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A method is described to incorporate the spatiotemporal noise covariance matrix into a spatiotemporal source analysis. The essential feature is that the estimation problem is split into two parts. First, a model is fitted to the observed noise covariance matrix. This model is a Kronecker product of a spatial and a temporal matrix. The spatial matrix models(More)
In electromagnetic source analysis, it is necessary to determine how many sources are required to describe the electroencephalogram or magnetoencephalogram adequately. Model selection procedures (MSPs) or goodness of fit procedures give an estimate of the required number of sources. Existing and new MSPs are evaluated in different source and noise settings:(More)
The suppression of spontaneous motor impulses is an essential facet of cognitive control that is linked to frontal-BG circuitry. BG dysfunction caused by Parkinson disease (PD) disrupts the proficiency of action suppression, but how pharmacotherapy for PD impacts impulsive motor control is poorly understood. Dopamine agonists improve motor symptoms of PD(More)
Interactions between cortical areas are crucial for cognitive functioning. Methods currently in use to assess such interactions are not well suited for this task because they lack timing precision, localization precision, or both. We present a method for simultaneous estimation of source location and orientation parameters and cross-spectral parameters to(More)
Several methods [model selection procedures (MSPs)] to determine the number of sources in electroencephalogram (EEG) and magnetoencphalogram (MEG) data have previously been investigated in an instantaneous analysis. In this paper, these MSPs are extended to a spatio-temporal analysis if possible. It is seen that the residual variance (RV) tends to(More)
Deficits in working memory (WM) and reinforcement sensitivity are thought to give rise to symptoms in the combined (ADHD-C) and inattentive subtype (ADHD-I) of ADHD. Children with ADHD are especially impaired on visuospatial WM, which is composed of short-term memory (STM) and a central executive. Although deficits in visuospatial WM and reinforcement(More)
In [1] we proposed to analyze cross-spectrum matrices obtained from electro-or mag-netoencephalographic (EEG/MEG) signals, to obtain estimates of the EEG/MEG sources and their coherence. In this paper we extend this method in two ways. First, by modelling such interactions as linear filters, and second, by taking the mean of the signals across different(More)
Connectivity analysis of fMRI data requires correct specification of regions-of-interest (ROIs). Selection of ROIs based on outcomes of a GLM analysis may be hindered by conservativeness of the multiple comparison correction, while selection based on brain anatomy may be biased due to inconsistent structure-to-function mapping. To alleviate these problems(More)
Individuals may differ systematically in their applied decision strategies, which has critical implications for decision neuroscience but is yet scarcely studied. Our study's main focus was therefore to investigate the neural mechanisms underlying compensatory versus noncompensatory strategies in risky choice. Here, we compared people using a compensatory(More)