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| Funder | NATIONAL INSTITUTE OF MENTAL HEALTH |
|---|---|
| Recipient Organization | Worcester Polytechnic Institute |
| Country | United States |
| Start Date | Aug 09, 2024 |
| End Date | Apr 30, 2026 |
| Duration | 629 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10995012 |
ABSTRACT Brain stimulation therapies are important and effective treatments for people with depression and other mental disorders. The National Institute of Mental Health (NIMH) is supporting studies exploring how to make brain stimulation therapies more personalized and effective while reducing side effects. For all brain stimulation
modalities, computational numerical modeling of the electric, magnetic and acoustic fields within a patient- specific head model is the leading and most promising way to develop improved spatial targeting methods and quantitatively determine the required stimulation dose. Similarly, neurophysiological signal analyses require
extensive numerical computational modeling to identify active cortical domains from limited electrode voltage and magnetometer measurements. The present proposal will facilitate development of fast and accurate brain and human body modeling methods and techniques via a dedicated and growing computational conference on
Brain and Human Body Modeling. Aligned with NIMH’s mission, the specific aims of this proposal will include the following: (i) Exchanging ideas, method, and approaches on computational modeling electric and magnetic fields within the brain targeting neurostimulation modalities (TMS, TES, DBS, tFUS) and associated neurophysiological
recordings (EEG, iEEG, MEG); (ii) Integration of modeling techniques into clinical practice; (iii) Hands-on training to keep pace with the rapidly evolving technologies by introducing four dedicated workshops in total as an integral part of the conference agenda; (iv) Inclusion of industrial participation in the form of dedicated presentations, demonstrations, and
booths/banners to provide opportunities for training and future high-tech employment of young professionals including women and underrepresented populations. These modeling techniques are aimed to provide better focality, targeting accuracy, and improve the overall efficiency of brain stimulation methods. They will also support promising combinations and derivatives of the
neuromodulation and neurophysiological recordings such as TMS-EEG and TES-EEG. No established computational methods for modeling these combined modalities currently exist. The conference will include related topics that share very similar, sometimes identical, computational methods and tools. We aim to synergistically share these computational tools for maximal benefit and to facilitate
interactions across disciplines.
Worcester Polytechnic Institute
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