TY - GEN
T1 - Cross-modal searchlight classification
T2 - 6th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2016
AU - Nastase, Samuel A.
AU - Halchenko, Yaroslav O.
AU - Davis, Ben
AU - Hasson, Uri
N1 - Funding Information:
This work was supported by ERC starting grant #263318 (NeuroInt) to U.H.
Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/8/24
Y1 - 2016/8/24
N2 - Multivariate cross-classification is a powerful tool for decoding abstract or supramodal representations from distributed neural populations. However, this approach introduces several methodological challenges not encountered in typical multivariate pattern analysis and information-based brain mapping. In the current report, we review these challenges, recommend solutions, and evaluate alternative approaches where possible. We address these challenges with reference to an example fMRI data set where participants were presented with brief series of auditory and visual stimuli of varying predictability with the aim of decoding predictability across auditory and visual modalities. In analyzing this data set, we highlight four particular challenges: response normalization, cross-validation, direction of cross-validation, and permutation testing.
AB - Multivariate cross-classification is a powerful tool for decoding abstract or supramodal representations from distributed neural populations. However, this approach introduces several methodological challenges not encountered in typical multivariate pattern analysis and information-based brain mapping. In the current report, we review these challenges, recommend solutions, and evaluate alternative approaches where possible. We address these challenges with reference to an example fMRI data set where participants were presented with brief series of auditory and visual stimuli of varying predictability with the aim of decoding predictability across auditory and visual modalities. In analyzing this data set, we highlight four particular challenges: response normalization, cross-validation, direction of cross-validation, and permutation testing.
KW - MVPA
KW - cross-classification
KW - cross-modal
KW - fMRI
UR - http://www.scopus.com/inward/record.url?scp=84988814454&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84988814454&partnerID=8YFLogxK
U2 - 10.1109/PRNI.2016.7552355
DO - 10.1109/PRNI.2016.7552355
M3 - Conference contribution
AN - SCOPUS:84988814454
T3 - PRNI 2016 - 6th International Workshop on Pattern Recognition in Neuroimaging
BT - PRNI 2016 - 6th International Workshop on Pattern Recognition in Neuroimaging
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 June 2016 through 24 June 2016
ER -