Several other methods of achieving dynamic range control were also discussed in the previous chapter. These methods are typically unsharp mask filters with large kernel sizes, and multi-scale approaches such as multi scale image contrast amplification (MUSICA) developed by the Agfa-Gevaert company (Vuylsteke & Schoeters, 1999). In achieving their goal of dynamic range control, these methods alt...

The precise probability of a compound event (e.g. e1 _ e2; e1 ^ e2) depends upon the known relationships (e.g. independence, mutual exclusion, ignorance of any relationship, etc.) between the primitive events that constitute the compound event. To date, most research on probabilistic logic programming 20, 19, 22, 23, 24] has assumed that we are ignorant of the relationship between primitive eve...

Brain tumor segmentation from Magnetic Resonance Images (MRIs) is an important task to measure tumor responses to treatments. However, automatic segmentation is very challenging. This paper presents an automatic brain tumor segmentation method based on a Normalized Gaussian Bayesian classification and a new 3D Fluid Vector Flow (FVF) algorithm. In our method, a Normalized Gaussian Mixture Model...

The slight perversion of the original title of this piece (The Future of the Bayesian Brain) reflects my attempt to write prospectively about 'Science and Stories' over the past 20 years. I will meet this challenge by dealing with the future and then turning to its history. The future of the Bayesian brain (in neuroimaging) is clear: it is the application of dynamic causal modeling to understan...

In this paper we consider the neuroscienti€c theory of the Bayesian brain in the light of adaptive web systems and content personalisation. In particular, we elaborate on neural mechanisms of human decision-making and the origin of lacking reliability of user feedback, o‰en denoted as noise or human uncertainty. To this end, we €rst introduce an adaptive model of cognitive agency in which popul...

The brain uses sensory information that is often uncertain in order to efficiently generate perceptual representations of the world. This observation has led to the Bayesian brain hypothesis, in which the brain combines internal expectations of the world with unreliable external sensory information in a nearly optimal probabilistic manner. Recent studies have suggested that to be true in statis...

When it comes to interpreting others' behaviour, we almost irrepressibly engage in the attribution of mental states (beliefs, emotions…). Such "mentalizing" can become very sophisticated, eventually endowing us with highly adaptive skills such as convincing, teaching or deceiving. Here, sophistication can be captured in terms of the depth of our recursive beliefs, as in "I think that you think ...

In this paper I will present a new model of eye control developed within the Probabilistic Population Code (PPC) framework. The posterior parietal cortex is believed to direct eye movements, especially in regards to target tracking tasks, and a number of debates exist over the precise nature of the computations performed by the parietal cortex, with each side supported by different sets of biol...