashibe, M., Muthalib, M., Chowdhury, S. R., Perrey, S., & Dutta, A. (2021). Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans. PLoS computational biology, 17(10), e1009386. https://doi.org/10.1371/journal.pcbi.1009386
Arora, Yashika, et al. "Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans." PLoS computational biology vol. 17,10 (2021): e1009386. doi: https://doi.org/10.1371/journal.pcbi.1009386
Arora Y, Walia P, Hayashibe M, Muthalib M, Chowdhury SR, Perrey S, Dutta A. Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans. PLoS Comput Biol. 2021 Oct 06;17(10):e1009386. doi: 10.1371/journal.pcbi.1009386. eCollection 2021 Oct. PMID: 34613970; PMCID: PMC8494321.
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PLoS Comput Biol. 2021 Oct 06;17(10):e1009386. doi: 10.1371/journal.pcbi.1009386. eCollection 2021 Oct.

Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans.

PLoS computational biology

Yashika Arora, Pushpinder Walia, Mitsuhiro Hayashibe, Makii Muthalib, Shubhajit Roy Chowdhury, Stephane Perrey, Anirban Dutta

Affiliations

  1. School of Computing and Electrical Engineering, Indian Institute of Technology, Mandi, India.
  2. Neuroengineering and Informatics for Rehabilitation Laboratory, Department of Biomedical Engineering, University at Buffalo, Buffalo, New York, United States of America.
  3. Neuro-Robotics Lab, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
  4. Silverline Research, Brisbane, Australia.
  5. EuroMov Digital Health in Motion, University of Montpellier, Montpellier, France.

PMID: 34613970 PMCID: PMC8494321 DOI: 10.1371/journal.pcbi.1009386

Abstract

Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-compartmental neurovascular unit model consisting of the vascular smooth muscle, perivascular space, synaptic space, and astrocyte glial cell. Then, model linearization was performed on the physiologically detailed nonlinear model to find appropriate complexity (Akaike information criterion) to fit functional near-infrared spectroscopy (fNIRS) based measure of blood volume changes, called cerebrovascular reactivity (CVR), to high-definition (HD) tDCS. The grey-box linear model was applied on the fNIRS-based CVR during the first 150 seconds of anodal HD-tDCS in eleven healthy humans. The grey-box linear models for each of the four nested pathways starting from tDCS scalp current density that perturbed synaptic potassium released from active neurons for Pathway 1, astrocytic transmembrane current for Pathway 2, perivascular potassium concentration for Pathway 3, and voltage-gated ion channel current on the smooth muscle cell for Pathway 4 were fitted to the total hemoglobin concentration (tHb) changes from optodes in the vicinity of 4x1 HD-tDCS electrodes as well as on the contralateral sensorimotor cortex. We found that the tDCS perturbation Pathway 3 presented the least mean square error (MSE, median <2.5%) and the lowest Akaike information criterion (AIC, median -1.726) from the individual grey-box linear model fitting at the targeted-region. Then, minimal realization transfer function with reduced-order approximations of the grey-box model pathways was fitted to the ensemble average tHb time series. Again, Pathway 3 with nine poles and two zeros (all free parameters), provided the best Goodness of Fit of 0.0078 for Chi-Square difference test of nested pathways. Therefore, our study provided a systems biology approach to investigate the initial transient hemodynamic response to tDCS based on fNIRS tHb data. Future studies need to investigate the steady-state responses, including steady-state oscillations found to be driven by calcium dynamics, where transcranial alternating current stimulation may provide frequency-dependent physiological entrainment for system identification. We postulate that such a mechanistic understanding from system identification of the hemodynamics response to transcranial electrical stimulation can facilitate adequate delivery of the current density to the neurovascular tissue under simultaneous portable imaging in various cerebrovascular diseases.

Conflict of interest statement

The authors have declared that no competing interests exist.

