Inter-subject Variability in Electric Fields of Motor Cortical tDCS
The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features. We employed an approach that combine...
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| Vydané v: | Brain stimulation Ročník 8; číslo 5; s. 906 - 913 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
United States
Elsevier Inc
01.09.2015
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| Predmet: | |
| ISSN: | 1935-861X, 1876-4754, 1876-4754 |
| On-line prístup: | Získať plný text |
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| Abstract | The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features.
We employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields.
Anatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis.
We observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength.
The variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains.
[Display omitted]
•TDCS electric fields are modeled in anatomically-accurate models of 24 subjects.•We propose a surface-based inter-subject registration method for variability analysis of electric fields.•The extent and main reasons of inter-subject variation are quantitatively characterized.•Cerebrospinal fluid thickness explains one-half of the inter-subject variability in the electric fields. |
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| AbstractList | The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features.BACKGROUNDThe sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features.We employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields.OBJECTIVEWe employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields.Anatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis.METHODSAnatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis.We observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength.RESULTSWe observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength.The variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains.CONCLUSIONSThe variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains. Abstract Background The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features. Objective We employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields. Methods Anatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis. Results We observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength. Conclusions The variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains. The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features. We employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields. Anatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis. We observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength. The variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains. [Display omitted] •TDCS electric fields are modeled in anatomically-accurate models of 24 subjects.•We propose a surface-based inter-subject registration method for variability analysis of electric fields.•The extent and main reasons of inter-subject variation are quantitatively characterized.•Cerebrospinal fluid thickness explains one-half of the inter-subject variability in the electric fields. The sources of inter-subject variability in the efficacy of transcranial direct current stimulation (tDCS) remain unknown. One potential source of variations is the brain's electric field, which varies according to each individual's anatomical features. We employed an approach that combines imaging and computational modeling to quantitatively study the extent and primary causes of inter-subject variation in tDCS electric fields. Anatomically-accurate models of the head and brain of 24 males (age: 38.63 ± 11.24 years) were constructed from structural MRI. Finite-element method was used to computationally estimate the electric fields for tDCS of the motor cortex. Surface-based inter-subject registration of the electric field and functional MRI data was used for group level statistical analysis. We observed large differences in each individual's electric field patterns. However, group level analysis revealed that the average electric fields