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Interpreting EEG Scalp Effects in the Presence of a CSF-Filled Cavity from Stroke or Neurosurgery
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Poster C113 in Poster Session C, Wednesday, October 25, 10:15 am - 12:00 pm CEST, Espace Vieux-Port
Vitoria Piai1, Robert Oostenveld1,2, Jan Mathijs Schoffelen1, Maria Carla Piastra3; 1Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands, 2NatMEG, Karolinska Institutet, Stockholm, Sweden, 3Clinical Neurophysiology, Technical Medical Centre, Faculty of Science and Technology, University of Twente, Enschede, The Netherlands
Electrophysiology plays a pivotal role in our understanding of cognitive and sensorimotor functions, including changes in these functions following brain damage. Importantly, in certain cases (e.g., stroke or neurosurgery), not only functional but also structural brain changes may affect aspects of the measured electrophysiological signals, impacting the inferences one can draw from them. Previous studies have found EEG amplitude and scalp topography differences between neurotypical and neurological/neurosurgical groups, being interpreted at the cognitive level. These changes that appear functional are invariably accompanied by anatomical changes that need careful consideration. Impressed neuronal currents in the brain only indirectly result in electric potentials, as measured over the scalp with EEG. Critical to the EEG signal are the so-called volume currents, which flow through the various tissues in the head. The spatial distribution of the different tissues will critically affect the path that the volume currents will take, and thus impact the EEG signal. In particular, it is critical to consider the effects of the redistribution of CSF, especially because for lesion-based studies, the sources of interest are often those close to the lesion. We investigated the effect of CSF-filled cavities on simulated EEG scalp data. We compared situations where we simulated the same active source(s), but using different volume conduction models, i.e. the anatomical models that govern the volume currents, using the finite element method. The reference model was created from an anatomical image of an undamaged brain. To this reference model, we added realistic CSF-filled cavities, taken from empirical lesion (stroke) data, gradually increasing in size. We then simulated EEG scalp potentials for known sources by “injecting” the same known signal through those different volume conduction models. We used this approach for 1) a single source (akin to early sensory components) about 6mm (close) or about 35mm (far) from the CSF-lesion cavity and 2) for a scenario with a distributed configuration of sources (akin to a cognitive ERP effect, e.g., N400 component). Magnitude and topography errors between the reference model and the lesion models were quantified using the Magnitude Difference Measure (MAG%) and Relative Difference Measure (RDM%), respectively. For the simulations of a single source closer to the lesion, the size of the CSF-filled lesion modulated signal amplitude with more than 17% magnitude error, and topography with more than 9% topographical error, in a monotonic fashion. Negligible modulation was found for the single source far from the lesion. For the multi-source simulations of the cognitive component, the size of the CSF-filled lesion modulated signal amplitude with more than 6% magnitude error, and topography with more than 16% topography error in a non-monotonic fashion. In conclusion, the impact of a CSF-filled cavity cannot be neglected for scalp-level data, especially for multi-source configurations, which is what most cognitive neuroscientists would like to study and understand. Especially when group-level comparisons are made, given heterogeneity in lesion size and shape, any scalp-level attenuated, aberrant, or absent effects are difficult to interpret without considering the confounding effect of CSF.
Topic Areas: Methods, Disorders: Acquired