Transcranial Current Brain Stimulation (tCS): Models and Technologies

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Transcranial Current Brain Stimulation (tCS):Models and Technologies

Giulio Ruffini, Fabrice Wendling, Isabelle Merlet, Behnam Molaee-Ardekani, Abeye Mekonnen,Ricardo Salvador, Aureli Soria-Frisch, Carles Grau, Stephen Dunne, and Pedro C. Miranda

Abstract—In this paper, we provide a broad overview of modelsand technologies pertaining to transcranial current brain stimu-lation (tCS), a family of related noninvasive techniques includingdirect current (tDCS), alternating current (tACS), and randomnoise current stimulation (tRNS). These techniques are based onthe delivery of weak currents through the scalp (with electrodecurrent intensity to area ratios of about 0.3-5 A/m ) at low fre-quencies (typically 1kHz) resulting in weak electric fields in thebrain (with amplitudes of about 0.2-2 V/m). Here we review thebiophysics and simulation of noninvasive, current-controlled gen-eration of electric fields in the human brain and the models for theinteraction of these electric fields with neurons, including a surveyof in vitro and in vivo related studies. Finally, we outline directionsfor future fundamental and technological research.

Index Terms—Brain stimulation, electrical stimulation, tran-scranial alternating current (tACS), transcranial current stim-ulation (tCS), transcranial direct current (tDCS), transcranialrandom noise current stimulation (tRNS).

I. INTRODUCTION

D URING the last decade we have witnessed a rapid in-crease in the use of transcranial current stimulation for

both research and clinical applications. In this paper, we providean overview of some important aspects in this field—funda-mental models and emerging technologies—and suggest somedirections for further research.Noninvasive current brain stimulation methods, namely

transcranial direct current stimulation (tDCS) and related

Manuscript received January 03, 2012; revised March 08, 2012; acceptedMay 09, 2012. This work was supported in part by the HIVE EU FP7 Project.The project HIVE acknowledges the support of the Future and Emerging Tech-nologies (FET) program within the Seventh Framework Program for Researchof the European Commission, under FET-Open Grant 222079.G. Ruffini, A. Soria-Frish, and S. Dunne are with the Starlab Neuro-

science Research, Starlab Barcelona, 08022 Barcelona, Spain (e-mail: [email protected]; [email protected]; [email protected]).C. Grau is with the Starlab Neuroscience Research, Starlab Barcelona, 08022

Barcelona, Spain, and also with the Neurodynamics Laboratory, Departmentof Psychiatry and Clinical Psychobiology, University of Barcelona, 8035Barcelona, Spain (e-mail: [email protected]).F. Wendling, I. Merlet, and B. Molaee-Ardekani are with INSERM, U642,

Rennes F-35000, France, and the Université de Rennes 1, F-35000 Rennes,France (e-mail: [email protected]; [email protected]; [email protected]).A. Mekonnen and R. Salvador are with the Institute of Biophysics and

Biomedical Engineering, Faculty of Science, University of Lisbon, 1749-016Lisbon, Portugal (e-mail: [email protected]; [email protected]).P. C. Miranda is with the Institute of Biophysics and Biomedical Engi-

neering, Faculty of Science, University of Lisbon, 1749-016 Lisbon, Portugal,and also with Neuroelectrics Barcelona, 08022 Barcelona, Spain (e-mail:[email protected]).Digital Object Identifier 10.1109/TNSRE.2012.2200046

techniques [transcranial alternating current stimulation (tACS),and transcranial random noise stimulation (tRNS)]—all ofwhich we refer to generically as tCS—stimulate the brain bygenerating electric fields through the delivery of currents tran-scranially from the scalp. These subthreshold neuromodulationtechniques provide a practical, complementary alternativeto invasive stimulation. Although not treated here, we pointout that transcranial magnetic stimulation (TMS) is a relatedand important noninvasive technique. TMS is based on theapplication of strong, short (pulsed), localized electric fieldsto the cortex, and, unlike tCS, is capable of inducing actionpotentials—see, e.g., [1]. Other suprathreshold noninvasivetechniques include transcranial (current) electrical stimulation(TES) and electro-convulsive therapy (ECT), both of whichinvolve much stronger currents and electric fields in the brainthan tCS.Here, we present an overview of some important aspects of

tCS: science, modeling, and new technologies. In Section II, wereview the theory of generation of electric fields in tCS: electricfield models and related stimulation technologies. In Section III,we review the interaction of electric fields with neurons and neu-ronal populations as well as long-term (plastic) effects. Finally,in Section IV we outline directions for further research.

II. GENERATION OF ELECTRIC FIELDS IN TCS

In this section, we review aspects related to the spatial andtemporal characteristics of the electric field produced in thebrain during transcranial electric current stimulation using weakcurrents (in the order of a few milliAmperes) applied by rela-tively large area electrodes in the scalp (typically 9–35 cmbut ranging more widely from 2 to 50 cm ).

A. Quasistatic Approximation

Given the low frequencies involved in tCS (dc to 1 kHz)and the dielectric properties of head tissues (conductivity

and relative permittivity ), several approxima-tions can be made which simplify the determination of the elec-tric field distribution [2]–[4]. The first “quasi-static” approxi-mation consists of neglecting propagation effects and is justi-fied by the fact that the electromagnetic wavelength in the rangedc-10 kHz is several orders of magnitude larger than the dimen-sions of the human head. This means that the electric field varieswith no significant phase differences throughout the brain. Thesecond approximation stems from the fact that the effect of themagnetic field produced by the currents in the tissue is negli-gible. Finally, capacitive effects are neglected and the tissue istreated as a purely resistive medium. The main consequences of

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2 IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

the quasistatic approximation are that the spatial and the tem-poral variations of the electric field can be described separatelywith the temporal variation of the total electric field in the brainmirroring that of the stimulus waveform. For human tissues inthe head, the approximation is valid in the range dc to more than10 kHz [5]. Capacitive currents may have to be taken into ac-count above 10 kHz.

B. Dielectric Properties of Head Tissues

The dielectric properties of the tissues play a key role in thecomputation of the electric field distribution in the brain duringtranscranial stimulation. In general, the relationship between theapplied electric field and the total current density is givenby

(1)

where, in the frequency domain, is the com-plex conductivity of the tissue, is the angular frequency, andand are its electrical conductivity and relative permittivity,

respectively. The conductivity is approximately constant below10 kHzwhereas the relative permittivity tends to increase by oneor two orders of magnitude as the frequency decreases from 10kHz to dc [6]. Even so, biological tissues are considered pre-dominantly resistive in this frequency range—i.e., .As far as the electric field is concerned, only the ratio of the dif-ferent conductivity values is relevant [7]. One of the earliest ref-erences for low frequency resistive properties of biological tis-sues is the compilation by Geddes and Baker [8]. In 1989, Fosteret al. reviewed the dielectric properties of tissues and biologicalmaterials from dc to 20 GHz [9]. Other reviews were presentedby Stuchly and Stuchly [10] and Duck [11]. Gabriel reported acomprehensive study of tissue dielectric properties [12]–[14].Experimental data were fitted across a wide frequency range formany different tissues. The authors pointed out that given thescarcity of data at low frequencies, the fitted data must be usedwith caution [14]. More recently, Baumann [15] reported a con-stant value of 1.79 S/m for the conductivity of cerebrospinalfluid (CSF) at 37 C in the range 10 Hz to 10 kHz. Logothetisreported an average value of 0.404 S/m for the conductivityof gray matter that is practically frequency independent in therange 1 Hz to 10 kHz [16].The conductivity of the skull has a major impact on the elec-

tric field in the brain because it is considerably lower than that ofthe surrounding tissues. It is also anisotropic and nonuniform.An average isotropic value of 0.0056 S/m was introduced byRush and Driscoll [17], corresponding to a brain to skull con-ductivity ratio of 80:1. However, recent studies employing a va-riety of sample types [18]–[22] and techniques [23], [24], reporthigher values for the conductivity of the skull and indicate thatthe average brain to conductivity ratio is likely to lie between40:1 and 20:1.It has been proposed that estimates of the conductivity tensor

can be obtained in vivo from diffusion tensor magnetic reso-nance data due to the strong linear relationship that exists be-tween the two tensors [25]. This approach was implemented toinvestigate the effect of white matter anisotropy on EEG source

localization, first without [26] and then with a normalization oftensor ellipsoid volume [27]–[29].

C. Spatial Distribution of Electric Field

A necessary first step in understanding the effects of tCS is todetermine the spatial distribution of the generated electric fieldin the brain. In the quasistatic regime of tCS, the electric fieldis given by the negative gradient of the electric potential, ,

i.e., . The electric field and the current density, , arerelated by , where is the electric conductivity of thetissue. Physically, the electric fields originate from charge ac-cumulation occurring at locations where conductivities are spa-tially varying (see Section III-A). In steady state, the electricpotential in a conductor obeys the current continuity equation

(2)

which has a unique solution given appropriate boundary condi-tions. Once the electric potential is known, the electric field andthe current density can be computed. Analytical solutions canbe obtained in some simple cases, but numerical methods haveto be used when complex geometries are involved.Rush and Driscoll [17], [30] obtained an analytical solution

for the potential variation in a three-layer spherical head model(scalp, skull and brain) due to two point electrodes on the scalp,with good agreement with experimental measurements. Theyinvestigated the effect of electrode separation on the currentdensity distribution and estimated that if the electrodes wereplaced on the occipital and frontal bones then as much as 45%of the injected current would penetrate into the brain. Saypolet al. used this model to compare and contrast the electric fielddistribution during transcranial electric and magnetic stimula-tion [31]. Ferdjallah extended the solution to four layers: scalp,skull, CSF and brain [32].A limitation of these studies is that they model point elec-

trodes, while electrodes used in tDCS are rather large—nor-mally about 9–35 cm . Stecker extended Rush and Driscoll’sanalytical solution to electrodes of finite size and investigatedthe effect of size on the current distribution [33]. Miranda etal. implemented a spherical head model using the finite ele-ment method (FE) to investigate the current density distributiontaking into account large electrode sizes [34], finding electricfield magnitude maxima of about 0.2 V/m for current intensi-ties of 2 mA. They found that the current density on the scalp ishighest in a narrow band under the perimeter of the electrodes.In the brain, the current density under the electrode was muchweaker andmore uniform due the attenuating and blurring effectof the skull. About 40%–60% of the injected current penetratedinto the brain, depending on the inter-electrode distance. Thecurrent direction in the brain was predominantly radial underthe electrode and tangential between electrodes. Datta also useda FE spherical head model to study the focality of different com-binations of disc and ring electrodes [35] and found that de-creasing electrode separation improved focality but increasedshunting through the scalp. Use of more than two disc electrodesor of ring electrodes allowed increasing focality in the sense thatthe current density could be made higher under one electrodeand lower under the others. Wagner developed a more realistic

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RUFFINI et al.: TRANSCRANIAL CURRENT BRAIN STIMULATION (TCS): MODELS AND TECHNOLOGIES 3

head FE model for tDCS based on MR images which includedfive tissue types: scalp, skull, CSF, grey and white matter [36].Using this model, they investigated the effect of electrode posi-tion, electrode size and the presence of cortical lesions.Recent head models, also based on MR images, include

greater structural detail. Some of these models use hexahe-dral meshes, which are easier to generate from image voxels,while others use tetrahedral meshes to represent the smoothcortical surface more realistically. Datta et al. used a realistichead model with seven tissues to compare the focality of twodifferent electrode montages and emphasized the importanceof the sulci and gyri on the electric field distribution [37]. Theylater used the same model to study the effect of skull defectsand skull plates on the current in the brain [38]. Sadleir builta realistic head model incorporating ten different tissues andexamined the current density in various predefined regionsof interest in the brain [39]. The model presented in [40]emphasized an accurate representation of the cortical surfaces,particularly the CSF-gray matter interface, and contrary toexpectation, the current density was found to be low in thegyri directly under a 25 cm electrode. Parazzini et al. useda head model with 40 different tissue types and investigatedthe effect of electrode area on the electric field distribution[41]. According to calculations performed using realistic headmodels, the maximum magnitude of the electric field in thegray matter is about 0.2–1.5 V/m for a current of 1 mA appliedthrough large electrodes (25–35 cm ).In most head models for tCS the skull is represented as an

isotropic tissue—yet the skull is anisotropic and nonuniform.Some models have shown that skull anisotropy has a major ef-fect on the electric field distribution in tCS [42], [43] and somepapers address the fundamental question of how to model skullanisotropy [22], [44].Finally, we note that empirical data on the current density in

the brain during tDCS is largelymissing. Dymond et al. reportedvalues for the electric field of 0.6–1.6 V/m for a current intensityof 1 mA; the stimulation electrodes were placed bilaterally overthe frontal pole and the mastoids and the recording electrodeswere implanted near the hippocampus [45]. Since in vivo mea-surements of the electric field are difficult to perform in humans,model validation may have to rely on testing other predictions,such as the variation of the electric field with electrode area orthe optimal electrode placement relative to the target area [46].

