In sensory processing of odors, the olfactory bulb is an important relay station, where odor representations are noise-filtered, sharpened, and possibly re-organized. An organization by perceptual qualities has been found previously in the piriform cortex, however several recent studies indicate that the olfactory bulb code reflects behaviorally relevant dimensions spatially as well as at the population level. We apply a statistical analysis on 2-deoxyglucose images, taken over the entire bulb of glomerular layer of the rat, in order to see how the recognition of odors in the nose is translated into a map of odor quality in the brain. We first confirm previous studies that the first principal component could be related to pleasantness, however the next higher principal components are not directly clear. We then find mostly continuous spatial representations for perceptual categories. We compare the space spanned by spatial and population codes to human reports of perceptual similarity between odors and our results suggest that perceptual categories could be already embedded in glomerular activations and that spatial representations give a better match than population codes. This suggests that human and rat perceptual dimensions of odorant coding are related and indicates that perceptual qualities could be represented as continuous spatial codes of the olfactory bulb glomerulus population.

Keywords: glomeruli,memory,odor quality,olfaction,olfactory bulb,organization,perception,population coding,spatial coding

The organization of representations in the brain has been observed to locally reflect subspaces of inputs that are relevant to behavioral or perceptual feature combinations, such as in areas receptive to lower and higher-order features in the visual system. The early olfactory system developed highly plastic mechanisms and convergent evidence indicates that projections from primary neurons converge onto the glomerular level of the olfactory bulb (OB) to form a code composed of continuous spatial zones that are differentially active for particular physico?-chemical feature combinations, some of which are known to trigger behavioral responses. In a model study of the early human olfactory system, we derive a glomerular organization based on a set of real-world, biologically-relevant stimuli, a distribution of receptors that respond each to a set of odorants of similar ranges of molecular properties, and a mechanism of axon guidance based on activity. Apart from demonstrating activity-dependent glomeruli formation and reproducing the relationship of glomerular recruitment with concentration, it is shown that glomerular responses reflect similarities of human odor category perceptions and that further, a spatial code provides a better correlation than a distributed population code. These results are consistent with evidence of functional compartmentalization in the OB and could suggest a function for the bulb in encoding of perceptual dimensions.

Keywords: axonal guidance,glomeruli,olfaction,olfactory bulb,olfactory coding,plasticity

The relationship between molecular properties of odorants and neural activities is arguably one of the most important issues in olfaction and the rules governing this relationship are still not clear. In the olfactory bulb (OB), glomeruli relay olfactory information to second-order neurons which in turn project to cortical areas. We investigate relevance of odorant properties, spatial localization of glomerular coding sites, and size of coding zones in a dataset of [(14)C] 2-deoxyglucose images of glomeruli over the entire OB of the rat. We relate molecular properties to activation of glomeruli in the OB using a non-parametric statistical test and a support-vector machine classification study. Our method permits to systematically map the topographic representation of various classes of odorants in the OB. Our results suggest many localized coding sites for particular molecular properties and some molecular properties that could form the basis for a spatial map of olfactory information. We found that alkynes, alkanes, alkenes, and amines affect activation maps very strongly as compared to other properties and that amines, sulfur-containing compounds, and alkynes have small zones and high relevance to activation changes, while aromatics, alkanes, and carboxylics acid recruit very big zones in the dataset. Results suggest a local spatial encoding for molecular properties.

Keywords: activity relation,activity relation-,glomeruli,odorants,olfactory bulb,olfactory coding,property

In this paper we propose a genetic al- gorithm that partitions data into a given number of clusters. The algorithm can use any cluster validity function as fitness function. Cluster validity is used as a criterion for cross-over operations. The cluster assignment for each point is accompanied by a tem- perature and points with low confidence are pref- erentially mutated. We present results applying this genetic algorithm to several UCI machine learning data sets and using several objective cluster validity functions for optimization. It is shown that given an appropriate criterion function, the algorithm is able to converge on good cluster partitions within few generations. Our main contributions are: 1. to present a genetic algorithm that is fast and able to converge on meaningful clusters for real-world data sets, 2. to define and compare several cluster validity criteria

Keywords: GA,clustering,clustering test suite,genetic algorithm,mutual information

In this paper we report on a study on feature selection within the minimum-redundancy maximum-relevance framework. Features are ranked by their correlations to the target vector. These relevance scores are then integrated with correlations between features in order to ob- tain a set of relevant and least-redundant features. Applied measures of correlation or distributional similarity for redundancy and relevance include Kolmogorov-Smirnov (KS) test, Spearman correlations, Jensen-Shannon divergence, and the sign-test. We introduce a metric called “value difference metric“ (VDM) and present a simple measure, which we call “fit criterion“ (FC). We draw conclusions about the usefulness of different measures. While KS-test and sign-test provided useful information, Spearman correlations are not fit for comparison of data of different measurement intervals. VDM was very good in our experiments as both redundancy and relevance measure. Jensen-Shannon and the sign-test are good redundancy measure alternatives and FC is a good relevance measure alternative.

