Automated Design of fMRI Paradigms

Katherine Bianchini Esper* (Corresponding Author), Felipe Meneguzzi* (Corresponding Author)

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)

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 design of sequences of stimuli intended to activate specific brain regions (i.e. paradigm design). In this paper, we use PDDL+ to model fMRI paradigms so that neuroscientists can use automated planning to design neuroimaging paradigms in a declarative way. Planning neuroimaging paradigms is especially important for functional studies and presurgical planning. 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, noninvasive, exploration of the cognitive functions that might be affected by debridement of brain lesions.

Original languageEnglish
Title of host publicationProceedings of the Thirty-First International Conference on Automated Planning and Scheduling (ICAPS 2021)
EditorsSusanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo
Place of PublicationPalo Alto, California
PublisherAssociation for the Advancement of Artificial Intelligence
Pages445-449
Number of pages5
Volume31
ISBN (Electronic)9781713832317
DOIs
Publication statusPublished - 17 May 2021
Event31st International Conference on Automated Planning and Scheduling, ICAPS 2021 - Guangzhou, Virtual, China
Duration: 2 Aug 202113 Aug 2021

Publication series

NameProceedings of the International Conference on Automated Planning and Scheduling, ICAPS
Number1
Volume31
ISSN (Print)2334-0835
ISSN (Electronic)2334-0843

Conference

Conference31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Country/TerritoryChina
CityGuangzhou, Virtual
Period2/08/2113/08/21

Bibliographical note

Funding Information:
This work was partially funded by Poatek, in the form of financial student aid for the main author of this research. Felipe Meneguzzi acknowledges support from CNPq with projects 407058/2018-4 (Universal) and 302773/2019-3 (PQ Fellowship).

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