D. Electrodes and Montages in TDCSThe usual electrode montage for tDCS is to place an “active”

electrode over the region to be affected and a “reference” elec-trode over a region where the effect of the current is thought tobe minimal. For example, the “active” electrode may be placedover the primary motor cortex and the “reference” electrodeover the contralateral eyebrow [47]. If both electrodes have thesame area then the magnitude of the current density in the brainunderneath will be similar, so such terminology is misleading:anodal stimulation under one of the electrodes implies cathodalstimulation under the other and vice versa [48].Electrodes in tDCS usually have areas of 35 cm (e.g.,

[49]) or 25 cm each (e.g., [50]). The use of large electrodesis perceived as being safer since they should produce lower

current densities in the scalp and in the brain. Recently, theuse of smaller electrodes was shown to achieve more focalstimulation and, conversely, the use of larger electrodes wasshown to render stimulation less effective [48]. Thus, thecombination of two electrodes of different sizes providesincreased focality in the sense that the electric field under oneelectrode may be larger than the electric field under the other.However, it is not clear yet how the current intensity should beadjusted as a function of electrode area [51]. Another methodto avoid stimulating two brain regions simultaneously is toplace one of the two electrodes below the neck [52]. Concernregarding stimulation of brainstem structures when using anextracephalic electrode may be unjustified [53]. Contrary toexpectation, experimental evidence suggests that the durationand magnitude of after effects depends on the distance betweenthe cranial and the extracephalic electrodes [54].Increased focality can also be achieved using concentric ring

electrodes [35] or a combination of five small electrodes withfour of them placed on a ring around the central one [37]. Inthese cases, improved focality results from the short distance be-tween electrodes, with a concomitant increase in the percentageof the current shunted through the scalp. The use of small elec-trodes for stimulation requires the choice of appropriate elec-trode and gel materials [55].A comprehensive synopsis of tDCS studies published be-

tween 1998 and early 2008, including electrode positions, wascompiled by Nitsche et al. [56]. Positions for one of the elec-trodes include the motor cortex (M1, hand area, leg area, C3/C4,premotor cortex), the somatosensory cortex (S1), the visualcortex (Oz, left V5), the frontal cortex (DLPFC, F3, F4, Fp3),the parietal cortex (P6, P8, CP5), the parietotemporal cortex(P3-T5, P4-T6) and the cerebellum. The second electrode wasusually positioned over the contralateral eyebrow, but otherpositions have also been used, such as Cz, the contralateralDLPFC for DLPFC stimulation, mastoids, chin, neck and rightdeltoid muscle. Using the EEG 10/20 or 10/10 InternationalSystem [57], [58] to position one or both electrodes on thescalp should improve reproducibility and facilitate placing theelectrodes over the selected anatomical target [59].The most often used current intensity is 1 mA but in some

studies this value was increased to 2 mA [56]. Polarity is an im-portant factor on the outcome of stimulation since it determinesthe direction of the field relative to the stimulated neurons. In themotor cortex, anodal stimulation increases cortical excitabilitywhereas cathodal stimulation decreases it [47]. Varying the in-jected current intensity by a certain factor, e.g., doubling it, fora given electrode montage does not affect the spatial distribu-tion or orientation of the electric field or of the current densityfield—it simply changes their magnitudes by that same factor.Changing the stimulus polarity merely reverses the direction ofthese fields.

E. tACS and tRNSTranscranial electric stimulation using weak alternating cur-

rents (tACS) has also been shown to influence brain function.The underlying idea is that the frequency used in the stimula-tion should match the brain waves or rhythms that are charac-teristic of the brain function to be influenced [60]–[63]. Such

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entrainment has been shown recently in vitro [64], as discussedin Section III-B. Terney et al. showed that stimulation with acurrent, whose amplitude varied randomly in time (tRNS) witha frequency spectrum of 100–640 Hz, was also able to increasethe excitability of the motor cortex [65], [66]. As discussed pre-viously, the calculation of the electric field distribution in tACSand tRNS is not fundamentally different from the tDCS case,because the quasistatic approximation holds in both instances.The temporal evolution of the electric field matches that of thestimulation current.

F. Multichannel Systems and FocalityWhen using two or more electrodes it is possible to choose

the position of the electrodes so as to optimize stimulation ata chosen target by making the relative magnitude of the elec-tric field at the target point as large as possible. A method todo this was implemented for two point electrodes in [67]. Later,the same group devised another method to maximize the mag-nitude of the electric field at the target location using two arraysof 4 3 electrodes placed at fixed positions on the scalp [68].The electric field magnitude distribution was optimized by con-trolling the intensity and the polarity of the current injected intoeach electrode. More sophisticated methods that can optimizeboth the magnitude of the electric field and its direction in a thetarget region have been reported [69]. In general, a greater inten-sity at the target point was achieved at the expense of focality.Nevertheless, significant improvements in intensity and focalitycould be attained compared to conventional montages. Finally,we note that at the low frequencies considered in tCS it is notpossible to focalize to a local maximum or minimum the elec-tric field in a constant conductivity medium [4], [70]. Local fieldmaxima or minima will occur at media boundaries only—e.g.,at the grey matter-CSF boundary. In practice, this may suffice.

III. PHYSIOLOGICAL MODELS OF EFFECTS OF TCS ELECTRICFIELDS ON NEURONAL SYSTEMS

A. Modeling Neuron-Field InteractionThe basic mechanism for interaction in tCS is today thought

to be through the coupling of electric fields to elongatedform-factor neurons such as pyramidal cells. The role of othertypes of neurons (e.g., interneurons such as basket cells) orother brain cells like glia is not well understood. Physically, theexternal electric field forces the displacement of intracellularions (which cancel the intracellular field), altering the neuron’sinternal charge distribution and modifying the transmembranepotential difference. Mathematically, these effects can bedescribed by the “cable equation” for the neuron’s potential(see, e.g., [71]) through a term proportional to the electric fieldgradient component along the fiber, and implicitly by boundaryconditions (terminations, connections), where the “effectivegradient” of the tCS field will be greatest [72]. For a long,straight finite fiber with space constant in a homogeneouselectric field, the transmembrane potential difference is largestat the fiber termination, with a value that can be approximatedby , where is the unit vector defining the fiber axis.This is an expected first-order result, with a spatial scale pro-vided by the space constant , and directions by field and fiber

orientation. In [72] it is also pointed out that of all the possiblemechanisms for polarization it is the one just described that isof greatest impact for TMS and tDCS (for which the externalfield gradients are small); the main mechanism will take placewhere fibers bend or end, and the effect is simply proportionalto field strength. Even though the effect of the electric field onthe membrane potential is the same in TMS and tDCS (exceptfor magnitude), the relative importance of the effect on thedifferent parts of the cell may not be the same. This is becauseTMS is suprathreshold (generating action potentials) and tDCSis not; in TMS what matters is where suprathrehold depolar-ization takes place, since that is where the action potential willbe generated. In tDCS, subthreshold polarization occurs at thesoma and along fibers. It is possible that a given polarization atthe soma may have a greater impact than the same polarizationin an axon. This is because the soma is a site of integrationof multiple inputs, whereas the axon is not. So, it may be thatin tDCS polarization at the soma may be the more relevantparameter, but further modeling and experimental work isneeded. These considerations indicate that the greatest effect ofstimulation will therefore occur at the locus of the maximumof the external field magnitude rather than its gradient (as maybe expected from the gradient term in the cable equation), andthat not only the strength of the field, but also its direction isrelevant in determining the locus and strength of the effect.The role of tissue conductivity heterogeneity is also dis-

cussed in [72] as a possible source of polarization: it occursas an axon crosses an internal conductivity boundary in thesurrounding medium, where charges will accumulate uponstimulation. Starting from Poisson’s equation it is easily seenthat accumulated charge density is proportional to the dotproduct of current density and resistivity gradient [70]

(3)

where and are the total and the “impressed” current den-sities, the resistivity of the medium and the charge density.In general, an electric field that points from the dendritic tree

towards the axon of a cell hyperpolarizes the dendritic tree anddepolarizes the axon or the soma [73]. If the field is strongenough, an action potential can be generated (as in TMS butnot in tCS). If the field points in the opposite direction then thesoma and the axon are hyperpolarized. This fact, and the orien-tation of pyramidal cells in the cortex, is related to the typicalexcitatory (inhibitory) effects found for anodal (cathodal) appli-cation of tDCS. Analytical solutions for subthreshold changesin the membrane potential due to a uniform electric field areavailable for simple cell shapes such as spherical or cylindricalcells [74]. Tranchina and Nicholson derived an analytical solu-tion for subthreshold changes in the membrane potential due auniform electric field for a neuron model that included a myeli-nated axon, the soma and a dendrite described by an “equivalentcylinder” [75]. They concluded that the net polarization at thesoma resulted from the contributions by the axon and by thedendritic tree weighted by the relative values of their input im-pedances.The electric field models for tDCS described in [34] and [36]

indicate that the low field intensities in tDCS compared to TMS

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[76], [77] do not actively stimulate the cortex, but may modu-late excitability by modifying the polarization state of the mem-brane, altering firing rates [78]–[81]. Although tDCS has beenshown to produce after effects hours and days after the stimu-lation session, current computational models account only forexcitability shifts during stimulation.

