@article {eichelbaum2014a,
	title = {Visualizing Simulated Electrical Fields from Electroencephalography and Transcranial Electric Brain Stimulation: A Comparative Evaluation},
	journal = {NeuroImage},
	year = {2014},
	note = {In Press},
	abstract = {Electrical activity of neuronal populations is a crucial aspect of brain activity. This activity is not measured directly but recorded as electrical potential changes using head surface electrodes (electroencephalogram - EEG). Head surface electrodes can also be deployed to inject electrical currents in order to modulate brain activity (transcranial electric stimulation techniques) for therapeutic and neuroscientific purposes. In electroencephalography and noninvasive electric brain stimulation, electrical fields mediate between electrical signal sources and regions of interest (ROI). These fields can be very complicated in structure, and are influenced in a complex way by the conductivity profile of the human head. Visualization techniques play a central role to grasp the nature of those fields because such techniques allow for an effective conveyance of complex data and enable quick qualitative and quantitative assessments. The examination of volume conduction effects of particular head model parameterizations (e.g., skull thickness and layering), of brain anomalies (e.g., holes in the skull, tumors), location and extent of active brain areas (e.g., high concentrations of current densities) and around current injecting electrodes can be investigated using visualization. Here, we evaluate a number of widely used visualization techniques, based on either the potential distribution or on the current-flow. In particular, we focus on the extractability of quantitative and qualitative information from the obtained images, their effective integration of anatomical context information, and their interaction. We present illustrative examples from clinically and neuroscientifically relevant cases and discuss the pros and cons of the various visualization techniques.},
	doi = {10.1016/j.neuroimage.2014.04.085},
	url = {http://www.sciencedirect.com/science/article/pii/S1053811914003656},
	author = {Eichelbaum, Sebastian and Moritz Dannhauer and Mario Hlawitschka and Dana Brooks and Thomas R. Kn{\"o}sche and Gerik Scheuermann}
}
@conference {eichelbaum2010c,
	title = {Visualization of Effective Connectivity of the Brain},
	booktitle = {Proceedings of the 15th International Workshop on Vision, Modeling and Visualization (VMV) Workshop 2010},
	year = {2010},
	pages = {155-162},
	abstract = {Diffusion tensor images and higher-order diffusion images are the foundation for neuroscience researchers who are trying to gain insight into the connectome, the wiring scheme of the brain. Although modern imaging devices allow even more detailed anatomical measurements, these pure anatomical connections are not sufficient for understanding how the brain processes external stimuli. Anatomical connections constraint the causal influences between several areas of the brain, as they mediate causal influence between them. Therefore, neuroscientists developed models to represent the causal coherence between several pre-defined areas of the brain, which has been measured using fMRI, MEG, or EEG. The dynamic causal modeling (DCM) technique is one of these models and has been improved to use anatomical connection as informed priors to build the effective connectivity model. In this paper, we present a visualization method allowing neuroscientists to perceive both, the effective connectivity and the underlying anatomical connectivity in an intuitive way at the same time. The metaphor of moving information packages is used to show the relative intensity of information transfer inside the brain using a GPU based animation technique. We provide an interactive way to selectively view one or multiple effective connections while conceiving their anatomical connectivity. Additional anatomical context is supplied to give further orientation cues.},
	author = {Eichelbaum, Sebastian and Alexander Wiebel and Mario Hlawitschka and Anwander, A. and Thomas R. Kn{\"o}sche and Gerik Scheuermann},
	editor = {Reinhard Koch and Andreas Kolb and Christof Rezk-Salama}
}
@conference { SHH*:2010,
	title = {Visualizing White Matter Fiber Tracts with Optimally Fitted Curved Dissection Surfaces},
	booktitle = {Proceedings of the Eurographics Workshop on Visual Computing for Biomedicine, VCBM 2010},
	year = {2010},
	pages = {41-48},
	publisher = {Eurographics Association},
	organization = {Eurographics Association},
	author = {Ralph Schurade and Mario Hlawitschka and Bernd Hamann and Gerik Scheuermann and Thomas R. Kn{\"o}sche and Anwander, A.},
	editor = {Bartz, Dirk and Botha, C. and Hornegger, J. and Machiraju, R. and Alexander Wiebel and Preim, B.}
}
