Cognition in Rodents

Cognition is a loosely defined term with divergent meanings in different disciplines and species. In human psychology, ‘cognition’ is often used in reference to concepts such as ‘mind’ or ‘higher mental functions’. However, in more general terms, ‘cognition’ is regularly used to refer to all manner of information organization by the brain: from collection, to processing, to storage and recognition or recall. Whereas ‘cognition’ would seem to permeate all mental functions, including subjective perception and innate responses, ‘cognitive ability’ has a slightly more specific connotation – something more akin to intelligence or information-processing ability. Thus, ‘cognition’ deals with mental process structure and ‘cognitive abilities’ with natural variations impinging upon functioning at the higher end of that structure. Although the term ‘cognition’ sometimes subsumes or substitutes ‘cognitive ability’ in the literature, understanding this methodological distinction allows us to read across the two fields without the misunderstandings that classical cognitive psychologists have sometimes shown for cognitive ability research

Minimizing the stabbing number of matchings, trees, and triangulations

The (axis-parallel) stabbing number of a given set of line segments is the maximum number of segments that can be intersected by any one (axis-parallel) line. This paper deals with finding perfect matchings, spanning trees, or triangulations of minimum stabbing number for a given set of points. The complexity of these problems has been a long-standing open question; in fact, it is one of the original 30 outstanding open problems in computational geometry on the list by Demaine, Mitchell, and O'Rourke. The answer we provide is negative for a number of minimum stabbing problems by showing them NP-hard by means of a general proof technique. It implies non-trivial lower bounds on the approximability. On the positive side we propose a cut-based integer programming formulation for minimizing the stabbing number of matchings and spanning trees. We obtain lower bounds (in polynomial time) from the corresponding linear programming relaxations, and show that an optimal fractional solution always contains an edge of at least constant weight. This result constitutes a crucial step towards a constant-factor approximation via an iterated rounding scheme. In computational experiments we demonstrate that our approach allows for actually solving problems with up to several hundred points optimally or near-optimally.Comment: 25 pages, 12 figures, Latex. To appear in "Discrete and Computational Geometry". Previous version (extended abstract) appears in SODA 2004, pp. 430-43

Wavelength-selected Neutron Pulses Formed by a Spatial Magnetic Neutron Spin Resonator

AbstractWe present a novel type of spatial magnetic neutron spin resonator whose time and wavelength resolution can be de- coupled from each other by means of a travelling wave mode of operation. Combined with a pair of highly efficient polarisers such a device could act simultaneously as monochromator and chopper, able to produce short neutron pulses, whose wavelength, spectral width and duration could be varied almost instantaneously by purely electronic means with- out any mechanical modification of the experimental setup. To demonstrate the practical feasibility of this technique we have designed and built a first prototype resonator consisting of ten individually switchable modules which allows to produce neutron pulses in the microsecond regime. It was installed at a polarised 2.6Å neutron beamline at the 250kW TRIGA research reactor of the Vienna University of Technology where it could deliver pulses of 55μs duration, which is about three times less than the passage time of the neutrons through the resonator itself. In order to further improve the achievable wavelength resolution to about 3% a second prototype resonator, consisting of 48 individual modules with optimised field homogeneity and enlarged beam cross-section of 6 × 6cm2 was developed. We present the results of first measurements which demonstrate the successful operation of this device

Deducing corticotropin-releasing hormone receptor type 1 signaling networks from gene expression data by usage of genetic algorithms and graphical Gaussian models

