Space-by-time decomposition for single-trial decoding of M/EEG activity
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Space-by-time decomposition for single-trial decoding of M/EEG activity. / Delis, Ioannis; Onken, Arno; Schyns, Philippe G; Panzeri, Stefano; Philiastides, Marios G.
In: NEUROIMAGE, Vol. 133, 06.2016, p. 504-515.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Space-by-time decomposition for single-trial decoding of M/EEG activity
AU - Delis, Ioannis
AU - Onken, Arno
AU - Schyns, Philippe G
AU - Panzeri, Stefano
AU - Philiastides, Marios G
N1 - Copyright © 2016 Elsevier Inc. All rights reserved.
PY - 2016/6
Y1 - 2016/6
N2 - We develop a novel methodology for the single-trial analysis of multichannel time-varying neuroimaging signals. We introduce the space-by-time M/EEG decomposition, based on Non-negative Matrix Factorization (NMF), which describes single-trial M/EEG signals using a set of non-negative spatial and temporal components that are linearly combined with signed scalar activation coefficients. We illustrate the effectiveness of the proposed approach on an EEG dataset recorded during the performance of a visual categorization task. Our method extracts three temporal and two spatial functional components achieving a compact yet full representation of the underlying structure, which validates and summarizes succinctly results from previous studies. Furthermore, we introduce a decoding analysis that allows determining the distinct functional role of each component and relating them to experimental conditions and task parameters. In particular, we demonstrate that the presented stimulus and the task difficulty of each trial can be reliably decoded using specific combinations of components from the identified space-by-time representation. When comparing with a sliding-window linear discriminant algorithm, we show that our approach yields more robust decoding performance across participants. Overall, our findings suggest that the proposed space-by-time decomposition is a meaningful low-dimensional representation that carries the relevant information of single-trial M/EEG signals.
AB - We develop a novel methodology for the single-trial analysis of multichannel time-varying neuroimaging signals. We introduce the space-by-time M/EEG decomposition, based on Non-negative Matrix Factorization (NMF), which describes single-trial M/EEG signals using a set of non-negative spatial and temporal components that are linearly combined with signed scalar activation coefficients. We illustrate the effectiveness of the proposed approach on an EEG dataset recorded during the performance of a visual categorization task. Our method extracts three temporal and two spatial functional components achieving a compact yet full representation of the underlying structure, which validates and summarizes succinctly results from previous studies. Furthermore, we introduce a decoding analysis that allows determining the distinct functional role of each component and relating them to experimental conditions and task parameters. In particular, we demonstrate that the presented stimulus and the task difficulty of each trial can be reliably decoded using specific combinations of components from the identified space-by-time representation. When comparing with a sliding-window linear discriminant algorithm, we show that our approach yields more robust decoding performance across participants. Overall, our findings suggest that the proposed space-by-time decomposition is a meaningful low-dimensional representation that carries the relevant information of single-trial M/EEG signals.
KW - Algorithms
KW - Brain Mapping/methods
KW - Electroencephalography/methods
KW - Female
KW - Humans
KW - Image Interpretation, Computer-Assisted/methods
KW - Magnetoencephalography/methods
KW - Male
KW - Pattern Recognition, Visual/physiology
KW - Reproducibility of Results
KW - Sensitivity and Specificity
KW - Spatio-Temporal Analysis
KW - Visual Cortex/physiology
KW - Young Adult
U2 - 10.1016/j.neuroimage.2016.03.043
DO - 10.1016/j.neuroimage.2016.03.043
M3 - SCORING: Journal article
C2 - 27033682
VL - 133
SP - 504
EP - 515
JO - NEUROIMAGE
JF - NEUROIMAGE
SN - 1053-8119
ER -