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Neuroimage. 2009 Aug 1;47(1):112-21. doi: 10.1016/j.neuroimage.2009.03.074. Epub 2009 Apr 8.

Combined distributed source and single-trial EEG-fMRI modeling: application to effortful decision making processes.

Author information

1
Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD Maastricht, Maastricht, The Netherlands. fabrizio.esposito@psychology.unimaas.nl

Abstract

Single-trial coupling of simultaneously recorded EEG and fMRI time-series can be used to generate fMRI patterns of brain activity with high spatial resolution from EEG responses with high temporal resolution. A forced choice reaction task under different effort conditions has been previously used to demonstrate single-trial EEG-fMRI coupling effects for an early ERP component (N1: 70-150 ms) measured on a single scalp channel (Cz), thereby providing the first multi-modal evidence of early anterior cingulate cortex (ACC) activation in effortful decision making (Mulert, C., Seifert, C., Leicht, G., Kirsch, V., Ertl, M., Karch, S., Moosmann, M., Lutz, J., Möller, H.J., Hegerl, U., Pogarell, O., Jäger, L., 2008. Single-trial coupling of EEG and fMRI reveals the involvement of early anterior cingulate cortex activation in effortful decision making. Neuroimage 42, 158-168.). In this work, we searched for "effort-specific" ERP-N1 sources and explored their single-trial EEG-fMRI correlations for discovering "source-specific" inter-modality coupling effects. To this end, we performed a whole-cortex distributed ERP analysis and used the local source power trial-by-trial variation as an input for single-trial EEG-fMRI coupling analysis. We found a high-effort-specific ERP-N1 source in the ACC and statistically significant differential EEG-fMRI coupling spots in five cortical regions, including the ACC. Our results provide new insights about the neural origins of effort-specific EEG and fMRI response modulations in a choice reaction task and confirm the central role of early ACC activation in motivation-related decision making processes; we discuss the importance of combining distributed source modeling with single-trial coupling for enriching the interpretation of EEG-fMRI patterns.

[Indexed for MEDLINE]

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