Atypical scrapie in a Swiss goat and implications for transmissible spongiform encephalopathy surveillance.

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.

A model of the ventral visual system based on temporal stability and local memory.

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.

Decoding a temporal population code.

Encoding of sensory events in internal states of the brain requires that this information can be decoded by other neural structures. The encoding of sensory events can involve both the spatial organization of neuronal activity and its temporal dynamics. Here we investigate the issue of decoding in the context of a recently proposed encoding scheme: the temporal population code. In this code, the geometric properties of visual stimuli become encoded into the temporal response characteristics of the summed activities of a population of cortical neurons. For its decoding, we evaluate a model based on the structure and dynamics of cortical microcircuits that is proposed for computations on continuous temporal streams: the liquid state machine. Employing the original proposal of the decoding network results in a moderate performance. Our analysis shows that the temporal mixing of subsequent stimuli results in a joint representation that compromises their classification. To overcome this problem, we investigate a number of initialization strategies. Whereas we observe that a deterministically initialized network results in the best performance, we find that in case the network is never reset, that is, it continuously processes the sequence of stimuli, the classification performance is greatly hampered by the mixing of information from past and present stimuli. We conclude that this problem of the mixing of temporally segregated information is not specific to this particular decoding model but relates to a general problem that any circuit that processes continuous streams of temporal information needs to solve. Furthermore, as both the encoding and decoding components of our network have been independently proposed as models of the cerebral cortex, our results suggest that the brain could solve the problem of temporal mixing by applying reset signals at stimulus onset, leading to a temporal segmentation of a continuous input stream.

Involving the motor system in decision making.

The control of behaviour is usually understood in terms of three distinct components: sensory processing, decision making and movement control. Recently, this view has been questioned on the basis of physiological and behavioural data, blurring the distinction between these three stages. This raises the question to what extent the motor system itself can contribute to the interpretation of behavioural situations. To investigate this question we use a neural model of sensory motor integration applied to a behaving mobile robot performing a navigation task. We show that the population response of the motor system provides a substrate for the categorization of behavioural situations. This categorization allows for the assessment of the complexity of a behavioural situation and regulates whether higher-level decision making is required to resolve behavioural conflicts. Our model lends credence to an emerging reconceptualization of behavioural control where the motor system can be considered as part of a high-level perceptual system.

Properties of a temporal population code.

The temporal patterning of neuronal activity may play a substantial role in the representation of sensory stimuli. One particular hypothesis suggests that visual stimuli are represented by the temporal evolution of the instantaneous firing rate averaged over a whole population of neurons. Using an implementation in a cortical type network with lateral interactions, we could previously show that this scheme can be successfully applied to a pattern recognition task. Here, we use a large set of artificially generated stimuli to investigate the coding properties of the network in detail. The temporal population code generated by the network is intrinsically invariant to stimulus translations. We show that the encoding is invariant to small deformations of the stimuli and robust with respect to static and dynamic variations in synaptic strength of the lateral connections in the network. Furthermore, we present several measures which indicate that the encoding maps the stimuli into a high-dimensional space. These results show that a temporal population code is a promising approach for the encoding of relevant stimulus properties while simultaneously discarding the irrelevant information.

Design for a brain revisited: the neuromorphic design and functionality of the interactive space 'Ada'.

While much is now known about the operation and organisation of the brain at the neuronal and microcircuit level, we are still some way from understanding it as a complete system from the lowest to the highest levels of description. One way to gain such an integrative understanding of neural systems is to construct them. We have built the largest neuromorphic system yet known, an interactive space called 'Ada' that is able to interact with many people simultaneously using a wide variety of sensory and behavioural modalities. 'She' received 553,700 visitors over 5 months during the Swiss Expo.02 in 2002. In this paper we present the broad motivations, design and technologies behind Ada, and discuss the construction and analysis of the system.

Invariant representations of visual patterns in a temporal population code.

Mammalian visual systems are characterized by their ability to recognize stimuli invariant to various transformations. Here, we investigate the hypothesis that this ability is achieved by the temporal encoding of visual stimuli. By using a model of a cortical network, we show that this encoding is invariant to several transformations and robust with respect to stimulus variability. Furthermore, we show that the proposed model provides a rapid encoding, in accordance with recent physiological results. Taking into account properties of primary visual cortex, the application of the encoding scheme to an enhanced network demonstrates favorable scaling and high performance in a task humans excel at.