Methodology for tDCS integration with fMRI

Abstract

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.

Group and Individual Level Variations between Symmetric and Asymmetric DLPFC Montages for tDCS over Large Scale Brain Network Nodes

“…Open questions remain about how to relate EFs with behavioral or neurophysiological changes. The relationship between EF intensity and neural/behavioral responses is not a trivial matter and there is still no clear understanding of the underlying tDCS mechanism of action at the networklevel [60]. Integrating EF modeling and neuroimaging information such as functional connectivity that incorporates the interactions within and between large-scale functional networks can provide for a better understanding of tDCS effects in terms of dose-response relationships.…”

“…Integrating EF modeling and neuroimaging information such as functional connectivity that incorporates the interactions within and between large-scale functional networks can provide for a better understanding of tDCS effects in terms of dose-response relationships. For example, Esmaeilpour et al reported a significant correlation between EF obtained from CHMs and changes in fMRI signals [60]. Kasten et al revealed a direct link between EF variability and alpha band frequency changes as a proxy indicator of neural activity in a transcranial alternative current stimulation (tACS) study combined with MEG [23].…”

Transcranial Direct Current Stimulation to Modulate Brain Reactivity to Food Cues: Study Protocol of a Randomized Controlled Trial with fMRI (NeuroStim-Obesity)

“…Exploratory analyses will be conducted for measures of subjective, behavioral, neuropsychological, or neural circuits which will be analyzed for identifying potential predictors of food cue-reactivity task performance, and responsiveness to the intervention, as measures by an exploratory regularized regression model. Additionally, the induced E-field in the prefrontal area, derived from analysis of computational finite element model, will be included as potential predictor of neural response to tDCS (Esmaeilpour et al, 2019;Ghobadi-Azbari et al, 2020).…”

Application of direct transcranial current as non-invasive therapy in eating disorders: an intervention proposal

“…Se empleará HD-tDCS por su mayor precisión y para facilitar el análisis de los datos mediante fMRI (Esmaeilpour et al, 2019), situando los electrodos en las zonas que han demostrado mayor efectividad; en la dlPFC izquierdo el ánodo (excitatorio) y en la dlPFC derecho el cátodo (inhibitorio), la intensidad será de 2mA, con una duración de 25 minutos, 15 sesiones de lunes a viernes, días alternos, una duración total de 5 semanas.…”