Developments From Electrosleep to Cranial Electrotherapy Stimulation

ES is the name for which the brain was stimulated to induce a sleep-like state in the subject. The first studies on ES were initiated in 1902 ( ); however, the first clinical report of ES was published 12 years later by Robinovitch ( ). New approaches, such as changing electrode position from covering the eyes to locations around the eyes, presumably to “reduce optic nerve irritation” ( ) were developed, mostly in Europe. ES dose waveform was typically pulsed at 30–100 Hz, but at least one (unsuccessful) case of use of DC current was documented ( ). In a symposium, it was reasoned that ES does not actually induce sleep, rather it is an indirect side effect of the relaxing effects of stimulation. Therefore, the name of ES was changed to CET ( ). This was the first of several changes of the name of ES over the next few decades, often with notable changes in dose. In 1969, TCET was proposed as another alternative name. However, such devices were renamed as CES ( ).

A notable device, produced after the name change to CET, was the Neurotone 101 , which was based on a Russian ES device brought to the United States. Although the Neurotone 101 is no longer in production, it was the first device to be approved by the FDA as a CES device ( ) and all subsequent CES devices approved by the FDA, such as the Alpha-Stim, the Oasis Pro, and the Fisher–Wallace Stimulator ( Fig. 135.2 ), were through a 510k process claiming equivalency, either direct or descendent, to the Neurotone 101.

These images show devices that have been used since 1900 for the purpose of transcranial stimulation.

Modern CES is thus a historical descendent of ES, even as dose and indications have continuously evolved. The FDA sanctioned CES in 1978 through a “grandfather clause” and have not, since then, advanced a regulatory consensus, even as more variants were being developed. CES, in this modern form, excludes DC waveforms, so it is distinct from tDCS, but its historical predicates include DC components.

Developments From Electroanesthesia to Limoge Current and Other Related Methods

EA, in short, was intended to induce anesthesia in the subject using high frequency stimulation so that chemicals did not have to be used, presurgery. EA studies started in 1903, but were first known as Electronarcosis (EN) ( ). Russian scientists used the term “EA” to describe local anesthesia, while “EN” described general anesthesia ( ). However, EA stopped being referred to as local, as applied to the periphery, and began to be known as general anesthesia, as applied to the brain.

Research into EA dosage continued and the term TCES was adopted around 1960–63. Even though the term TCES was not adopted until the early 1960s, similar protocols were used, as early as 1902 by Leduc ( ). In 1951, Denier proposed that high frequency trains of 90 kHz could be used to avoid muscular contraction ( ). Three years later, claimed that alternating currents (AC) at 700 Hz should be applied, but this was abandoned in 1958 due to cardiovascular complications ( ). In 1957, investigators in the Soviet Union attempted to add a Direct Current (DC) component to Leduc’s currents but, as claimed by an American scientist, Robert Smith, it resulted in a collection of undesirable side effects ( ). In 1964, a study claimed that pulsating currents are more effective than DC for the induction of EA ( ). Another study suggested that the use of pure DC for EA required high intensities of approximately 40 mA ( ). EA, and its derivative technologies, are not explicitly integrated into contemporary neuromodulation research and treatment, but represent important historical precedents that include cases of testing of DC waveforms.

Development of Direct Current Stimulation

DCS has been used intermittently as a component in both ES and EA. In 1957, a DC bias was added to ES, which is traditionally applied using only AC or Pulse Current (PC). The advent of TCES, around 1960–63, in the third resurgence of EA research, also incorporated a DC bias. In 1969, pure direct current stimulation was investigated for inducing anesthesia ( ). However, it was not until 1964 that preliminary studies, heralding modern tDCS, were published ( ).

In 1964, Redfearn and Lippold investigated Polarizing Current for the treatment of neuropsychiatric diseases ( ). Their use of prolonged (minutes) of stimulation was motivated by animal studies showing that prolonged DCS could produce lasting changes in excitability ( ). While further open, pilot studies and clinical observations suggested efficacy ( ), a following negative, controlled trial ( ) seems to have halted investigation (at least as published in Western journals) for several decades.

