Simultaneous Transcranial Alternating Current Stimulation and Functional Magnetic Resonance Imaging

Williams, Kathleen A.; Cabral‐Calderín, Yuranny; Schmidt‐Samoa, Carsten; Weinrich, Christiane Anne; Dechent, Peter; Wilke, Melanie

doi:10.3791/55866

Cited by 15 publications

(33 citation statements)

References 33 publications

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“…A main hardware precaution to be aware of when bringing any electronic equipment into the MRI scanner is not allowing the wires to become RF transmitters and introduce noise into the MRI data. To prevent this, currently two similar hardware configurations for MRI‐compatible tDCS are used (Meinzer et al, ; Williams et al, ). The procedures are described below: Connect the leads from the tDCS power supply to an RF filter box (MRI control room), from the RF filter box to a nonmagnetic, shielded local network cable that enters the MRI scanner room via the RF waveguide tube, carefully oriented to reduce resonant capacitive coupling, and then finally sent through another RF filter box (MRI‐compatible, inside scanner room) before connecting to the tDCS electrodes (Figure a). Connect the leads from the tDCS power supply (MRI control room) to an RF filter attached to the penetration panel, and then connect the other end of the penetration panel (MRI scanner room) to the electrode leads (Figure b). …”

Section: Practical Considerations When Combining Tdcs With Functionalmentioning

confidence: 99%

Section: Mri-compatible Stimulator Setupmentioning

confidence: 99%

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Methodology for tDCS integration with fMRI

Esmaeilpour

Shereen

Ghobadi‐Azbari

et al. 2019

Human Brain Mapping

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Understanding and reducing variability of response to transcranial direct current stimulation (tDCS) requires measuring what factors predetermine sensitivity to tDCS and tracking individual response to tDCS. Human trials, animal models, and computational models suggest structural traits and functional states of neural systems are the major sources of this variance. There are 118 published tDCS studies (up to October 1, 2018) that used fMRI as a proxy measure of neural activation to answer mechanistic, predictive, and localization questions about how brain activity is modulated by tDCS. FMRI can potentially contribute as: a measure of cognitive state‐level variance in baseline brain activation before tDCS; inform the design of stimulation montages that aim to target functional networks during specific tasks; and act as an outcome measure of functional response to tDCS. In this systematic review, we explore methodological parameter space of tDCS integration with fMRI spanning: (a) fMRI timing relative to tDCS (pre, post, concurrent); (b) study design (parallel, crossover); (c) control condition (sham, active control); (d) number of tDCS sessions; (e) number of follow up scans; (f) stimulation dose and combination with task; (g) functional imaging sequence (BOLD, ASL, resting); and (h) additional behavioral (cognitive, clinical) or quantitative (neurophysiological, biomarker) measurements. Existing tDCS‐fMRI literature shows little replication across these permutations; few studies used comparable study designs. Here, we use a representative sample study with both task and resting state fMRI before and after tDCS in a crossover design to discuss methodological confounds. We further outline how computational models of current flow should be combined with imaging data to understand sources of variability. Through the representative sample study, we demonstrate how modeling and imaging methodology can be integrated for individualized analysis. Finally, we discuss the importance of conducting tDCS‐fMRI with stimulation equipment certified as safe to use inside the MR scanner, and of correcting for image artifacts caused by tDCS. tDCS‐fMRI can address important questions on the functional mechanisms of tDCS action (e.g., target engagement) and has the potential to support enhancement of behavioral interventions, provided studies are designed rationally.

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Section: Practical Considerations When Combining Tdcs With Functionalmentioning

confidence: 99%

Section: Mri-compatible Stimulator Setupmentioning

confidence: 99%

Methodology for tDCS integration with fMRI

Esmaeilpour

Shereen

Ghobadi‐Azbari

et al. 2019

Human Brain Mapping

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“…Several EEG/fMRI studies revealed how the manipulated oscillatory activity of tACS is represented in the brain’s metabolism while demonstrating that increased alpha and beta amplitudes correlate with deactivation in occipital areas measured by reduced blood oxygenation level dependent (BOLD) contrasts ( Cabral-Calderin et al, 2016 ; Williams et al, 2017 ). Moreover, Vosskuhl et al (2016) confirmed that entrainment of EEG alpha oscillations by tACS at the IAF reduces the BOLD response to visual stimuli ( Vosskuhl et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Brain Oscillatory and Hemodynamic Activity in a Bimanual Coordination Task Following Transcranial Alternating Current Stimulation (tACS): A Combined EEG-fNIRS Study

Berger

Pixa

Steinberg

et al. 2018

Front. Behav. Neurosci.

