Abstract
During the past decade, it became clear that the effects of non-invasive brain stimulation (NIBS) techniques such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) are substantially influenced by variations in individual head and brain anatomy. In addition to structural variations in the healthy, several psychiatric disorders are characterized by anatomical alterations that are likely to further constrain the intracerebral effects of NIBS. Here, we present high-resolution realistic head models derived from structural magnetic resonance imaging data of 19 healthy adults and 19 patients diagnosed with major depressive disorder (MDD). By using a freely available software package for modelling the effects of different NIBS protocols, we show that our head models are well-suited for assessing inter-individual and between-group variability in the magnitude and focality of tDCS-induced electric fields for two protocols targeting the left dorsolateral prefrontal cortex.
Highlights
During the past decade, it became clear that the effects of non-invasive brain stimulation (NIBS) techniques such as transcranial direct current stimulation and transcranial magnetic stimulation (TMS) are substantially influenced by variations in individual head and brain anatomy
We present 38 head models created from magnetic resonance (MR) images of 19 healthy participants and 19 patients with major depressive disorder (MDD)
Given the different protocols used for left dorsolateral prefrontal cortex targeting with NIBS21,22, computational modelling using these head models will enable the development of protocols for more selective lDLPFC stimulation in this disorder
Summary
It became clear that the effects of non-invasive brain stimulation (NIBS) techniques such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) are substantially influenced by variations in individual head and brain anatomy. Given the heterogeneity in the efficacy of NIBS protocols in modulating behavior and clinical symptoms, there has been a move towards computational modelling of the spatial distribution of E-fields in the brain to understand how stimulation parameters such as electrode placement, rotation or type affects current flow in the neural tissue.
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