Non-canonical actions of Nogo-A and its receptors

Nogo-A is a myelin associated protein and one of the most potent neurite growth inhibitors in the central nervous system. Interference with Nogo-A signaling has thus been investigated as therapeutic target to promote functional recovery in CNS injuries. Still, the finding that Nogo-A presents a fairly ubiquitous expression in many types of neurons in different brain regions, in the eye and even in the inner ear suggests for further functions besides the neurite growth repression. Indeed, a growing number of studies identified a variety of functions including regulation of neuronal stem cells, modulation of microglial activity, inhibition of angiogenesis and interference with memory formation. Aim of the present commentary is to draw attention on these less well-known and sometimes controversial roles of Nogo-A. Furthermore, we are addressing the role of Nogo-A in neuropathological conditions such as ischemic stroke, schizophrenia and neurodegenerative diseases.

Online Reputation Systems and Cumulative Advantage

The study of online reputation systems and their importance for promoting trust and cooperation and, therefore, the smooth functioning of online markets has received considerable attention over the last few years. In the first part of our talk we will try to give a brief overview of the existing theoretical and empirical work in this field, summarize the main findings from this research and identify open questions where results are either controversial or do not yet exist. The second part of our talk will focus on one of these issues that deserve further research, namely the relation between online reputation systems and processes of "cumulative advantage." Cumulative advantage is the mechanism where a favorable relative position of having a good reputation becomes a resource for further relative gains. The process leads to increased status inequality and a heavily skewed distribution of number of feedbacks, i.e. the ties in the reputation network. We present empirical evidence for direct and indirect reputation effects on the micro level of an auction reputation system and discuss the distributional consequences for the market level.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.