Patterns of structural neural network abnormalities in children with epileptic encephalopathies, with or without autism spectrum disorder symptoms

• Grant number: 21/02300-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2021
• End date: May 31, 2022
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: Ana Carolina Coan
• Grantee: Fernanda Germano de Azevedo
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology, AP.CEPID

Abstract

Epileptic encephalopathy (EE) is called epileptiform, ictal or interictal, abnormalities, whichmay contribute to behavioral and cognitive impairment at greater intensity than expected by the underlying cause of epilepsy. The term EE thus defines conditions in which isoleted epileptic activity contributes to neurological decline. In children, this activity determines expected developmental difficulty compared to peers with the same age or regression in skills. Abnormal activity may also be related to autism spectrum disorder (ASD) symptoms, with the development of brain patterns to be studied. Despite studies of structural neuroimaging in children with ESEs of unknown cause, which demonstrated that, in magnetic resonance imaging (MRI) analysis, there is a difference in the gray matter and white matter structural networks, no studies have elucidatedwhether there are also differences in brain abnormality patterns between children with andwithout ASD. Thus, future investigations are needed to clarify the mechanisms of occurrence of ASD symptoms in EEs. The purpose of this study, therefore, is to evaluate the patterns of gray matter and white matter structural changes in children's brains with EEs, which may or may not be accompanied by characteristic symptoms of ASD. With the hypothesis that there are differences between such patterns, will be included in the study patients registered at the UNICAMP Clinical Hospital (HC - UNICAMP), with clinical and encephalographic diagnosis, followed at the ambulatory of Childhood Neurology of UNICAMP. Clinical data and complementary exams will be collected in the respective medical records of theambulatory. Encephalographic data will be selected from weighted MRI sequences on T1, 3D, volumetric, pre-processing MRI images throughSPM12 and post-processing using the voxel-based morphometry technique. The analysisstatistics will be performed using the SPSS24 program. This study is expected to elucidate the relationship between EE and ASD symptoms associated or not in children.