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The primate orbitofrontal cortex (OFC) is involved in reward processing, learning, and decision making. Research in monkeys has shown that this region is densely connected with higher sensory, limbic, and subcortical regions. Moreover, a parcellation of the monkey OFC into two subdivisions has been suggested based on its intrinsic anatomical connections.(More)
Neural activity in mammalian brains exhibits large spontaneous fluctuations whose structure reveals the intrinsic functional connectivity of the brain on many spatial and temporal scales. Between remote brain regions, spontaneous activity is organized into large-scale functional networks. To date, it has remained unclear whether the intrinsic functional(More)
In everyday life, successful decision making requires precise representations of expected values. However, for most behavioral options more than one attribute can be relevant in order to predict the expected reward. Thus, to make good or even optimal choices the reward predictions of multiple attributes need to be integrated into a combined expected value.(More)
Visual imagery allows us to vividly imagine scenes in the absence of visual stimulation. The likeness of visual imagery to visual perception suggests that they might share neural mechanisms in the brain. Here, we directly investigated whether perception and visual imagery share cortical representations. Specifically, we used a combination of functional(More)
The cortical control of eye movements is highly sophisticated. Not only can eye movements be made to the most salient target in a visual scene, but they can also be controlled by top-down rules as is required for visual search or reading. The cortical area called frontal eye fields (FEF) has been shown to play a key role in the visual to oculomotor(More)
The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between(More)
It is a vital ability of humans to flexibly adapt their behavior to different environmental situations. Constantly, the rules for our sensory-to-motor mappings need to be adapted to the current task demands. For example, the same sensory input might require two different motor responses depending on the actual situation. How does the brain prepare for such(More)
BACKGROUND Dynamic causal modeling (DCM) for fMRI is an established method for Bayesian system identification and inference on effective brain connectivity. DCM relies on a biophysical model that links hidden neuronal activity to measurable BOLD signals. Currently, biophysical simulations from DCM constitute a serious computational hindrance. Here, we(More)