References

  1. J Theor Biol. 2011 Oct 7;286(1):13-23 - PubMed
  2. Comput Methods Biomech Biomed Engin. 2017 Apr;20(5):508-518 - PubMed
  3. J Neurosci. 2011 Jul 6;31(27):9836-47 - PubMed
  4. Nat Rev Neurol. 2012 Dec;8(12):711-6 - PubMed
  5. Neuroimage. 2020 Dec;223:117311 - PubMed
  6. Brain Stimul. 2015 Sep-Oct;8(5):906-13 - PubMed
  7. Front Neurosci. 2016 Jun 20;10:261 - PubMed
  8. Hum Brain Mapp. 2020 Apr 15;41(6):1644-1666 - PubMed
  9. J Neurotrauma. 1992 Mar;9 Suppl 1:S333-48 - PubMed
  10. J Theor Biol. 2012 Oct 21;311:80-93 - PubMed
  11. Am J Physiol. 1990 Sep;259(3 Pt 2):H902-8 - PubMed
  12. Neuroimage. 2004;23 Suppl 1:S220-33 - PubMed
  13. J Theor Biol. 2016 Apr 7;394:1-17 - PubMed
  14. Microcirculation. 2018 Jan;25(1): - PubMed
  15. Nat Rev Neurosci. 2017 Jul;18(7):419-434 - PubMed
  16. Brain Stimul. 2021 Jan-Feb;14(1):80-87 - PubMed
  17. J Theor Biol. 2008 May 7;252(1):123-30 - PubMed
  18. Brain Stimul. 2015 Nov-Dec;8(6):1130-7 - PubMed
  19. Brain Stimul. 2016 Sep-Oct;9(5):641-661 - PubMed
  20. J Physiol. 2013 May 15;591(10):2563-78 - PubMed
  21. J Comput Neurosci. 2018 Feb;44(1):97-114 - PubMed
  22. Microcirculation. 2018 Jan;25(1): - PubMed
  23. Nat Commun. 2016 Mar 22;7:11100 - PubMed
  24. Neuroimage. 2014 Aug 15;97:71-80 - PubMed
  25. BMJ. 2020 Oct 9;371:m3692 - PubMed
  26. Neurophotonics. 2017 Oct;4(4):041503 - PubMed
  27. Cell. 2015 Nov 19;163(5):1064-1078 - PubMed
  28. Nat Commun. 2020 Jan 20;11(1):395 - PubMed
  29. Int J Neuropsychopharmacol. 2014 Dec 07;18(5): - PubMed
  30. J Appl Physiol (1985). 2006 Mar;100(3):1059-64 - PubMed
  31. Math Biosci. 1994 Feb;119(2):127-67 - PubMed
  32. PLoS One. 2016 Feb 05;11(2):e0147292 - PubMed
  33. Neuromodulation. 2020 Dec 19;: - PubMed
  34. PLoS One. 2012;7(8):e43640 - PubMed
  35. Biophys J. 2013 Nov 5;105(9):2046-54 - PubMed
  36. Proc Natl Acad Sci U S A. 2010 Jul 13;107(28):12670-5 - PubMed
  37. J Biomed Opt. 2005 Jan-Feb;10(1):11014 - PubMed
  38. Brain Stimul. 2021 Sep-Oct;14(5):1093-1094 - PubMed
  39. J Cereb Blood Flow Metab. 2012 Dec;32(12):2135-45 - PubMed
  40. Proc Natl Acad Sci U S A. 2020 Jul 14;117(28):16626-16637 - PubMed
  41. Brain Stimul. 2014 May-Jun;7(3):372-80 - PubMed
  42. Front Psychiatry. 2012 Oct 22;3:91 - PubMed
  43. J Physiol. 1996 Apr 15;492 ( Pt 2):419-30 - PubMed
  44. J Cereb Blood Flow Metab. 2016 Mar;36(3):492-512 - PubMed
  45. Clin Neurophysiol. 2012 Oct;123(10):2006-9 - PubMed
  46. Trends Neurosci. 1997 Oct;20(10):435-42 - PubMed
  47. Neuroimage. 2010 Feb 1;49(3):2304-10 - PubMed
  48. J Neural Eng. 2017 Aug;14(4):046029 - PubMed
  49. Cell Rep. 2018 Jun 26;23(13):3878-3890 - PubMed
  50. FEBS J. 2012 Sep;279(18):3513-27 - PubMed
  51. Mol Neurobiol. 2003 Oct;28(2):195-208 - PubMed
  52. Neurophotonics. 2018 Jul;5(3):030901 - PubMed
  53. Stroke. 1975 Sep-Oct;6(5):564-616 - PubMed
  54. Front Neurosci. 2018 Jun 19;12:409 - PubMed
  55. Philos Trans R Soc Lond B Biol Sci. 2005 May 29;360(1457):1025-41 - PubMed
  56. Neurophotonics. 2016 Jul;3(3):031405 - PubMed
  57. Brain Stimul. 2020 Nov - Dec;13(6):1753-1764 - PubMed
  58. Neuroimage. 2012 Nov 1;63(2):921-35 - PubMed
  59. Clin Neurophysiol. 2017 Sep;128(9):1774-1809 - PubMed
  60. J Neurosci Methods. 2016 Dec 1;274:71-80 - PubMed
  61. Front Syst Neurosci. 2015 Aug 10;9:107 - PubMed
  62. Front Syst Neurosci. 2015 Mar 09;9:27 - PubMed
  63. J Med Syst. 2015 Apr;39(4):205 - PubMed
  64. Brain. 2001 Mar;124(Pt 3):457-67 - PubMed
