The long term goal of this proposed research project is to establish a dynamic spatio-temporal source imaging methodology that is able to image and localize epileptogenic brain from noninvasive high resolution electroencephalogram (EEG) measurements to aid surgical planning in epilepsy patients. Epilepsy is one of the most common neurological disorders, affecting 50 million people worldwide. In approximately 30% of these patients the seizures are not controlled by any available drug therapy, and surgery is a viable option for partial epilepsy. Localization and imaging of epileptogenic brain responsible for seizures is of paramount importance for successful epilepsy surgery. Currently, definite localization of epileptogenic zone is performed from invasive intracranial EEG. In the proposed research project, we propose to develop novel noninvasive source imaging methods that promise to localize and image source extent corresponding to epileptogenic zone, from interictal spikes and high frequency oscillation activities that can be measured using high density electrode array. We also propose to validate rigorously the proposed source imaging techniques in a group of epilepsy patients undergoing intracranial EEG recordings and surgical resection.
The specific aims are:
Aim 1) Development of EEG source extent imaging methods for imaging epileptogenic brain.
Aim 2) Development of high-frequency source imaging methods for imaging epileptogenic brain.
Aim 3) Validation of source imaging methods from intracranial recordings and surgical resections in partial epilepsy patients. The successful completion of the proposed research promises to lead to establishment of a disruptive technology to localizing and imaging of epileptogenic brain from noninvasive high resolution EEG, which can significantly advance state-of-the-art of management of intractable epilepsy. The development of such novel technology would benefit numerous patients suffering from partial epilepsy and the healthcare system.

Public Health Relevance

The long-term goal of this proposed research project is to develop and validate a high-resolution dynamic source imaging technology that is able to image and localize epileptogenic brain from dense array noninvasive electrical measurements to aid clinical surgical planning in epilepsy patients. The availability of a noninvasive imaging technology to localize and image the epileptogenic brain would benefit numerous patients suffering from intractable epilepsy and the healthcare system.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
1R01NS096761-01
Application #
9116519
Study Section
Neuroscience and Ophthalmic Imaging Technologies Study Section (NOIT)
Program Officer
Stewart, Randall R
Project Start
2016-06-01
Project End
2020-05-31
Budget Start
2016-06-01
Budget End
2017-05-31
Support Year
1
Fiscal Year
2016
Total Cost
$374,783
Indirect Cost
$93,842
Name
University of Minnesota Twin Cities
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Case, Michelle; Shirinpour, Sina; Zhang, Huishi et al. (2018) Increased theta band EEG power in sickle cell disease patients. J Pain Res 11:67-76
Hosseini, Seyed Amir Hossein; Sohrabpour, Abbas; He, Bin (2018) Electromagnetic source imaging using simultaneous scalp EEG and intracranial EEG: An emerging tool for interacting with pathological brain networks. Clin Neurophysiol 129:168-187
Edelman, Bradley J; Meng, Jianjun; Gulachek, Nicholas et al. (2018) Exploring Cognitive Flexibility With a Noninvasive BCI Using Simultaneous Steady-State Visual Evoked Potentials and Sensorimotor Rhythms. IEEE Trans Neural Syst Rehabil Eng 26:936-947
Meng, Jianjun; Streitz, Taylor; Gulachek, Nicholas et al. (2018) Three-Dimensional Brain-Computer Interface Control Through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks. IEEE Trans Biomed Eng 65:2417-2427
Johnson, N N; Carey, J; Edelman, B J et al. (2018) Combined rTMS and virtual reality brain-computer interface training for motor recovery after stroke. J Neural Eng 15:016009
Baxter, Bryan S; Edelman, Bradley J; Sohrabpour, Abbas et al. (2017) Anodal Transcranial Direct Current Stimulation Increases Bilateral Directed Brain Connectivity during Motor-Imagery Based Brain-Computer Interface Control. Front Neurosci 11:691
Liu, Jiaen; Wang, Yicun; Katscher, Ulrich et al. (2017) Electrical Properties Tomography Based on $B_{{1}}$ Maps in MRI: Principles, Applications, and Challenges. IEEE Trans Biomed Eng 64:2515-2530
Vijayakumar, Vishal; Case, Michelle; Shirinpour, Sina et al. (2017) Quantifying and Characterizing Tonic Thermal Pain Across Subjects From EEG Data Using Random Forest Models. IEEE Trans Biomed Eng 64:2988-2996
Aarabi, Ardalan; He, Bin (2017) Seizure prediction in patients with focal hippocampal epilepsy. Clin Neurophysiol 128:1299-1307
Roy, Abhrajeet V; Jamison, Keith W; He, Sheng et al. (2017) Deactivation in the posterior mid-cingulate cortex reflects perceptual transitions during binocular rivalry: Evidence from simultaneous EEG-fMRI. Neuroimage 152:1-11

Showing the most recent 10 out of 15 publications