The neurophysiological basis of neuromodulation using short-duration tDCS was investigated by Priori et al. in . Shortly after, Nitsche and Paulus established that prolonged (minutes) tDCS could produce lasting and polarity-specific changes in cortical excitability ( ). This was followed by pilot clinical studies ( ) for indications spanning depression ( ), pain ( ), epilepsy ( ), and a broad range of neuropsychiatric disorders ( ). tDCS is further explored for rehabilitation after stroke ( ). Moreover, due to the perceived safety of tDCS, it was initially validated for neurophysiological changes in healthy subjects and continues to be investigated in healthy individuals for changes in behavior and cognitive performance ( ).

In 2007, HD-tDCS was proposed as a focalized form of tDCS ( ). HD-tDCS electrodes were designed for increased charge-passage capacity through a smaller contact area ( ), arranged in arrays that can be optimized per indication ( ). HD-tDCS montages tested have included the 4 × 1 configuration ( ) as well as individually optimized arrays ( ). The focalization of current with HD-tDCS is an improvement upon tDCS, where previously a broad area would be stimulated, and now specific targets can be stimulated. Some of the devices that have been used are the Schneider (tDCS), Soterix Medical 1 × 1 (tDCS), and the Soterix Medical 4 × 1 (HD-tDCS) ( Fig. 135.2 ).

Transcranial Micropolarization is a technique investigated in Russia which is a modified version of tDCS that uses small electrodes instead of pads and currents up to 1 mA, that are claimed to be “weak” ( ). GVS has been extensively tested for effects on ocular and postural movement ( ). Alongside GVS, Caloric Vestibular Stimulation (CVS) is under investigation due to similar areas being targeted by stimulation. However, CVS does not utilize electricity; rather, it uses irrigation of the ear canal using cold or warm water ( ).

Anatomical Transcranial Direct Current Stimulation Specificity and the “Sliding-Scale” Model

Anatomical specificity refers to the preferential neuromodulation of targeted brain regions by delivering stimulation current to the targeted area. The number, location, and size of anatomical targets are application specific. For example, the targeted, brain region may be a specific cortical area, implicated in a task or pathology. Anatomical specificity is achieved only through the control of tDCS electrode dose (defined as electrode montage and current) to guide current to specific brain regions ( ). However, applied without consideration for functional specificity, anatomical specificity is technically and conceptually limited.

Both computational models of current flow in the brain and imaging studies indicate that conventional tDCS methodology using two large sponge pads (5 × 5 cm) produce dispersed current through much of the cortex ( ) and even deep brain structures ( ). It is important to distinguish between well conducted studies that demonstrate dose-specific (e.g., electrode position) outcomes ( ), from implications that current flow is limited to one brain target. These studies also typically leverage other forms of functional targeting.

Technology for HD-tDCS using arrays of electrodes allows categorical increases in anatomical targeting by increasing the focus of current flow ( ), but even so, any brain region is evidently involved in multiple tasks. Which presents the inherent conceptual challenge when relying exclusively on anatomical specificity: How can passing DC current through a multitasking, complex, brain region produce specific functional changes?

