Prediction of subsequent recognition performance using brain activity in the medial temporal lobe

NeuroImage
Takamitsu WatanabeSeiki Konishi

Abstract

Application of multivoxel pattern analysis (MVPA) to functional magnetic resonance imaging (fMRI) data enables reconstruction and classification of cognitive status from brain activity. However, previous studies using MVPA have extracted information about cognitive status that is experienced simultaneously with fMRI scanning, but not one that will be observed after the scanning. In this study, by focusing on activity in the medial temporal lobe (MTL), we demonstrate that MVPA on fMRI data is capable of predicting subsequent recognition performance. In this experiment, six runs of fMRI signals were acquired during encoding of phonogram stimuli. In the analysis, using data acquired in runs 1-3, we first conducted MVPA-based voxel-wise search for the clusters in the MTL whose signals contained the most information about subsequent recognition performance. Next, using the fMRI signals acquired in runs 1-3 from the selected clusters, we trained a classifier function in MVPA. Finally, the trained classifier function was applied to fMRI signals acquired in runs 4-6. Consequently, we succeeded in predicting the subsequent recognition performance for stimuli studied in runs 4-6 with significant accuracy. This accurate prediction suggest...Continue Reading

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Citations

Apr 5, 2013·Social Cognitive and Affective Neuroscience·Takamitsu WatanabeHidenori Yamasue
Sep 29, 2011·Annual Review of Psychology·Jesse Rissman, Anthony D Wagner
Jan 13, 2016·Proceedings of the National Academy of Sciences of the United States of America·Mariam Aly, Nicholas B Turk-Browne
Sep 26, 2013·NeuroImage·Eunho NohVirginia R de Sa
Aug 19, 2015·Frontiers in Human Neuroscience·Jeffery G BednarkRoss Cunnington
Sep 23, 2016·Wiley Interdisciplinary Reviews. Cognitive Science·Matt Faw, Bill Faw
Nov 1, 2016·Social Cognitive and Affective Neuroscience·Takamitsu WatanabeHidenori Yamasue
Aug 24, 2017·Wiley Interdisciplinary Reviews. Cognitive Science·Matt Faw, Bill Faw

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