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Objective. In electroencephalography (EEG) measurements, the signal of each recording electrode is contrasted with a reference electrode or a combination of electrodes. The estimation of a neutral reference is a long-standing issue in EEG data analysis, which has motivated the proposal of different re-referencing methods, among which linked-mastoid re-referencing (LMR), average re-referencing (AR) and reference electrode standardization technique (REST). In this study we quantitatively assessed the extent to which the use of a high-density montage and a realistic head model can impact on the optimal estimation of a neutral reference for EEG recordings. Approach. Using simulated recordings generated by projecting specific source activity over the sensors, we assessed to what extent AR, REST and LMR may distort the scalp topography. We examined the impact electrode coverage has on AR and REST, and how accurate the REST reconstruction is for realistic and less realistic (three-layer and single-layer spherical) head models, and with possible uncertainty in the electrode positions. We assessed LMR, AR and REST also in the presence of typical EEG artifacts that are mixed in the recordings. Finally, we applied them to real EEG data collected in a target detection experiment to corroborate our findings on simulated data. Main results. Both AR and REST have relatively low reconstruction errors compared to LMR, and that REST is less sensitive than AR and LMR to artifacts mixed in the EEG data. For both AR and REST, high electrode density yields low re-referencing reconstruction errors. A realistic head model is critical for REST, leading to a more accurate estimate of a neutral reference compared to spherical head models. With a low-density montage, REST shows a more reliable reconstruction than AR either with a realistic or a three-layer spherical head model. Conversely, with a high-density montage AR yields better results unless precise information on electrode positions is available. Significance. Our study is the first to quantitatively assess the performance of EEG re-referencing techniques in relation to the use of a high-density montage and a realistic head model. We hope our study will help researchers in the choice of the most effective re-referencing approach for their EEG studies., Journal of Neural Engineering, 12 (5), ISSN:1741-2560, ISSN:1741-2552

Background: Rivastigmine enhances cholinergic activity and has been shown in clinical trials to decrease the rate of deterioration in Alzheimer's disease. It remains unclear where in the brain it exerts its effect. Functional magnetic resonance imaging (fMRI) can be used to measure changes in brain function and relate these to cognition. Objectives: To use fMRI to study brain activation with rivastigmine treatment. Methods: The effect on brain activation of a single dose of rivastigmine was tested in seven patients with mild Alzheimer's disease using fMRI during face encoding, and in five patients during a parametric working memory task. Results: During face encoding, rivastigmine increased bilateral activation in the fusiform gyrus. Brain activation was also enhanced in the prefrontal cortex in a simple working memory task. When working memory load was further increased, not only was increased activation seen, but in certain areas there was also decreased activation. Conclusions: These findings link the previously observed increase in cognitive performance in Alzheimer's disease after treatment with a cholinesterase inhibitor to altered brain activation. Although the results cannot be generalised to the Alzheimer's disease population at large, they provide evidence that in mild Alzheimer's disease, rivastigmine enhances brain activation in the fusiform and frontal cortices. This is compatible with the concept of cholinergic circuitry.