concentrated in the vicinity of the primary motor cortex. The variations in the electric fields in the hand motor area could be characterized by a normal distribution with a standard deviation of approximately 20% of the mean. The cerebrospinal fluid (CSF) thickness was the primary factor influencing an individual's electric field, thereby explaining 50% of the inter-individual variability, a thicker layer of CSF decreasing the electric field strength. The variability in the electric fields is related to each individual's anatomical features and can only be controlled using detailed image processing. Age was found to have a slight negative effect on the electric field, which might have implications on tDCS studies on aging brains. |
| Author | Hirata, Akimasa Laakso, Ilkka Tanaka, Satoshi Koyama, Soichiro De Santis, Valerio |
| Author_xml | – sequence: 1 givenname: Ilkka surname: Laakso fullname: Laakso, Ilkka email: laakso.ilkka@nitech.ac.jp organization: Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan – sequence: 2 givenname: Satoshi surname: Tanaka fullname: Tanaka, Satoshi organization: Laboratory of Psychology, Hamamatsu University School of Medicine, Shizuoka 431-3192, Japan – sequence: 3 givenname: Soichiro surname: Koyama fullname: Koyama, Soichiro organization: Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi 444-8585, Japan – sequence: 4 givenname: Valerio surname: De Santis fullname: De Santis, Valerio organization: Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan – sequence: 5 givenname: Akimasa surname: Hirata fullname: Hirata, Akimasa organization: Department of Computer Science and Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya 466-8555, Japan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26026283$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.3389/fnagi.2014.00146 10.1016/j.nicl.2013.05.011 10.1109/TBME.2011.2116019 10.1016/j.neulet.2014.01.054 10.1016/j.brs.2014.02.003 10.1016/j.jns.2006.05.062 10.1088/0031-9155/57/21/6961 10.1016/j.neuroimage.2013.11.015 10.1113/jphysiol.2010.190314 10.1038/ncpneuro0530 10.3389/fpsyt.2012.00091 10.1097/00001756-199807130-00020 10.3389/fnagi.2014.00115 10.1088/0031-9155/57/23/7753 10.1016/j.brs.2011.03.002 10.1088/1741-2560/10/3/036018 10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4 10.1006/nimg.1998.0395 10.1073/pnas.200033797 10.1016/j.neuroimage.2015.01.033 10.1006/nimg.2001.0786 10.1088/1741-2560/11/3/036002 10.1111/j.1469-7793.2000.t01-1-00633.x 10.1113/jphysiol.2012.249730 10.1016/j.brs.2014.02.004 10.3389/fnsys.2014.00025 10.1088/1741-2560/11/1/016002 10.1212/WNL.57.10.1899 10.1109/TBME.2014.2322774 10.1007/s00221-007-1149-z 10.1016/j.brs.2008.09.003 10.3389/fpsyt.2012.00083 10.1016/j.brs.2014.10.003 10.1016/j.brs.2009.03.005 10.1142/S012906571430006X |
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| References | Suh, Lee, Kim (bib37) 2012; 57 Ridding, Ziemann (bib12) 2010; 588 Kim, Kim, Chang, Kim, Kim, Im (bib22) 2014; 564 Opitz, Paulus, Will, Antunes, Thielscher (bib24) 2015; 109 Fischl, Sereno, Tootell, Dale (bib27) 1999; 8 Friston (bib28) 1994; 2 Parazzini, Fiocchi, Liorni, Priori, Ravazzani (bib23) 2014; 24 Good, Johnsrude, Ashburner, Henson, Friston, Frackowiak (bib33) 2001; 14 Bai, Dokos, Ho, Loo (bib26) 2014; 87 Truong, Magerowski, Blackburn, Bikson, Alonso-Alonso (bib18) 2013; 2 Datta, Bansal, Diaz, Patel, Reato, Bikson (bib14) 2009; 2 Batsikadze, Moliadze, Paulus, Kuo, Nitsche (bib32) 2013; 591 Nitsche, Paulus (bib2) 2000; 527 Dale, Fischl, Sereno (bib29) 1999; 9 Heise, Niehoff, Feldheim, Liuzzi, Gerloff, Hummel (bib36) 2014; 6 Brunoni, Nitsche, Bolognini (bib8) 2012; 5 Wagner, Rampersad, Aydin (bib20) 2014; 11 Fischl, Dale (bib30) 2000; 97 Boggio, Ferrucci, Rigonatti (bib34) 2006; 249 Noetscher, Yanamadala, Makarov, Pascual-Leone (bib21) 2014; 61 Fregni, Pascual-Leone (bib5) 2007; 3 Datta, Zhou, Su, Parra, Bikson (bib17) 2013; 10 Nitsche, Paulus (bib3) 2001; 57 Tanaka, Watanabe (bib7) 2009; 61 Tremblay, Lepage, Latulipe-Loiselle, Fregni, Pascual-Leone, Théoret (bib10) 2014; 7 Wiethoff, Hamada, Rothwell (bib11) 2014; 7 Fujiyama, Hyde, Hinder (bib35) 2014; 6 Laakso, Hirata (bib31) 2012; 