  65. Neuron. 2003 Jul 17;39(2):353-9 - PubMed
  66. Hum Brain Mapp. 2006 Nov;27(11):896-914 - PubMed
  67. Proc Natl Acad Sci U S A. 2018 Jun 26;115(26):6858-6863 - PubMed
  68. Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:3399-402 - PubMed
  69. Nat Neurosci. 2006 Nov;9(11):1397-1403 - PubMed
  70. Sci Adv. 2020 Nov 4;6(45): - PubMed
  71. Front Neurorobot. 2018 Oct 26;12:69 - PubMed
  72. Neuroscientist. 2011 Feb;17(1):37-53 - PubMed
  73. Neuroimage. 2018 Jul 1;174:69-86 - PubMed
  74. J ECT. 2018 Sep;34(3):144-152 - PubMed
  75. J Physiol. 2000 Sep 15;527 Pt 3:633-9 - PubMed
  76. J Theor Biol. 2015 Jan 7;364:49-70 - PubMed
  77. PLoS One. 2013 Aug 14;8(8):e70469 - PubMed
  78. Neuroimage. 2018 Jun;173:322-331 - PubMed
  79. Elife. 2020 Oct 05;9: - PubMed
  80. Front Neurosci. 2015 Dec 18;9:467 - PubMed
  81. Neuroimage. 2019 Aug 15;197:792-805 - PubMed
  82. Brain Stimul. 2013 Jan;6(1):25-39 - PubMed
  83. Neuroimage. 2007 Apr 15;35(3):1113-24 - PubMed
  84. Sci Adv. 2021 Jul 21;7(30): - PubMed
  85. Brain Topogr. 2019 Sep;32(5):825-858 - PubMed
  86. Neuroimage. 2020 Aug 1;216:116734 - PubMed
  87. J Theor Biol. 2008 Jan 7;250(1):172-85 - PubMed
  88. Ann Biomed Eng. 2020 Apr;48(4):1256-1270 - PubMed
  89. Brain Stimul. 2012 Jul;5(3):175-195 - PubMed
  90. Neuroimage. 2014 Feb 15;87:323-31 - PubMed
  91. J Biomed Opt. 2016 Sep;21(9):091312 - PubMed
  92. J Neurosci. 2002 Feb 1;22(3):1042-53 - PubMed
  93. Cereb Cortex. 1996 Mar-Apr;6(2):93-101 - PubMed
  94. Bioelectromagnetics. 2013 Jan;34(1):22-30 - PubMed
  95. Br J Anaesth. 1999 Mar;82(3):418-26 - PubMed
  96. Int J Vasc Med. 2011;2011:823525 - PubMed
  97. Brain Sci. 2020 Nov 13;10(11): - PubMed
  98. Elife. 2017 Feb 07;6: - PubMed
  99. PLoS One. 2020 Dec 23;15(12):e0244186 - PubMed
  100. Clin Neurophysiol. 2006 Jul;117(7):1623-9 - PubMed
  101. Trends Neurosci. 2018 Jul;41(7):409-413 - PubMed
  102. Med Phys. 2015 Sep;42(9):5391-403 - PubMed
  103. Neuroimage. 2010 Feb 1;49(3):2113-22 - PubMed
  104. PLoS One. 2012;7(11):e48802 - PubMed
  105. Circ Res. 2004 Nov 12;95(10):e73-81 - PubMed
  106. PLoS Comput Biol. 2008 Nov;4(11):e1000212 - PubMed
  107. Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:4764-4767 - PubMed
  108. Bioelectromagnetics. 1997;18(1):77-80 - PubMed
  109. Microcirculation. 2013 Apr;20(3):217-38 - PubMed
  110. Neuroimage. 2000 Oct;12(4):466-77 - PubMed
  111. Am J Physiol. 1995 Apr;268(4 Pt 1):C799-822 - PubMed
  112. Front Syst Neurosci. 2015 Mar 30;9:54 - PubMed
  113. FEBS J. 2009 Feb;276(4):903-22 - PubMed
  114. Front Cell Neurosci. 2016 Aug 08;10:188 - PubMed
  115. J Cereb Blood Flow Metab. 2001 Jan;21(1):77-84 - PubMed
  116. Neurosci Biobehav Rev. 2019 Jan;96:174-181 - PubMed
  117. Neuromodulation. 2018 Jun;21(4):348-354 - PubMed
  118. Circ Res. 1972 Aug;31(2):240-7 - PubMed
  119. J Cereb Blood Flow Metab. 2012 Jul;32(7):1259-76 - PubMed
  120. Brain Stimul. 2009 Oct;2(4):201-7, 207.e1 - PubMed
  121. PLoS Comput Biol. 2011 Jun;7(6):e1002070 - PubMed
  122. Neuroimage. 2011 Sep 1;58(1):26-33 - PubMed
  123. J Neurosci. 2009 Apr 22;29(16):5202-6 - PubMed
  124. Neuroimage. 2012 Feb 15;59(4):3933-40 - PubMed
  125. Neuroimage. 2020 Jul 15;215:116827 - PubMed
  126. Neuroimage. 2010 Feb 15;49(4):3039-46 - PubMed
  127. Adv Exp Med Biol. 2017;977:141-147 - PubMed
  128. Clin Neurophysiol Pract. 2016 Dec 21;2:19-25 - PubMed

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