The cerebral cortex is a remarkably homogeneous structure suggesting a rather generic computational machinery. Indeed, under a variety of conditions, functions attributed to specialized areas can be supported by other regions. However, a host of studies have laid out an ever more detailed map of functional cortical areas. This leaves us with the puzzle of whether different cortical areas are intrinsically specialized, or whether they differ mostly by their position in the processing hierarchy and their inputs but apply the same computational principles. Here we show that the computational principle of optimal stability of sensory representations combined with local memory gives rise to a hierarchy of processing stages resembling the ventral visual pathway when it is exposed to continuous natural stimuli. Early processing stages show receptive fields similar to those observed in the primary visual cortex. Subsequent stages are selective for increasingly complex configurations of local features, as observed in higher visual areas. The last stage of the model displays place fields as observed in entorhinal cortex and hippocampus. The results suggest that functionally heterogeneous cortical areas can be generated by only a few computational principles and highlight the importance of the variability of the input signals in forming functional specialization.

Abstract. Different types of transmissible spongiform encephalopathies (TSEs) affect sheep and goats. In addition to the classical form of scrapie, both species are susceptible to experimental infections with the bovine spongiform encephalopathy (BSE) agent, and in recent years atypical scrapie cases have been reported in sheep from different European countries. Atypical scrapie in sheep is characterized by distinct histopathologic lesions and molecular characteristics of the abnormal scrapie prion protein (PrP sc ). Characteristics of atypical scrapie have not yet been described in detail in goats. A goat presenting features of atypical scrapie was identified in Switzerland. Although there was no difference between the molecular characteristics of PrP sc in this animal and those of atypical scrapie in sheep, differences in the distribution of histopathologic lesions and PrP sc deposition were observed. In particular the cerebellar cortex, a major site of PrP sc deposition in atypical scrapie in sheep, was found to be virtually unaffected in this goat. In contrast, severe lesions and PrP sc deposition were detected in more rostral brain structures, such as thalamus and midbrain. Two TSE screening tests and PrP sc immunohistochemistry were either negative or barely positive when applied to cerebellum and obex tissues, the target samples for TSE surveillance in sheep and goats. These findings suggest that such cases may have been missed in the past and could be overlooked in the future if sampling and testing procedures are not adapted. The epidemiological and veterinary public health implications of these atypical cases, however, are not yet known.

Vibration inspection of electro-mechanical components and systems is an important tool for automated reliable online as well as post-process production quality assurance. Considering that bad electromotor samples are very rare in the production line, we propose a novel automated fault detection method named "Tilear", based on Deep Belief Networks (DBNs) training only with good electromotor samples. Tilear consctructs an auto-encoder with DBNs, aiming to reconstruct the inputs as closely as possible. Tilear is structured in two parts: training and decision-making. During training, Tilear is trained only with informative features extracted from preprocessed vibration signals of good electromotors, which enables the trained Tilear only to know how to reconstruct good electromotor vibration signal features. In the decision-making part, comparing the recorded signal from test electromotor and the Tilear reconstructed signal, allows to measure how well a recording from a test electromotor matches the Tilear model learned from good electromotors. A reliable decision can be made. Keywords