Single-trial analysis of neuroimaging data: inferring neural networks underlying perceptual decision-making in the human brain

Sajda, P., Philiastides, M.G. and Parra, L. (2009) Single-trial analysis of neuroimaging data: inferring neural networks underlying perceptual decision-making in the human brain. IEEE Reviews in Biomedical Engineering, 2, pp. 97-109.

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Abstract

Advances in neural signal and image acquisition as well as in multivariate signal processing and machine learning are enabling a richer and more rigorous understanding of the neural basis of human decision-making. Decision-making is essentially characterized behaviorally by the variability of the decision across individual trials - e.g., error and response time distributions. To infer the neural processes that govern decision-making requires identifying neural correlates of such trial-to-trial behavioral variability. In this paper, we review efforts that utilize signal processing and machine learning to enable single-trial analysis of neural signals acquired while subjects perform simple decision-making tasks. Our focus is on neuroimaging data collected noninvasively via electroencephalograpy (EEG) and functional magnetic resonance imaging (fMRI). We review the specific framework for extracting decision-relevant neural components from the neuroimaging data, the goal being to analyze the trial-to-trial variability of the neural signal along these component directions and to relate them to elements of the decision-making process. We review results for perceptual decision-making and discrimination tasks, including paradigms in which EEG variability is used to inform an fMRI analysis. We discuss how single-trial analysis reveals aspects of the underlying decision-making networks that are unobservable using traditional trial-averaging methods.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Philiastides, Dr Marios
Authors: Sajda, P., Philiastides, M.G., and Parra, L.
College/School:College of Medical Veterinary and Life Sciences > Institute of Neuroscience and Psychology
Journal Name:IEEE Reviews in Biomedical Engineering
ISSN:1937-3333

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