Within-subject joint independent component analysis of simultaneous fMRI/ERP in an auditory oddball paradigm
NeuroImage, ISSN: 1053-8119, Vol: 60, Issue: 4, Page: 2247-2257
2012
- 31Citations
- 77Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations31
- Citation Indexes31
- CrossRef31
- 31
- Captures77
- Readers77
- 74
Article Description
The integration of event-related potential (ERP) and functional magnetic resonance imaging (fMRI) can contribute to characterizing neural networks with high temporal and spatial resolution. This research aimed to determine the sensitivity and limitations of applying joint independent component analysis (jICA) within-subjects, for ERP and fMRI data collected simultaneously in a parametric auditory frequency oddball paradigm. In a group of 20 subjects, an increase in ERP peak amplitude ranging 1–8 μV in the time window of the P300 (350–700 ms), and a correlated increase in fMRI signal in a network of regions including the right superior temporal and supramarginal gyri, was observed with the increase in deviant frequency difference. JICA of the same ERP and fMRI group data revealed activity in a similar network, albeit with stronger amplitude and larger extent. In addition, activity in the left pre- and post-central gyri, likely associated with right hand somato-motor response, was observed only with the jICA approach. Within-subject, the jICA approach revealed significantly stronger and more extensive activity in the brain regions associated with the auditory P300 than the P300 linear regression analysis. The results suggest that with the incorporation of spatial and temporal information from both imaging modalities, jICA may be a more sensitive method for extracting common sources of activity between ERP and fMRI.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S1053811912002078; http://dx.doi.org/10.1016/j.neuroimage.2012.02.030; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84858741593&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/22377443; https://linkinghub.elsevier.com/retrieve/pii/S1053811912002078
Elsevier BV
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