Abstract Insight problems are difficult because the initially activated knowledge hinders successful solving. The crucial information needed for a solution is often so far removed that gaining access to it through restructuring leads to the subjective experience of “Aha!”. Although this assumption is shared by most insight theories, there is little empirical evidence for the […]

Many cognitive, sensory and motor processes have correlates in oscillatory neural source activity, which is embedded as a subspace in the recorded brain signals. Decoding such processes from noisy magnetoencephalogram/electroencephalogram (M/EEG) signals usually requires data-driven analysis methods. The objective evaluation of such decoding algorithms on experimental raw signals, however, is a challenge: the amount of […]

Neural network simulation is an important tool for generating and evaluating hypotheses on the structure, dynamics and function of neural circuits. For scientific questions addressing organisms operating autonomously in their environments, in particular where learning is involved, it is crucial to be able to operate such simulations in a closed-loop fashion. In such a set-up, […]