Machine learning and individual variability in electric field characteristics predict tDCS treatment response

Abstract

Background: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delivery to the brain can vary significantly across individuals. Quantification of this variability could enable person-specific optimization of tDCS outcomes. This pilot study used machine learning and MRI-derived electric field models to predict working memory improvements as a proof of concept for precision cognitive intervention. Methods: Fourteen healthy older adults received 20 minutes of 2 mA tDCS stimulation (F3/F4) during a two-week cognitive training intervention. Participants performed an N-back working memory task pre-/ post-intervention. MRI-derived current models were passed through a linear Support Vector Machine (SVM) learning algorithm to characterize crucial tDCS current components (intensity and direction) that induced working memory improvements in tDCS responders versus non-responders. Main results: SVM models of tDCS current components had 86% overall accuracy in classifying treatment responders vs. non-responders, with current intensity producing the best overall model differentiating changes in working memory performance. Median current intensity and direction in brain regions near the electrodes were positively related to intervention responses (r ¼ 0:811; p < 0:001 and r ¼ 0:774; p ¼ 0:001). Conclusions: This study provides the first evidence that pattern recognition analyses of MRI-derived tDCS current models can provide individual prognostic classification of tDCS treatment response with 86% accuracy. Individual differences in current intensity and direction play important roles in determining treatment response to tDCS. These findings provide important insights into mechanisms of tDCS response as well as proof of concept for future precision dosing models of tDCS intervention.

A Systematic Review and Meta-Analysis of Transcranial Direct Current Stimulation to Remediate Age-Related Cognitive Decline in Healthy Older Adults

“…For instance, adjusting current intensity level and using custom electrode placement to target desired brain region in each person. Further, application of one-size-fit-all may need improving for future tDCS application such as through the use of machine learning approaches 89 to optimize outcomes and reduce inter-individual variability observed across tDCS participants.…”

“…This observation suggests that the directional component of applied electrical field may play a crucial role in determining optimum current dose in tDCS application to elicit observed outcomes which support recent research findings in this topic. [86][87][88][89] tDCS and Cognitive Tasks Positive tDCS effects have been found to be state-dependent, and thus, the level of engagement in cognitive tasks may be important to generate desired outcomes. Electrical current from tDCS alone is considered weak and non-specific to enhance synaptic efficacy.…”

Identifying regions in prefrontal cortex related to working memory improvement: a novel meta-analytic method using electric field modeling

“…In the present study we introduced a novel way of systematically investigating tDCS parameters across multiple studies. Recently, studies used individualized electric field simulations and compared these to changes in behavior (Albizu et al, 2020;Caulfield et al, 2020;Evans et al, 2020;Kim et al, 2014). Thereby, these studies were able to control for interindividual electric field variability when interpreting tDCS-related effects.…”

White matter hyperintensities affect transcranial electrical stimulation in the aging brain

“…However, the potential effects of current pooling within the lesion regions on neuronal firing warrant further research. In addition, findings reported in this study i.e., nominal changes in delivered current dose resulted from WMH presence will require further investigation in dose-response relationship that is crucial for refining the formulation of precision dosing applications in tES based on FEM [27]. As WMH appear to alter the intensity of electric current induced within non-lesioned brain tissue, attempts to derive precision dosing approaches from FEM may underestimate the required dosing if WMH are not accounted for in models of older adult brain.…”