B. Small-Scale Systems: Insights From In Vitro Models

In vitro preparations offer an easy access to many featuresof the brain tissue that would be difficult to measure other-wise, particularly in the presence of exogenous electric fields.In addition, they allow for both extracellular and intracellularelectrophysiological recordings. Some studies also make useof more recent imaging techniques such as optical mappingof transmembrane potential changes based on voltage sensitivedyes [82], [83]. Extracellular recordings are analyzed to studypopulation responses including synaptic and firing parameters,during and after external stimulation. Intracellular recordingsbringmore microscopic information to characterize the synapticresponses or the properties of ion channels and receptors. Themain features of applied electric fields (ac versus dc, mono-versus bi-phasic stimulation, intensity and orientation with re-spect to the cell) can considerably vary from one study to an-other, depending on the general objective of the work.This in vitro preparation is highly versatile and well suited

for multifacet research strategies regarding the effects of ex-ternal currents on neurons and small networks. However, al-though these points are rarely discussed in papers (but see [84]),it should be mentioned that: 1) the complex relationship be-tween oxygen delivery and energy demand/supply is stronglyaltered in slice preparations; 2) the composition of the artificialcerebrospinal fluid (ACSF) is an essential issue as real cere-brospinal fluid contains many metabolites that are not includedin the ACSF; and 3) many of the intrinsic and most of the ex-trinsic connections are severed in the slice model reducing thepotential use in the interpretation of field effects on specificbrain rhythms. Therefore, one should be cautious with the ex-trapolation of in vitro results to in vivo situations.Most of the studies reviewed in this section are based on hip-

pocampal slices. A typical experimental setup is described in[85]. This setup allows for application of electric fields gen-erated across brain slices by passing current between two par-allel wires placed on the surface of the ACSF in the chamber.The properties (orientation, intensity and (nonuniformity w.r.t.space) of the applied field can be controlled.The first “quantitative” study about the effects of imposed

electric currents on the polarization of the neuron membrane isprobably that published by Terzuolo and Bullock in 1956 [81].At that time, although recording techniques were less sophis-ticated than they are now and although our knowledge aboutthe properties of the excitable membrane was less advanced,these authors noticed some striking effects of weak field po-larizing electrodes on the firing of nerve cells in the peripheralnervous system: modulation effect on the firing frequency, pref-erential axis of polarization and acceleration of the frequency ofthe rhythmic bursts for currents as low as 4.3 10 A. Theseobservations led them to conclude that firing in nerve cells can

be easily modulated in frequency by very low voltage gradients(of the order of 1 V/m). The issue of the direction of the extra-cellular field was also addressed by Jefferys [86] who carefullypositioned the pairs of polarizing electrodes with respect to theorientation of the cell layers in hippocampal slices. Soma-de-polarizing currents (pulses of 25–250 ms) parallel to the cellaxis were found to strongly enhance the cell excitability (in-crease of the population spike amplitude and decrease of thetime to peak). Conversely, currents of equal strength but per-pendicular to main cell axis were found to have no consistenteffect on the responses, suggesting that the altered excitabilitywas primarily due to a modification of the membrane poten-tial in the vicinity of the cell body due to a fraction of currentflowing intracellularly. This first study was followed by a morecomprehensive and quantified study [82] whose objective wasto revisit some basic assumptions about field parameters: 1) po-larity and degree of cell polarization with respect to the orien-tation of the applied dc field; 2) dendrites versus soma polar-ization; 3) time variance or invariance in the efficacy of applieddc fields; and 4) short-term after effects of dc fields. Regardingthe field orientation, authors confirmed that electric fields par-allel to the somato-dendritic axis induced polarization of CA1pyramidal cells. Electric fields perpendicular to the somato-den-dritic axis did not induce somatic polarization. However, theymodulated orthodromic responses. Regarding the polarity, neg-ative electric fields decreased the delay and increased the am-plitude of population spikes evoked by oriens stimulation. Pos-itive electric fields had an inverse effect. In terms of intensity,changes in the population spike amplitude started to occur forpolarizing gradients greater than 4.0 V/m, as already reported in[86]. However, the authors mentioned that weaker fields mightas well have an influence. Further studies confirmed this hypoth-esis later on, although awell-defined electric field threshold elic-iting an action potential can hardly be determined. The first ex-perimental evidence that neuronal networks are detectably sen-sitive to electric fields lower than 1 V/m was published quiterecently in [87]. Using electrophysiological recordings in lon-gitudinal hippocampal slices (maximizing the alignment of CA1or CA3 neurons with the parallel electric field lines), the authorsexamined the effects of weak fields both on single neuron andnetwork responses. In CA1, synchronization between networkactivity and electric field stimulus (26 ms duration Gaussianpulses) was obtained at 1.75 V/m rms. CA1 pyramidal cell net-works were sensitive to fields with RMS amplitudes as smallas 0.140 V/m and CA1 networks were found to be more sensi-tive to electric fields than CA3 networks. A possible explana-tion is that in the CA1 subfield, pyramidal cells are more regu-larly aligned in contrast to CA3. An interesting finding is alsothat networks are more sensitive than the average single neuronthreshold to field modulation. Interestingly, from extracellularrecordings, Bikson et al. [82] plotted the amplitude of the popu-lation spike evoked by stratum oriens stimulation as a functionof the strength of the applied field. They also found that smallelectric fields 40 V/m , applied parallel to the somato-den-dritic axis, induced polarization of CA1 pyramidal cells. Thisstudy revealed that the relationship between applied field andinduced polarization was linear, a result in agreement with bio-physical models.

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A number of papers dealing with the effects and safetyof electric fields on neuronal networks in slice preparationsreport that these fields can induce epileptiform activity in“normal” slices [82], [86], [88], [89] or can alter epileptiformactivity generated in “epileptogenic” slices, whatever the ex-perimental model [85], [90]–[93]. Constant dc fields have beenshown to suppress epileptiform bursting in high [94]and low Ca [90], [95] models by directly hyperpolarizingpyramidal neurons. The ac fields can also have a similar effectwith appropriate settings of the frequency and amplitude [96].High amplitude dc fields have also been shown to induceepileptiform activity [82].Bikson et al. reported a direct measurement of membrane

time constants for polarization by electric fields [82] andshowed that the peak amplitude and time constant of membranepolarization varied along the axis of neurons, with the maximalpolarization observed at the tips of basal and apical dendrites.They suggested that the modulation of neuronal excitability isnot only a simple function of the orientation of neurons withrespect to applied field. They also emphasized that neuronsshould be less sensitive to relatively fast ac electric fields

15 Hz , whether exogenous or endogenous. In addition,using laminar electrodes and current source density (CSD)analysis, they showed that electric fields could move the site ofpopulation spike initiation.More recently, Fröhlich andMcCormick [64] have carried out

similar in vitro studies in the ferret visual cortex. They foundthat weak electric fields with amplitude similar to those endoge-nously generated in vivo 2 V/m caused somatic membranedepolarization 0.5 mV and accelerated oscillation frequen-cies in the slice. In this study, others aspects of tCS were studied,including entrainment of spontaneous oscillations using weaksinusoidal stimulation (0.5 to 4.0 V/m) at a frequency matchingthe spontaneous oscillation frequency in the slice. Further, theauthors used recorded fields as stimulation waveforms (withpeak amplitude adjusted to 4 V/m) and found that applicationof such a temporally naturalistic fields strongly modulated theongoing activity of the local cortical network. The threshold forfield effects was found to be between 0.25 and 0.5 V/m.Cortical plasticity is commonly achieved through changes in

synaptic strength. This ability provides a learning and memorytool for the brain [97], [98]. Stimulation of the synapse is oneof the many ways to modify the synaptic strength. Variousstimulation protocols (electrical, chemical, etc.) mimickingphysiological conditions that are believed to occur during theformation of new memories were proposed [89], [99]–[102].Long-term potentiation (LTP) is a persistent increase insynaptic strength and long-term depression (LTD) is the weak-ening of neuronal synaptic strength that may last from hoursto months. Three classes of electrical stimulation protocols(mostly near/suprathreshold) are known to generally producelong-term potentiation (LTP) in synaptic gains: tetanic, thetaburst and primed burst stimulations of synapses [89]. Thetetanic stimulation typically includes one or more trains of50–100 stimuli (square pulses) at 100 Hz. Their LTP effect maypersist for 1–3 or more hours according to the characteristics ofthe stimulation [103]–[106]. Theta burst stimulation includesone or more train of low-frequency bursts each typically in-

cludes 3–10 pulses at 100 Hz [107]. This class is based on theobservation that theta activity increases in EEG when animalsare engaged in learning-related exploratory behaviors. Primedburst potentiation typically includes five pulses where the firstpulse precedes the last four pulses (at 100 Hz) by 170 ms. Ithas been hypothesized that the LTP is a two-step procedure:sensitization and persistent changing [108], [109].Recently, an in vitro experiment on slices of mice motor

cortex has shown that stimulation of synapses by a directcurrent (subthreshold) may also generate LTP [110], [111].Anodal stimulation coupled with synaptic activation induceda persisting increase of the amplitude of the field excitatorypostsynaptic potentials elicited in layer II/III after stimulatingthe vertical pathway at 0.1 Hz.Regarding long-term depression (LTD) of neuronal synaptic

strengths, it has been shown that a prolonged low frequency3 Hz stimulation of synapses for several minutes results in

a persistent reduction in synaptic transmission [112]. The inten-sity of low-frequency stimulations may change the persistencyof LTD response [113].The ability of the above-mentioned electrical protocols to in-

duce LTP/LTD responses may vary or even reverse according tosynaptic and cellular conditioning. For instance, in [110] it wasshown that in the absence of low-frequency synaptic activation,direct currents could only generate short-term potentiation ofsynaptic gains for a few minutes. The ability or inability of acti-vation and inactivation of AMPA and NMDA receptors duringelectrical stimulation, and the level of ionic concentrations suchas Mg and Ca in intra- or extra-cellular mediums, maychange LTP/LTD responses. It has been shown that a tetanicstimulation may induce both LTP and LTD plasticity responseson different subthalamic nucleus cells [114] or in different ex-ternal Mg concentrations [115]. In another study it is shownthat three trains of pulses (3 s duration at 100 Hz, 20 s intervals)may induce LTD response, while if the frequency of pulses is re-duced to 10 or 1 Hz, LTD is not observed, because not enoughcalcium ions are accumulated in postsynaptic neuron [116].Although these studies used near- or suprathreshold stimu-

lation, a few animal studies (see Section III-C) also suggestedthat LTP/LTD-like mechanisms might be involved after sub-threshold stimulation after tDCS. Along the same lines, it isknown that tDCS after-effects (subthreshold stimulation) aremediated by changes in NMDA receptor strength [117]–[119].There is increasing evidence that the long-term after-effects oftDCS are driven by (GABAergic and glutamatergic) synapticmodification and that tDCSmodulates cortical synaptic strengthwith the involvement of intracortical neurons [120].“Ephaptic” or longer range “field interaction” are terms

used to describe the influence of electric fields generated byactivated neurons on neighboring neurons, that is, the postu-lated functionally relevant, bidirectional, direct interaction ofneurons via electric field coupling. These small electric fieldsare thought to play a role in the synchronization of neuronalnetworks. Richardson and Turner [88] examined the ephapticinteractions in rat hippocampus slices and showed that in bothortho- and anti-dromic stimulation of CA1 pyramidal cells, aninduced negative intracellular wave (referenced to bath ground)can be recorded inside those neurons that were not activated

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directly by the stimulations. Extracellular recordings indicatedthat this ground-based intracellular response was coincidentwith the falling phase of the extracellular population spikeand it could be observed even if the synaptic transmissionwas blocked, indicating that the negative intracellular wavewas generated ephaptically in response to neural populationactivity. It is worth mentioning that similar results were alsoobtained by Taylor and Dudek in the same year [121]. Asdiscussed previously, recent work in vitro by Fröhlich andMcCormick hints at the potential role of ephaptic interactionsin the cortex by showing that weak endogenous fields canenhance and entrain physiological neocortical network activity[64]. The authors conclude that such significant susceptibilityof active networks to endogenous fields that only cause smallchanges in membrane potential in individual neurons suggeststhat such endogenous fields could guide neocortical networkactivity. These observations imply that neural stimulation usingtCS may be tapping into very powerful natural mechanismsof brain function, since the magnitude of tCS and endogenouselectric fields are similar.Finally, although several papers mention the possible effects

of applied electrical fields on interneurons and glial cells [82],[85], we were not able to find a quantitative study specificallyaddressing this issue.