57 Priori, Berardelli, Rona, Accornero, Manfredi (bib1) 1998; 9 Parazzini, Fiocchi, Rossi, Paglialonga, Ravazzani (bib15) 2011; 58 Datta, Truong, Minhas, Parra, Bikson (bib25) 2012; 3 Shahid, Bikson, Salman, Wen, Ahfock (bib19) 2014; 11 Krause, Cohen Kadosh (bib13) 2014; 8 López-Alonso, Cheeran, Rio-Rodriguez, Fernández-Del-Olmo (bib9) 2014; 7 Furubayashi, Terao, Arai (bib4) 2008; 185 Neuling, Wagner, Wolters, Zaehle, Herrmann (bib16) 2012; 3 Hummel, Celnik, Pascual-Leone (bib6) 2008; 1 Priori (10.1016/j.brs.2015.05.002_bib1) 1998; 9 Datta (10.1016/j.brs.2015.05.002_bib25) 2012; 3 Boggio (10.1016/j.brs.2015.05.002_bib34) 2006; 249 Furubayashi (10.1016/j.brs.2015.05.002_bib4) 2008; 185 Datta (10.1016/j.brs.2015.05.002_bib14) 2009; 2 Nitsche (10.1016/j.brs.2015.05.002_bib2) 2000; 527 Truong (10.1016/j.brs.2015.05.002_bib18) 2013; 2 Friston (10.1016/j.brs.2015.05.002_bib28) 1994; 2 Suh (10.1016/j.brs.2015.05.002_bib37) 2012; 57 Kim (10.1016/j.brs.2015.05.002_bib22) 2014; 564 Noetscher (10.1016/j.brs.2015.05.002_bib21) 2014; 61 Parazzini (10.1016/j.brs.2015.05.002_bib23) 2014; 24 Dale (10.1016/j.brs.2015.05.002_bib29) 1999; 9 Wiethoff (10.1016/j.brs.2015.05.002_bib11) 2014; 7 Parazzini (10.1016/j.brs.2015.05.002_bib15) 2011; 58 Fujiyama (10.1016/j.brs.2015.05.002_bib35) 2014; 6 Ridding (10.1016/j.brs.2015.05.002_bib12) 2010; 588 Brunoni (10.1016/j.brs.2015.05.002_bib8) 2012; 5 Krause (10.1016/j.brs.2015.05.002_bib13) 2014; 8 Tremblay (10.1016/j.brs.2015.05.002_bib10) 2014; 7 Heise (10.1016/j.brs.2015.05.002_bib36) 2014; 6 Wagner (10.1016/j.brs.2015.05.002_bib20) 2014; 11 Bai (10.1016/j.brs.2015.05.002_bib26) 2014; 87 Fischl (10.1016/j.brs.2015.05.002_bib30) 2000; 97 Good (10.1016/j.brs.2015.05.002_bib33) 2001; 14 Opitz (10.1016/j.brs.2015.05.002_bib24) 2015; 109 Fischl (10.1016/j.brs.2015.05.002_bib27) 1999; 8 Batsikadze (10.1016/j.brs.2015.05.002_bib32) 2013; 591 Nitsche (10.1016/j.brs.2015.05.002_bib3) 2001; 57 Fregni (10.1016/j.brs.2015.05.002_bib5) 2007; 3 Shahid (10.1016/j.brs.2015.05.002_bib19) 2014; 11 Tanaka (10.1016/j.brs.2015.05.002_bib7) 2009; 61 Datta (10.1016/j.brs.2015.05.002_bib17) 2013; 10 López-Alonso (10.1016/j.brs.2015.05.002_bib9) 2014; 7 Hummel (10.1016/j.brs.2015.05.002_bib6) 2008; 1 Laakso (10.1016/j.brs.2015.05.002_bib31) 2012; 57 Neuling (10.1016/j.brs.2015.05.002_bib16) 2012; 3 |
| References_xml | – volume: 87 start-page: 332 year: 2014 end-page: 344 ident: bib26 article-title: A computational modelling study of transcranial direct current stimulation montages used in depression publication-title: Neuroimage – volume: 249 start-page: 31 year: 2006 end-page: 38 ident: bib34 article-title: Effects of transcranial direct current stimulation on working memory in patients with Parkinson’s disease publication-title: J Neurol Sci – volume: 9 start-page: 179 year: 1999 end-page: 194 ident: bib29 article-title: Cortical surface-based analysis. i. segmentation and surface reconstruction publication-title: Neuroimage – volume: 1 start-page: 370 year: 2008 end-page: 382 ident: bib6 article-title: Controversy: noninvasive and invasive cortical stimulation show efficacy in treating stroke patients publication-title: Brain Stimul – volume: 61 start-page: 2488 year: 2014 end-page: 2498 ident: bib21 article-title: Comparison of cephalic and extracephalic montages for transcranial direct current stimulation–a numerical study publication-title: IEEE Trans Biomed Eng – volume: 57 start-page: 6961 year: 2012 end-page: 6980 ident: bib37 article-title: Influence of anisotropic conductivity in the skull and white matter on transcranial direct current stimulation via an anatomically realistic finite element head model publication-title: Phys Med Biol – volume: 97 start-page: 11050 year: 2000 end-page: 11055 ident: bib30 article-title: Measuring the thickness of the human cerebral cortex from magnetic resonance images publication-title: Proc Natl Acad Sci U S A – volume: 14 start-page: 21 year: 2001 end-page: 36 ident: bib33 article-title: A voxel-based morphometric study of ageing in 465 normal adult human brains publication-title: Neuroimage – volume: 6 start-page: 146 year: 2014 ident: bib36 article-title: