Researchers of the Human Brain Project have simulated how an epilepsy seizure spreads through healthy tissue in the brain, potentially increasing the precision of virtual predictive tools available to clinicians.
We aimed to collect data from a large rare genetic epilepsy cohort treated with perampanel, to detect possible subgroups with high efficacy.
Pediatric Epilepsy
To our knowledge, this is the first study to evaluate the clinical utility of exome sequencing for a pediatric epilepsy cohort with broad epilepsy phenotypes. This work supports the implementation of exome sequencing as part of clinical care in this population.
Pediatric Epilepsy, SUDEP
Research suggests that the timing of the death of certain inhibitory neurons in the brain shortly after birth may be at least partly to blame for infantile spasms syndrome (ISS), a rare but devastating form of epilepsy that develops most frequently between four and eight months of age but can emerge within weeks of birth until ages 4 or 5.
Many clinical studies are often limited to predefined symptoms like seizures or developmental milestones, and as such, these studies could be missing valuable information about an aspect of the disease that could be treated and significantly improve a patient’s quality of life.
Researchers from the Human Brain Project (HBP) have developed advanced brain modelling methods that could help doctors more reliably identify where epileptic seizures start in the brain and consequently improve surgical prognoses.
Researchers noted that prior studies examining veterans with epilepsy suggest this population may present with unique psychiatric and clinical features, with implications for quality of life and service utilization. However, there remains a paucity of literature assessing risk of psychiatric dysfunction in veterans with drug-resistant epilepsy.
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We asked US and European neurologists to predict two-year seizure risk after antiseizure medication (ASM) withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before versus after viewing calculated predictions, using generalized linear models.