C. Large-Scale Systems: Insights From In Vivo ModelsIn the early 1960s, studies conducted in animals showed

that brief anodal currents applied on the motor, visual or so-matosensory cortex of cats, rabbits or rats could increase theneuronal firing or even activate neurons that were previouslysilent whereas cathodal currents reduced the spontaneous firingor inhibited it [78], [79], [122]. These effects were assumedto be dependent on the orientation of the pyramidal cells inthe cortical layers [78] and were attributed to the depolariza-tion of the initial segment and cell body during anodal andto hyperpolarization during cathodal stimulation [80], [123].Besides spontaneous neuronal activity, dc stimulation wasalso shown to influence the cortical somatosensory and motorevoked responses in rats and cats [78], [80]. More recentlysimilar studies conducted in mice confirmed that tDCS couldmodulate motor [124] and visual [125] evoked responses in apolarity-specific way.In addition to immediate effects, most of the previous

studies also revealed that dc fields had long-lasting effects onboth the spontaneous and evoked neuronal activity [78], [80].More recently, persisting effects either on neuron excitability[126] or on cerebral blow flow [127] were also observed afterrepeated dc or tDCS stimulation, respectively. More than40 years ago, a seminal study showed that the long-lastingmodulation of neuronal activity depended on protein synthesis[128] suggesting that synaptic plasticity could be one of themechanisms underlying these sustained effects. Since then,some of the molecular changes induced by polarizing currents,and known to be in close relation with neuroplastic changes,have been extensively explored. These studies reported that,in rats, anodal polarization of the somatosensory cortex mod-ulated the accumulation of cyclic adenosine monophosphate(cAMP) [129], [130], increase the extracellular concentration

of Ca [131], transiently increase early gene expression(c-fos), and increase the cytoplasmic level of protein kinaseC [132], [133]. Concomitantly with molecular studies, earlybehavioral studies showed that cathodal current applied overthe visual cortex decreased the rabbit learning in an avoidancetask [134], [135], delayed the learning processes of rats ina visual categorization task [136] and induced a transientimpairment of the visuo-spatial orientation behavior in cats[137]. Conversely, anodal currents applied over the visualcortex were shown to increase the learning in an avoidancetask [138] and anodal tDCS applied over the motor corteximproved motor skill learning, a phenomenon that could beexplained by brain-derived neurotrophic factor BDNF-depen-dent synaptic potentiation mechanisms [110]. All these resultsconverge towards a potential LTP-like mechanism after anodalstimulation. On one hand, c-fos expression has been proposedto be associated with the maintenance of LTP [139]. On theother, protein kinase C and Ca release are both persistentlypromoted by the activation neurotransmitter receptors (sero-tonin 5-HT2AB, acetylcholine M1) and involved in learningand memory processes (see [140] for a recent review).To investigate further the possible mechanisms of action of dc

stimulation, a few experimental studies have examined its rela-tionships to cortical spreading depression (CSD) propagation.CSD is characterized by a massive depolarization, followed bya depression of neuronal activity that propagates through thecortex after chemical or mechanical stimulation of the braintissue [141]. This phenomenon is associated with major mod-ifications of the ionic concentrations and with excitotoxic ef-fects in the cortex and can occur spontaneously, as proposed inmigraine and epilepsy or following ischemia or brain injury. In-terestingly, cathodal polarizing currents could block the CSDinitiation in rats for up to 1 h [142], [143]. In turn, other studiesin rats revealed that repetitive electrical stimulation [144] or an-odal tDCS [145] increased the velocity of cortical spreading de-pression both in a frequency-dependent and sustained manner.These results have safety implications as tDCS might increasethe probability of migraine attack, but also suggest the potentialtherapeutic repercussion of tDCS in pathologies characterizedby a reduced cortical excitability, such as stroke, Parkinson’sdisease and major depression.Recent work by Marquez-Ruiz et al. in behaving rabbits

has shown that tDCS modulates cortical processes and leadsto after effects with longer stimulation periods [146]. Con-sistent with the polarity-specific effects, the acquisition ofclassical eyeblink conditioning was potentiated or depressedby the simultaneous application of anodal or cathodal tDCS,respectively, when stimulation of the whisker pad was usedas conditioned stimulus, suggesting that tDCS modulates thesensory perception process necessary for associative learning.In this paper it is also shown that blocking the activationof adenosine A1 receptors prevents the long-term depression(LTD) evoked in the somatosensory cortex after cathodal tDCS.As in TMS, although to a lesser extent, epilepsy has become a

challenging domain of therapeutic application for tDCS. In spiteof a study reporting the pro-convulsive effects of anodal dc stim-ulation in rabbits [147] most experimental work has exploredthe potential anti-convulsant use of tDCS in animal models of

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epilepsy. These studies revealed that low-frequency cathodaldc increased the threshold and decreased the duration of amyg-dala-kindled seizures [148], both effects being intensity depen-dent and remaining stable for weeks or months [126]. Similarly,cathodal dc increased the threshold for seizure induction in arat electric-ramp model of focal seizures [149] and decreasedthe seizure frequency in the litium-pilocarpine model of statusepilepticus in immature rats [150].

D. Insights From Computational ModelsIn order to study the immediate effects of stimulation

on a single neuron, compartmental models that include theHodgkin-Huxley membrane conductance equations can beemployed. Such models are discussed, e.g., in [151]. Severalstudies have been done with simple neuron models by, e.g.,[152]. Recently, the work of Fröhlich and McCormick [64] pro-vides a study comparing a two-compartment model positivelywith in vitro studies using tDCS, tACS and also endogenousfields in ferret slices, and highlighting the importance of en-trainment and natural feedback loops. Not much work hasbeen done to study dynamic tCS in detailed multicompartmentmodels, which would be especially interesting to understandhow different types of neurons (e.g., pyramidal cells versusbasket cells) respond to electric fields in different orientations,and their response to dynamic electrics fields (tACS, tRNS,etc.). In addition, single neuron models for long-term effectsare lacking.Compared with the large number of computational modeling

studies relating to the effects of external fields on single neu-rons, the number of studies dealing with the effects of fields onlarge-scale neural networks is very limited. The first detailedmodel which included an externally applied field induced byTMS in the model was introduced quite recently [153]. In thismodel, the effects of single and paired pulse TMS and the gen-eration of I-waves were studied in different layers of corticalstructures (layers L2/L3, L5, and L6). TMS pulses were sim-ulated by synchronous activation of a chosen fraction of fiberterminals throughout the motor cortex patch. This representa-tion of activation is consistent with experimental studies indi-cating peripheral nerves are most easily stimulated at termina-tions [154]. It is also supported by nerve modeling studies in-dicating that a neuron is most likely to be activated by TMSwhere a geometric discontinuity, such as fiber termination (e.g.,dendrites or synapses) occurs [155], [156]. More recently, An-derson et al. [157] used realistic simulations of cortical activityto examine the effects of external electrical stimulation, with theelectric field generated by either one or two 1 mm radius cir-cular disks. The medium was assumed homogenous with a con-ductivity value corresponding to grey matter. The second differ-ence of the voltage along initial segments mof axons and along nodes of Ranvier (located in the middle ofhorizontal axon branches, m) was used as a parameterto determine whether an action potential should be generatedin neurons in response to the stimulation. Thresholds foralong initial segments and nodes of Ranvier were set to 3 and 8mV, respectively. These values were set according to neuronalmodeling studies accomplished by McIntyre [158], [159]. Themodel proposed by Anderson provided the first framework for

studying the evolution of seizure activity in response to an elec-trical stimulation. They used monopolar or dipolar electrodesemitting a single pulse or a train of rectangular pulses (durationof pulse s) in a frequency range from 60 to 200Hz. Simula-tions showed that a 0.1 s external field induced by themonopolarelectrode could cease the seizure activity and could delay thenext population spike for about 0.6 s. The delay increased withthe frequency of stimulating pulses. The effect of polarity andorientation of the stimulation was also studied in this model. Ifthe orientation of stimulation was parallel to the orientation ofconnections (in both polarities), the effects of stimulations onstopping the seizure increased.As for detailed models, pioneering work on models of lo-

calized populations of neurons started in the early 1970s withWilson and Cowan [160], who laid the theoretical bases of thesemodels. During the past decades, this class of models has beenused in numerous theoretical and experimental studies, mainlyrelated to interpretation of neurophysiological data [161]–[165].However, the first attempt to reproduce electrical stimulationeffects in macroscopic models was published recently [166]. Inorder to obtain a deeper insight into the excitability mechanismsleading to seizures, authors reproduced direct stimulation ef-fects into a macroscopic model of a hippocampal network [163].They demonstrated the superiority of “active” paradigms (i.e.,stimulation-based) as compared with “passive” ones (analysisof the spontaneous activity only). Regarding the effects of suchexternal stimulation performed by an extracellular bipolar elec-trode, the authors assumed that the change of membrane po-tential is proportional to the generated extracellular current inall subpopulations (principal neurons and interneurons) repre-sented in the model, although in real tissue it would depend onthe relative position and orientation of neurons with respect tothe electrode. Using this simplified model of stimulation, linksbetween physiological parameters controlling excitability of thehippocampal network, on the one hand, and some EEG mea-sures computed from the responses to active stimulations, onthe other, were investigated. More recently, a detailed compu-tational network model of spiking neurons was developed byReato et al. [167]. In this network, each neuron was representedby the single compartment phenomenological model reportedin [168] and the degree and time course of the membrane po-larization resulting from applied fields was adjusted based onexperimental data. Through this modeling approach in combi-nation with in vitro slice experiments the authors were able toexplain how low-intensity electrical stimulation modulates theneuronal population rate and spike timing, impacting the overallnetwork dynamics. More specifically, results revealed that weakdc and slow ac fields lead to changes in neuronal firing rate andto marked changes in gamma oscillations. For higher frequencyapplied ac fields of low magnitude, a modulation of the spiketiming was reported. For higher amplitude ac fields, results sug-gested that increased synchronization of firing times across neu-rons occurs.