Differential behavioral and physiological effects of anodal transcranial direct current stimulation in healthy adults of younger and older age publication-title: Front Aging Neurosci – volume: 3 start-page: 83 year: 2012 ident: bib16 article-title: Finite element model predicts current density distribution for clinical applications of tDCS and tACS publication-title: Front Psychiatry – volume: 3 start-page: 383 year: 2007 end-page: 393 ident: bib5 article-title: Technology insight: noninvasive brain stimulation in neurology-perspectives on the therapeutic potential of rTMS and tDCS publication-title: Nat Clin Pract Neurol – volume: 7 start-page: 372 year: 2014 end-page: 380 ident: bib9 article-title: Inter-individual variability in response to non-invasive brain stimulation paradigms publication-title: Brain Stimul – volume: 9 start-page: 2257 year: 1998 end-page: 2260 ident: bib1 article-title: Polarization of the human motor cortex through the scalp publication-title: Neuroreport – volume: 58 start-page: 1773 year: 2011 end-page: 1780 ident: bib15 article-title: Transcranial direct current stimulation: estimation of the electric field and of the current density in an anatomical human head model publication-title: IEEE Trans Biomed Eng – volume: 24 start-page: 1430006 year: 2014 ident: bib23 article-title: Computational modeling of transcranial direct current stimulation in the child brain: implications for the treatment of refractory childhood focal epilepsy publication-title: Int J Neural Syst – volume: 57 start-page: 1899 year: 2001 end-page: 1901 ident: bib3 article-title: Sustained excitability elevations induced by transcranial DC motor cortex stimulation in humans publication-title: Neurology – volume: 6 start-page: 115 year: 2014 ident: bib35 article-title: Delayed plastic responses to anodal tDCS in older adults publication-title: Front Aging Neurosci – volume: 185 start-page: 279 year: 2008 end-page: 286 ident: bib4 article-title: Short and long duration transcranial direct current stimulation (tDCS) over the human hand motor area publication-title: Exp Brain Res – volume: 10 start-page: 036018 year: 2013 ident: bib17 article-title: Validation of finite element model of transcranial electrical stimulation using scalp potentials: implications for clinical dose publication-title: J Neural Eng – volume: 2 start-page: 759 year: 2013 end-page: 766 ident: bib18 article-title: Computational modeling of transcranial direct current stimulation (tDCS) in obesity: Impact of head fat and dose guidelines publication-title: Neuroimage Clin – volume: 11 start-page: 036002 year: 2014 ident: bib19 article-title: The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation publication-title: J Neural Eng – volume: 7 start-page: 773 year: 2014 end-page: 783 ident: bib10 article-title: The uncertain outcome of prefrontal tDCS publication-title: Brain Stimul – volume: 591 start-page: 1987 year: 2013 end-page: 2000 ident: bib32 article-title: Partially non-linear stimulation intensity-dependent effects of direct current stimulation on motor cortex excitability in humans publication-title: J Physiol (Lond) – volume: 57 start-page: 7753 year: 2012 end-page: 7765 ident: bib31 article-title: Fast multigrid-based computation of the induced electric field for transcranial magnetic stimulation publication-title: Phys Med Biol – volume: 588 start-page: 2291 year: 2010 end-page: 2304 ident: bib12 article-title: Determinants of the induction of cortical plasticity by non-invasive brain stimulation in healthy subjects publication-title: J Physiol (Lond) – volume: 109 start-page: 140 year: 2015 end-page: 150 ident: bib24 article-title: Determinants of the electric field during transcranial direct current stimulation publication-title: Neuroimage – volume: 2 start-page: 5678 year: 1994 ident: bib28 article-title: Functional and effective connectivity in neuroimaging: a synthesis publication-title: Hum Brain Mapp – volume: 8 start-page: 272 year: 1999 end-page: 284 ident: bib27 article-title: High-resolution intersubject averaging and a coordinate system for the cortical surface publication-title: Hum Brain Mapp – volume: 5 