Short-term plasticity in the human brain induced by transcranial electrical stimulation and memory training (Plast-Mem): a multi-modal MRI approach

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Non-invasive brain stimulation (NIBS) techniques such as transcranial electrical stimulation (tES) with transcranial direct current stimulation (tDCS) as the most common approach, have been used to examine brain-behavior relationships and modulate human cognitive function. With regard to neuronal mechanisms, anodal tDCS over task-relevant brain regions is thought to increase excitability of the cortex and induce long-term potentiation (LTP)-like processes, leading to enhancement in behavioral task performance. The combination of tDCS with brain imaging techniques, either consecutively or concurrently, has allowed characterization of neural modulation on the levels of brain activity, brain connectivity and metabolite concentrations in the human brain. Synaptic and cellular processes, reflecting underlying the structural plasticity in vivo, have been assessed so far using electrophysiology and spectroscopy approaches in the human brain. Microstructural plasticity in brain gray and white matter, an important marker of learning-related plasticity in the brain, has not been assessed in the context of tDCS yet. To this end, the superordinate aim of this project is to investigate short-term structural brain plasticity on the level of microstructure and neurometabolite concentrations of tDCS-supported memory training in the human brain using multi-modal MR imaging. We will apply focal (high-definition) anodal tDCS over temporo-parietal sites during an object-location memory paradigm and acquire multi-modal MRI before, immediately after (work package 1, WP1) and 12-hours after training (WP2) to assess microstructural plasticity using DTI metrics in memory-related network hubs and white matter pathways and metabolite concentrations using MRS as markers for neuronal function. The inter-dependency of microstructural and metabolic plasticity will additionally be investigated (WP3), together with the linkage of behavioral and functional network effects to individually induced electric fields estimated using computational modeling (WP4). This project will advance the comprehensive understanding of tDCS-induced plasticity and support the development of individually adjusted applications to target cognitive systems in the future.