IV. FUTURE RESEARCHBased on this review, we propose a short list of themes for

further work. Firstly, even though biophysical models are wellunderstood, further experimental validation of tCS electric field

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modeling in realistic heads is needed. The dielectric properties(conductivity values) of tissues are not well known yet, par-ticularly for ac stimulation. Furthermore, the effects of tissueanisotropy in the resulting electric fields should be better under-stood.With regards to neuron-field interaction, follow-up neuronal

tCS modeling studies need to consider the complex geometryof different types of neurons to better understand their interac-tion with electric fields. In addition, the role of interneurons andother brain cells such as glial cells in tCS needs to be elucidated.Computational neuronal population models should then explorethe interaction of dynamic tCS with the brain and link them withobservable measures such as EEG.Although significant advances have been made, tCS after

effects need to be better understood through experimental work.With this knowledge, long-term effects mechanisms of tCSshould be included in computational models at various scales.The importance of ephaptic interactions, which may play a

role in the recruitment and synchronization of neuronal activity,is still not well understood today. Yet, ephaptic coupling is con-ceptually related to tCS given the central role, in both cases, ofthe electric field, and the similar amplitudes of endogenous andtCS electric fields. For this reason, tCS may provide a practicaltool to study ephaptic effects, while a better understanding ofthe nature of ephaptic phenomena may open new prospects intCS research and clinical translation.With regards to further technology development in tCS, it

should provide the means for reproducible stimulation both inthe laboratory and, no less importantly, in the clinical setting.Multisite stimulation with arbitrary current waveforms—withcontrol of frequencies, amplitudes and phase relationships ateach site—should allow for adaptation to specific rhythms andspatio-temporal patterns in the oscillating brain, providing co-ordinated stimulation in space and time over the entire cortex.This would permit us, e.g., to explore and exploit resonance phe-nomena to amplify or reduce desired oscillatory patterns locally,with improved focusing to specific cortical sites. Finally, stim-ulation techniques should also evolve to benefit from feedbackfrom EEG or other forms of brain activity monitoring to dynam-ically adapt stimulation parameters to patient brain state.

REFERENCES[1] E.Wassermann, C.M. Epstein, U. Ziemann, T. Paus, and S. H. Lisanby,

The Oxford Handbook of Transcranial Stimulation. New York: Ox-ford Univ. Press, 2008.

[2] R. Plonsey and D. B. Heppner, “Considerations of quasi-stationarityin electrophysiological systems,” Bull. Math. Biophys., vol. 29, pp.657–664, Dec. 1967.

[3] B. J. Roth, L. G. Cohen, and M. Hallett, “The electric field inducedduring magnetic stimulation,” Electroencephalogr. Clin. Neuro-physiol. Suppl., vol. 43, pp. 268–278, 1991.

[4] L. Heller and D. B. van Hulsteyn, “Brain stimulation using electromag-netic sources: Theoretical aspects,” Biophys. J., vol. 63, pp. 129–138,Jul. 1992.

[5] B. J. Roth, “The electrical conductivity of tissues,” in The BiomedicalEngineering Handbook, B. Raton, Ed., 2nd ed. Boca Raton, FL: CRCPress, 2000, vol. 1, pp. 10.1–10.12.

[6] J. P. Reilly, Applied Bioelectricity : From Electrical Stimulations toElectropathology. New York: Springer, 1998.

[7] H. Eaton, “Electric field induced in a spherical volume conductor fromarbitrary coils: Application to magnetic stimulation and MEG,” Med.Biol. Eng. Comput., vol. 30, pp. 433–440, Jul. 1992.

[8] L. A. Geddes and L. E. Baker, “The specific resistance of biologicalmaterial—A compendium of data for the biomedical engineer andphysiologist,” Med. Biol. Eng., vol. 5, pp. 271–293, May 1967.

[9] K. R. Foster and H. P. Schwan, “Dielectric properties of tissues andbiological materials: A critical review,” Crit. Rev. Biomed. Eng., vol.17, pp. 25–104, 1989.

[10] M. A. Stuchly and S. S. Stuchly, “Dielectric properties of biologicalsubstances—Tabulated,” J. Microwave Power, vol. 15, pp. 19–26,1980.

[11] F. A. Duck, Physical Properties of Tissues. A Comprehensive Refer-ence Book. London, U.K.: Academic, 1990.

[12] C. Gabriel, S. Gabriel, and E. Corthout, “The dielectric properties ofbiological tissues: I. Literature survey,” Phys. Med. Biol., vol. 41, pp.2231–2249, Nov. 1996.

[13] S. Gabriel, R. W. Lau, and C. Gabriel, “The dielectric properties ofbiological tissues: II. Measurements in the frequency range 10 Hz to20 Ghz,” Phys. Med. Biol., vol. 41, pp. 2251–2269, Nov. 1996.

[14] S. Gabriel, R. W. Lau, and C. Gabriel, “The dielectric properties ofbiological tissues: III. Parametric models for the dielectric spectrum oftissues,” Phys. Med. Biol., vol. 41, pp. 2271–2293, Nov. 1996.

[15] S. B. Baumann, D. R. Wozny, S. K. Kelly, and F. M. Meno, “The elec-trical conductivity of human cerebrospinal fluid at body temperature,”IEEE Trans. Biomed. Eng., vol. 44, no. 3, pp. 220–223, Mar. 1997.

[16] N. K. Logothetis, C. Kayser, and A. Oeltermann, “In vivomeasurementof cortical impedance spectrum in monkeys: Implications for signalpropagation,” Neuron, vol. 55, pp. 809–23, Sep. 2007.

[17] S. Rush and D. A. Driscoll, “EEG electrode sensitivity—An appli-cation of reciprocity,” IEEE Trans. Biomed. Eng., vol. 16, no. 1, pp.15–22, Jan. 1969.

[18] S. K. Law, “Thickness and resistivity variations over the upper surfaceof the human skull,” Brain Topogr., vol. 6, pp. 99–109, Dec. 1993.

[19] T. F. Oostendorp, J. Delbeke, and D. F. Stegeman, “The conductivity ofthe human skull: Results of in vivo and in vitro measurements,” IEEETrans. Biomed. Eng., vol. 47, no. 11, pp. 1487–1492, Nov. 2000.

[20] M. Akhtari, H. C. Bryant, A. N. Mamelak, E. R. Flynn, L. Heller, J. J.Shih, M. Mandelkern, A. Matlachov, D. M. Ranken, E. D. Best, M. A.DiMauro, R. R. Lee, and W. W. Sutherling, “Conductivities of three-layer live human skull,” Brain Topogr., vol. 14, pp. 151–167, 2002.

[21] R. Hoekema, G. H. Wieneke, F. S. Leijten, C. W. van Veelen, P. C. vanRijen, G. J. Huiskamp, J. Ansems, and A. C. van Huffelen, “Measure-ment of the conductivity of skull, temporarily removed during epilepsysurgery,” Brain Topogr., vol. 16, pp. 29–38, 2003.

[22] R. J. Sadleir and A. Argibay, “Modeling skull electrical properties,”Ann. Biomed. Eng., vol. 35, pp. 1699–1712, Oct. 2007.

[23] S. I. Goncalves, J. C. de Munck, J. P. Verbunt, F. Bijma, R. M.Heethaar, and F. H. L. da Silva, “In vivo measurement of the brainand skull resistivities using an EIT-based method and realistic modelsfor the head,” IEEE Trans. Biomed. Eng., vol. 50, no. 6, pp. 754–767,Jun. 2003.

[24] Y. Lai, W. van Drongelen, L. Ding, K. E. Hecox, V. L. Towle, D. M.Frim, and B. He, “Estimation of in vivo human brain-to-skull conduc-tivity ratio from simultaneous extra- and intra-cranial electrical poten-tial recordings,” Clin. Neurophysiol., vol. 116, pp. 456–465, Feb. 2005.

[25] D. S. Tuch, V. J. Wedeen, A. M. Dale, J. S. George, and J. W. Bel-liveau, “Conductivity tensor mapping of the human brain using dif-fusion tensor MRI,” in Proc. Nat. Acad. Sci., Sep. 2001, vol. 98, pp.11697–11701.

[26] J. Haueisen, D. S. Tuch, C. Ramon, P. H. Schimpf, V. J. Wedeen, J. S.George, and J. W. Belliveau, “The influence of brain tissue anisotropyon human EEG and MEG,” Neuroimage, vol. 15, pp. 159–166, Jan.2002.

[27] H. Hallez, B. Vanrumste, P. van Hese, S. Delputte, and I. Lemahieu,“Dipole estimation errors due to differences in modeling anisotropicconductivities in realistic head models for EEG source analysis,” Phys.Med. Biol., vol. 53, pp. 1877–1894, Apr. 2008.

[28] C. H. Wolters, A. Anwander, X. Tricoche, D. Weinstein, M. A. Koch,and R. S. Macleod, “Influence of tissue conductivity anisotropy onEEG/MEG field and return current computation in a realistic headmodel: A simulation and visualization study using high-resolutionfinite element modeling,” Neuroimage, vol. 30, pp. 813–826, Apr.2006.

[29] D. Gullmar, J. Haueisen, and J. R. Reichenbach, “Influence ofanisotropic electrical conductivity in white matter tissue on theEEG/MEG forward and inverse solution. A high-resolution wholehead simulation study,” Neuroimage, vol. 51, pp. 145–163, May 2010.

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Proof


[30] S. Rush and D. A. Driscoll, “Current distribution in the brain fromsurface electrodes,” Anesth. Analg, vol. 47, pp. 717–723, Nov.–Dec.1968.

[31] J. M. Saypol, B. J. Roth, L. G. Cohen, and M. Hallett, “A theoreticalcomparison of electric and magnetic stimulation of the brain,” Ann.Biomed. Eng., vol. 19, pp. 317–328, 1991.

[32] M. Ferdjallah, F. X. Bostick, Jr, and R. E. Barr, “Potential and currentdensity distributions of cranial electrotherapy stimulation (CES) in afour concentric-spheres model,” IEEE Trans. Biomed. Eng., vol. 43,no. 9, pp. 939–943, Sep. 1996.

[33] M. M. Stecker, “Transcranial electric stimulation of motor pathways:A theoretical analysis,” Comput. Biol. Med., vol. 35, pp. 133–155, Feb.2005.

[34] P. C. Miranda, M. Lomarev, and M. Hallett, “Modeling the currentdistribution during transcranial direct current stimulation,” Clin. Neu-rophysiol., vol. 117, pp. 1623–1629, Jul. 2006.

[35] A. Datta, M. Elwassif, F. Battaglia, and M. Bikson, “Transcranial cur-rent stimulation focality using disc and ring electrode configurations:FEM analysis,” J. Neural. Eng., vol. 5, pp. 163–174, Jun. 2008.

[36] T. Wagner, F. Fregni, S. Fecteau, A. Grodzinsky, M. Zahn, and A.Pascual-Leone, “Transcranial direct current stimulation: A computer-based human model study,” Neuroimage, vol. 35, pp. 1113–1124, Apr.2007.

[37] A. Datta, V. Bansal, J. Diaz, J. Patel, D. Reato, and M. Bikson, “Gyri-precise head model of transcranial direct current stimulation: Improvedspatial focality using a ring electrode versus conventional rectangularpad,” Brain Stimul., vol. 2, no. E1, pp. 201–207, Oct. 2009.

[38] A. Datta, M. Bikson, and F. Fregni, “Transcranial direct current stimu-lation in patients with skull defects and skull plates: High-resolutioncomputational FEM study of factors altering cortical current flow,”Neuroimage, vol. 52, pp. 1268–1278, Oct. 2010.

[39] R. J. Sadleir, T. D. Vannorsdall, D. J. Schretlen, and B. Gordon, “Tran-scranial direct current stimulation (tDCS) in a realistic head model,”Neuroimage, vol. 51, pp. 1310–1318, Jul. 2010.

[40] R. Salvador, A. Mekonnen, G. Ruffini, and P. C. Miranda, “Mod-eling the electric field induced in a high resolution realistic headmodel during transcranial current stimulation,” in Proc. IEEE Eng. inMedicine and Biology Soc. (EMBC) Annu. Int. Conf., Buenos Aires,2010, pp. 2073–2076.

