نوع مقاله : مقاله کامل پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی امیرکبیر، تهران، ایران

2 استادیار، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی امیرکبیر، تهران، ایران

3 استاد، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی امیرکبیر، تهران، ایران

4 محقق، موسسه‌ی تحقیقاتی لوریت، تولسا، اکلاهما، آمریکا

10.22041/ijbme.2020.129325.1602

چکیده

تحریک الکتریکی جریان مستقیم فراجمجمه­ای (tDCS) پرکاربردترین روش تحریک غیرتهاجمی مغز بوده که چالش اساسی آن تفاوت­های بین فردی گزارش شده در پاسخ به این تحریک می­باشد. یکی از منابع ایجاد این اختلاف‌ها تفاوت در توزیع میدان الکتریکی بوده که به دلیل تفاوت در ساختارهای مغزی ایجاد می­شود. شواهد نشان می­دهد که میدان ناشی از tDCS می­تواند فعالیت‌های مغزی را تحت تاثیر قرار داده و باعث ایجاد تغییر در رفتار گردد اما ارتباط بین توزیع میدان و فعالیت­های مغزی هنوز مورد بررسی قرار نگرفته است. از این رو در این مطالعه‌ی متقاطع دوسو کور، tDCS با شدت 2 میلی­آمپر به قشر پیش­پیشانی 14 فرد وابسته به مت­آمفتامین اعمال شده و برای تعیین توزیع میدان و مشاهده‌ی فعالیت مغزی در پاسخ به نشانه­های مواد، تصویر تشدید مغناطیسی ساختاری و عمل‌کردی قبل و بعد از تحریک ثبت شده است. تحریک الکتریکی برای هر فرد یک مرتبه به صورت واقعی و یک مرتبه به صورت غیرواقعی (با فاصله‌ی حداقل یک هفته) انجام شده است. با استفاده از مدل­های سر مبتنی بر روش­های المان محدود برای نمایش توزیع میدان شبیه­سازی شده و آنالیز گروهی نشان داده شده که بیش‌ترین میدان در ناحیه‌ی پیش­پیشانی ایجاد شده (07/0±3424/0) و توزیع مکانی میدان در بین افراد متفاوت بوده است. داده­­های کارکردی حاکی از آن بوده که در تفاوت بین پاسخ به نشانه­های مواد و تصاویری که مربوط به مواد نیستند، تحریک واقعی در مقایسه با تحریک غیرواقعی فعالیت مغزی را در چین گیج‌گاهی فوقانی و قشر کمربندی خلفی کاهش داده (0001/0p<) اما همبستگی معناداری بین شدت میدان و تغییرات فعالیت مغزی به دست نیامده است. در این مطالعه یک روش کار برای ترکیب مدل­های سر با اطلاعات مربوط به عمل‌کرد مغز ارائه شده که تاکنون مورد بررسی قرار نگرفته و می­تواند دریچه­ای رو به درک بهتر مکانیسم اثر tDCS به شمار آید.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Effects of Transcranial Direct Current Stimulation based on Electric Field Distribution Patterns and Changes in Brain Activity

نویسندگان [English]

  • Ghazaleh Soleimani 1
  • Mehrdad Saviz 2
  • Farzad Towhidkhah 3
  • Hamed Ekhtiari 4

1 Ph.D. Student, Bioelectric Group, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

2 Assistant Professor, Bioelectric Group, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

3 Professor, Bioelectric Group, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

4 Associate Investigator, Laureate Institute of Brain Research (LIBR), Tulsa, Oklahoma, United States

چکیده [English]

