Work

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

Year: 2006

Type: article

Abstract: 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.

Source: IEEE Transactions on Biomedical Engineering

DOI: 10.1109/tbme.2006.886605

Authors: Zhisong Wang, A. Maier, D.A. Leopold, Hualou Liang

Institutions: The University of Texas Health Science Center at Houston, National Institutes of Health

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke

Awards: Quantitative Approach to Analysis of Cortical Dynamics, Quantitative Tools for Analyzing Brain Circuits, Attention Related Ensemble Activity in Visual Cortex, Neural Mechanisms of Natural Visual Perception