Project Grant R01NS132121

Award Date 7/1/24
Completion Date 6/30/29
Dollars Obligated $1.3M
Federal Grant Program
93.853
Assistance Type
Project Grant
Place of Performance
New Haven, CT 06510, USA
Similar Awards
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 $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 (CFDA 93.853) program, provides $690,763 to Brigham & Women's Hospital Inc. to research optimizing neuromodulation therapies for epilepsy. The project aims to identify factors that determine patient response to responsive neurostimulation (RNS), focusing on connectivity, stimulation timing, and background...
This Project Grant award of $555,499 from the National Institute of Neurological Disorders and Stroke (NINDS) under the Extramural Research Programs in the Neurosciences and Neurological Disorders (CFDA 93.853) is funding research to develop novel, non-invasive behavioral biomarkers for predicting seizures and mortality in mouse models of epilepsy. The principal investigators at Stanford University, in collaboration with researchers at Harvard Medical School, will use artificial...
This federal Project Grant award of $657,958, 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, supports research to elucidate the cellular and network mechanisms underlying epileptic activity and seizures, as well as investigate the neuronal impact of neurostimulation for treating drug-resistant epilepsy. The 5-year award to Trustees of Boston University...
This Project Grant award, totaling $224,258, 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) federal grant program. The award supports research to assess the feasibility of using machine learning to improve the diagnostic process for patients with functional seizures, a condition that can be mistaken for epilepsy. Key objectives include validating the use of...
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 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...
Florida International University was awarded a $250,000 Project Grant from the National Science Foundation's Technology, Innovation, and Partnerships program (CFDA 47.084) to develop an artificial intelligence-enabled real-time system for early epileptic seizure detection and prediction. The two-year project will design and develop advanced machine learning algorithms to identify neuromarkers in wearable electroencephalography data that can predict epileptic seizures. Researchers will...
This Project Grant award from the National Institute of Neurological Disorders and Stroke (NINDS), under CFDA 93.853 "Extramural Research Programs in the Neurosciences and Neurological Disorders", provides $230,904 to Boston Children's Hospital from January 1, 2025 to December 31, 2029. The award will support research to identify novel genetic causes of infantile epilepsies and evaluate the impact of genetic diagnosis on patient outcomes and families. Key objectives include applying...

PERSONALIZED SEIZURE FORECASTING: A PRECISION MEDICINE APPROACH - PROJECT SUMMARY THE HALLMARK OF EPILEPSY IS RECURRENT SEIZURES, I.E., PAROXYSMAL ATTACKS OF ABNORMAL BRAIN ELECTRICAL ACTIVITY THAT ARE ASSOCIATED WITH HIGH MORBIDITY AND PREMATURE MORTALITY. IN ADDITION TO THE DIRECT MORBIDITY OF SEIZURES, PEOPLE WITH EPILEPSY MUST ALSO CONTEND WITH THE EVER-PRESENT UNCERTAINTY ABOUT WHEN THE NEXT SEIZURE WILL OCCUR. THE UNPREDICTABILITY OF SEIZURES REPRESENTS A SIGNIFICANT AND DISABLING FEATURE OF EPILEPSY. DESPITE DECADES OF RESEARCH, THERE IS NO ESTABLISHED METHOD FOR DETERMINING WHEN A SEIZURE COULD OCCUR. AKIN TO WEATHER FORECASTS THAT ESTIMATE THE PROBABILITY OF RAIN, SEIZURE FORECASTS THAT QUANTIFY THE LIKELIHOOD OF SEIZURES OVER A FUTURE TEMPORAL WINDOW COULD INCREASE THE QUALITY OF LIFE FOR PATIENTS AND FAMILIES LIVING WITH EPILEPSY, SO THEY COULD PLAN AROUND A SEIZURE EVENT. A FORECAST COULD HELP PATIENTS AND FAMILIES PREPARE FOR, OR EVEN MITIGATE UPCOMING SEIZURES. THE OVERARCHING GOALS OF THE PRESENT PROPOSAL ARE (1) TO ELUCIDATE THE RELATIONSHIP BETWEEN BIOCHEMICAL CHANGES IN SALIVA (A READILY AVAILABLE BIOFLUID THAT REFLECTS SYSTEMIC CHEMISTRY) AND ELECTROPHYSIOLOGICAL FEATURES THAT DETERMINE SEIZURE LIKELIHOOD (RECORDED FROM A RESPONSIVE NEUROSTIMULATION (RNS) SYSTEM) AND (2) TO LEVERAGE THESE RELATIONSHIPS TO DEVELOP EFFECTIVE SEIZURE FORECASTING METHODS THAT WILL EMPOWER PEOPLE WITH EPILEPSY WITH THE UNPRECEDENTED ABILITY TO ANTICIPATE AND PREVENT SEIZURES. WE HAVE STRONG PRELIMINARY DATA FROM PEOPLE WITH EPILEPSY THAT SEVERAL SALIVA CHEMICALS EXHIBIT NOVEL MULTIDIEN (MULTI- DAY) AND CIRCADIAN (~24-HOUR) CONCENTRATION CHANGES THAT CORRELATE WITH PERIODS OF INCREASED SEIZURE LIKELIHOOD. OUR CENTRAL HYPOTHESIS STATES THAT A LATENT BIOCHEMICAL VARIABLE FOR SEIZURE LIKELIHOOD CAN BE DETECTED IN PEOPLE WITH EPILEPSY USING SERIAL SALIVARY SAMPLING. WE WILL PURSUE THE FOLLOWING SPECIFIC AIMS: (1) ESTABLISH BIOCHEMICAL SIGNATURES OF MULTIDIEN SEIZURE LIKELIHOOD AND DEVELOP EFFECTIVE SEIZURE FORECASTING APPROACHES; AND (2) ESTABLISH BIOCHEMICAL SIGNATURES OF INCREASED SEIZURE LIKELIHOOD OVER THE CIRCADIAN CYCLE. SUCCESSFUL COMPLETION OF THIS PROJECT WILL SIGNIFICANTLY ADVANCE THE FIELDS OF CHRONOBIOLOGY, METABOLISM, AND EPILEPSY BY: (A) IDENTIFYING NOVEL MULTIDIEN AND CIRCADIAN RHYTHMS IN BIOCHEMICAL AND METABOLIC PATHWAYS IN PEOPLE WITH EPILEPSY AND HEALTHY CONTROLS, (B) LINKING THESE CHANGES TO POSSIBLE CAUSES OF SEIZURES, AND (C) USING THESE CHANGES TO FORECAST SEIZURES AND DEFINE A MORE EFFECTIVE STANDARD OF CARE. THE EXPECTED POSITIVE IMPACTS ON PUBLIC HEALTH WILL BE TO (A) EMPOWER PEOPLE WITH EPILEPSY WITH THE ABILITY TO ANTICIPATE AND PREVENT SEIZURES, (B) PROVIDE RESEARCHERS WITH VALIDATED SALIVA SAMPLE COLLECTION AND ANALYSIS APPROACHES, AND (C) DISCOVER GROUND-BREAKING BIOCHEMICAL INSIGHT INTO THE HUMAN CHRONO-METABOLOME. DETAILED KNOWLEDGE ABOUT THE CHRONO-METABOLOME IS EXPECTED TO FUEL INNOVATIVE STUDIES ON VARIOUS EPISODIC BRAIN DISORDERS THAT PLACE A LARGE BURDEN ON SOCIETY, LIKE MIGRAINE, CLUSTER HEADACHES, AFFECTIVE DISORDERS, AND SUBSTANCE USE DISORDERS.

Posted 7/1/24, 12:00 AM