start-page: 175 year: 2012 end-page: 195 ident: bib8 article-title: Clinical research with transcranial direct current stimulation (tDCS): challenges and future directions publication-title: Brain Stimul – volume: 564 start-page: 6 year: 2014 end-page: 10 ident: bib22 article-title: Inconsistent outcomes of transcranial direct current stimulation may originate from anatomical differences among individuals: electric field simulation using individual MRI data publication-title: Neurosci Lett – volume: 527 start-page: 633 year: 2000 end-page: 639 ident: bib2 article-title: Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation publication-title: J Physiol (Lond) – volume: 11 start-page: 016002 year: 2014 ident: bib20 article-title: Investigation of tDCS volume conduction effects in a highly realistic head model publication-title: J Neural Eng – volume: 8 start-page: 25 year: 2014 ident: bib13 article-title: Not all brains are created equal: the relevance of individual differences in responsiveness to transcranial electrical stimulation publication-title: Front Syst Neurosci – volume: 61 start-page: 53 year: 2009 end-page: 64 ident: bib7 article-title: Transcranial direct current stimulation–a new tool for human cognitive neuroscience publication-title: Brain Nerve – volume: 3 start-page: 91 year: 2012 ident: bib25 article-title: Inter-individual variation during transcranial direct current stimulation and normalization of dose using MRI-derived computational models publication-title: Front Psychiatry – volume: 2 start-page: 201 year: 2009 end-page: 207 ident: bib14 article-title: Gyri-precise head model of transcranial direct current stimulation: Improved spatial focality using a ring electrode versus conventional rectangular pad publication-title: Brain Stimul – volume: 7 start-page: 468 year: 2014 end-page: 475 ident: bib11 article-title: Variability in response to transcranial direct current stimulation of the motor cortex publication-title: Brain Stimul – volume: 6 start-page: 146 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib36 article-title: Differential behavioral and physiological effects of anodal transcranial direct current stimulation in healthy adults of younger and older age publication-title: Front Aging Neurosci doi: 10.3389/fnagi.2014.00146 – volume: 2 start-page: 759 year: 2013 ident: 10.1016/j.brs.2015.05.002_bib18 article-title: Computational modeling of transcranial direct current stimulation (tDCS) in obesity: Impact of head fat and dose guidelines publication-title: Neuroimage Clin doi: 10.1016/j.nicl.2013.05.011 – volume: 58 start-page: 1773 issue: 6 year: 2011 ident: 10.1016/j.brs.2015.05.002_bib15 article-title: Transcranial direct current stimulation: estimation of the electric field and of the current density in an anatomical human head model publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2011.2116019 – volume: 564 start-page: 6 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib22 article-title: Inconsistent outcomes of transcranial direct current stimulation may originate from anatomical differences among individuals: electric field simulation using individual MRI data publication-title: Neurosci Lett doi: 10.1016/j.neulet.2014.01.054 – volume: 7 start-page: 468 issue: 3 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib11 article-title: Variability in response to transcranial direct current stimulation of the motor cortex publication-title: Brain Stimul doi: 10.1016/j.brs.2014.02.003 – volume: 249 start-page: 31 issue: 1 year: 2006 ident: 10.1016/j.brs.2015.05.002_bib34 article-title: Effects of transcranial direct current stimulation on working memory in patients with Parkinson’s disease publication-title: J Neurol Sci doi: 10.1016/j.jns.2006.05.062 – volume: 57 start-page: 6961 issue: 21 year: 2012 ident: 10.1016/j.brs.2015.05.002_bib37 article-title: Influence of anisotropic conductivity in the skull and white matter on transcranial direct current stimulation via an anatomically realistic finite element head model publication-title: Phys Med Biol doi: 10.1088/0031-9155/57/21/6961 – volume: 87 start-page: 332 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib26 