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Relaxation-Based Multichannel Signal Combination (RELAX-MUSIC) for ROC Analysis of Percept-Related Neuronal Activity
Journal article   Open access

Relaxation-Based Multichannel Signal Combination (RELAX-MUSIC) for ROC Analysis of Percept-Related Neuronal Activity

Zhisong Wang, Alexander Maier, David A Leopold and Hualou Liang
IEEE transactions on biomedical engineering, v 53(12), pp 2615-2618
Dec 2006
PMID: 17152443
url
https://doi.org/10.1109/TBME.2006.886605View
Published, Version of Record (VoR) Open

Abstract

Neurons structure from motion (SFM) visual cortex Fisher linear discriminant (FLD) Gaussian distribution Probability Predictive models multichannel combination single unit activity (SUA) Neurophysiology Electrodes receiver operating characteristic (ROC) middle temporal (MT) Brain modeling Signal analysis Testing
In this letter, we consider how to combine neuronal signals from multiple electrodes to optimally predict behavioral choices from observed neural activity. The predictability is often quantified by the area under the receiver operating characteristic (ROC) curve, also called choice probability (CP) in neurophysiology. We exploit a distribution-free relaxation based multichannel signal combination (RELAX-MUSIC) approach that requires only simple pairwise combination and recursive implementation for optimizing the area under the ROC curve. A permutation test is employed to assess the statistical significance of the derived CP. We demonstrate that the RELAX-MUSIC approach outperforms the commonly used response pooling and Fisher linear discriminant (FLD) methods. The excellent performances of the RELAX-MUSIC approach for predicting perceptual decisions from neural activity are demonstrated via examples using simulated and experimental data

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Collaboration types
Domestic collaboration
Web of Science research areas
Engineering, Biomedical
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