Neurosurgery for patients with drug-resistant epilepsy requires locating the precise brain areas that are generating the seizures. Typically, patients undergo seven to 10 days of invasive intracranial EEG monitoring, with electrodes surgically implanted inside the brain through one or more skull openings to capture seizure activity as it happens. Eleonora Tamilia, Ph.
D., directs the Epilepsy Monitoring Unit Signal and Data Science Program within the Epilepsy Center at Boston Children's Hospital. Her team has piloted a much briefer method for mapping seizure zones.
Not only is it noninvasive, but can it provide information a traditional EEG reading cannot. It combines standard scalp EEG readings with MRI data on brain structure to identify connections between different areas of the brain and uses machine learning to locate the most epileptogenic brain regions. "Using computational tools , we can reconstruct cortical activity that the eye cannot catch and understand how different regions are functionally connected," explains Tamilia, who is also part of the Fetal-Neonatal Developmental Science Center (FNNDSC).
"If a seizure starts in one region of the cortex, it's likely to spread to another network it connects to. Even regions that are far apart may fire together." Predicting seizure zones As described in Epilepsia , Tamilia and her colleagues retrospectively analyzed about five minutes of scalp EEG data from 50 patients with drug-resistant epilepsy who had neurosurgery.
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