Journal
JOURNAL OF INTEGRATIVE NEUROSCIENCE
Volume 9, Issue 4, Pages 453-476Publisher
IMR PRESS
DOI: 10.1142/S0219635210002512
Keywords
Neuroimaging; information fusion; functional segregation; functional integration; event-related; neurophysiology; data-driven; model-based; Bayesian analysis; model comparison
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Funding
- Foundation for Science and Technology, Portugal
- Wellcome Trust
- Swiss Systems Biology initiative SystemsX.ch
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The diverse nature of cerebral activity, as measured using neuroimaging techniques, has been recognised long ago. It seems obvious that using single modality recordings can be limited when it comes to capturing its complex nature. Thus, it has been argued that moving to a multimodal approach will allow neuroscientists to better understand the dynamics and structure of this activity. This means that integrating information from different techniques, such as electroencephalography (EEG) and the blood oxygenated level dependent (BOLD) signal recorded with functional magnetic resonance imaging (fMRI), represents an important methodological challenge. In this work, we review the work that has been done thus far to derive EEG/fMRI integration approaches. This leads us to inspect the conditions under which such an integration approach could work or fail, and to disclose the types of scientific questions one could (and could not) hope to answer with it.
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