Review of individualized current flow modeling studies for transcranial electrical stimulation. Issue 4 (20th December 2022)

• Record Type: Journal Article
• Authors: Hunold, Alexander; Haueisen, Jens; Nees, Frauke; Moliadze, Vera
• Is Part Of: Journal of neuroscience research. Volume 101:Issue 4(2023)
• Page Start: 405
• Page End: 423
• Publication Date: 2022-12-20
• Subjects: age -- current flow simulation -- forward modeling -- precision medicine -- transcranial electrical stimulation (tES); Neurobiology -- Periodicals; 612
• DOI: 10.1002/jnr.25154
• Languages: English
• ISSNs: 0360-4012

Abstract

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 one‐size‐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.