[41] M. Parazzini, S. Fiocchi, E. Rossi, A. Paglialonga, and P. Ravazzani,“Transcranial direct current stimulation: Estimation of the electric fieldand of the current density in an anatomical human head model,” IEEETrans. Biomed. Eng., vol. 58, no. 6, pp. 1773–1780, Jun. 2011.

[42] T. F. Oostendorp and A. van Oosterom, “Modelling the fetal magne-tocardiogram,” Clin. Phys. Physiol. Meas., vol. 12, no. Suppl A, pp.15–18, 1991.

[43] H. S. Suh, W. H. Lee, Y. S. Cho, J. H. Kim, and T. S. Kim, “Reducedspatial focality of electrical field in tDCS with ring electrodes due totissue anisotropy,” in Proc. IEEE Eng. Med. Biol. Soc. (EMBC) Annu.Int. Conf., Buenos Aires, 2010, pp. 2053–6.

[44] M. Dannhauer, B. Lanfer, C. H.Wolters, and T. R. Knosche, “Modelingof the human skull in EEG source analysis,” Human Brain Mapp., vol.32, pp. 1383–99, Sep. 2011.

[45] A. M. Dymond, R. W. Coger, and E. A. Serafetinides, “Intracerebralcurrent levels in man during electrosleep therapy,” Biol. Psychiatry,vol. 10, pp. 101–104, Feb. 1975.

[46] P. Faria, M. Hallett, and P. C. Miranda, “A finite element analysis ofthe effect of electrode area and inter-electrode distance on the spatialdistribution of the current density in tDCS,” J. Neural Eng., vol. 8, p.066017, Dec. 2011.

[47] M. A. Nitsche and W. Paulus, “Excitability changes induced in thehuman motor cortex by weak transcranial direct current stimulation,”J. Physiol., vol. 527, pp. 633–639, Sep. 2000.

[48] M. A. Nitsche, S. Doemkes, T. Karakose, A. Antal, D. Liebetanz, N.Lang, F. Tergau, andW. Paulus, “Shaping the effects of transcranial di-rect current stimulation of the human motor cortex,” J. Neurophysiol.,vol. 97, pp. 3109–3117, Apr. 2007.

[49] F. Fregni, P. S. Boggio, M. Nitsche, F. Bermpohl, A. Antal, E. Fere-does, M. A. Marcolin, S. P. Rigonatti, M. T. Silva, W. Paulus, and A.Pascual-Leone, “Anodal transcranial direct current stimulation of pre-frontal cortex enhances working memory,” Exp. Brain Res., vol. 166,pp. 23–30, Sep. 2005.

[50] M. B. Iyer, U. Mattu, J. Grafman, M. Lomarev, S. Sato, and E. M.Wassermann, “Safety and cognitive effect of frontal DC brain polar-ization in healthy individuals,” Neurology, vol. 64, pp. 872–285, Mar.2005.

[51] P. C.Miranda, P. Faria, andM. Hallett, “What does the ratio of injectedcurrent to electrode area tell us about current density in the brain duringtDCS?,” Clin. Neurophysiol., vol. 120, pp. 1183–1187, Jun. 2009.

[52] A. Priori, “Brain polarization in humans: A reappraisal of an old tool forprolonged non-invasive modulation of brain excitability,” Clin. Neuro-physiol., vol. 114, pp. 589–595, Apr. 2003.

[53] Y. Vandermeeren, J. Jamart, and M. Ossemann, “Effect of tDCS withan extracephalic reference electrode on cardio-respiratory and auto-nomic functions,” BMC Neurosci., vol. 11, p. 38, Mar. 2010.

[54] V. Moliadze, A. Antal, and W. Paulus, “Electrode-distance dependentafter-effects of transcranial direct and random noise stimulation withextracephalic reference electrodes,” Clin. Neurophysiol., vol. 121, pp.2165–2171, Dec. 2010.

[55] P. Minhas, V. Bansal, J. Patel, J. S. Ho, J. Diaz, A. Datta, and M.Bikson, “Electrodes for high-definition transcutaneous DC stimulationfor applications in drug delivery and electrotherapy, including tDCS,”J. Neurosci. Methods, vol. 190, pp. 188–97, Jul. 2010.

[56] M. A. Nitsche, L. G. Cohen, E. M. Wassermann, A. Priori, N. Lang, A.Antal, W. Paulus, F. Hummel, P. S. Boggio, F. Fregni, and A. Pascual-Leone, “Transcranial direct current stimulation: State of the art 2008,”Brain Stimul., vol. 1, pp. 206–223, Jul. 2008.

[57] H. H. Jasper, “Report of the committee on methods of clinical exam-ination in electroencephalography: 1957,” Electroencephalogr. Clin.Neurophysiol., vol. 10, pp. 370–375, May 1958.

[58] V. Jurcak, D. Tsuzuki, and I. Dan, “10/20, 10/10, and 10/5 systems re-visited: Their validity as relative head-surface-based positioning sys-tems,” Neuroimage, vol. 34, pp. 1600–1611, Feb. 2007.

[59] L. Koessler, L. Maillard, A. Benhadid, J. P. Vignal, J. Felblinger, H.Vespignani, andM. Braun, “Automated cortical projection of EEG sen-sors: Anatomical correlation via the international 10–10 system,” Neu-roimage, vol. 46, pp. 64–72, May 2009.

[60] L. Marshall, H. Helgadottir, M. Molle, and J. Born, “Boosting slowoscillations during sleep potentiates memory,” Nature, vol. 444, pp.610–613, Nov. 2006.

[61] R. Kanai, L. Chaieb, A. Antal, V. Walsh, and W. Paulus, “Frequency-dependent electrical stimulation of the visual cortex,” Curr. Biol., vol.18, pp. 1839–1843, Dec. 2008.

[62] T. Zaehle, S. Rach, and C. S. Herrmann, “Transcranial alternating cur-rent stimulation enhances individual alpha activity in human EEG,”PloS One, vol. 5, p. E13766, Nov. 2010.

[63] M. Feurra, W. Paulus, V. Walsh, and R. Kanai, “Frequency specificmodulation of human somatosensory cortex,” Front Psychol., vol. 2,p. 13, Feb. 2011.

[64] F. Frohlich and D. A. McCormick, “Endogenous electric fields mayguide neocortical network activity,” Neuron, vol. 67, pp. 129–143, Jul.2010.

[65] D. Terney, L. Chaieb, V. Moliadze, A. Antal, and W. Paulus, “In-creasing human brain excitability by transcranial high-frequencyrandom noise stimulation,” J. Neurosci., vol. 28, pp. 14147–14155,Dec. 2008.

[66] W. Paulus, “Transcranial electrical stimulation (tES -tDCS; tRNS,tACS) methods,” Neuropsychol. Rehabil., vol. 21, pp. 602–17, Oct.2011.

[67] C. H. Im, H. H. Jung, J. D. Choi, S. Y. Lee, and K. Y. Jung, “Deter-mination of optimal electrode positions for transcranial direct currentstimulation (tDCS),” Phys. Med. Biol., vol. 53, pp. N219–N225, Jun.2008.

[68] J. H. Park, S. B. Hong, D. W. Kim, M. Suh, and C. H. Im, “A novelarray-type transcranial direct current stimulation (tDCS) system for ac-curate focusing on targeted brain areas,” IEEE Trans. Magn., vol. 47,no. 5, p. 885, May 2011.

[69] J. P. Dmochowski, A. Datta, M. Bikson, Y. Su, and L. C. Parra, “Op-timized multi-electrode stimulation increases focality and intensity attarget,” J. Neural Eng., vol. 8, p. 046011, Aug. 2011.

[70] P. C. Miranda, F. Wendling, I. Merlet, B. Molaee-Ardekani, S. Dunne,A. Soria-Frisch, and D.Whitmer, G. Ruffini, Ed., in Brain Stimulation.Models, Experiments and Open Questions. HIVE Deliverable D1.1,Barcelona, Starlab, 2009, p. 350 [Online]. Available: http://hive-eu.organd http://starlab.es

[71] J. M. Bower and D. Beeman, “Constructing realistic neural simulationswith GENESIS,” in Neuroinformatics, C. J. Crasto, Ed. New York:Springer, 2007, vol. 401, pp. 103–125.

[72] P. C. Miranda, L. Correia, R. Salvador, and P. J. Basser, “Tissue het-erogeneity as a mechanism for localized neural stimulation by appliedelectric fields,” Phys. Med. Biol., vol. 52, pp. 5603–5617, Sep. 2007.

IEEE

Proof


[73] J. B. Ranck, Jr., “Which elements are excited in electrical stimulationof mammalian central nervous system: A review,” Brain Res., vol. 98,pp. 417–440, Nov. 1975.

[74] R. Plonsey and K. W. Altman, “Electrical-stimulation of excitablecells—A model approach,” Proc. IEEE, vol. 76, no. 9, pp. 1122–1129,Sep. 1988.

[75] D. Tranchina and C. Nicholson, “A model for the polarization of neu-rons by extrinsically applied electric fields,” Biophys. J., vol. 50, pp.1139–1156, Dec. 1986.

[76] P. C. Miranda, M. Hallett, and P. J. Basser, “The electric field inducedin the brain by magnetic stimulation: A 3-D finite-element analysis ofthe effect of tissue heterogeneity and anisotropy,” IEEE Trans. Biomed.Eng., vol. 50, no. 9, pp. 1074–1085, Sep. 2003.

[77] T. Wagner, M. Zahn, A. J. Grodzinsky, and A. Pascual-Leone, “Three-dimensional head model simulation of transcranial magnetic stimula-tion,” IEEE Trans. Biomed. Eng., vol. 51, no. 9, pp. 1586–1598, Sep.2004.

[78] L. J. Bindman, O. C. Lippold, and J. W. Redfearn, “The action of briefpolarizing currents on the cerebral cortex of the rat (1) during currentflow and (2) in the production of long-lasting after-Effects,” J. Physiol.,vol. 172, pp. 369–382, Aug. 1964.

[79] O. D. Creutzfeldt, G. H. Fromm, and H. Kapp, “Influence of transcor-tical d-c currents on cortical neuronal activity,” Exp. Neurol., vol. 5,pp. 436–452, Jun. 1962.

[80] D. P. Purpura and J. G. McMurtry, “Intracellular activities and evokedpotential changes during polarization of motor cortex,” J. Neuro-physiol., vol. 28, pp. 166–185, Jan. 1965.

[81] C. A. Terzuolo and T. H. Bullock, “Measurement of imposed voltagegradient adequate to modulate neuronal firing,” in Proc. Nat. Acad.Sci., Sep. 1956, vol. 42, pp. 687–694.

[82] M. Bikson, M. Inoue, H. Akiyama, J. K. Deans, J. E. Fox, H.Miyakawa, and J. G. Jefferys, “Effects of uniform extracellular DCelectric fields on excitability in rat hippocampal slices in vitro,” J.Physiol., vol. 557, pp. 175–190, May 2004.

[83] J. K. Deans, A. D. Powell, and J. G. Jefferys, “Sensitivity of coherentoscillations in rat hippocampus to AC electric fields,” J. Physiol., vol.583, pp. 555–565, Sep. 2007.

[84] A. Schurr and B. M. Rigor, Brain Slices in Basic and Clinical Re-search. Boca Raton, FL: CRC Press, 1995.

[85] M. Bikson, J. Lian, P. J. Hahn, W. C. Stacey, C. Sciortino, and D.M. Durand, “Suppression of epileptiform activity by high frequencysinusoidal fields in rat hippocampal slices,” J. Physiol., vol. 531, pp.181–191, Feb. 2001.

