This project aims at developing novel methods for predicting the large-scale cortical network that is activated by spatially focused transcranial magnetic stimulation (TMS). Presently there is no integrated framework that would allow predicting how the activation will spread from the primary target area to secondary locations. The proposal will combine accurate and efficient electromagnetic field computation methods for calculating the primary activations with data from diffusion weighted magnetic resonance imaging (MRI) tractography to predict the effects of TMS on an anatomically connected cortical network. We will evaluate the modeling framework by measuring the effects of TMS with simultaneous electroencephalography EEG (TMS-EEG) and functional MRI (TMS-fMRI) in humans, and also using TMS adapted to small animals. During the mentored phase, I will utilize my training in theoretical physics, applied mathematics, and computational engineering to build a set of tools to model the TMS-induced network activity. Anatomical MRI data acquisitions and functional TMS-EEG and TMS-fMRI measurements will be carried out for verifying the proposed model. During the second phase, the software will be optimized for real-time operation and more extensive experiments for evaluation of the system performance and prediction accuracy will be carried out. This project optimally fits my long-term career goal of becoming a multi-disciplinary researcher capable of both methodological development and carrying out neuroscientific studies combining TMS with non-invasive imaging. The outcome of the proposed project will be an entirely novel framework for understanding the effects of TMS on cortical networks for scientific studies and therapeutic applications. The grant will allow me to reach the immediate goal of strengthening my skills in the experimental side of imaging neuroscience and broadening my knowledge of the neurophysiology of TMS. The mentored phase will be carried out at MGH-Harvard-MIT Martinos Center for Biomedical Imaging. The affiliated institutions offer first-rate education pertinent to my career development. Specifically, in addition to building my experimental expertise, I will audit courses on neural engineering and complex networks at Harvard and MIT. The collaborative effort for validating the models with a small animal TMS experiment will also provide hands-on training in electrophysiology. The Martinos Center has cutting edge imaging facilities for carrying out the experimental work and world-class experts available for mentoring and consultation.

Public Health Relevance

Transcranial Magnetic Stimulation (TMS) is a noninvasive brain stimulation technique having current FDA approvals for treatment of depression and pre-neurosurgical localization, with more clinical applications under large-scale investigations. The overall goal of this project is to develop - and experimentally validate - an anatomical connectivity based model for predicting how TMS-induced activations spread from the primary target to secondary areas. This approach enables understanding the clinical and experimental effects of TMS at the network level.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Transition Award (R00)
Project #
5R00EB015445-05
Application #
9348648
Study Section
Special Emphasis Panel (NSS)
Program Officer
Weitz, Andrew Charles
Project Start
2015-09-04
Project End
2019-08-31
Budget Start
2017-09-01
Budget End
2019-08-31
Support Year
5
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114
Fan, Qiuyun; Nummenmaa, Aapo; Wichtmann, Barbara et al. (2018) A comprehensive diffusion MRI dataset acquired on the MGH Connectome scanner in a biomimetic brain phantom. Data Brief 18:334-339
Setsompop, Kawin; Fan, Qiuyun; Stockmann, Jason et al. (2018) High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS). Magn Reson Med 79:141-151
Fan, Qiuyun; Nummenmaa, Aapo; Wichtmann, Barbara et al. (2018) Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300?mT/m maximum gradient strength. Neuroimage 182:469-478
Makarov, Sergey N; Noetscher, Gregory M; Yanamadala, Janakinadh et al. (2017) Virtual Human Models for Electromagnetic Studies and Their Applications. IEEE Rev Biomed Eng 10:95-121
Diana, Marco; Raij, Tommi; Melis, Miriam et al. (2017) Rehabilitating the addicted brain with transcranial magnetic stimulation. Nat Rev Neurosci 18:685-693
Fan, Qiuyun; Nummenmaa, Aapo; Polimeni, Jonathan R et al. (2017) HIgh b-value and high Resolution Integrated Diffusion (HIBRID) imaging. Neuroimage 150:162-176
Raij, Tommi; Nummenmaa, Aapo; Marin, Marie-France et al. (2017) Prefrontal Cortex Stimulation Enhances Fear Extinction Memory in Humans. Biol Psychiatry :
Sundaram, Padmavathi; Nummenmaa, Aapo; Wells, William et al. (2016) Direct neural current imaging in an intact cerebellum with magnetic resonance imaging. Neuroimage 132:477-490
Tian, Qiyuan; Rokem, Ariel; Folkerth, Rebecca D et al. (2016) Q-space truncation and sampling in diffusion spectrum imaging. Magn Reson Med 76:1750-1763
Huang, Susie Y; Tobyne, Sean M; Nummenmaa, Aapo et al. (2016) Characterization of Axonal Disease in Patients with Multiple Sclerosis Using High-Gradient-Diffusion MR Imaging. Radiology 280:244-51

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