Project Grant K23NS135134
Award Date
1/1/25
Completion Date
12/31/29
Dollars Obligated
$224K
Federal Agency
National Institute of Neurological Disorders and Stroke
Federal Grant Program
93.853
Assistance Type
Project Grant
Place of Performance
Pittsburgh, PA 15222, USA
Similar Awards
This $148,956 federal Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS), under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program, supports research to develop scalable methods for quantifying epileptic networks and guiding epilepsy surgery. The primary objectives are to: (1) develop standardized quantitative methods to analyze structural imaging, intracranial EEG (IEEG), and clinical data across...
This Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS), under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program, provides $234,276 over 5 years to the University of California, San Diego (UCSD) to conduct research on predicting outcomes for epilepsy surgery. The project aims to use functional MRI (fMRI) and advanced statistical/machine learning methods to identify associations between brain network...
This federal Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS), under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program, will provide $606,548 to the University of Pittsburgh to develop a new "mesoscopic electrophysiology" recording system for non-human primates. The goal is to create a system that combines the large field of view and spatial resolution of fMRI with the high temporal...
The National Science Foundation awarded a $550,000 Project Grant to Northeastern University under the Technology, Innovation, and Partnerships federal grant program (CFDA 47.084) to develop a smart seizure prediction system using AI-enabled implantable sensor networks. The system will use embedded artificial intelligence algorithms to enable in-situ medical inference for patients with neurological disorders not treatable with antiepilepsy medications. Northeastern University will develop the...
This federal Project Grant award, totaling $684,451, was provided by the National Institute of Neurological Disorders and Stroke (NINDS) under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) program. The award supports a 5-year research project focused on advancing precision medicine for Parkinson's disease through the use of integrative machine learning techniques. The primary objectives are to: 1) identify Parkinson's disease progression...
This $199,005 National Science Foundation project grant funds research at the University of North Florida to develop machine learning algorithms using noninvasive wearable sensors to forecast seizures and optimize antiseizure medication dosing for women with epilepsy. Funded under the NSF's Engineering program (CFDA 47.041), which supports innovation and excellence in engineering research and education, the two-year award will investigate hormonal changes associated with the menstrual cycle...
This Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS), under the Extramural Research Programs in the Neurosciences and Neurological Disorders federal grant program (CFDA 93.853), provides $1,204,564.00 to Neurologic Solutions Inc. to further develop and validate the EPISCALP EEG analytics algorithm. The goal is to enhance the accuracy of epilepsy diagnosis by leveraging EPISCALP's predictive capabilities to reduce misdiagnosis rates, which currently...
The National Institute of Neurological Disorders and Stroke (NINDS) awarded a Project Grant of $438,836 to The Trustees of the Stevens Institute of Technology under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) federal grant program. The award supports research to develop a unified paradigm using simultaneous multimodal measurement of scalp EEG and intracranial EEG (iEEG) signals to estimate the electrophysiological networks of the whole brain....
This Project Grant from the National Science Foundation Division of Social and Economic Science, under the Social, Behavioral, and Economic Sciences federal grant program (CFDA 47.075), provides $275,112 to the University of Pittsburgh for the project "Bayesian Inference of Whole-Brain Directed Networks using Neuroimaging Data." The project will develop new statistical models and computationally efficient algorithms to analyze functional magnetic resonance imaging (fMRI) data to better...
This federal Project Grant award from the National Institute of General Medical Sciences (NIGMS), under the Biomedical Research and Research Training program (CFDA 93.859), provides $174,794 to Idaho State University to develop machine learning methods based on nonlocal equations and operators to model brain dynamics and extract diagnostic indicators of cognitive pathologies. The project aims to leverage the spatiotemporal information in brain recordings to improve the diagnosis of cognitive...