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EEG-fMRI Gregor Leicht and Christoph Mulert

Abbreviations AAS ACC ADHD BCG BOLD DAN DMN EPSP ERP GBR GLM HRF IPSP LFPs LORETA PCA RF SN

4.1

Average artefact subtraction Anterior cingulate cortex Attention deficit/hyperactivity disorder Ballistocardiogram Blood oxygenation level dependent Dorsal attention network Default-mode network Excitatory postsynaptic potential Event-related potential Gamma-band response General linear model Haemodynamic response function Inhibitory postsynaptic potential Local field potentials Low-resolution brain electromagnetic tomography Principal component analysis Radio frequency Salience network

Introduction

Multimodal brain imaging has already been shown to be a very important approach for gaining new insights into physiological brain functions and G. Leicht • C. Mulert (*) Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany e-mail: [email protected]

pathophysiological mechanisms in neuropsychiatric disorders over the last few years. Referring to this, the simultaneous measurement of electrical activity and the corresponding haemodynamic responses with combined recordings of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represents one of the most powerful techniques. The complex dealing with the specific practical problems of this approach is easily outweighed by the opportunity to relate both modalities to actual brain events combining the high temporal resolution of EEG with the superior spatial information provided by fMRI. In this manner, it is possible to make progress in several important up-to-date research questions addressed in psychiatric neurosciences (Villringer et al. 2010). Key principles in the organisation of brain function are functional segregation and integration (Friston 2009). Therefore, the characterisation of connectivity mechanisms in brain networks is the major goal in human neuroscience today (Fox and Friston 2012). Disturbances of connectivity are supposed to be a very relevant pathophysiological factor of neuropsychiatric disorders such as schizophrenia (Schmitt et al. 2011). fMRI is a powerful tool in characterising network structures (e.g. brain regions involved in a specific cognitive task) and interactions of brain regions. These interactions can be examined concerning the correlational relationship between brain regions (functional connectivity) or, even more sophisticated, with respect to the directed influence from one region to another

C. Mulert, M.E. Shenton (eds.), MRI in Psychiatry, DOI 10.1007/978-3-642-54542-9_4, © Springer Berlin Heidelberg 2014

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(Friston et al. 2011). However, fMRI does not directly take the measurement of neuronal activity. In fact, functional coupling in the brain is realised by oscillation patterns in different frequency bands which can be directly assessed using EEG (Buzsaki and Watson 2012). For instance, low-frequency activity such as theta oscillations (4–8 Hz) is c