Take a Ramble into Solution Spaces for Classification Problems in Neural Networks

International audienc

Virulence exaltation of Clostridium perfringens strains from bovines

Ten out of eighty-nine strains biochemically identified as Clostridium perfringens, isolated from bovine organs, were selected by their different results showed in toxigenicity test on mice. Those and the standard strains, ATCC types A, B, C, and D, had their virulence exalted through serial intramuscular inoculation into guinea pigs. Results showed that, for toxigenic strains (6), one or two passages were enough to cause exaltation, while for the atoxigenic (4), five or six inoculations were needed. Esterase electrophoresis of standard and isolated strains, with and without exaltation, was performed. Electrophoresis analysis permits the following conclusions: strains that do not show any clinical symptoms in mice, when exalted demonstrate decreased esterase activity; on the contrary, it is increased when correlated with animal symptoms

Characterization of visual object representations in rat primary visual cortex

For most animal species, quick and reliable identification of visual objects is critical for survival. This applies also to rodents, which, in recent years, have become increasingly popular models of visual functions. For this reason in this work we analyzed how various properties of visual objects are represented in rat primary visual cortex (V1). The analysis has been carried out through supervised (classification) and unsupervised (clustering) learning methods. We assessed quantitatively the discrimination capabilities of V1 neurons by demonstrating how photometric properties (luminosity and object position in the scene) can be derived directly from the neuronal responses

MISTIC2: Comprehensive server to study coevolution in protein families

Correlated mutations between residue pairs in evolutionarily related proteins arise from constraints needed to maintain a functional and stable protein. Identifying these inter-related positions narrows down the search for structurally or functionally important sites. MISTIC is a server designed to assist users to calculate covariation in protein families and provide them with an interactive tool to visualize the results. Here, we present MISTIC2, an update to the previous server, that allows to calculate four covariation methods (MIp, mfDCA, plmDCA and gaussianDCA). The results visualization framework has been reworked for improved performance, compatibility and user experience. It includes a circos representation of the information contained in the alignment, an interactive covariation network, a 3D structure viewer and a sequence logo. Others components provide additional information such as residue annotations, a roc curve for assessing contact prediction, data tables and different ways of filtering the data and exporting figures. Comparison of different methods is easily done and scores combination is also possible. A newly implemented web service allows users to access MISTIC2 programmatically using an API to calculate covariation and retrieve results. MISTIC2 is available at: https://mistic2.leloir.org.ar.Fil: Colell, Eloy A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Iserte, Javier Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Marino Buslje, Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentin

Learning with a network of competing synapses

Competition between synapses arises in some forms of correlation-based plasticity. Here we propose a game theory-inspired model of synaptic interactions whose dynamics is driven by competition between synapses in their weak and strong states, which are characterized by different timescales. The learning of inputs and memory are meaningfully definable in an effective description of networked synaptic populations. We study, numerically and analytically, the dynamic responses of the effective system to various signal types, particularly with reference to an existing empirical motor adaptation model. The dependence of the system-level behavior on the synaptic parameters, and the signal strength, is brought out in a clear manner, thus illuminating issues such as those of optimal performance, and the functional role of multiple timescales.Comment: 16 pages, 9 figures; published in PLoS ON

The Spatial and Temporal Construction of Confidence in the Visual Scene

Human subjects can report many items of a cluttered field a few hundred milliseconds after stimulus presentation. This memory decays rapidly and after a second only 3 or 4 items can be stored in working memory. Here we compared the dynamics of objective performance with a measure of subjective report and we observed that 1) Objective performance beyond explicit subjective reports (blindsight) was significantly more pronounced within a short temporal interval and within specific locations of the visual field which were robust across sessions 2) High confidence errors (false beliefs) were largely confined to a small spatial window neighboring the cue. The size of this window did not change in time 3) Subjective confidence showed a moderate but consistent decrease with time, independent of all other experimental factors. Our study allowed us to asses quantitatively the temporal and spatial access to an objective response and to subjective reports

Probabilistic Computation in Human Perception under Variability in Encoding Precision

A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain’s remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making