Bump time-frequency toolbox: a toolbox for time-frequency oscillatory bursts extraction in electrophysiological signals

Background: oscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies. Oscillatory burst events should consequently play a specific functional role, distinct from background EEG activity – especially for cognitive tasks (e.g. working memory tasks), binding mechanisms and perceptual dynamics (e.g. visual binding), or in clinical contexts (e.g. effects of brain disorders). However extracting oscillatory events in single trials, with a reliable and consistent method, is not a simple task. Results: in this work we propose a user-friendly stand-alone toolbox, which models in a reasonable time a bump time-frequency model from the wavelet representations of a set of signals. The software is provided with a Matlab toolbox which can compute wavelet representations before calling automatically the stand-alone application. Conclusion: The tool is publicly available as a freeware at the address: http:// www.bsp.brain.riken.jp/bumptoolbox/toolbox_home.html

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Repurposing Social Tagging Data for Extraction of Domain-level Concepts

The World Wide Web, the world¿s largest resource for information, has evolved from organizing information using controlled, top-down taxonomies to a bottom up approach that emphasizes assigning meaning to data via mechanisms such as the Social Web (Web 2.0). Tagging adds meta-data, (weak semantics) to the content available on the web. This research investigates the potential for repurposing this layer of meta-data. We propose a multi-phase approach that exploits user-defined tags to identify and extract domain-level concepts. We operationalize this approach and assess its feasibility by application to a publicly available tag repository. The paper describes insights gained from implementing and applying the heuristics contained in the approach, as well as challenges and implications of repurposing tags for extraction of domain-level concepts.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Bioinspired electronic white cane implementation based on a LIDAR, a tri-axial accelerometer and a tactile belt

This work proposes the creation of a bioinspired electronic white cane for blind people using the whiskers principle for short-range navigation and exploration. Whiskers are coarse hairs of an animal's face that tells the animal that it has touched something using the nerves of the skin. In this work the raw data acquired from a low-size terrestrial LIDAR and a tri-axial accelerometer is converted into tactile information using several electromagnetic devices configured as a tactile belt. The LIDAR and the accelerometer are attached to the user’s forearm and connected with a wire to the control unit placed on the belt. Early validation experiments carried out in the laboratory are promising in terms of usability and description of the environment.

Evaluation of the indication for surgical extraction of third molars according to the oral surgeon and the primary care dentist. Experience in the Master of Oral Surgery and Implantology at Barcelona University Dental School

Introduction: Third molar extraction is the most frequent procedure in oral surgery. The present study evaluates the indication of third molar extraction as established by the primary care dentist (PCD) and the oral surgeon, and compares the justification for extraction with the principal reason for patient consultation. Patients and method: A descriptive study was made of 319 patients subjected to surgical removal of a third molar in the context of the Master of Oral Surgery and Implantology (Barcelona University Dental School, Barcelona, Spain) between July 2004 and March 2005. The following parameters were evaluated: sex, age, molar, type of impaction, position according to the classifications of Pell and Gregory and of Winter, and the reasons justifying extraction. Results: The lower third molars were the most commonly extracted molars (73.7%). A total of 69.6% of the teeth were covered by soft tissues only. Fifty-six percent of the lower molars corresponded to Pell and Gregory Class IIB, while 42.1% were in the vertical position. The most common reason for patient reference to our Service of Oral Surgery on the part of the PCD was prophylactic removal (51.0% versus 46.1% in the case of the oral surgeon). Discussion and conclusions. Our results show prophylaxis to be the principal indication of third molar extraction, followed by orthodontic reasons. Regarding third molars with associated clinical symptoms or signs, infectious disease-including pericoronitis- was the pathology most often observed by the oral surgeon, followed by caries. This order of frequency was seen to invert in the case of third molars referred for extraction by the PCD. A vertical position predominated among the third molars with associated pathology

Social network extraction and analysis based on multimodal dyadic interaction

Social interactions are a very important component in people"s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times" Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links" weights are a measure of the"influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

Features extraction based on the Discrete Hartley Transform for closed contour

In this paper the authors propose a new closed contour descriptor that could be seen as a Feature Extractor of closed contours based on the Discrete Hartley Transform (DHT), its main characteristic is that uses only half of the coefficients required by Elliptical Fourier Descriptors (EFD) to obtain a contour approximation with similar error measure. The proposed closed contour descriptor provides an excellent capability of information compression useful for a great number of AI applications. Moreover it can provide scale, position and rotation invariance, and last but not least it has the advantage that both the parameterization and the reconstructed shape from the compressed set can be computed very efficiently by the fast Discrete Hartley Transform (DHT) algorithm. This Feature Extractor could be useful when the application claims for reversible features and when the user needs and easy measure of the quality for a given level of compression, scalable from low to very high quality.

