The project “An Open Software Solution to Integrate Non-Invasive Brain Stimulation and Functional Imaging Analysis” is funded by the NIH BRAIN Initiative and is a collaborative effort between local researchers at DRCMR led by Axel Thielscher with Alexander Opitz (project PI, University of Minnesota) and Dr. Michael P. Milham (Child Mind Institute, New York).
Noninvasive tools capable of selectively manipulating neural systems in the human brain are needed to advance our neuroscientific understanding of brain function and develop novel non-pharmacologic psychotherapeutics and are a major focus of the NIH BRAIN Initiative. Transcranial magnetic stimulation (TMS), transcranial direct current (tDCS) and alternating current (tACS) stimulation have well-established capacities to noninvasively modulate neural activity by inducing electric fields in the brain, as well as ease of application and favorable safety profiles. To further advance their efficacy in research and treatment, it is important to understand the relation between their physical stimulation fields and the resulting physiological responses. However, no integrated software platform exists to date, which integrates accurate simulations of the electric field induced for an individual with the analysis of the physiological response measured with neuroimaging. This severely hampers efforts to compare results across studies, participants or species.
This project has several complementary aims to overcome the above limitations. We propose to promote the widespread use of accurate simulations based on finite-element methods (FEM) in research and clinical environments through extending and scaling SimNIBS (‘Simulation of Non-Invasive Brain Stimulation’) - the leading open source software platform for generating FEM-based models of the electric field distribution produced by TMS, tDCS or tACS. Specifically, we will create direct interfaces with commercial neuro-navigation systems and optimize SimNIBS for analyses of large-scale datasets, including the creation of a containerized version for use in the cloud. Further, we will develop a module for integrated analysis of simulated fields with functional network maps generated with resting state functional MRI to enable the optimization of targeting based on individualized predicted network profiles. Finally, we will create a non-human primate (NHP) SimNIBS module to allow for the processing of NHP data facilitating translational and comparative neuroscience goals of the BRAIN Initiative.
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