Literature DB >> 24047390

Attention to detail: why considering task demands is essential for single-trial analysis of BOLD correlates of the visual P1 and N1.

Tracy Warbrick1, Jorge Arrubla, Franks Boers, Irene Neuner, N Jon Shah.   

Abstract

Single-trial fluctuations in the EEG signal have been shown to temporally correlate with the fMRI BOLD response and are valuable for modeling trial-to-trial fluctuations in responses. The P1 and N1 components of the visual ERP are sensitive to different attentional modulations, suggesting that different aspects of stimulus processing can be modeled with these ERP parameters. As such, different patterns of BOLD covariation for P1 and N1 informed regressors would be expected; however, current findings are equivocal. We investigate the effects of variations in attention on P1 and N1 informed BOLD activation in a visual oddball task. Simultaneous EEG-fMRI data were recorded from 13 healthy participants during three conditions of a visual oddball task: Passive, Count, and Respond. We show that the P1 and N1 components of the visual ERP can be used in the integration-by-prediction method of EEG-fMRI data integration to highlight brain regions related to target detection and response production. Our data suggest that the P1 component of the ERP reflects changes in sensory encoding of stimulus features and is more informative for the Passive and Count conditions. The N1, on the other hand, was more informative for the Respond condition, suggesting that it can be used to model the processing of stimulus, meaning specifically discriminating one type of stimulus from another, and processes involved in integrating sensory information with response selection. Our results show that an understanding of the underlying electrophysiology is necessary for a thorough interpretation of EEG-informed fMRI analysis.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 24047390     DOI: 10.1162/jocn_a_00490

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  10 in total

1.  Electrophysiological evidence of perceived sexual attractiveness for human female bodies varying in waist-to-hip ratio.

Authors:  Marzia Del Zotto; Alan J Pegna
Journal:  Cogn Affect Behav Neurosci       Date:  2017-06       Impact factor: 3.282

2.  Transferring cognitive tasks between brain imaging modalities: implications for task design and results interpretation in FMRI studies.

Authors:  Tracy Warbrick; Martina Reske; N Jon Shah
Journal:  J Vis Exp       Date:  2014-09-22       Impact factor: 1.355

3.  Understanding age-related reductions in visual working memory capacity: examining the stages of change detection.

Authors:  Philip C Ko; Bryant Duda; Erin Hussey; Emily Mason; Robert J Molitor; Geoffrey F Woodman; Brandon A Ally
Journal:  Atten Percept Psychophys       Date:  2014-10       Impact factor: 2.199

4.  A multimodal encoding model applied to imaging decision-related neural cascades in the human brain.

Authors:  Jordan Muraskin; Truman R Brown; Jennifer M Walz; Tao Tu; Bryan Conroy; Robin I Goldman; Paul Sajda
Journal:  Neuroimage       Date:  2017-06-30       Impact factor: 6.556

5.  Investigating the effect of modifying the EEG cap lead configuration on the gradient artifact in simultaneous EEG-fMRI.

Authors:  Karen J Mullinger; Muhammad E H Chowdhury; Richard Bowtell
Journal:  Front Neurosci       Date:  2014-07-29       Impact factor: 4.677

6.  Removal of pulse artefact from EEG data recorded in MR environment at 3T. Setting of ICA parameters for marking artefactual components: application to resting-state data.

Authors:  Eleonora Maggioni; Jorge Arrubla; Tracy Warbrick; Jürgen Dammers; Anna M Bianchi; Gianluigi Reni; Michela Tosetti; Irene Neuner; N Jon Shah
Journal:  PLoS One       Date:  2014-11-10       Impact factor: 3.240

7.  Effects of aging on neural processing during an active listening task.

Authors:  Abin Kuruvilla-Mathew; Peter R Thorne; Suzanne C Purdy
Journal:  PLoS One       Date:  2022-09-07       Impact factor: 3.752

8.  Data-driven analysis of simultaneous EEG/fMRI using an ICA approach.

Authors:  Lena Schmüser; Alexandra Sebastian; Arian Mobascher; Klaus Lieb; Oliver Tüscher; Bernd Feige
Journal:  Front Neurosci       Date:  2014-07-01       Impact factor: 4.677

9.  Neural Correlates of Drug-Related Attentional Bias in Heroin Dependence.

Authors:  Qinglin Zhao; Hongqian Li; Bin Hu; Yonghui Li; Céline R Gillebert; Dante Mantini; Quanying Liu
Journal:  Front Hum Neurosci       Date:  2018-01-23       Impact factor: 3.169

Review 10.  Simultaneous EEG-fMRI: What Have We Learned and What Does the Future Hold?

Authors:  Tracy Warbrick
Journal:  Sensors (Basel)       Date:  2022-03-15       Impact factor: 3.576

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.