In the absence of further sophistication, the goals of tDCS are often described as increasing excitability (near the anode) or decreasing excitability (near the cathode) of the target brain region, with brain function and disease thus reduced to a “sliding-scale” of excitability, to be adjusted by stimulation (cf., ). For example, under the sliding-scale concept “anodal tDCS” can enhance the performance of a cognitive task by exciting an implicated brain region. Similarly, anodal tDCS is intended to increase left, prefrontal cortex activity in depression and enhance rehabilitation around lesions, after stroke. Following early evaluations of transcranial/transcortical polarization in humans and animal models ( ), influential neurophysiological studies of tDCS ( ) established modulation of experimental, evoked potentials (e.g., motor-evoked potential responses to Transcranial Magnetic Stimulation (TMS)). There is significant extrapolation from these experimental findings to behavior and cognition (TMS evoked responses may provide poor evidence for effects on behavior ). Moreover, even the direction of this basic modulation of experimentally, evoked potentials is highly sensitive to both tDCS dose intensity ( ), direction ( ), and dependent on brain state ( ). Animal studies that show anodal/cathodal DCS producing somatic depolarization/hyperpolarizing ( ), and increase/decrease in firing rate ( ), are cited to support a sliding-scale concept; however, global changes in firing rate across a brain region implies a nonspecific effect ( ). In summary, it is reasonable to conclude from neurophysiologic studies that tDCS can produce dose-specific changes in brain functions ( ) that can, with careful extrapolation, serve as a basis for behavioral interventions ( ). However, relying solely on anatomical specificity by guiding current to specific brain regions (and so the “sliding-scale” rationale) remains limited by the complex and divergent functions of any brain region.

Further sophistication in anatomical targeting follows from considering tangential as well as radial inward/outward currents ( ). Indeed, the assumption of inward (“excitatory”) and outward (“inhibitory”) current under the anode and cathode, respectively, may be a further oversimplification. Electrophysiological studies, in animal models of DCS, suggest differential processing of afferent information ( ) and that polarity-specific effects invert due to neuronal morphology ( ).

Activity-Selectivity and Task-Specific Modulation

Activity-selectivity refers to tDCS preferentially modulating a neuronal network that is already activated, while not modulating separate, neuronal networks that are inactive. The active, neuronal network may be activated for a host of reasons described. The active and inactive networks can in fact overlap in space (e.g., in the same cortical column) such that activity-selectivity does not require physical separation, in contrast to anatomical specificity. Therefore, we refer to activity-selectivity as a form of functional specificity. The active network may represent a subset of neurons and/or a subset of connections (synapses). Because tDCS produces low-intensity, electric fields in the brain, “subthreshold” neuromodulation may reflect changes in ongoing processes, in contrast to suprathreshold driven firing by TMS. Activity-selectivity thus assumes there is some feature of the active network that makes it preferentially sensitive to modulation by tDCS when compared to other inactive networks. We consider two neurophysiological substrates for this preferred sensitivity: ongoing activity-selectivity and input-selectivity.

Activity-selectivity is based on the assumption that tDCS will preferentially modulate specific forms of ongoing activity. For example, at a cellular level, DCS may enhance plasticity in a given synaptic pathway while stimulated at a preferential frequency (0.1 Hz in ( )) or consolidate a specific pattern of activity, presented during DCS ( ). DCS may preferentially modulate the level of potentiation in the activated pathway ( ). It may facilitate long-term potentiation through membrane polarization and removal of Mg+ block ( ), but only those pathways activated during DCS (by a task or experimental stimulation) would benefit from this facilitation. It may be too weak and/or unspecific in isolation to enhance synaptic efficacy, but may boost ongoing (e.g., Hebbian) plasticity, activated by task performance (i.e., modulation of input specific plasticity along an activated synaptic pathway while sparing quiescent synapses). In humans, TES may also preferentially modulate networks with heightened oscillatory activity ( ) or preferentially change the progression of an active network during memory consolidation or synaptic downscaling ( ).

At a behavioral level, specific brain activity is often targeted by training, in conjunction with tDCS, with the goal that this select activity be sensitized to tDCS neuromodulation (and so, it implies that other brain functions, not active in training, may be less so). For example, use-dependent modulation and learning of motor skills is modulated by tDCS ( ). Clinically, tDCS is often applied to enhance the efficacy of rehabilitation or cognitive training ( ), which may further confer functional specificity through activity-selectivity. Clinically, when tDCS is applied to subjects at rest, we can speculate that any functional specificity results from increased sensitivity of pathological network activity to tDCS (e.g., dysfunctional pain or mood regulating networks). It has been speculated that altered network function, associated with brain injury (stroke), may alter the susceptibility to tDCS ( ). Generally, any interaction between brain activity and the efficacy of tDCS modulation ( ) suggests that “tDCS can be highly focal when guided by a behavioral task” ( ).

