Literature DB >> 19345734

Single-trial discrimination for integrating simultaneous EEG and fMRI: identifying cortical areas contributing to trial-to-trial variability in the auditory oddball task.

Robin I Goldman1, Cheng-Yu Wei, Marios G Philiastides, Adam D Gerson, David Friedman, Truman R Brown, Paul Sajda.   

Abstract

The auditory oddball task is a well-studied stimulus paradigm used to investigate the neural correlates of simple target detection. It elicits several classic event-related potentials (ERPs), the most prominent being the P300 which is seen as a neural correlate of subjects' detection of rare (target) stimuli. Though trial-averaging is typically used to identify and characterize such ERPs, their latency and amplitude can vary on a trial-to-trial basis reflecting variability in the underlying neural information processing. Here we simultaneously recorded EEG and fMRI during an auditory oddball task and identified cortical areas correlated with the trial-to-trial variability of task-discriminating EEG components. Unique to our approach is a linear multivariate method for identifying task-discriminating components within specific stimulus- or response-locked time windows. We find fMRI activations indicative of distinct processes that contribute to the single-trial variability during target detection. These regions are different from those found using standard, including trial-averaged, regressors. Of particular note is the strong activation of the lateral occipital complex (LOC). The LOC was not seen when using traditional event-related regressors. Though LOC is typically associated with visual/spatial attention, its activation in an auditory oddball task, where attention can wax and wane from trial to trial, indicates that it may be part of a more general attention network involved in allocating resources for target detection and decision making. Our results show that trial-to-trial variability in EEG components, acquired simultaneously with fMRI, can yield task-relevant BOLD activations that are otherwise unobservable using traditional fMRI analysis.

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Year:  2009        PMID: 19345734      PMCID: PMC2789455          DOI: 10.1016/j.neuroimage.2009.03.062

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  47 in total

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2.  Simultaneous 3-T fMRI and high-density recording of human auditory evoked potentials.

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Journal:  Neuroimage       Date:  2004-11       Impact factor: 6.556

3.  An adaptive reflexive processing model of neurocognitive function: supporting evidence from a large scale (n = 100) fMRI study of an auditory oddball task.

Authors:  Kent A Kiehl; Michael C Stevens; Kristin R Laurens; Godfrey Pearlson; Vince D Calhoun; Peter F Liddle
Journal:  Neuroimage       Date:  2005-04-15       Impact factor: 6.556

4.  Cortical origins of response time variability during rapid discrimination of visual objects.

Authors:  Adam D Gerson; Lucas C Parra; Paul Sajda
Journal:  Neuroimage       Date:  2005-09-19       Impact factor: 6.556

5.  Assessing the spatiotemporal evolution of neuronal activation with single-trial event-related potentials and functional MRI.

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-11-28       Impact factor: 11.205

6.  Trial-by-trial coupling of concurrent electroencephalogram and functional magnetic resonance imaging identifies the dynamics of performance monitoring.

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7.  Recipes for the linear analysis of EEG.

Authors:  Lucas C Parra; Clay D Spence; Adam D Gerson; Paul Sajda
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10.  Statistical methods of estimation and inference for functional MR image analysis.

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  43 in total

1.  Within-subject joint independent component analysis of simultaneous fMRI/ERP in an auditory oddball paradigm.

Authors:  J Mangalathu-Arumana; S A Beardsley; E Liebenthal
Journal:  Neuroimage       Date:  2012-02-22       Impact factor: 6.556

Review 2.  Single-trial analysis of neuroimaging data: inferring neural networks underlying perceptual decision-making in the human brain.

Authors:  Paul Sajda; Marios G Philiastides; Lucas C Parra
Journal:  IEEE Rev Biomed Eng       Date:  2009

3.  Fusing multiple neuroimaging modalities to assess group differences in perception-action coupling.

Authors:  Jordan Muraskin; Jason Sherwin; Gregory Lieberman; Javier O Garcia; Timothy Verstynen; Jean M Vettel; Paul Sajda
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2016-07-15       Impact factor: 10.961

4.  Fast, Exact Model Selection and Permutation Testing for ℓ2-Regularized Logistic Regression.

Authors:  Bryan Conroy; Paul Sajda
Journal:  JMLR Workshop Conf Proc       Date:  2012

5.  Simultaneous EEG-fMRI reveals temporal evolution of coupling between supramodal cortical attention networks and the brainstem.

Authors:  Jennifer M Walz; Robin I Goldman; Michael Carapezza; Jordan Muraskin; Truman R Brown; Paul Sajda
Journal:  J Neurosci       Date:  2013-12-04       Impact factor: 6.167

6.  Coupling electrophysiological and hemodynamic responses to errors.

Authors:  Nuria Doñamayor; Urs Heilbronner; Thomas F Münte
Journal:  Hum Brain Mapp       Date:  2011-05-26       Impact factor: 5.038

7.  Loss of reliable temporal structure in event-related averaging of naturalistic stimuli.

Authors:  Aya Ben-Yakov; Christopher J Honey; Yulia Lerner; Uri Hasson
Journal:  Neuroimage       Date:  2012-07-14       Impact factor: 6.556

8.  Knowing when not to swing: EEG evidence that enhanced perception-action coupling underlies baseball batter expertise.

Authors:  Jordan Muraskin; Jason Sherwin; Paul Sajda
Journal:  Neuroimage       Date:  2015-08-20       Impact factor: 6.556

9.  Prospective active marker motion correction improves statistical power in BOLD fMRI.

Authors:  Jordan Muraskin; Melvyn B Ooi; Robin I Goldman; Sascha Krueger; William J Thomas; Paul Sajda; Truman R Brown
Journal:  Neuroimage       Date:  2012-12-05       Impact factor: 6.556

10.  Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing.

Authors:  Tao Tu; Noam Schneck; Jordan Muraskin; Paul Sajda
Journal:  J Neurosci       Date:  2017-11-08       Impact factor: 6.167

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