[86] J. G. Jefferys, “Influence of electric fields on the excitability of granulecells in guinea-pig hippocampal slices,” J. Physiol., vol. 319, pp.143–152, Oct. 1981.

[87] J. T. Francis, B. J. Gluckman, and S. J. Schiff, “Sensitivity of neurons toweak electric fields,” J. Neurosci., vol. 23, pp. 7255–7261, Aug. 2003.

[88] T. L. Richardson, R.W. Turner, and J. J. Miller, “Extracellular fields in-fluence transmembrane potentials and synchronization of hippocampalneuronal activity,” Brain Res., vol. 294, pp. 255–262, Mar. 1984.

[89] B. C. Albensi, D. R. Oliver, J. Toupin, and G. Odero, “Electricalstimulation protocols for hippocampal synaptic plasticity and neuronalhyper-excitability: Are they effective or relevant?,” Exp. Neurol., vol.204, pp. 1–13, Mar. 2007.

[90] R. S. Ghai, M. Bikson, and D. M. Durand, “Effects of applied electricfields on low-calcium epileptiform activity in the CA1 region of rathippocampal slices,” J. Neurophysiol., vol. 84, pp. 274–280, Jul. 2000.

[91] B. J. Gluckman, H. Nguyen, S. L.Weinstein, and S. J. Schiff, “Adaptiveelectric field control of epileptic seizures,” J. Neurosci., vol. 21, pp.590–600, Jan. 2001.

[92] K. A. Richardson, B. J. Gluckman, S. L. Weinstein, C. E. Glosch, J.B. Moon, R. P. Gwinn, K. Gale, and S. J. Schiff, “In vivo modula-tion of hippocampal epileptiform activity with radial electric fields,”Epilepsia, vol. 44, pp. 768–77, Jun. 2003.

[93] T. L. Richardson and C. N. O’Reilly, “Epileptiform activity in the den-tate gyrus during low-calcium perfusion and exposure to transient elec-tric fields,” J Neurophysiol., vol. 74, pp. 388–99, Jul. 1995.

[94] B. J. Gluckman, E. J. Neel, T. I. Netoff, W. L. Ditto, M. L. Spano,and S. J. Schiff, “Electric field suppression of epileptiform activity inhippocampal slices,” J. Neurophys., vol. 76, pp. 4202–4205, Dec. 1996.

[95] R. J. Warren and D. M. Durand, “Effects of applied currents on spon-taneous epileptiform activity induced by low calcium in the rat hip-pocampus,” Brain Res., vol. 806, pp. 186–195, Sep. 1998.

[96] T. Radman, Y. Su, J. H. An, L. C. Parra, and M. Bikson, “Spike timingamplifies the effect of electric fields on neurons: Implications for en-dogenous field effects,” J. Neurosci., vol. 27, pp. 3030–3036, Mar.2007.

[97] A. Knoblauch, G. Palm, and F. T. Sommer, “Memory capacitiesfor synaptic and structural plasticity,” Neural Comput., vol. 22, pp.289–341, Feb. 2010.

[98] R. Mozzachiodi and J. H. Byrne, “More than synaptic plasticity: Roleof nonsynaptic plasticity in learning and memory,” Trends Neurosci.,vol. 33, pp. 17–26, Jan. 2010.

[99] V. A. Doze, R. S. Papay, B. L. Goldenstein, M. K. Gupta, K. M. Col-lette, B. W. Nelson, M. J. Lyons, B. A. Davis, E. J. Luger, S. G. Wood,J. R. Haselton, P. C. Simpson, and D. M. Perez, “Long-term {alpha}1A-Adrenergic receptor stimulation improves synaptic plasticity, cog-nitive function, mood, and longevity,” Mol. Pharmacol., vol. 80, pp.747–758, Oct. 2011.

[100] G. Rammes, M. Eder, W. Zieglgansberger, and H. U. Dodt, “In-frared-guided laser stimulation as a tool for elucidating the synapticsite of expression of long-term synaptic plasticity,” in Patch-ClampMethods and Protocols, P. Molnar and J. J. Hickman, Eds. NewYork: Springer, 2007, vol. 403, pp. 113–122.

[101] A. Floel and L. G. Cohen, “Contribution of noninvasive cortical stim-ulation to the study of memory functions,” Brain Res. Rev., vol. 53, pp.250–259, Feb. 2007.

[102] S. Fujii, H. Sasaki, K. Mikoshiba, Y. Kuroda, Y. Yamazaki, A. M.Taufiq, and H. Kato, “A chemical LTP induced by co-activation ofmetabotropic and N-methyl-D-aspartate glutamate receptors in hip-pocampal CA1 neurons,” Brain Res., vol. 999, pp. 20–28, Feb. 2004.

[103] Y. Y. Huang and E. R. Kandel, “Recruitment of long-lasting and pro-tein kinase a—Dependent long-term potentiation in the CA1 region ofhippocampus requires repeated tetanization,” Learn. Mem., vol. 1, pp.74–82, May/Jun. 1994.

[104] H. Matthies and K. G. Reymann, “Protein kinase a inhibitors preventthe maintenance of hippocampal long-term potentiation,” Neurorep.,vol. 4, pp. 712–714, Jun. 1993.

[105] U. Frey, Y. Y. Huang, and E. R. Kandel, “Effects of cAMP simulate alate stage of LTP in hippocampal CA1 neurons,” Science, vol. 260, pp.1661–1664, Jun. 1993.

[106] R. P. Vertes, “Hippocampal theta rhythm: A tag for short-termmemory,” Hippocampus, vol. 15, pp. 923–35, 2005.

[107] S. L. Morgan and T. J. Teyler, “Electrical stimuli patterned after thetheta-rhythm induce multiple forms of LTP,” J. Neurophysiol., vol. 86,pp. 1289–96, Sep. 2001.

[108] D. M. Diamond, T. V. Dunwiddie, and G. M. Rose, “Characteristics ofhippocampal primed burst potentiation in vitro and in the awake rat,”J. Neurosci., vol. 8, pp. 4079–4088, Nov. 1988.

[109] G. M. Rose and T. V. Dunwiddie, “Induction of hippocampal long-term potentiation using physiologically patterned stimulation,” Neu-rosci. Lett., vol. 69, pp. 244–248, Sep. 1986.

[110] B. Fritsch, J. Reis, K. Martinowich, H. M. Schambra, Y. Ji, L. G.Cohen, and B. Lu, “Direct current stimulation promotes BDNF-de-pendent synaptic plasticity: Potential implications for motor learning,”Neuron, vol. 66, pp. 198–204, Apr. 2010.

[111] J. Reis and B. Fritsch, “Modulation of motor performance and motorlearning by transcranial direct current stimulation,” Curr. Opin.Neurol., vol. 24, pp. 590–6, Dec. 2011.

[112] B. Mockett, C. Coussens, and W. C. Abraham, “NMDA receptor-me-diated metaplasticity during the induction of long-term depression bylow-frequency stimulation,” Eur. J. Neurosci., vol. 15, pp. 1819–1826,Jun. 2002.

[113] S. Sajikumar and J. U. Frey, “Late-associativity, synaptic tagging, andthe role of dopamine during LTP and LTD,” Neurobiol. Learn. Mem.,vol. 82, pp. 12–25, Jul. 2004.

[114] K. Z. Shen, Z. T. Zhu, A. Munhall, and S. W. Johnson, “Synaptic plas-ticity in rat subthalamic nucleus induced by high-frequency stimula-tion,” Synapse, vol. 50, pp. 314–319, Dec. 2003.

[115] P. Calabresi, A. Pisani, N. B. Mercuri, and G. Bernardi, “Long-termpotentiation in the striatum is unmasked by removing the voltage-de-pendent magnesium block of NMDA receptor channels,” Eur. J. Neu-rosci., vol. 4, pp. 929–935, Oct. 1992.

[116] P. Bonsi, A. Pisani, G. Bernardi, and P. Calabresi, “Stimulus frequency,calcium levels and striatal synaptic plasticity,” Neurorep., vol. 14, pp.419–422, Mar. 2003.

[117] D. Liebetanz, M. A. Nitsche, F. Tergau, and W. Paulus, “Pharmaco-logical approach to the mechanisms of transcranial DC-stimulation-in-duced after-effects of human motor cortex excitability,” Brain, vol.125, pp. 2238–2247, Oct. 2002.

IEEE

Proof


[118] M. A. Nitsche, D. Liebetanz, A. Antal, N. Lang, F. Tergau, andW. Paulus, “Modulation of cortical excitability by weak directcurrent stimulation—Technical, safety and functional aspects,” inTranscranial Magnetic Stimulation and Transcranial Direct CurrentStimulation, W. Paulus, F. Tergau, M. A. Nitsche, J. C. Rothwell,U. Ziemann, and M. Hallett, Eds. Amsterdam, The Netherlands:Elsevier, 2003, vol. 56, pp. 255–276.

[119] M. A. Nitsche, A. Antal, D. Liebetanz, N. Lang, F. Tergau, and W.Paulus, “Induction and modulation of neuroplasticity by transcranialdirect current stimulation,” in Transcranial Brain Stimulation forTreatment of Psychiatric Disorders, M. A. Marcolin and F. Padberg,Eds. Basel, New York: Karger, 2007, pp. 172–186.

[120] C. J. Stagg and M. A. Nitsche, “Physiological basis of transcranial di-rect current stimulation,”Neuroscientist, vol. 17, pp. 37–53, Feb. 2011.

[121] C. P. Taylor and F. E. Dudek, “Excitation of hippocampal pyramidalcells by an electrical field effect,” J. Neurophysiol., vol. 52, pp.126–142, Jul. 1984.

[122] F. Morrell, “Effect of anodal polarization on the firing pattern of singlecortical cells,” Ann. NY Acad. Sci., vol. 92, pp. 860–876, Jul. 1961.

[123] C. N. Scholfield, “Properties of K-currents in unmyelinated presynapticaxons of brain revealed revealed by extracellular polarisation,” BrainRes., vol. 507, pp. 121–8, Jan. 1990.

[124] M. Cambiaghi, S. Velikova, J. J. Gonzalez-Rosa, M. Cursi, G. Comi,and L. Leocani, “Brain transcranial direct current stimulation mod-ulates motor excitability in mice,” Eur. J. Neurosci., vol. 31, pp.704–709, Feb. 2010.

[125] M. Cambiaghi, L. Teneud, S. Velikova, J. J. Gonzalez-Rosa, M. Cursi,G. Comi, and L. Leocani, “Flash visual evoked potentials in mice canbemodulated by transcranial direct current stimulation,”Neuroscience,vol. 185, pp. 161–165, Jun. 2011.

[126] S. R. Weiss, A. Eidsath, X. L. Li, T. Heynen, and R. M. Post,“Quenching revisited: Low level direct current inhibits amygdala-kin-dled seizures,” Exp. Neurol., vol. 154, pp. 185–192, Nov. 1998.

[127] D. Wachter, A. Wrede, W. Schulz-Schaeffer, A. Taghizadeh-Waghefi,M. A. Nitsche, A. Kutschenko, V. Rohde, and D. Liebetanz, “Transcra-nial direct current stimulation induces polarity-specific changes of cor-tical blood perfusion in the rat,” Exp. Neurol., vol. 227, pp. 322–327,Feb. 2011.

