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Transcranial direct current stimulation effects on healthy language networks.

Subject Area Human Cognitive and Systems Neuroscience
Term from 2020 to 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 435334755
 
Final Report Year 2025

Final Report Abstract

Transcranial direct current stimulation (tDCS) has sparked considerable scientific, clinical and public interest because it allows modulation of human brain function and behavior without significant adverse effects. To date, hundreds of scientific papers have reported beneficial behavioral effects of tDCS in healthy and clinical populations. However, recent studies have also highlighted variable stimulation effects and small effect sizes. This has prompted calls for more rigorous methodology and emphasized the need to increase knowledge about the mechanisms by which tDCS affects complex human brain networks, which is currently lacking. Notably, information from (a) functional neuroimaging, (b) modelling of electrical current flow in the brain and (c) simulations of brain stimulation effects in virtual environments have all demonstrated potential to provide insight into how tDCS affects neural processing at the whole brain level. However, this information has never been systematically integrated in a mutually informative way, to develop a comprehensive model of how tDCS impacts human brain functions. This was addressed in the present project, that acquired functional magnetic resonance imaging (fMRI) data with concurrent (intrascanner) tDCS in a sham tDCS controlled cross-over design. 120 healthy young participants completed two imaging sessions and received conventional or focalized (N=30 each) active and sham tDCS to either the primary motor or inferior frontal gyrus (M1, IFG, N=30 each) during resting-state and task-based (semantic verbal fluency) fMRI. This approach aimed to investigate behavioral and neural modulation by active tDCS. Structural imaging was acquired to verify correct electrode placement on the scalp and to conduct individualized computer simulations of current flow induced by the respective montages. Preliminary analyses of functional imaging data suggests stronger behavioral and neural network modulation by conventional compared to focal tDCS. Current modeling revealed that electrode placement errors resulted in disproportionate current flow reductions to the target regions for focal compared to conventional set-ups. Based on this outcome, we developed a novel neuronavigated focalized tDCS approach, that improved electrode placement accuracy by 40%. We also developed and validated a novel machine learning approach for fully automated electrode position extraction from structural MRI data, to improve the validity and efficiency of individualized current modeling that considers actual electrode positions in this and future tDCS-fMRI studies. Integration of functional imaging analyses with structural and modeling data into a virtual brain model are currently ongoing, which has potential to substantially improve our understanding of brain network modulation by tDCS.

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