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Specialties

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Languages

  • English
  • Italian

Professional History

Eleonora Tamilia received her PhD and MS in Biomedical Engineering (from University Campus Bio-Medico and University Tor Vergata of Rome, respectively) and conducted her post-doctoral training at BCH/HMS (from 2015 to 2019). She is an expert in biomedical signal processing and data analysis with particular focus on neurological disorders.

Her research work has been recognized through numerous awards from national and international committees, which include young investigator awards from the American Epilepsy Society, the International Federation of Clinical Neurophysiology and the IEEE Engineering in Medicine and Biology Society. She is also the Director of the Epilepsy Monitoring Unit (EMU) Signal and Data Science Program in Neurology.

Her current research is dedicated to the advanced analysis of electroencephalography (EEG) and magnetoencephalography (MEG) from children with epilepsy to identify new electrophysiological epilepsy biomarkers, test their clinical value for surgical treatment and translate such technological advances to the clinical practice. She also conducts research for the development of new non-invasive methods that facilitates the early diagnosis of brain injury in neonates through the combined monitoring of brain and motor activity.

Publications

  1. Noninvasive classification of physiological and pathological high frequency oscillations in children. Brain Commun. 2025; 7(3):fcaf170. View Abstract

  2. Machine learning on interictal intracranial EEG predicts surgical outcome in drug resistant epilepsy. NPJ Digit Med. 2025 Mar 05; 8(1):138. View Abstract

  3. Spikes on ripples are better interictal biomarkers of epilepsy than spikes or ripples. Brain Commun. 2025; 7(1):fcaf056. View Abstract

  4. Overlap of spike and ripple propagation onset predicts surgical outcome in epilepsy. Ann Clin Transl Neurol. 2024 Oct; 11(10):2530-2547. View Abstract

  5. Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician. Neuroradiol J. 2025 Feb; 38(1):7-20. View Abstract

  6. Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach. Epilepsia. 2024 Apr; 65(4):944-960. View Abstract

  7. Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain?. Algorithms. 2023; 12(16):567. View Abstract

  8. Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain? Algorithms. 2023 Dec; 16(12). View Abstract

  9. Sleep Spindle Generation Before and After Epilepsy Surgery: A Source Imaging Study in Children with Drug-Resistant Epilepsy. Brain Topogr. 2024 01; 37(1):88-101. View Abstract

  10. Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy. Brain. 2023 09 01; 146(9):3898-3912. View Abstract

  11. Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia. Clin Neurophysiol. 2023 09; 153:88-101. View Abstract

  12. Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy. Sci Rep. 2023 06 14; 13(1):9622. View Abstract

  13. Non-invasive mapping of epileptogenic networks predicts surgical outcome. Brain. 2023 05 02; 146(5):1916-1931. View Abstract

  14. Phase-amplitude coupling between low- and high-frequency activities as preoperative biomarker of focal cortical dysplasia subtypes. Clin Neurophysiol. 2023 06; 150:40-48. View Abstract

  15. A Role for Data Science in Precision Nutrition and Early Brain Development. Front Psychiatry. 2022; 13:892259. View Abstract

  16. Reply to "Added value of high-resolution electrical source imaging of ictal activity in children with structural focal epilepsy". Clin Neurophysiol. 2022 08; 140:254-255. View Abstract

  17. Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy. Clin Neurophysiol. 2022 07; 139:49-57. View Abstract

  18. Novel User-Friendly Application for MRI Segmentation of Brain Resection following Epilepsy Surgery. Diagnostics (Basel). 2022 Apr 18; 12(4). View Abstract

  19. Mapping Propagation of Interictal Spikes, Ripples, and Fast Ripples in Intracranial EEG of Children with Refractory Epilepsy. Annu Int Conf IEEE Eng Med Biol Soc. 2021 11; 2021:194-197. View Abstract

  20. Mapping Functional Connectivity of Epileptogenic Networks through Virtual Implantation. Annu Int Conf IEEE Eng Med Biol Soc. 2021 11; 2021:408-411. View Abstract

  21. Electric Source Imaging on Intracranial EEG Localizes Spatiotemporal Propagation of Interictal Spikes in Children with Epilepsy. Annu Int Conf IEEE Eng Med Biol Soc. 2021 11; 2021:2668-2671. View Abstract

  22. Association between semiologic, autonomic, and electrographic seizure characteristics in children with generalized tonic-clonic seizures. Epilepsy Behav. 2021 09; 122:108228. View Abstract

  23. Changes in the Functional Brain Network of Children Undergoing Repeated Epilepsy Surgery: An EEG Source Connectivity Study. Diagnostics (Basel). 2021 Jul 09; 11(7). View Abstract

  24. Source imaging of seizure onset predicts surgical outcome in pediatric epilepsy. Clin Neurophysiol. 2021 07; 132(7):1622-1635. View Abstract