article-title: A computational modelling study of transcranial direct current stimulation montages used in depression publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.11.015 – volume: 588 start-page: 2291 issue: Pt 13 year: 2010 ident: 10.1016/j.brs.2015.05.002_bib12 article-title: Determinants of the induction of cortical plasticity by non-invasive brain stimulation in healthy subjects publication-title: J Physiol (Lond) doi: 10.1113/jphysiol.2010.190314 – volume: 3 start-page: 383 issue: 7 year: 2007 ident: 10.1016/j.brs.2015.05.002_bib5 article-title: Technology insight: noninvasive brain stimulation in neurology-perspectives on the therapeutic potential of rTMS and tDCS publication-title: Nat Clin Pract Neurol doi: 10.1038/ncpneuro0530 – volume: 3 start-page: 91 year: 2012 ident: 10.1016/j.brs.2015.05.002_bib25 article-title: Inter-individual variation during transcranial direct current stimulation and normalization of dose using MRI-derived computational models publication-title: Front Psychiatry doi: 10.3389/fpsyt.2012.00091 – volume: 9 start-page: 2257 issue: 10 year: 1998 ident: 10.1016/j.brs.2015.05.002_bib1 article-title: Polarization of the human motor cortex through the scalp publication-title: Neuroreport doi: 10.1097/00001756-199807130-00020 – volume: 6 start-page: 115 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib35 article-title: Delayed plastic responses to anodal tDCS in older adults publication-title: Front Aging Neurosci doi: 10.3389/fnagi.2014.00115 – volume: 57 start-page: 7753 issue: 23 year: 2012 ident: 10.1016/j.brs.2015.05.002_bib31 article-title: Fast multigrid-based computation of the induced electric field for transcranial magnetic stimulation publication-title: Phys Med Biol doi: 10.1088/0031-9155/57/23/7753 – volume: 5 start-page: 175 issue: 3 year: 2012 ident: 10.1016/j.brs.2015.05.002_bib8 article-title: Clinical research with transcranial direct current stimulation (tDCS): challenges and future directions publication-title: Brain Stimul doi: 10.1016/j.brs.2011.03.002 – volume: 10 start-page: 036018 issue: 3 year: 2013 ident: 10.1016/j.brs.2015.05.002_bib17 article-title: Validation of finite element model of transcranial electrical stimulation using scalp potentials: implications for clinical dose publication-title: J Neural Eng doi: 10.1088/1741-2560/10/3/036018 – volume: 8 start-page: 272 issue: 4 year: 1999 ident: 10.1016/j.brs.2015.05.002_bib27 article-title: High-resolution intersubject averaging and a coordinate system for the cortical surface publication-title: Hum Brain Mapp doi: 10.1002/(SICI)1097-0193(1999)8:4<272::AID-HBM10>3.0.CO;2-4 – volume: 61 start-page: 53 issue: 1 year: 2009 ident: 10.1016/j.brs.2015.05.002_bib7 article-title: Transcranial direct current stimulation–a new tool for human cognitive neuroscience publication-title: Brain Nerve – volume: 9 start-page: 179 issue: 2 year: 1999 ident: 10.1016/j.brs.2015.05.002_bib29 article-title: Cortical surface-based analysis. i. segmentation and surface reconstruction publication-title: Neuroimage doi: 10.1006/nimg.1998.0395 – volume: 97 start-page: 11050 issue: 20 year: 2000 ident: 10.1016/j.brs.2015.05.002_bib30 article-title: Measuring the thickness of the human cerebral cortex from magnetic resonance images publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.200033797 – volume: 109 start-page: 140 year: 2015 ident: 10.1016/j.brs.2015.05.002_bib24 article-title: Determinants of the electric field during transcranial direct current stimulation publication-title: Neuroimage doi: 10.1016/j.neuroimage.2015.01.033 – volume: 14 start-page: 21 issue: 1 Pt 1 year: 2001 ident: 10.1016/j.brs.2015.05.002_bib33 article-title: A voxel-based morphometric study of ageing in 465 normal adult human brains publication-title: Neuroimage doi: 10.1006/nimg.2001.0786 – volume: 2 start-page: 5678 issue: 1–2 year: 1994 ident: 10.1016/j.brs.2015.05.002_bib28 article-title: Functional and effective connectivity in neuroimaging: a synthesis publication-title: Hum Brain Mapp – volume: 11 start-page: 036002 issue: 3 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib19 article-title: