EEG-fMRI Based Information Theoretic Characterization of the Human Perceptual Decision System

Dirk Ostwald,Stephen D. Mayhew,Camillo Porcaro,Andrew P. Bagshaw,Stefan J. Kiebel

doi:10.1371/journal.pone.0033896

Abstract

The modern metaphor of the brain is that of a dynamic information processing device. In the current study we investigate how a core cognitive network of the human brain, the perceptual decision system, can be characterized regarding its spatiotemporal representation of task-relevant information. We capitalize on a recently developed information theoretic framework for the analysis of simultaneously acquired electroencephalography (EEG) and functional magnetic resonance imaging data (fMRI) (Ostwald et al. (2010), NeuroImage 49: 498–516). We show how this framework naturally extends from previous validations in the sensory to the cognitive domain and how it enables the economic description of neural spatiotemporal information encoding. Specifically, based on simultaneous EEG-fMRI data features from n = 13 observers performing a visual perceptual decision task, we demonstrate how the information theoretic framework is able to reproduce earlier findings on the neurobiological underpinnings of perceptual decisions from the response signal features' marginal distributions. Furthermore, using the joint EEG-fMRI feature distribution, we provide novel evidence for a highly distributed and dynamic encoding of task-relevant information in the human brain.

Highlights

The modern metaphor for the human brain is that of a dynamic, information processing device [1]
Traditional psychophysical, event-related potential and functional magnetic resonance imaging data (fMRI)-GLM analyses are presented prior to the information theoretic analyses. These analyses serve the following purposes: 1) to make the reported IT results more comparable to similar studies of perceptual decisions, 2) to determine whether the experimental manipulations resulted in behavioural modulations, 3) to guide the identification of data features of interest, i.e. timewindows of interest for the EEG data and regions of interest for the fMRI data based on group results, and 4) to allow data quality assessment and inspection prior to single-trial feature distribution estimation
No single brain region or single time-point in the first 500 ms of the perceptual decision process was identified to be of sole relevance

Summary

Introduction

The modern metaphor for the human brain is that of a dynamic, information processing device [1]. A first step in understanding how neural activity represents this set of variables is to quantify the spatiotemporal dynamics of information representation in the brain. A remaining obstacle preventing the full exploitation of the potential spatiotemporal resolution of EEGfMRI in identifying information-carrying features of cortical activity is the uncertainty about how to integrate the two modalities. To this end, recent work has underlined the importance of single-trial fluctuations in EEG and fMRI data features in terms of their information content regarding stimulation and task performance, and the effect of ongoing brain activity on evoked responses [7,8,9,10]

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Conclusion