<p>Abstract</p> <p>Background</p> <p>Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a hallmark of complex and multifactorial psychiatric diseases such as anxiety and mood disorders. About 50-60% of patients with major depression show HPA axis dysfunction, i.e. hyperactivity and impaired negative feedback regulation. The neuropeptide corticotropin-releasing hormone (CRH) and its receptor type 1 (CRHR1) are key regulators of this neuroendocrine stress axis. Therefore, we analyzed CRH/CRHR1-dependent gene expression data obtained from the pituitary corticotrope cell line AtT-20, a well-established <it>in vitro </it>model for CRHR1-mediated signal transduction. To extract significantly regulated genes from a genome-wide microarray data set and to deduce underlying CRHR1-dependent signaling networks, we combined supervised and unsupervised algorithms.</p> <p>Results</p> <p>We present an efficient variable selection strategy by consecutively applying univariate as well as multivariate methods followed by graphical models. First, feature preselection was used to exclude genes not differentially regulated over time from the dataset. For multivariate variable selection a maximum likelihood (MLHD) discriminant function within GALGO, an R package based on a genetic algorithm (GA), was chosen. The topmost genes representing major nodes in the expression network were ranked to find highly separating candidate genes. By using groups of five genes (chromosome size) in the discriminant function and repeating the genetic algorithm separately four times we found eleven genes occurring at least in three of the top ranked result lists of the four repetitions. In addition, we compared the results of GA/MLHD with the alternative optimization algorithms greedy selection and simulated annealing as well as with the state-of-the-art method random forest. In every case we obtained a clear overlap of the selected genes independently confirming the results of MLHD in combination with a genetic algorithm.</p> <p>With two unsupervised algorithms, principal component analysis and graphical Gaussian models, putative interactions of the candidate genes were determined and reconstructed by literature mining. Differential regulation of six candidate genes was validated by qRT-PCR.</p> <p>Conclusions</p> <p>The combination of supervised and unsupervised algorithms in this study allowed extracting a small subset of meaningful candidate genes from the genome-wide expression data set. Thereby, variable selection using different optimization algorithms based on linear classifiers as well as the nonlinear random forest method resulted in congruent candidate genes. The calculated interacting network connecting these new target genes was bioinformatically mapped to known CRHR1-dependent signaling pathways. Additionally, the differential expression of the identified target genes was confirmed experimentally.</p

Deletion of the Coffin-Lowry Syndrome Gene Rsk2 in Mice is Associated With Impaired Spatial Learning and Reduced Control of Exploratory Behavior

Coffin-Lowry Syndrome (CLS) is an X-linked syndromic form of mental retardation associated with skeletal abnormalities. It is caused by mutations of the Rsk2 gene, which encodes a growth factor regulated kinase. Gene deletion studies in mice have shown an essential role for the Rsk2 gene in osteoblast differentiation and function, establishing a causal link between Rsk2 deficiency and skeletal abnormalities of CLS. Although analyses in mice have revealed prominent expression of Rsk2 in brain structures that are essential for learning and memory, evidence at the behavioral level for an involvement of Rsk2 in cognitive function is still lacking. Here, we have examined Rsk2-deficient mice in two extensive batteries of behavioral tests, which were conducted independently in two laboratories in Zurich (Switzerland) and Orsay (France). Despite the known reduction of bone mass, all parameters of motor function were normal, confirming the suitability of Rsk2-deficient mice for behavioral testing. Rsk2-deficient mice showed a mild impairment of spatial working memory, delayed acquisition of a spatial reference memory task and long-term spatial memory deficits. In contrast, associative and recognition memory, as well as the habituation of exploratory activity were normal. Our studies also revealed mild signs of disinhibition in exploratory activity, as well as a difficulty to adapt to new test environments, which likely contributed to the learning impairments displayed by Rsk2-deficient mice. The observed behavioral changes are in line with observations made in other mouse models of human mental retardation and support a role of Rsk2 in cognitive function

Distributed rate allocation in switch-based multiparty videoconference

Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have however, large requirements in terms of both network and computational resources and have to deal with sets of heterogenous clients. The multiparty videoconferencing systems can be grouped in two classes. They are based either on expensive central nodes, called multipoint control units (MCU), with transcoding capabilities, or, on a peer-to-peer strategy where users help each other to distribute the different video streams. Whereas the first one requires an expensive central hardware, the second one depends completely on the redistribution capacity of the users, which sometimes might neither provide sufficient bandwidth nor be reliable enough. In this work we propose an alternative solution where we use a central node to distribute the video streams but at the same time we maintain the hardware complexity and the computational requirements of this node as low as possible. The proposed solution uses a distributed algorithm to allocate the users' rates in a Quality of Service (QoS) aware manner. The allocation algorithm is also extremely fast and is able to quickly reallocate the rates in case the conditions change. We have further implemented our solution in a network simulator where we show that our rate allocation algorithm is able to properly optimize users' QoS and adapt to dynamic changes in the system. We also illustrate the benefits of our solution in terms network usage and average utility when compared to a baseline heuristic method operating on the same system architecture