Although the mechanisms may vary, in any case, functional specificity through activity-selectivity presumes that the enhanced activity of the network makes it preferentially sensitive to modulation by tDCS. Thus, activity-selectivity necessitates an ongoing network process becoming preferentially tuned to influence by DCS when compared to the myriad of other ongoing (background) brain functions.

Input-Selectivity and Bias

A third form of specificity is input-selectivity, which assumes a neuronal network that is predisposed to serve at least two functions or operate in at least two states, such that tDCS can switch the network from one function/state to another (for example, attentional bias in the prefrontal cortex ( )). tDCS would change the state of the system toward a different input bias and thus enhance information processing of a specific stream of information. Input-selectivity may activate endogenous “gating” systems (e.g., gate theory of pain) or bistable, neuronal states, where a nonspecific DC signal is able to “switch” a system between complex functions or modes. In contrast to a sliding-scale hypothesis for a stimulated brain region or activity-selectivity affecting a specific ongoing process, input-selectivity implies that a regional process is enhanced, at the cost of another process, and not that input-selectivity results in a zero-sum effect in regard to lasting cognition or behavior outcomes. However, input-selectivity does emphasize the “cost” of acute stimulation. Input-selectivity is also considered a form of functional specificity since it does not require gross anatomical targeting of current flow. Input-selectivity thus differs conceptually from functional-selectivity, in that it does not presuppose coactivation (e.g., by training), and moreover implies that one process may be enhanced at the cost of enhancing another.

Animal studies that have investigated the modulation of information processing, for example, through synaptic efficacy (as opposed to simply membrane polarization and excitability ( )), have observed that DCS will differentially modulate incoming inputs. We initially showed in hippocampal slice that DCS enhances some and inhibits other afferent inputs ( ), a finding verified ( ) and extended to the cortex ( ). The cellular origins of bias in favor of selective inputs are two-fold. First, although anodal and cathodal tDCS are mistakenly referred to as depolarizing and hyperpolarizing, it is more accurate to describe tDCS as redistributing polarization across the cellular axis (for example, one dendritic branch vs. another ( )). This change in “weights” across the dendrite may provide a cellular substrate to influence the input bias of a network. Second, polarization of afferent axons, itself, appears to exert pathway specific modulation ( ; ).

Computational Models of Transcranial Direct Current Stimulation for Electrode Placement

tDCS is a single, programmable, electrotherapy device that can be simply configured to provide a diversity of dosages. Though this flexibility underpins the utility of neuromodulation, the myriad of potential dosages (e.g., stimulator settings and combinations of electrode placements) can lead to a great number of possibilities, thus making the optimal choice very difficult to readily ascertain. The essential issue in dose design is to relate each externally, controlled dose with the associated, brain regions targeted (and spared) by the resulting current flow and hence, the desired clinical outcome. Computational forward models aim to represent a critical tool in the rational design, interpretation, and optimization of neuromodulation ( ).

Common Montages

Primary motor cortex (M1) (Anode)-Supraorbital (SO) (Cathode): this is the most common tDCS montage. M1 is a target that modulates the sensory and motor, subthalamic activity, associated with chronic pain. It has been shown that the cortical excitability can be changed up to 40% ( ). The polarity (anode/cathode) of the electrode refers to the M1 electrode. Anodal stimulation results in neuronal, soma depolarization and increasing neuronal excitability, while cathodal stimulation has opposite results ( ). Only one motor cortex is stimulated, so that bilateral montages are an alternative for bilateral pain syndromes ( ). Potential confounding effects of the supraorbital electrode needs to be considered.

Dorsolateral Prefrontal Cortex (DLPFC) (Anode)-SO (Cathode): Is commonly tested for the treatment of depression ( ) and chronic pain ( ). This montage has yielded encouraging results ( ). Typical montages are bilateral DLPFC stimulation with the anode over the left DLPFC, but unilateral montages are possible ( ).