Effect of diet composition and ration size on key enzyme activities of glycolysis-gluconeogenesis, pentose phosphate pathway and amino acid metabolism in liver of Sparus aurata

The effects of diet composition and ration size on the activities of key enzymes involved in intermediary metabolism were studied in the liver of gilthead sea bream (Sparus aurata). Highcarbohydrate, low-protein diets stimulated 6-phosphofructo 1-kinase (EC 2.7.1.11), pyruvate kinase (EC 2.7.1.40), glucose-6-phosphate dehydrogenase (EC 1.1.1.49) and 6-phosphogluconate dehydrogenase (EC 1.1.1.44) enzyme activities, while they decreased alanine aminotransferase (EC 2.6.1.2) activity. A high degree of correlation was found between food ration size and the activity of the enzymes 6-phosphofructo 1-kinase, pyruvate kinase, glucose-6-phosphate dehydrogenase (positive correlations) and fructose-1,6-bisphosphatase (EC 3.1.3.11) (negative correlation). These correlations matched well with the high correlation also found between ration size and growth rate in starved fish refed for 22 d. Limited feeding (5 g/kg body weight) for 22 d decreased the activities of the key enzymes for glycolysis and lipogenesis, and alanine aminotransferase activity. The findings presented here indicate a high level of metabolic adaptation to both diet type and ration size. In particular, adaptation of enzyme activities to the consumption of a diet with a high carbohydrate level suggests that a carnivorous fish like Sparus aurata can tolerate partial replacement of protein by carbohydrate in the commercial diets supplied in culture. The relationship between enzyme activities, ration size and fish growth indicates that the enzymes quickly respond to dietary manipulations of cultured fish.

Effect of diet composition and ration size on key enzyme activities of glycolysis-gluconeogenesis, pentose phosphate pathway and amino acid metabolism in liver of Sparus aurata

The effects of diet composition and ration size on the activities of key enzymes involved in intermediary metabolism were studied in the liver of gilthead sea bream (Sparus aurata). Highcarbohydrate, low-protein diets stimulated 6-phosphofructo 1-kinase (EC 2.7.1.11), pyruvate kinase (EC 2.7.1.40), glucose-6-phosphate dehydrogenase (EC 1.1.1.49) and 6-phosphogluconate dehydrogenase (EC 1.1.1.44) enzyme activities, while they decreased alanine aminotransferase (EC 2.6.1.2) activity. A high degree of correlation was found between food ration size and the activity of the enzymes 6-phosphofructo 1-kinase, pyruvate kinase, glucose-6-phosphate dehydrogenase (positive correlations) and fructose-1,6-bisphosphatase (EC 3.1.3.11) (negative correlation). These correlations matched well with the high correlation also found between ration size and growth rate in starved fish refed for 22 d. Limited feeding (5 g/kg body weight) for 22 d decreased the activities of the key enzymes for glycolysis and lipogenesis, and alanine aminotransferase activity. The findings presented here indicate a high level of metabolic adaptation to both diet type and ration size. In particular, adaptation of enzyme activities to the consumption of a diet with a high carbohydrate level suggests that a carnivorous fish like Sparus aurata can tolerate partial replacement of protein by carbohydrate in the commercial diets supplied in culture. The relationship between enzyme activities, ration size and fish growth indicates that the enzymes quickly respond to dietary manipulations of cultured fish.

Sharp mandibular bone irregularities after lower third molar extraction: Incidence, clinical features and risk factors

Objectives: The purpose of this study was to determine the incidence and clinical symptoms associated with sharp mandibular bone irregularities (SMBI) after lower third molar extraction and to identify possible risk factors for this complication. Study Design: A mixed study design was used. A retrospective cohort study of 1432 lower third molar extractions was done to determine the incidence of SMBI and a retrospective case-control study was done to determine potential demographic and etiologic factors by comparing those patients with postoperative SMBI with controls. Results: Twelve SMBI were found (0.84%). Age was the most important risk factor for this complication. The operated side and the presence of an associated radiolucent image were also significantly related to the development of mandibular bone irregularities. The depth of impaction of the tooth might also be an important factor since erupted or nearly erupted third molars were more frequent in the SMBI group. Conclusions: SMBI are a rare postoperative complication after lower third molar removal. Older patients having left side lower third molars removed are more likely to develop this problem. The treatment should be the removal of the irregularity when the patient is symptomatic

Interactions of bacteria and fungi on decomposing litter: differential extracellular enzyme activities

Fungi and bacteria are key agents in plant litter decomposition in freshwater ecosystems. However, the specific roles of these two groups and their interactions during the decomposition process are unclear. We compared the growth and patterns of degradativeenzymes expressed by communities of bacteria and fungi grown separately and in coexistence on Phragmites leaves. The two groups displayed both synergistic and antagonistic interactions. Bacteria grew better together with fungi than alone. In addition, there was a negative effect of bacteria on fungi, which appeared to be caused by suppression of fungal growth and biomass accrual rather than specifically affecting enzyme activity. Fungi growing alone had a high capacity for the decomposition of plant polymers such as lignin, cellulose, and hemicellulose. In contrast, enzyme activities were in general low when bacteria grew alone, and the activity of key enzymes in the degradation of lignin and cellulose (phenol oxidase and cellobiohydrolase) was undetectable in the bacteria-only treatment. Still, biomass-specific activities of most enzymes were higher in bacteria than in fungi. The low total activity and growth of bacteria in the absence of fungi in spite of apparent high enzymatic efficiency during the degradation of many substrates suggest that fungi provide the bacteria with resources that the bacteria were not able to acquire on their own, most probably intermediate decomposition products released by fungi that could be used by bacteria

Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.