Transcranial direct current stimulation (tDCS) is the most-used non-invasive brain stimulation method. However, the main challenge in tDCS studies is its heterogeneity and large inter-individual variability in response. Brain anatomy, that varies from person to person, can change electric field distribution patterns in the brain and should be considered as a source of variation. Previous findings support that tDCS-induced EFs affect brain activity and ultimately change behavioral outcomes. Nonetheless, the exact relationship between EFs and brain activity alterations has not yet been investigated. In this randomized double-blinded sham-controlled crossover study, 14 subjects with methamphetamine use disorders were recruited and tDCS with 2 mA current intensity was applied over the dorsolateral prefrontal cortex. Each subject participated in two sessions for sham or real stimulation with at least a 1-week washout period. In each session, structural and functional MRI during a cue-induced craving task were collected immediately before and after tDCS. Individualized computational head models were simulated based on structural MR images and finite element methods. Group-level analysis of the models showed inter-individual variability across the subjects with maximum electric field intensity in frontal pole (0.3424±0.07). Furthermore, functional data, based on a drug minus neutral contrast, showed that real versus sham stimulation decreased brain activity in superior temporal gyrus and posterior cingulate cortex (P<0.001). However, we did not find a significant correlation between induced EFs and brain activity alterations. In sum, in this study, we suggested a pipeline for integrating electric fields with functional neuroimaging data to bring new insights into the tDCS mechanism of action and future studies are required to establish, or to refute, this conclusion.

کلیدواژه‌ها [English]