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Motor control is associated with synchronized oscillatory activity at alpha (8–12 Hz) and beta (12–30 Hz) frequencies in a cerebello-thalamo-cortical network. Previous studies demonstrated that transcranial alternating current stimulation (tACS) is capable of entraining ongoing oscillatory activity while also modulating motor control. However, the modulatory effects of tACS on both motor control and its underlying electro- and neurophysiological mechanisms remain ambiguous. Thus, the purpose of this study was to contribute to gathering neurophysiological knowledge regarding tACS effects by investigating the after-effects of 10 Hz tACS and 20 Hz tACS at parietal brain areas on bimanual coordination and its concurrent oscillatory and hemodynamic activity. Twenty-four right-handed healthy volunteers (12 females) aged between 18 and 30 (M = 22.35 ± 3.62) participated in the study and performed a coordination task requiring bimanual movements. Concurrent to bimanual motor training, participants received either 10 Hz tACS, 20 Hz tACS or a sham stimulation over the parietal cortex (at P3/P4 electrode positions) for 20 min via small gel electrodes (3,14 cm2 Ag/AgCl, amperage = 1 mA). Before and three time-points after tACS (immediately, 30 min and 1 day), bimanual coordination performance was assessed. Oscillatory activities were measured by electroencephalography (EEG) and hemodynamic changes were examined using functional near-infrared spectroscopy (fNIRS). Improvements of bimanual coordination performance were not differently between groups, thus, no tACS-specific effect on bimanual coordination performance emerged. However, physiological measures during the task revealed significant increases in parietal alpha activity immediately following 10 Hz tACS and 20 Hz tACS which were accompanied by significant decreases of Hboxy concentration in the right hemispheric motor cortex compared to the sham group. Based on the physiological responses, we conclude that tACS applied at parietal brain areas provoked electrophysiological and hemodynamic changes at brain regions of the motor network which are relevant for bimanual motor behavior. The existence of neurophysiological alterations immediately following tACS, especially in the absence of behavioral effects, are elementary for a profound understanding of the mechanisms underlying tACS. The lack of behavioral modifications strengthens the need for further research on tACS effects on neurophysiology and behavior using combined electrophysiological and neuroimaging methods.

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“…tDCS effects with high spatial resolution across the entire brain [10]. Combining tACS with simultaneous fMRI has shown that the stimulation effects are state-, current-, and frequency-dependent, and that modulation of brain activity is not limited to the area directly below the electrodes [11].…”

Section: Introductionmentioning

confidence: 99%

Modeling radio-frequency energy-induced heating due to the presence of transcranial electric stimulation setup at 3T

Kozlov

Horner

Kainz

et al. 2020

Magn Reson Mater Phy

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Purpose The purpose of the present study was to develop a numerical workflow for simulating temperature increase in a high-resolution human head and torso model positioned in a whole-body magnetic resonance imaging (MRI) radio-frequency (RF) coil in the presence of a transcranial electric stimulation (tES) setup. Methods A customized human head and torso model was developed from medical image data. Power deposition and temperature rise (ΔT) were evaluated with the model positioned in a whole-body birdcage RF coil in the presence of a tES setup. Multiphysics modeling at 3T (123.2 MHz) on unstructured meshes was based on RF circuit, 3D electromagnetic, and thermal co-simulations. ΔT was obtained for (1) a set of electrical and thermal properties assigned to the scalp region, (2) a set of electrical properties of the gel used to ensure proper electrical contact between the tES electrodes and the scalp, (3) a set of electrical conductivity values of skin tissue, (4) four gel patch shapes, and (5) three electrode shapes. Results Significant dependence of power deposition and ΔT on the skin’s electrical properties and electrode and gel patch geometries was observed. Differences in maximum ΔT (> 100%) and its location were observed when comparing the results from a model using realistic human tissue properties and one with an external container made of acrylic material. The electrical and thermal properties of the phantom container material also significantly (> 250%) impacted the ΔT results. Conclusion Simulation results predicted that the electrode and gel geometries, skin electrical conductivity, and position of the temperature sensors have a significant impact on the estimated temperature rise. Therefore, these factors must be considered for reliable assessment of ΔT in subjects undergoing an MRI examination in the presence of a tES setup.

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Simultaneous Transcranial Alternating Current Stimulation and Functional Magnetic Resonance Imaging

Cited by 15 publications

References 33 publications

Methodology for tDCS integration with fMRI

Methodology for tDCS integration with fMRI

Brain Oscillatory and Hemodynamic Activity in a Bimanual Coordination Task Following Transcranial Alternating Current Stimulation (tACS): A Combined EEG-fNIRS Study

Modeling radio-frequency energy-induced heating due to the presence of transcranial electric stimulation setup at 3T

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