4 × 1 High-Definition (HD)-tDCS: Experimental results demonstrate the neurophysiological efficacy of HD-tDCS on motor cortex plasticity. 4 × 1 HD-tDCS, as well as other HD deployments, may offer the opportunity to induce plasticity more focally than conventional tDCS protocols ( ). Most published studies on 4 × 1 HD-tDCS have targeted the primary motor cortex (M1), particularly for pain-related outcomes ( ). However, there is a study that DLPFC was targeted also ( ).

Methods for the Generation and Use of Computational Forward Models of Transcranial Direct Current Stimulation

Computational models of tDCS range in complexity from concentric, sphere models to high-resolution models, based on an individual’s MRI. The appropriate level of modeling detail depends on the clinical question, being asked (as well as the available computational resources). Whereas simple geometries (e.g., spheres) may be solved analytically, realistic geometries employ specialized software, as described later, that include numerical solvers (namely finite element methods [FEM]). Regardless of complexity, all forward models share the primary outcome of correctly predicting brain-current flow during transcranial stimulation to guide clinical, therapeutic delivery.

For clinicians interested in using computational forward models to inform study design or interpretation, several options are available: (1) a collaboration with a modeling group or a company can allow for customized exploration of montage options (2) referencing existing published reports or databases for comparable montages (3) by utilizing a recently developed process, where a desired brain target can be selected and the optimized stimulation electrode montage is proposed within seconds ( ). If tDCS continues to emerge as an effective tool in clinical treatment and cognitive neuroscience, and concurrent modeling studies emphasize the need for rational (and in cases of patient-specific) dose decisions, then it will become incumbent for clinical research teams to understand the applications (and limitations) of computational forward models ( ).

While the specific software applications used can vary across modeling groups, in general, the approach and work-flow for model generation follows a similar pattern. The steps for generating high-resolution (anatomically specific) forward models of noninvasive neuromodulation are adapted from extensive, prior work on computational modeling. These involve various steps:

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  Step 1, demarcation of individual, tissue types (masks) from high-resolution, anatomical data, using a combination of automated and manual segmentation tools. It is worth noting that the respective contribution of the automated/manual interventions depends on (a) sophistication of the particular automated algorithm employed, since they are usually not optimized for forward, transcranial modeling ( ) and (b) the need for identification of anomalies, in suspect populations like skull defects, lesions, shunts, and so on. Consequently, as emphasized later in this section, the number and precision of the individual masks obtained is pivotal for the generation of accurate, three-dimensional (3D) models to capture critical, anatomical details that may influence current flow.

  
  
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  Step 2, modeling of the exact, physical properties of the electrodes (e.g., shape and size) and precise placement within the segmented image data (i.e., along the skin mask outer surface).

  
  
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  Step 3, generation of accurate meshes (with high-quality factor) from the tissue/electrode masks, while preserving resolution of subject and anatomical data.

  
  
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  Step 4, resulting volumetric meshes are then imported into a commercial, finite element solver.

  
  
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  Step 5, at this step, resistivity is assigned to each mask and the boundary conditions are imposed. The standard Laplacian equation is solved using appropriate numerical solver and tolerance settings ( ).

  
  
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  Step 6, data are plotted as induced, cortical electric fields or current density maps.

As head size and shape vary from person to person, it is important to use a method for common localization of electrode position. There are several methods for addressing this issue:

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  international 10–20 (or 10–5) electrode placement system ( ), or another, gross anatomical, coordinate system ( ),

  
  
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  neuronavigation systems (e.g., MRI guided; ), or

  
  
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  physiology-based placement (e.g., TMS generated MEPs). At present, physiology-based placement can only be performed for motor and other primary cortices (e.g., sensory). However, further options may become available in the future (e.g., Transcranial magnetic stimulation (TMS)-electroencephalogram (EEG) methods). Regardless, these methods can be used to reproducibly center each electrode on the head, accommodating varied head shape or size ( ).