  • Transcranial Direct Current Stimulation
  • Computational Head Model
  • Brain Activity
  • Addiction
  1. Nitsche, M. A., Cohen, L. G., Wassermann, E. M., Priori, A., Lang, N., Antal, A., ... & Pascual-Leone, A. (2008). Transcranial direct current stimulation: state of the art 2008. Brain stimulation, 1(3), 206-223.
  2. Woods, A. J., Antal, A., Bikson, M., Boggio, P. S., Brunoni, A. R., Celnik, P., ... & Knotkova, H. (2016). A technical guide to tDCS, and related non-invasive brain stimulation tools. Clinical neurophysiology, 127(2), 1031-1048.
  3. Boggio, P. S., Bermpohl, F., Vergara, A. O., Muniz, A. L., Nahas, F. H., Leme, P. B., ... & Fregni, F. (2007). Go-no-go task performance improvement after anodal transcranial DC stimulation of the left dorsolateral prefrontal cortex in major depression. Journal of affective disorders, 101(1-3), 91-98.
  4. Song, J. J., Vanneste, S., Van de Heyning, P., & De Ridder, D. (2012). Transcranial direct current stimulation in tinnitus patients: a systemic review and meta-analysis. The Scientific World Journal, 2012.
  5. Doruk, D., Gray, Z., Bravo, G. L., Pascual-Leone, A., & Fregni, F. (2014). Effects of tDCS on executive function in Parkinson's disease. Neuroscience letters, 582, 27-31.
  6. Brunelin, J., Mondino, M., Bation, R., Palm, U., Saoud, M., & Poulet, E. (2018). Transcranial direct current stimulation for obsessive-compulsive disorder: a systematic review. Brain sciences, 8(2), 37.
  7. Fregni, F., Boggio, P. S., Nitsche, M., Bermpohl, F., Antal, A., Feredoes, E., ... & Pascual-Leone, A. (2005). Anodal transcranial direct current stimulation of prefrontal cortex enhances working memory. Experimental brain research, 166(1), 23-30.
  8. Sparing, R., Dafotakis, M., Meister, I. G., Thirugnanasambandam, N., & Fink, G. R. (2008). Enhancing language performance with non-invasive brain stimulation—a transcranial direct current stimulation study in healthy humans. Neuropsychologia, 46(1), 261-268.
  9. Foerster, Á., Rocha, S., Wiesiolek, C., Chagas, A. P., Machado, G., Silva, E., ... & Monte‐Silva, K. (2013). Site‐specific effects of mental practice combined with transcranial direct current stimulation on motor learning. European Journal of Neuroscience, 37(5), 786-794.
  10. Ekhtiari, H., Tavakoli, H., Addolorato, G., Baeken, C., Bonci, A., Campanella, S., ... & Dannon, P. N. (2019). Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead. Neuroscience & Biobehavioral Reviews, 104, 118-140..
  11. Yang, L. Z., Shi, B., Li, H., Zhang, W., Liu, Y., Wang, H., ... & Hudak, J. (2017). Electrical stimulation reduces smokers’ craving by modulating the coupling between dorsal lateral prefrontal cortex and parahippocampal gyrus. Social Cognitive and Affective Neuroscience, 12(8), 1296-1302.
  12. Boggio, P. S., Zaghi, S., Villani, A. B., Fecteau, S., Pascual-Leone, A., & Fregni, F. (2010). Modulation of risk-taking in marijuana users by transcranial direct current stimulation (tDCS) of the dorsolateral prefrontal cortex (DLPFC). Drug and alcohol dependence, 112(3), 220-225.
  13. Shahbabaie, A., Ebrahimpoor, M., Hariri, A., Nitsche, M. A., Hatami, J., Fatemizadeh, E., ... & Ekhtiari, H. (2018). Transcranial DC stimulation modifies functional connectivity of large‐scale brain networks in abstinent methamphetamine users. Brain and behavior, 8(3), e00922.
  14. Batista, E. K., Klauss, J., Fregni, F., Nitsche, M. A., & Nakamura-Palacios, E. M. (2015). A randomized placebo-controlled trial of targeted prefrontal cortex modulation with bilateral tDCS in patients with crack-cocaine dependence. International Journal of Neuropsychopharmacology, 18(12), pyv066.
  15. Hsu, T. Y., Juan, C. H., & Tseng, P. (2016). Individual differences and state-dependent responses in transcranial direct current stimulation. Frontiers in human neuroscience, 10, 643.
  16. Li, L. M., Uehara, K., & Hanakawa, T. (2015). The contribution of interindividual factors to variability of response in transcranial direct current stimulation studies. Frontiers in cellular neuroscience, 9, 181.
  17. Laakso, I., Tanaka, S., Koyama, S., De Santis, V., & Hirata, A. (2015). Inter-subject variability in electric fields of motor cortical tDCS. Brain stimulation, 8(5), 906-913.
  18. Datta, A. (2012). Inter-individual variation during transcranial direct current stimulation and normalization of dose using MRI-derived computational models. Frontiers in psychiatry, 3, 91.
  19. Laakso, I., Mikkonen, M., Koyama, S., Hirata, A., & Tanaka, S. (2019). Can electric fields explain inter-individual variability in transcranial direct current stimulation of the motor cortex?. Scientific reports, 9(1), 1-10.
