Functional connectivity analysis of drug-resistant epilepsy patients submitted to epilepsy surgery

• Grant number: 11/08573-4
• Support Opportunities: Research Grants - Young Investigators Grants
• Start date: August 01, 2011
• End date: February 28, 2014
• Field of knowledge: Health Sciences - Medicine - Medical Radiology
• Principal Investigator: Jaime Shinsuke Ide
• Grantee: Jaime Shinsuke Ide
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
• Associated researchers: Antonio Carlos dos Santos ; Carlo Rondinoni ; Carlos Ernesto Garrido Salmon ; Fábio Augusto Menocci Cappabianco ; João Pereira Leite ; Regina Célia Coelho ; Tonicarlo Rodrigues Velasco

Abstract

Recent advances in biomedical imaging have provided a better understanding of altered neural networks, and their consequences on pathological conditions. In particular, functional magnetic resonance imaging (fMRI) made possible to noninvasively detect brain injuries in neural circuits involved in the propagation of seizures. However, although there is an increasing amount of information about the neural dysfunctions in patients with drug-resistant epilepsy who are submitted to pre-surgical evaluation, few advances were done in understanding the functional changes after resection of epileptogenic regions. Which parts of the brain become functionally disconnected or what is the compensatory functional mechanism following resection of epileptogenic lesion? From these alterations, is it possible to determine better surgery strategies for seizure control? The answer to these questions has important implications to improve surgical planning, and eventually to provide guidance for placement of devices targeting the seizure propagation network. Nevertheless, these investigations offer technical challenges because of distortions caused by the surgical cavity following the resection. To address these questions, in this Jovem Pesquisador project, we propose to use fMRI to investigate the functional connectivity of drug-resistant epilepsy patients submitted to lobectomy, in particular the changes following the resection of brain tissues. To this aim, technical challenges have to be dealt with, because in patients with surgical cavity, functional changes have to be considered in light of structural and potential hemodynamic variabilities. The candidate has experience in developing and applying functional connectivity methods, and has the support and expertise of leading researchers in epilepsy from CINAPCE (Cooperação Interinstitucional de Apoio a Pesquisas sobre o Cérebro) groups. Results will be evaluated by publications and creation of a biomedical imaging group in the proponent's emerging center at UNIFESP. (AU)

Scientific publications

(6)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

IDE, JAIME S.; ZHANG, SHENG; LI, CHIANG-SHAN R.. Bayesian network models in brain functional connectivity analysis. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, v. 55, n. 1, 1, SI, p. 23-35, JAN 2014. (11/08573-4)

LI, CHIANG-SHAN R.; IDE, JAIME S.; ZHANG, SHENG; HU, SIEN; CHAO, HERTA H.; ZABORSZKY, LASZLO. Resting state functional connectivity of the basal nucleus of Meynert in humans: In comparison to the ventral striatum and the effects of age. NeuroImage, v. 97, p. 321-332, AUG 15 2014. (11/08573-4)

IDE, JAIME S.; HU, SIEN; ZHANG, SHENG; YU, ANGELA J.; LI, CHIANG-SHAN R.. Impaired Bayesian learning for cognitive control in cocaine dependence. DRUG AND ALCOHOL DEPENDENCE, v. 151, p. 220-227, JUN 1 2015. (11/08573-4)

NEDIC, SANJA; STUFFLEBEAM, STEVEN M.; RONDINONI, CARLO; VELASCO, TONICARLO R.; DOS SANTOS, ANTONIO C.; LEITE, JOAO P.; GARGARO, ANA C.; MUJICA-PARODI, LILIANNE R.; IDE, JAIME S.. Using network dynamic fMRI for detection of epileptogenic foci. BMC Neurology, v. 15, DEC 21 2015. (11/08573-4)

IDE, JAIME S.; SHENOY, PRADEEP; YU, ANGELA J.; LI, CHIANG-SHAN R.. Bayesian Prediction and Evaluation in the Anterior Cingulate Cortex. JOURNAL OF NEUROSCIENCE, v. 33, n. 5, p. 2039-2047, JAN 30 2013. (11/08573-4)

IDE, JAIME S.; ZHANG, SHENG; LI, CHIANG-SHAN R.. Bayesian network models in brain functional connectivity analysis. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, v. 55, n. 1, p. 13-pg., 2014-01-01. (11/08573-4)