Keywords: biomedical images,distributional simi-,divergence,divergence measure,feature extraction,feature selection,larity,measures of fit,redundancy,relevance,relevance and redundancy

The relationship between physicochemical properties of odor molecules and perceived odor quality is arguably one of the most important issues in olfaction and the rules governing this relationship remain unknown. Any given odor molecule will stimulate more than one type of receptor in the nose, perhaps hundreds, and this stimulation reflects itself in the neural code of the olfactory nervous system. We present a method to investigate neural coding at the glomerular level of the olfactory bulb, the first relay for olfactory processing in the brain. Our results give insights into localization of coding sites, relevance of odorant properties for information processing, and the size of coding zones.

Keywords: activity relationship,biomedical images,classification,glomeruli,nonpara-,odorants,olfactory bulb,olfactory coding,olfactory system,property

With the goal of deepen in the understanding of coding of chemical information in the olfactory system, a large data setconsisting of rat's olfactory bulb activity values in response toseveral different volatile compounds has been analyzed by fuzzy c-meansclustering methods. Clustering should help to discover groups of glomerulithat are similary activated according to their response profiles acrossthe odorants. To investigate the significance of the achieved fuzzypartitions we developed and applied a novel validity approach basedon cluster stability. Our results show certain level of glomerularclustering in the olfactory bulb and indicate that exist amain chemo-topic subdivision of the glomerular layer in few macro-areawhich are rather specific to particular functional groups of thevolatile molecules. ©2009 American Institute of Physics

Keywords: biomedical engineering,biomedical images,chemical sensors,clustering,fuzzy control,olfactory bulb,olfactory system,pattern recognition

A beowulf cluster is a cluster of Linux computers designed to run computing jobs in parallel. This article is going to give an up-to date example of assembled hardware, and installed programs (plus configuration). Finally there will be explanations of how to run processes in parallel in computing languages such as matlab and R. After the computers are setup we may want to transfer the configuration to other computers, a process which is called cloning. In the last section, we will deal with profiling.

Keywords: beowulf,compute cluster,linux

We study filter-based feature selection methods for classification of biomedical images. For feature selection, we use two filters - a relevance filter which measures usefulness of individual features for target prediction, and a redundancy filter, which measures similarity between features. As selection method that combines relevance and redundancy we try out a Hopfield network. We experimentally compare selection methods, running unitary redundancy and relevance filters, against a greedy algorithm with redundancy thresholds [9], the min-redundancy max-relevance integration [8,23,36], and our Hopfield network selection. We conclude that on the whole, Hopfield selection was one of the most successful methods, outperforming min-redundancy max-relevance when more features are selected.

Keywords: feature selection,image features,pattern classification

In university programming classes often hundreds of students participate having to solve each hundreds of programming assignments a situation which puts instructors to the difficult task of validating hundreds of programming assignments. We present a framework that can help instructors and students in organization and validation of program code. Our “System for Automated Assistance in Correction of Programming Exercises“ (short: SAC) is a web-platform for test-driven development and automated validation. The web-platform is based on Java Server Pages technology with tomcat as servlet container, and allows teachers to specify and define program exercises and students to upload their solutions. Students can get immediate feedback on the validity of their code and both instructors and students can see statistics about each programming assignment. We explain our platform and propose how the automatic validation can be extended.

Keywords: assignment management system,automated evalutation,computer aided assessment,computer science,source code evaluation,teaching support,web platform

Spectral clustering is a powerful technique in data analysis that has found increasing support and application in many areas. This report is geared to give an introduction to its methods, presenting the most common algorithms, discussing advantages and disadvantages of each, rather than endorsing one of them as the best, because, arguably, there is no black-box algorithm, which performs equally well for any data. We present results from previous studies and conclude that methods based on Ncut and multiway are most promising for general application.

Keywords: clustering,graph clustering,spectral clustering

Image processing of natural scenes is very processing-intensive. Through the localization of salient regions, later recognition processes can take place more efficiently by focusing computation-intensive processing on several areas. Our approach to designing an artificial visual system is inspired by early filtering mechanisms in the human visual system. Our technique of calculating salient regions is computationally efficient and flexible, and can be extended to other applications.

Keywords: autonomous robots,feature maps,vision