  20. Kim, J. H., Kim, D. W., Chang, W. H., Kim, Y. H., Kim, K., & Im, C. H. (2014). Inconsistent outcomes of transcranial direct current stimulation may originate from anatomical differences among individuals: electric field simulation using individual MRI data. Neuroscience letters, 564, 6-10.
  21. Datta, A., Bansal, V., Diaz, J., Patel, J., Reato, D., & Bikson, M. (2009). Gyri-precise head model of transcranial direct current stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad. Brain stimulation, 2(4), 201-207.
  22. Dmochowski, J. P., Datta, A., Bikson, M., Su, Y., & Parra, L. C. (2011). Optimized multi-electrode stimulation increases focality and intensity at target. Journal of neural engineering, 8(4), 046011.
  23. Gomez-Tames, J., Asai, A., Mikkonen, M., Laakso, I., Tanaka, S., Uehara, S., ... & Hirata, A. (2019). Group-level and functional-region analysis of electric-field shape during cerebellar transcranial direct current stimulation with different electrode montages. Journal of neural engineering, 16(3), 036001.
  24. Truong, D. Q., Magerowski, G., Blackburn, G. L., Bikson, M., & Alonso-Alonso, M. (2013). Computational modeling of transcranial direct current stimulation (tDCS) in obesity: impact of head fat and dose guidelines. NeuroImage: Clinical, 2, 759-766.
  25. Fritsch, B., Reis, J., Martinowich, K., Schambra, H. M., Ji, Y., Cohen, L. G., & Lu, B. (2010). Direct current stimulation promotes BDNF-dependent synaptic plasticity: potential implications for motor learning. Neuron, 66(2), 198-204.
  26. Rahman, A., Reato, D., Arlotti, M., Gasca, F., Datta, A., Parra, L. C., & Bikson, M. (2013). Cellular effects of acute direct current stimulation: somatic and synaptic terminal effects. The Journal of physiology, 591(10), 2563-2578.
  27. Cancel, L. M., Arias, K., Bikson, M., & Tarbell, J. M. (2018). Direct current stimulation of endothelial monolayers induces a transient and reversible increase in transport due to the electroosmotic effect. Scientific reports, 8(1), 1-13.
  28. Kronberg, G., Rahman, A., Sharma, M., Bikson, M., & Parra, L. C. (2020). Direct current stimulation boosts hebbian plasticity in vitro. Brain Stimulation, 13(2), 287-301.
  29. Lang, N., Siebner, H. R., Ward, N. S., Lee, L., Nitsche, M. A., Paulus, W., ... & Frackowiak, R. S. (2005). How does transcranial DC stimulation of the primary motor cortex alter regional neuronal activity in the human brain?. European Journal of Neuroscience, 22(2), 495-504.
  30. Polanía, R., Nitsche, M. A., & Paulus, W. (2011). Modulating functional connectivity patterns and topological functional organization of the human brain with transcranial direct current stimulation. Human brain mapping, 32(8), 1236-1249.
  31. Reato, D., Rahman, A., Bikson, M., & Parra, L. C. (2010). Low-intensity electrical stimulation affects network dynamics by modulating population rate and spike timing. Journal of Neuroscience, 30(45), 15067-15079.
  32. Esmaeilpour, Z., Shereen, A. D., Ghobadi‐Azbari, P., Datta, A., Woods, A. J., Ironside, M., ... & Ekhtiari, H. (2020). Methodology for tDCS integration with fMRI. Human Brain Mapping, 41(7), 1950-1967.
  33. Logothetis, N. K., & Pfeuffer, J. (2004). On the nature of the BOLD fMRI contrast mechanism. Magnetic resonance imaging, 22(10), 1517-1531.
  34. Howseman, A. M., & Bowtel, R. W. (1999). Functional magnetic resonance imaging: imaging techniques and contrast mechanisms. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 354(1387), 1179-1194.
  35. Nitsche, M. A., & Paulus, W. (2000). Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation. The Journal of physiology, 527(Pt 3), 633.
  36. Conti, C. L., & Nakamura-Palacios, E. M. (2014). Bilateral transcranial direct current stimulation over dorsolateral prefrontal cortex changes the drug-cued reactivity in the anterior cingulate cortex of crack-cocaine addicts. Brain Stimulation, 7(1), 130-132.
  37. Thielscher, A., Antunes, A., & Saturnino, G. B. (2015, August). Field modeling for transcranial magnetic stimulation: a useful tool to understand the physiological effects of TMS?. In 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC) (pp. 222-225). IEEE.
  38. Geuzaine, C., & Remacle, J. F. (2009). Gmsh: A 3‐D finite element mesh generator with built‐in pre‐and post‐processing facilities. International journal for numerical methods in engineering, 79(11), 1309-1331.