The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation publication-title: J Neural Eng doi: 10.1088/1741-2560/11/3/036002 – volume: 527 start-page: 633 issue: Pt 3 year: 2000 ident: 10.1016/j.brs.2015.05.002_bib2 article-title: Excitability changes induced in the human motor cortex by weak transcranial direct current stimulation publication-title: J Physiol (Lond) doi: 10.1111/j.1469-7793.2000.t01-1-00633.x – volume: 591 start-page: 1987 issue: Pt 7 year: 2013 ident: 10.1016/j.brs.2015.05.002_bib32 article-title: Partially non-linear stimulation intensity-dependent effects of direct current stimulation on motor cortex excitability in humans publication-title: J Physiol (Lond) doi: 10.1113/jphysiol.2012.249730 – volume: 7 start-page: 372 issue: 3 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib9 article-title: Inter-individual variability in response to non-invasive brain stimulation paradigms publication-title: Brain Stimul doi: 10.1016/j.brs.2014.02.004 – volume: 8 start-page: 25 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib13 article-title: Not all brains are created equal: the relevance of individual differences in responsiveness to transcranial electrical stimulation publication-title: Front Syst Neurosci doi: 10.3389/fnsys.2014.00025 – volume: 11 start-page: 016002 issue: 1 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib20 article-title: Investigation of tDCS volume conduction effects in a highly realistic head model publication-title: J Neural Eng doi: 10.1088/1741-2560/11/1/016002 – volume: 57 start-page: 1899 issue: 10 year: 2001 ident: 10.1016/j.brs.2015.05.002_bib3 article-title: Sustained excitability elevations induced by transcranial DC motor cortex stimulation in humans publication-title: Neurology doi: 10.1212/WNL.57.10.1899 – volume: 61 start-page: 2488 issue: 9 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib21 article-title: Comparison of cephalic and extracephalic montages for transcranial direct current stimulation–a numerical study publication-title: IEEE Trans Biomed Eng doi: 10.1109/TBME.2014.2322774 – volume: 185 start-page: 279 issue: 2 year: 2008 ident: 10.1016/j.brs.2015.05.002_bib4 article-title: Short and long duration transcranial direct current stimulation (tDCS) over the human hand motor area publication-title: Exp Brain Res doi: 10.1007/s00221-007-1149-z – volume: 1 start-page: 370 issue: 4 year: 2008 ident: 10.1016/j.brs.2015.05.002_bib6 article-title: Controversy: noninvasive and invasive cortical stimulation show efficacy in treating stroke patients publication-title: Brain Stimul doi: 10.1016/j.brs.2008.09.003 – volume: 3 start-page: 83 year: 2012 ident: 10.1016/j.brs.2015.05.002_bib16 article-title: Finite element model predicts current density distribution for clinical applications of tDCS and tACS publication-title: Front Psychiatry doi: 10.3389/fpsyt.2012.00083 – volume: 7 start-page: 773 issue: 6 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib10 article-title: The uncertain outcome of prefrontal tDCS publication-title: Brain Stimul doi: 10.1016/j.brs.2014.10.003 – volume: 2 start-page: 201 issue: 4 year: 2009 ident: 10.1016/j.brs.2015.05.002_bib14 article-title: Gyri-precise head model of transcranial direct current stimulation: Improved spatial focality using a ring electrode versus conventional rectangular pad publication-title: Brain Stimul doi: 10.1016/j.brs.2009.03.005 – volume: 24 start-page: 1430006 issue: 2 year: 2014 ident: 10.1016/j.brs.2015.05.002_bib23 article-title: Computational modeling of transcranial direct current stimulation in the child brain: implications for the treatment of refractory childhood focal epilepsy publication-title: Int J Neural Syst doi: 10.1142/S012906571430006X |
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| SubjectTerms | Adult Analysis of Variance Brain Waves Electric field Finite-element method Humans Inter-subject variability Male Middle Aged Motor cortex Motor Cortex - physiology Neurology tDCS Transcranial Direct Current Stimulation - methods |
| Title | Inter-subject Variability in Electric Fields of Motor Cortical tDCS |
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