@MASTERSTHESIS{ 2022:447079250,
 	title = {Neuro-symbolic automated design of fMRI paradigms},
 	year = {2022},
 	url = "https://tede2.pucrs.br/tede2/handle/tede/10586",
 	abstract = "Neuroimaging techniques have been widely used in recent decades to assess brain activation patterns for neuroscience. Task design is the most important challenge for neuroimaging studies to achieve the best modeling for assessing brain patterns within and across subjects. Specifically, functional magnetic resonance imaging (fMRI) experiments rely on the precise and effective paradigm design, selecting the best sequences of stimuli to activate specific brain regions. In this project, we propose to use Planning Domain Definition Language (PDDL+) to model fMRI paradigms so that neuroscientists can design neuroimaging paradigms in a declarative way. We develop an application of automated planning for neuroscience research and presurgical planning, resulting in and a tool for automatic stimuli generation for fMRI scans. The former should help to ensure an experimental design that allows the analysis of the brain regions that are interesting in the study. The latter should help surgeons select the correct stimuli for a presurgical non-invasive exploration of the cognitive functions that might be affected by debridement of brain lesions.",
 	publisher = {Pontifícia Universidade Católica do Rio Grande do Sul},
 	scholl = {Programa de Pós-Graduação em Ciência da Computação},
 	note = {Escola Politécnica}
}