Review of individualized current flow modeling studies for transcranial electrical stimulation

Abstract

There is substantial intersubject variability of behavioral and neurophysiological responses to transcranial electrical stimulation (tES), which represents one of the most important limitations of tES. Many tES protocols utilize a fixed experimental parameter set disregarding individual anatomical and physiological properties. This onesize-fits-all approach might be one reason for the observed interindividual response variability. Simulation of current flow applying head models based on available anatomical data can help to individualize stimulation parameters and contribute to the understanding of the causes of this response variability. Current flow modeling can be used to retrospectively investigate the characteristics of tES effectivity. Previous studies examined, for example, the impact of skull defects and lesions on the modulation of current flow and demonstrated effective stimulation intensities in different age groups. Furthermore, uncertainty analysis of electrical conductivities in current flow modeling indicated the most influential tissue compartments. Current flow modeling, when used in prospective study planning, can potentially guide stimulation configurations resulting in individually effective tES. Specifically, current flow modeling using individual or matched head models can be employed by clinicians and scientists to, for example, plan dosage in tES protocols for individuals or groups of participants.We review studies that show a relationship between the presence of behavioral/ neurophysiological responses and features derived from individualized current flow models. We highlight the potential benefits of individualized current flow modeling.

How does the electric field induced by tDCS influence motor-related connectivity? Model-guided perspectives

“…Also, models obtained by headreco do not discriminate stratification of extracerebral tissues, which impact the dielectric properties assigned to the skin and consequently the EF distribution predicted in the brain (Colella et al 2021). On the other hand, individual specific anatomical characteristics influence the current flow and thus the EF induced by tDCS, which reflects in variable outcomes from subject to subject (Hunold et al 2023). Modulation of brain networks with non-invasive techniques such as tDCS, are strongly subject-dependent, thus precision medicine approaches are more and more recommended, guided by personalised models (Antal et al 2022).…”

Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function

“…In the same vein, Reihart and Nguyen demonstrated fast working-memory performance improvement in elders by applying HD-tACS with frequencies tuned in an individualized fashion ( Reinhart and Nguyen, 2019 ). Nowadays, the importance of personalization is further emphasized in the clinical usage of personalized neurostimulation for epilepsy ( Beumer et al, 2021 ), sensorimotor disorders ( Gupta et al, 2023 ), cognitive function ( Albizu et al, 2023 ), and dysfunction ( Hunold et al, 2022 ; Reinhart, 2022 ; Aiello et al, 2023 ), and several other applications. In fact, researchers are actively exploring tailored approaches that leverage computational models, machine learning, and Bayesian optimization algorithms to optimize stimulation parameters and enhance treatment outcomes.…”

“…A major effort in this direction has been the individualized modeling of current flow, which relies on volume conductor models to analyze the distribution of the electric field and electric current density within the complete head under stimulation ( Hunold et al, 2022 ). This technique is based on the quasi-stationary approximation of Maxwell’s equations, assuming a linear connection between the electric field and current density, determined by the electrical conductivity of the tissues.…”

“…Overall, findings of the reviewed studies pointed to the benefits of adopting a personalization strategy. Not only improved cognitive performance and amelioration of symptoms were observed, but the modelling allowed for the reduction of side-effects and better predictability of outcomes ( Hunold et al, 2022 ).…”

Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans

“…The analysis of the individualized electric field clarified the role of stimulation parameters and anatomical aspects shaping the electric field in the brain cortex [ 19 , 20 ] and deep brain areas [ 21 , 22 ]. Ongoing efforts aim to clarify the relationship between tES-generated electric fields and physiological/behavioral responses [ 23 ]. Recently, not only has individualized-level knowledge of the electric field been gained, but population-level knowledge of the electric field distribution has also gained interest based on registration techniques of the individualized electric field into brain templates [ 24 , 25 , 26 , 27 ].…”