14 citations · 41 across the 16 of their papers we have counts for
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Overview of Bayesian Solvers in EEG Distributed Source Models: Prior Selection, Algorithmic Implementation, and Depth Bias Reduction
Joonas Lahtinen, Alexandra Koulouri
Electroencephalography (EEG) source imaging aims to reconstruct the spatial distribution of neural activity within the brain from non-invasive scalp measurements. This inverse prob…
Tracking EEG Thalamic and Cortical Focal Brain Activity using Standardized Kalman Filtering with Kinematics Modeling
Veikka Piispa, Dilshanie Prasikala, Joonas Lahtinen +2
Kalman filtering has proven to be effective for estimating brain activity using EEG recordings. In particular, the introduced post hoc standardization step of the algorithm, inspir…
The Effect of Prior Parameters on Standardized Kalman Filter-Based EEG Source Localization
Dilshanie Prasikala, Joonas Lahtinen, Alexandra Koulouri +1
EEG Source localization is a critical tool in neuroscience, with applications ranging from epilepsy diagnosis to cognitive research. It involves solving an ill-posed inverse proble…
Conditionally Exponential Prior in Focal Near- and Far-Field EEG Source Localization via Randomized Multiresolution Scanning (RAMUS)
Joonas Lahtinen, Alexandra Koulouri, Atena Rezaei +1
In this paper, we focus on the inverse problem of reconstructing distributional brain activity with cortical and weakly detectable deep components in non-invasive Electroencephalog…
Randomized Multiresolution Scanning in Focal and Fast E/MEG Sensing of Brain Activity with a Variable Depth
Atena Rezaei, Alexandra Koulouri, Sampsa Pursiainen
We focus on electromagnetoencephalography imaging of the neural activity and, in particular, finding a robust estimate for the primary current distribution via the hierarchical Bay…