[128] I. B. Gartside, “Mechanisms of sustained increases of firing rate ofneurones in the rat cerebral cortex after polarization: Role of proteinsynthesis,” Nature, vol. 220, pp. 383–384, Oct. 1968.

[129] Y. Hattori, A. Moriwaki, and Y. Hori, “Biphasic effects of polarizingcurrent on adenosine-sensitive generation of cyclic amp in rat cerebralcortex,” Neurosci. Lett., vol. 116, pp. 320–324, Aug. 1990.

[130] A. Moriwaki, Y. Hattori, Y. Hayashi, Y. F. Lu, N. Islam, and Y. Hori,“Repeated application of anodal direct current produces regional domi-nance in histamine-elicited cyclic AMP accumulation in rabbit cerebralcortex,” Acta Med Okayama, vol. 48, pp. 323–326, Dec. 1994.

[131] N. Islam, M. Aftabuddin, A. Moriwaki, Y. Hattori, and Y. Hori, “In-crease in the calcium level following anodal polarization in the ratbrain,” Brain Res., vol. 684, pp. 206–208, Jul. 1995.

[132] N. Islam, A. Moriwaki, and Y. Hori, “Co-localization of c-fos proteinand protein kinase C gamma in the rat brain following anodal polariza-tion,” Indian J. Physiol. Pharmacol., vol. 39, pp. 209–215, Jul. 1995.

[133] N. Islam, M. Aftabuddin, A. Moriwaki, and Y. Hori, “Effects of anodalpolarization on protein kinase cgamma (PKCgamma) in the rat brain,”Indian J. Physiol. Pharmacol., vol. 41, pp. 204–210, Jul. 1997.

[134] D. J. Albert, “The effect of spreading depression on the consolidationof learning,” Neuropsychologia, vol. 4, pp. 49–64, Feb. 1966.

[135] F. Morrell and P. Naitoh, “Effect of cortical polarization on a condi-tioned avoidance response,” Exp. Neurol., vol. 6, pp. 507–523, Dec.1962.

[136] I. Kupferman, “Effects of cortical polarization on visual discrimina-tions,” Exp. Neurol., vol. 12, pp. 179–189, Jun. 1965.

[137] L. Schweid, R. J. Rushmore, and A. Valero-Cabre, “Cathodal tran-scranial direct current stimulation on posterior parietal cortex disruptsvisuo-spatial processing in the contralateral visual field,” Exp. BrainRes., vol. 186, pp. 409–417, Apr. 2008.

[138] F. Szeligo, “Electrophysiological and behavioral effects of transcor-tical polarizing current: Comparison with the behaviorally determinedcharacteristics of learning,” Brain Res., vol. 103, pp. 463–475, Feb.1976.

[139] M. Dragunow, W. C. Abraham, M. Goulding, S. E. Mason, H. A.Robertson, and R. L. Faull, “Long-term potentiation and the inductionof c-fos mRNA and proteins in the dentate gyrus of unanesthetizedrats,” Neurosci. Lett., vol. 101, pp. 274–280, Jul. 1989.

[140] P. K. Dash, A. N. Moore, N. Kobori, and J. D. Runyan, “Molecularactivity underlying working memory,” Learn. Mem., vol. 14, pp.554–563, Aug. 2007.

[141] A. A. P. Leao, “Spreading depression of activity in the crebral cortex,”J. Neurophysiol., vol. 7, pp. 359–390, Nov. 1944.

[142] F. Richter, R. Fechner, W. Haschke, and V. V. Fanardijan, “Transcor-tical polarization in rat inhibits spreading depression,” Int. J. Neurosci.,vol. 75, pp. 145–151, Apr. 1994.

[143] F. Richter, R. Fechner, and W. Haschke, “Initiation of spreading de-pression can be blocked by transcortical polarization of rat cerebralcortex,” Int. J. Neurosci., vol. 86, pp. 111–118, Jul. 1996.

[144] F. Fregni, K. K. Monte-Silva, M. B. Oliveira, S. D. Freedman, A. Pas-cual-Leone, and R. C. Guedes, “Lasting accelerative effects of 1 Hzand 20 Hz electrical stimulation on cortical spreading depression: Rel-evance for clinical applications of brain stimulation,” Eur. J. Neurosci.,vol. 21, pp. 2278–2284, Apr. 2005.

[145] D. Liebetanz, F. Fregni, K. K. Monte-Silva, M. B. Oliveira, A.Amancio-dos-Santos, M. A. Nitsche, and R. C. Guedes, “After-effectsof transcranial direct current stimulation (tDCS) on cortical spreadingdepression,” Neurosci. Lett., vol. 398, pp. 85–90, May 2006.

[146] J. Marquez-Ruiz, R. Leal-Campanario, R. Sanchez-Campusano, B.Molaee-Ardekani, F. Wendling, P. C. Miranda, G. Ruffini, A. Gruart,and J. M. Delgado-Garcia, “Transcranial direct-current stimulationmodulates synaptic mechanisms involved in associative learning inbehaving rabbits,” in Proc. Nat. Acad. Sci., Apr. 2012, vol. 109, pp.6710–6715.

[147] Y. Hayashi, Y. Hattori, A.Moriwaki, H. Asaki, and Y. Hori, “Effects ofprolonged weak anodal direct current on electrocorticogram in awakerabbit,” Acta Med Okayama, vol. 42, pp. 293–296, Oct. 1988.

[148] S. R. Weiss, X. L. Li, J. B. Rosen, H. Li, T. Heynen, and R. M. Post,“Quenching: Inhibition of development and expression of amygdalakindled seizures with low frequency stimulation,” Neuroreport, vol. 6,pp. 2171–2176, Nov. 1995.

[149] D. Liebetanz, F. Klinker, D. Hering, R. Koch, M. A. Nitsche, H.Potschka, W. Loscher, W. Paulus, and F. Tergau, “Anticonvulsanteffects of transcranial direct-current stimulation (tDCS) in the rat cor-tical ramp model of focal epilepsy,” Epilepsia, vol. 47, pp. 1216–1224,Jul. 2006.

[150] T. Kamida, S. Kong, N. Eshima, T. Abe, M. Fujiki, and H. Kobayashi,“Transcranial direct current stimulation decreases convulsions and spa-tial memory deficits following pilocarpine-induced status epilepticus inimmature rats,” Behav. Brain Res., vol. 217, pp. 99–103, Feb. 2011.

[151] [PUBLISHER?]J. M. Bower and D. Beeman, The Bookof GENESIS : Exploring Realistic Neural Models with the GEneralNEural SImulation System: Internet Edition. : , 2003.

[152] F. Rattay, “Analysis of models for external stimulation of axons,” IEEETrans. Biomed. Eng., vol. 33, no. 10, pp. 974–977, Oct. 1986.

[153] S. K. Esser, S. L. Hill, and G. Tononi, “Modeling the effects of tran-scranial magnetic stimulation on cortical circuits,” J. Neurophysiol.,vol. 94, pp. 622–639, Jul. 2005.

[154] P. J. Maccabee, V. E. Amassian, L. P. Eberle, and R. Q. Cracco, “Mag-netic coil stimulation of straight and bent amphibian and mammalianperipheral nerve in vitro: Locus of excitation,” J. Physiol., vol. 460, pp.201–219, Jan. 1993.

[155] J. Ruohonen, P. Ravazzani, J. Nilsson, M. Panizza, F. Grandori, andG. Tognola, “A volume-conduction analysis of magnetic stimulation ofperipheral nerves,” IEEE Trans. Biomed. Eng., vol. 43, pp. 669–678,Jul. 1996.

[156] M. A. Abdeen and M. A. Stuchly, “Modeling of magnetic fieldstimulation of bent neurons,” IEEE Trans. Biomed. Eng., vol. 41, pp.1092–1095, Nov. 1994.

[157] W. S. Anderson, P. Kudela, J. Cho, G. K. Bergey, and P. J.Franaszczuk, “Studies of stimulus parameters for seizure disrup-tion using neural network simulations,” Biol. Cybern., vol. 97, pp.173–194, Aug. 2007.

[158] C. C. McIntyre and W. M. Grill, “Excitation of central nervous systemneurons by nonuniform electric fields,” Biophys. J., vol. 76, pp.878–888, Feb. 1999.

[159] C. C. McIntyre, W. M. Grill, D. L. Sherman, and N. V. Thakor, “Cel-lular effects of deep brain stimulation: Model-based analysis of activa-tion and inhibition,” J. Neurophysiol., vol. 91, pp. 1457–69, Apr. 2004.

[160] H. R. Wilson and J. D. Cowan, “Excitatory and inhibitory interactionsin localized populations of model neurons,” Biophys. J., vol. 12, pp.1–24, Jan. 1972.

IEEE

Proof


[161] O. David, D. Cosmelli, and K. J. Friston, “Evaluation of differentmeasures of functional connectivity using a neural mass model,”Neuroimage, vol. 21, pp. 659–673, Feb. 2004.

[162] P. Suffczynski, S. Kalitzin, G. Pfurtscheller, and F. H. L. de Silva,“Computational model of thalamo-cortical networks: Dynamicalcontrol of alpha rhythms in relation to focal attention,” Int. J. Psy-chophysiol., vol. 43, pp. 25–40, Dec. 2001.

[163] F. Wendling, A. Hernandez, J. J. Bellanger, P. Chauvel, and F. Bar-tolomei, “Interictal to ictal transition in human temporal lobe epilepsy:Insights from a computational model of intracerebral EEG,” J. Clin.Neurophysiol., vol. 22, pp. 343–356, Oct. 2005.

[164] M. Zavaglia, L. Astolfi, F. Babiloni, and M. Ursino, “A neural massmodel for the simulation of cortical activity estimated from high res-olution EEG during cognitive or motor tasks,” J. Neurosci. Methods.,vol. 157, pp. 317–329, Oct. 2006.

[165] B. Molaee-Ardekani, P. Benquet, F. Bartolomei, and F. Wendling,“Computational modeling of high-frequency oscillations at the onsetof neocortical partial seizures: From ’altered structure’ to ’dysfunc-tion,” Neuroimage, vol. 52, pp. 1109–1122, Sep. 2010.

[166] P. Suffczynski, S. Kalitzin, F. L. de Silva, J. Parra, D. Velis, and F.Wendling, “Active paradigms of seizure anticipation: Computer modelevidence for necessity of stimulation,” Phys. Rev. E Stat. Nonlin. SoftMatter Phys., vol. 78, p. 051917, Nov. 2008.

[167] D. Reato, A. Rahman,M. Bikson, and L. C. Parra, “Low-intensity elec-trical stimulation affects network dynamics by modulating populationrate and spike timing,” J. Neurosci., vol. 30, pp. 15067–15079, Nov.2010.

[168] E. M. Izhikevich, “Simple model of spiking neurons,” IEEE Trans.Neural Netw., vol. 14, pp. 1569–1572, Nov. 2003.

Giulio Ruffini Please provide Biographical information.

Fabrice Wendling Please provide Biographical information.

Isabelle Merlet Please provide Biographical information.

Behnam Molaee-Ardekani Please provide Biographical information.

Abeye Mekkonen Please provide Biographical information.

Ricardo Salvador Please provide Biographical information.

Aureli Soria-Frisch Please provide Biographical information.

Carles Grau Please provide Biographical information.

Stephen Dunne Please provide Biographical information.

Pedro C. Miranda Please provide Biographical information.

Transcranial Current Brain Stimulation (tCS): Models and Technologies

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