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Title: | Multivariate Bayesian decoding of single-trial event-related fMRI responses for memory retrieval of voluntary actions | Authors: | Lee, Dongha Yun, Sungjae Jang, Changwon Park, Hae-Jeong |
Issue Date: | 2017 | Publisher: | Public Library of Science | Project: | grant from National Research Foundation of Korea (NRF), funded by the Korean government (MSIP) (No. 2014R1A2A1A10052762 | Serial title, monograph or event: | PLoS ONE | Volume: | 12 | Issue: | 8 | Abstract: | This study proposes a method for classifying event-related fMRI responses in a specialized setting of many known but few unknown stimuli presented in a rapid event-related design. Compared to block design fMRI signals, classification of the response to a single or a few stimulus trial(s) is not a trivial problem due to contamination by preceding events as well as the low signal-to-noise ratio. To overcome such problems, we proposed a single trial-based classification method of rapid event-related fMRI signals utilizing sparse multivariate Bayesian decoding of spatio-temporal fMRI responses. We applied the proposed method to classification of memory retrieval processes for two different classes of episodic memories: a voluntarily conducted experience and a passive experience induced by watching a video of others' actions. A cross-validation showed higher classification performance of the proposed method compared to that of a support vector machine or of a classifier based on the general linear model. Evaluation of classification performances for one, two, and three stimuli from the same class and a correlation analysis between classification accuracy and target stimulus positions among trials suggest that presenting two target stimuli at longer inter-stimulus intervals is optimal in the design of classification experiments to identify the target stimuli. The proposed method for decoding subject-specific memory retrieval of voluntary behavior using fMRI would be useful in forensic applications in a natural environment, where many known trials can be extracted from a simulation of everyday tasks and few target stimuli from a crime scene. | URI: | https://hdl.handle.net/10316/108324 | ISSN: | 1932-6203 | DOI: | 10.1371/journal.pone.0182657 | Rights: | openAccess |
Appears in Collections: | FPCEUC - Artigos em Revistas Internacionais |
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Multivariate-Bayesian-decoding-of-singletrial-eventrelated-fMRI-responses-for-memory-retrieval-of-voluntary-actionsPLoS-ONE.pdf | 10.45 MB | Adobe PDF | View/Open |
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