  39. Friston, K. J., Holmes, A. P., Poline, J. B., Grasby, P. J., Williams, S. C. R., Frackowiak, R. S., & Turner, R. (1995). Analysis of fMRI time-series revisited. Neuroimage, 2(1), 45-53.
  40. Fischer, D. B., Fried, P. J., Ruffini, G., Ripolles, O., Salvador, R., Banus, J., ... & Fox, M. D. (2017). Multifocal tDCS targeting the resting state motor network increases cortical excitability beyond traditional tDCS targeting unilateral motor cortex. Neuroimage, 157, 34-44.
  41. Mikkonen, M., Laakso, I., Tanaka, S., & Hirata, A. (2020). Cost of focality in TDCS: Interindividual variability in electric fields. Brain stimulation, 13(1), 117-124.
  42. Shahbabaie, A., Hatami, J., Farhoudian, A., Ekhtiari, H., Khatibi, A., & Nitsche, M. A. (2018). Optimizing electrode montages of transcranial direct current stimulation for attentional bias modification in early abstinent methamphetamine users. Frontiers in pharmacology, 9, 907.
  43. Sinha, R., & Li, C. S. (2007). Imaging stress‐and cue‐induced drug and alcohol craving: association with relapse and clinical implications. Drug and alcohol review, 26(1), 25-31.
  44. Fransson, P., & Marrelec, G. (2008). The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis. Neuroimage, 42(3), 1178-1184.
  45. Hester, R., Lubman, D. I., & Yücel, M. (2010). The role of executive control in human drug addiction. In Behavioral neuroscience of drug addiction (pp. 301-318). Springer, Berlin, Heidelberg.
  46. Spreng, R. N., Sepulcre, J., Turner, G. R., Stevens, W. D., & Schacter, D. L. (2013). Intrinsic architecture underlying the relations among the default, dorsal attention, and frontoparietal control networks of the human brain. Journal of cognitive neuroscience, 25(1), 74-86.
  47. Ma, N., Liu, Y., Fu, X. M., Li, N., Wang, C. X., Zhang, H., ... & Zhang, D. R. (2011). Abnormal brain default-mode network functional connectivity in drug addicts. PloS one, 6(1), e16560.
  48. Goldstein, R. Z., & Volkow, N. D. (2011). Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nature reviews neuroscience, 12(11), 652-669.
  49. Liston, C., Chen, A. C., Zebley, B. D., Drysdale, A. T., Gordon, R., Leuchter, B., ... & Dubin, M. J. (2014). Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological psychiatry, 76(7), 517-526.
  50. Alves, P. N., Foulon, C., Karolis, V., Bzdok, D., Margulies, D. S., Volle, E., & de Schotten, M. T. (2019). An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings. Communications biology, 2(1), 1-14.
  51. Kilts, C. D., Gross, R. E., Ely, T. D., & Drexler, K. P. (2004). The neural correlates of cue-induced craving in cocaine-dependent women. American Journal of Psychiatry, 161(2), 233-241.
  52. Park, M. S., Sohn, J. H., Suk, J. A., Kim, S. H., Sohn, S., & Sparacio, R. (2007). Brain substrates of craving to alcohol cues in subjects with alcohol use disorder. Alcohol & Alcoholism, 42(5), 417-422.
  53. Bonson, K. R., Grant, S. J., Contoreggi, C. S., Links, J. M., Metcalfe, J., Weyl, H. L., ... & London, E. D. (2002). Neural systems and cue-induced cocaine craving. Neuropsychopharmacology, 26(3), 376-386.
  54. Pelletier, S. J., & Cicchetti, F. (2015). Cellular and molecular mechanisms of action of transcranial direct current stimulation: evidence from in vitro and in vivo models. International Journal of Neuropsychopharmacology, 18(2), pyu047.
  55. Seo, H., Schaworonkow, N., Jun, S. C., & Triesch, J. (2016). A multi-scale computational model of the effects of TMS on motor cortex. F1000Research, 5.
  56. Saturnino, G. B., Puonti, O., Nielsen, J. D., Antonenko, D., Madsen, K. H., & Thielscher, A. (2019). Simnibs 2.1: A comprehensive pipeline for individualized electric field modelling for transcranial brain stimulation. In Brain and Human Body Modeling (pp. 3-25). Springer, Cham.
  57. Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L., ... & Fox, P. T. (2016). The human brainnetome atlas: a new brain atlas based on connectional architecture. Cerebral cortex, 26(8), 3508-3526.
  58. Hacker, C. D., Laumann, T. O., Szrama, N. P., Baldassarre, A., Snyder, A. Z., Leuthardt, E. C., & Corbetta, M. (2013). Resting state network estimation in individual subjects. Neuroimage, 82, 616-633.
  59. Suh, H. S., Lee, W. H., & Kim, T. S. (2012). Influence of anisotropic conductivity in the skull and white matter on transcranial direct current stimulation via an anatomically realistic finite element head model. Physics in Medicine & Biology, 57(21), 6961.
  60. Shahid, S. S., Bikson, M., Salman, H., Wen, P., & Ahfock, T. (2014). The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation. Journal of neural engineering, 11(3), 036002.