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-i

SUBMITTER: Albizu A 

PROVIDER: S-EPMC7731513 | biostudies-literature | 2020 Nov - Dec

REPOSITORIES: biostudies-literature