Research Lab of Eleonora Tamilia, Ph.D.
Director of the Epilepsy Monitoring Unit (EMU) Signal and Data Science Program at BCH (Dept. Neurology)
Associate Scientific Research Staff at BCH (Dept. Pediatrics, Newborn Medicine Division)
Faculty member at the Fetal-Neonatal Neuroimaging Developmental Science Center (FNNDSC) of BCH
Assistant Professor of Pediatrics at Harvard Medical School
The research lab of Eleonora Tamilia at Boston Children's Hospital (BCH) is a dynamic and innovative space dedicated to advancing neurological research and improving clinical practices.
With a focus on epilepsy, the lab is pioneering methods to optimize EEG (scalp or intracranial) and MEG data analysis and interpretation in children with drug-resistant epilepsy. In parallel, the team is actively identifying novel EEG biomarkers for identifying drug-resistant epilepsy by leveraging EEG signal processing and predictive AI. Tamilia's lab is part of the Fetal-Neonatal Neuroimaging and Developmental Science Center (FNNDSC) of BCH, which brings together a multidisciplinary team of researchers from the fields of medicine, engineering, computer science, and neuroscience to support and foster cutting edge clinical and translational science.
Dr. Tamilia is also the director of the EMU Signal and Data Science Program, a cutting-edge initiative established in 2023, designed to integrate science into the clinical workflow within BCH Epilepsy Monitoring Unit (EMU).
Expanding its reach, the lab is also developing a new noninvasive method to assess feeding behavior in newborns through electromyography (EMG), aiming to enhance understanding of early developmental challenges.
Through a blend of advanced signal processing, neuroimaging, artificial intelligence, and interdisciplinary collaboration, the lab strives to translate complex data into meaningful clinical applications, ultimately improving outcomes and quality of life for children with neurological disorders or infants with early motor deficits.
Recent funding:
- "Identifying Novel Network-based EEG Biomarkers of Drug-Resistant and Surgery-Resistant Epilepsy in Children", 2023 Pilot Research Grant by the Rosamund Stone Zander Translational Neuroscience Center (RSZ TNC) - PI: Tamilia.
- "Combining Brain Connectivity and Excitability to Plan Epilepsy Surgery in Children: A New Approach to Get the Most from Intracranial Electroencephalography", Role PI, NIH (NINDS) R03NS127044-01 - PI: Tamilia.
- "Developing A Novel Bedside Approach to Enable Objective Quantitative Feeding Assessment In the Newborn” - 2024 Institutional Centers for Clinical and Translational Research (ICCTR) Pediatric Clinical Research Pilot grant - PI: Tamilia.
Recent Publications
- Targeting interictal low-entropy zones during epilepsy surgery predicts successful outcomes in pediatric drug-resistant epilepsy.
- Noninvasive classification of physiological and pathological high frequency oscillations in children.
- Spikes on ripples are better interictal biomarkers of epilepsy than spikes or ripples.
- Machine learning on interictal intracranial EEG predicts surgical outcome in drug resistant epilepsy.
- Overlap of spike and ripple propagation onset predicts surgical outcome in epilepsy.
- Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach.