Parieto-occipital suppression eliminates implicit bidirectionality in grapheme-colour synaesthesia

Synaesthesia is a condition in which the input of one sensory modality triggers extraordinary additional experiences. On an explicit level, subjects affected by this condition normally report unidirectional experiences. In grapheme-colour synaesthesia for example, the letter A printed in black may trigger a red colour experience but not vice versa. However on an implicit level, at least for some types of synaesthesia, bidirectional activation is possible. In this study we tested whether bidirectional implicit activation is mediated by the same brain areas as explicit synaesthetic experiences. Specifically, we demonstrated suppression of implicit bidirectional activation with the application of transcranial magnetic stimulation over parieto-occipital brain areas. Our findings indicate that parieto-occipital regions are not only involved in explicit but also implicit synaesthetic binding.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Slowdown of gist perception in colour diagnostic scenes

Humans perceive the content (gist) of a scene very rapidly within about 40 ms [Castelhano and Henderson, 2008 Journal of Experimental Psychology Human Perception and Performance 43(3) 660-675]. It has also been demonstrated that colours contribute to the perception of the gist of a scene if the colours are diagnostic for the distinction of scenes (Oliva and Schyns, 2000 Cognitive Psychology 41 176-210). We presented 320 coloured photographs of 2 diagnostic (mountains and coasts) and 2 nondiagnostic colour scenes (cities and rooms), 80 per category, in a masking paradigm. The mask consisted of randomly distributed colour patches. SOA was varied between 20 and 80 ms, in steps of 20 ms and subjects had to indicate the gist of the scene (4AFC). A control condition without masking was also included. In line with previous results we have found that the gist of nondiagnostic coloured scenes is extracted within 40 ms. However, if colour comes into play, the extraction of the scene gist is prolonged by about 20 ms. A possible reason for this outcome might be that nondiagnostic colour scenes are identified by their luminance components which are processed faster than the colour information, which in turn mediates the identification of diagnostic colour scenes

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Sympatric colour polymorphisms associated with nonrandom gene flow in cichlid fish of Lake Victoria

Colour polymorphisms have fascinated evolutionary ecologists for a long time. Yet, knowledge on the mechanisms that allow their persistence is restricted to a handful of well-studied cases. We studied two species of Lake Victoria cichlid fish, Neochromis omnicaeruleus and Neochromis greenwoodi, exhibiting very similar sex-linked colour polymorphisms. The ecology and behaviour of one of these species is well studied, with colour-based mating and aggression preferences. Here, we ask whether the selection potentially resulting from female and male mating preferences and aggression biases reduces gene flow between the colour morphs and permits differentiation in traits other than colour. Over the past 14 years, the frequencies of colour morphs have somewhat oscillated, but there is no evidence for directional change, suggesting the colour polymorphism is persistent on an ecological timescale. We find limited evidence of ecomorphological differentiation between sympatric ancestral (plain) and derived (blotched) colour morphs. We also find significantly nonrandom genotypic assignment and an excess of linkage disequilibrium in the plain morph, which together with previous information on mating preferences suggests nonrandom mating between colour morphs. This, together with negative frequency-dependent sexual selection, found in previous studies, may facilitate maintenance of these polymorphisms in sympatry

Genetics of male nuptial colour divergence between sympatric sister species of a Lake Victoria cichlid fish

The hypothesis of sympatric speciation by sexual selection has been contentious. Several recent theoretical models of sympatric speciation by disruptive sexual selection were tailored to apply to African cichlids. Most of this work concludes that the genetic architecture of female preference and male trait is a key determinant of the likelihood of disruptive sexual selection to result in speciation. We investigated the genetic architecture controlling male nuptial colouration in a sympatric sibling species pair of cichlid fish from Lake Victoria, which differ conspicuously in male colouration and female mating preferences for these. We estimated that the difference between the species in male nuptial red colouration is controlled by a minimum number of two to four genes with significant epistasis and dominance effects. Yellow colouration appears to be controlled by one gene with complete dominance. The two colours appear to be epistatically linked. Knowledge on how male colouration segregates in hybrid generations and on the number of genes controlling differences between species can help us assess whether assumptions made in simulation models of sympatric speciation by sexual selection are realistic. In the particular case of the two sister species that we studied a small number of genes causing major differences in male colouration may have facilitated the divergence in male colouration associated with speciation.