  25. Presurgical accuracy of dipole clustering in MRI-negative pediatric patients with epilepsy: Validation against intracranial EEG and resection. Clin Neurophysiol. 2022 09; 141:126-138. View Abstract

  26. Noninvasive Mapping of Ripple Onset Predicts Outcome in Epilepsy Surgery. Ann Neurol. 2021 05; 89(5):911-925. View Abstract

  27. Abnormal Nutritive Sucking as an Indicator of Neonatal Brain Injury. Front Pediatr. 2020; 8:599633. View Abstract

  28. Photoplethysmography: A measure for the function of the autonomic nervous system in focal impaired awareness seizures. Epilepsia. 2020 08; 61(8):1617-1626. View Abstract

  29. Photoplethysmographic evaluation of generalized tonic-clonic seizures. Epilepsia. 2020 08; 61(8):1606-1616. View Abstract

  30. Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery. Ann Clin Transl Neurol. 2020 03; 7(3):329-342. View Abstract

  31. Ictal and interictal source imaging on intracranial EEG predicts epilepsy surgery outcome in children with focal cortical dysplasia. Clin Neurophysiol. 2020 03; 131(3):734-743. View Abstract

  32. Nutritive sucking abnormalities and brain microstructural abnormalities in infants with established brain injury: a pilot study. J Perinatol. 2019 11; 39(11):1498-1508. View Abstract

  33. Noninvasive Localization of High-Frequency Oscillations in Children with Epilepsy: Validation against Intracranial Gold-Standard. Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul; 2019:1555-1558. View Abstract

  34. Assessing the localization accuracy and clinical utility of electric and magnetic source imaging in children with epilepsy. Clin Neurophysiol. 2019 04; 130(4):491-504. View Abstract

  35. Altered White Matter Connectivity Associated with Intergyral Brain Disorganization in Hemiplegic Cerebral Palsy. Neuroscience. 2019 02 10; 399:146-160. View Abstract

  36. Surgical resection of ripple onset predicts outcome in pediatric epilepsy. Ann Neurol. 2018 09; 84(3):331-346. View Abstract

  37. Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes. J Clin Neurophysiol. 2018 Jul; 35(4):339-345. View Abstract

  38. Magnetoencephalographic Spike Analysis in Patients With Focal Cortical Dysplasia: What Defines a "Dipole Cluster"? Pediatr Neurol. 2018 06; 83:25-31. View Abstract

  39. Quantifying Neonatal Sucking Performance: Promise of New Methods. Semin Speech Lang. 2017 04; 38(2):147-158. View Abstract

  40. Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy. Front Neurol. 2017; 8:14. View Abstract

  41. Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy. J Vis Exp. 2016 12 06; (118). View Abstract

  42. An Automated System for the Analysis of Newborns' Oral-Motor Behavior. IEEE Trans Neural Syst Rehabil Eng. 2016 12; 24(12):1294-1303. View Abstract

  43. An automated system for quantitative analysis of newborns' oral-motor behavior and coordination during bottle feeding. Annu Int Conf IEEE Eng Med Biol Soc. 2015; 2015:7386-9. View Abstract

  44. Development of goal-directed action selection guided by intrinsic motivations: an experiment with children. Exp Brain Res. 2014 Jul; 232(7):2167-77. View Abstract

  45. A new calibration methodology for thorax and upper limbs motion capture in children using magneto and inertial sensors. Sensors (Basel). 2014 Jan 09; 14(1):1057-72. View Abstract

  46. Technological solutions and main indices for the assessment of newborns' nutritive sucking: a review. Sensors (Basel). 2014 Jan 02; 14(1):634-58. View Abstract

  47. An automatized system for the assessment of nutritive sucking behavior in infants: a preliminary analysis on term neonates. Annu Int Conf IEEE Eng Med Biol Soc. 2014; 2014:5752-5. View Abstract

  48. A transistors-based, bidirectional flowmeter for neonatal ventilation: design and experimental characterization. Annu Int Conf IEEE Eng Med Biol Soc. 2014; 2014:2131-4. View Abstract

  49. Design, development and experimental validation of a non-invasive device for recording respiratory events during bottle feeding. Annu Int Conf IEEE Eng Med Biol Soc. 2014; 2014:2123-6. View Abstract

  50. An MR-compatible force sensor based on FBG technology for biomedical application. Annu Int Conf IEEE Eng Med Biol Soc. 2014; 2014:5731-4. View Abstract

  51. An experimental protocol for the definition of upper limb anatomical frames on children using magneto-inertial sensors. Annu Int Conf IEEE Eng Med Biol Soc. 2013; 2013:4903-6. View Abstract

  52. A new ecological method for the estimation of Nutritive Sucking Efficiency in newborns: measurement principle and experimental assessment. Annu Int Conf IEEE Eng Med Biol Soc. 2013; 2013:6720-3. View Abstract
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