Myelin is dependent on the Charcot-Marie-Tooth Type 4H disease culprit protein FRABIN/FGD4 in Schwann cells

Studying the function and malfunction of genes and proteins associated with inherited forms of peripheral neuropathies has provided multiple clues to our understanding of myelinated nerves in health and disease. Here, we have generated a mouse model for the peripheral neuropathy Charcot-Marie-Tooth disease type 4H by constitutively disrupting the mouse orthologue of the suspected culprit gene FGD4 that encodes the small RhoGTPase Cdc42-guanine nucleotide exchange factor Frabin. Lack of Frabin/Fgd4 causes dysmyelination in mice in early peripheral nerve development, followed by profound myelin abnormalities and demyelination at later stages. At the age of 60 weeks, this was accompanied by electrophysiological deficits. By crossing mice carrying alleles of Frabin/Fgd4 flanked by loxP sequences with animals expressing Cre recombinase in a cell type-specific manner, we show that Schwann cell-autonomous Frabin/Fgd4 function is essential for proper myelination without detectable primary contributions from neurons. Deletion of Frabin/Fgd4 in Schwann cells of fully myelinated nerve fibres revealed that this protein is not only required for correct nerve development but also for accurate myelin maintenance. Moreover, we established that correct activation of Cdc42 is dependent on Frabin/Fgd4 function in healthy peripheral nerves. Genetic disruption of Cdc42 in Schwann cells of adult myelinated nerves resulted in myelin alterations similar to those observed in Frabin/Fgd4-deficient mice, indicating that Cdc42 and the Frabin/Fgd4-Cdc42 axis are critical for myelin homeostasis. In line with known regulatory roles of Cdc42, we found that Frabin/Fgd4 regulates Schwann cell endocytosis, a process that is increasingly recognized as a relevant mechanism in peripheral nerve pathophysiology. Taken together, our results indicate that regulation of Cdc42 by Frabin/Fgd4 in Schwann cells is critical for the structure and function of the peripheral nervous system. In particular, this regulatory link is continuously required in adult fully myelinated nerve fibres. Thus, mechanisms regulated by Frabin/Fgd4-Cdc42 are promising targets that can help to identify additional regulators of myelin development and homeostasis, which may crucially contribute also to malfunctions in different types of peripheral neuropathie

The Gdap1 knockout mouse mechanistically links redox control to Charcot-Marie-Tooth disease

Mutations in the mitochondrial fission factor GDAP1 are associated with severe peripheral neuropathies, but why the CNS remains unaffected is unclear. Using a Gdap1−/− mouse, Niemann et al. demonstrate that a CNS-expressed Gdap1 paralogue changes its subcellular localisation under oxidative stress conditions to also act as a mitochondrial fission facto

Comparing apples and oranges: assessment of the relative video quality in the presence of different types of distortions

<p>Abstract</p> <p>Video quality assessment is essential for the performance analysis of visual communication applications. Objective metrics can be used for estimating the relative quality differences, but they typically give reliable results only if the compared videos contain similar types of quality distortion. However, video compression typically produces different kinds of visual artifacts than transmission errors. In this article, we focus on a novel subjective quality assessment method that is suitable for comparing different types of quality distortions. The proposed method has been used to evaluate how well different objective quality metrics estimate the relative subjective quality levels for content with different types of quality distortions. Our conclusion is that none of the studied objective metrics works reliably for assessing the co-impact of compression artifacts and transmission errors on the subjective quality. Nevertheless, we have observed that the objective metrics' tendency to either over- or underestimate the perceived impact of transmission errors has a high correlation with the spatial and temporal activity levels of the content. Therefore, our results can be useful for improving the performance of objective metrics in the presence of both source and channel distortions.</p