Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

An ergonomic approach to reorganize parking inspection agents` work productivity, health and safety in Sao Paulo, Brazil

Objective: The Traffic Engineering Company of the City of Sao Paulo (Brazil) observed a decrease in productivity, and an increase in sick leave, accidents and psychological distress among their parking inspection agents. To document this situation, qualitative research was undertaken to obtain an in-depth comprehension of work activity. Participants: Workers, managers and health and safety professionals contributed to the documentation of the problem and to the proposal of possible solutions. Methods: Ergonomic work analysis focusing on real work activity, as well as interviews with individual or groups of stakeholders, were conducted. Results: This research revealed that political-economic factors gradually contributed to: 1) an increasing work load; 2) growing fatigue throughout the day, increasing the workers` vulnerability to incidents and accidents and their tendency to react inappropriately to violence experienced on the street; and 3) excessive individual responsibility to manage dangerous situations. Conclusions: Recommendations to ameliorate the situation are proposed. These suggestions are discussed in terms of feasibility given the impact of macro social factors upon micro work activity, and the associated potential expansion of the ergonomist`s role.

Proton transport model in the ionosphere .1. Multistream approach of the transport equations

The suprathermal particles, electrons and protons, coming from the magnetosphere and precipitating into the high-latitude atmosphere are an energy source of the Earth's ionosphere. They interact with ambient thermal gas through inelastic and elastic collisions. The physical quantities perturbed by these precipitations, such as the heating rate, the electron production rate, or the emission intensities, can be provided in solving the kinetic stationary Boltzmann equation. This equation yields particle fluxes as a function of altitude, energy, and pitch angle. While this equation has been solved through different ways for the electron transport and fully tested, the proton transport is more complicated. Because of charge-changing reactions, the latter is a set of two-coupled transport equations that must be solved: one for protons and the other for H atoms. We present here a new approach that solves the multistream proton/hydrogen transport equations encompassing the collision angular redistributions and the magnetic mirroring effect. In order to validate our model we discuss the energy conservation and we compare with another model under the same inputs and with rocket observations. The influence of the angular redistributions is discussed in a forthcoming paper.

Cue exposure in moderation drinking: A comparison with cognitive-behavior therapy

To date, the published controlled trials on exposure to alcohol cues have had an abstinence treatment goal. A modification of cue exposure (CE) for moderation drinking, which incorporated priming doses of alcohol, could train participants to stop drinking after 2 to 3 drinks. This study examined the effects of modified CE within sessions, combined with directed homework practice. Nondependent problem drinkers who requested a moderation drinking goal were randomly allocated to modified CE or standard cognitive-behavior therapy (CBT) for alcohol abuse. Both interventions were delivered in 6 90-min group sessions. Eighty-one percent of eligible participants completed treatment and follow-up assessment. Over 6 months, CE produced significantly greater reductions than CBT in participants' reports of drinking frequency and consumption on each occasion. No pretreatment variables significantly predicted outcome, The modified CE procedure appears viable for nondependent drinkers who want to adopt a moderate drinking goal.

Latent inhibition and autonomic responses: a psychophysiological approach

Latent inhibition, retarded learning after preexposure to the to-be-conditioned stimulus, has been implied as a tool for the investigation of attentional deficits in schizophrenia and related disorders. The present paper reviews research that used Pavlovian conditioning as indexed by autonomic responses (electrodermal, vasomotor, cardiac) to investigate latent inhibition in adult humans. Latent inhibition has been demonstrated repeatedly in healthy subjects in absence of a masking task that is required in other latent inhibition paradigms. Moreover, latent inhibition of Pavlovian conditioning is stimulus-specific and increases with an increased number of preexposure trials which mirrors results from research in animals. A reduction of latent inhibition has been shown in healthy subjects who score high on questionnaire measures of psychosis proneness and in unmedicated schizophrenic patients. The latter result was obtained in a within-subject paradigm that holds promise for research with patient samples. (C) 1997 Elsevier Science B.V.

A semi-empirical approach to optimise the quantity of drying aids required to spray dry sugar-rich foods

A semi-empirical linear equation has been developed to optimise the amount of maltodextrin additive (DE 6) required to successfully spray dry a sugar-rich product on the basis of its composition. Based on spray drying experiments, drying index values for individual sugars (sucrose, glucose, frutose) and citric acid were determined, and us;ng these index values an equation for model mixtures of these components was established. This equation has been tested with two sugar-rich natural products, pineapple juice and honey. The relationship was found to be valid for these products.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Further evidences on a new diagnostic approach for monitoring human Leishmania (L.) infantum chagasi infection in Amazonian Brazil

This was a prospective study carried out during a period over 2 years (May/2006-September/2008) with a cohort of 1,099 individuals of both genders, aged 1 year old and older, from an endemic area of American visceral leishmaniasis (AVL) in Para state, Brazil. The object was to analyze the prevalence and incidence of human Leishmania (L.) infantum chagasi infection as well as the dynamics evolution of its clinical-immunological profiles prior identified: (1) asymptomatic infection (AI); (2) symptomatic infection (SI = AVL); (3) sub-clinical oligosymptomatic infection (SOI); (4) sub-clinical resistant infection (SRI) and; (5) indeterminate initial infection (III). The infection diagnosis was performed by using both the indirect fluorescent antibody test and leishmanin skin test with amastigotes and promastigotes antigens of L. (L.) i. chagasi, respectively. A total of 187 cases of infection were recorded in the prevalence (17%), 117 in the final incidence (6.9%), and 304 in the accumulated prevalence (26.7%), which provided the following distribution into the clinical-immunological profiles: AI, 51.6%; III, 22.4%; SRI, 20.1%; SOI, 4.3%; and SI (=AVL), 1.6%. The major finding regarding the dynamics evolution of infection was concerned to III profile, from which the cases of infection evolved to either the resistant profiles, SRI (21 cases, 30.8%) and AI (30 cases, 44.1%), or the susceptible SI (=AVL; 1 case, 1.5%); the latter 16 cases remained as III till the end of the study. These results provided the conclusion that this diagnostic approach may be useful for monitoring human L. (L.) i. chagasi infection in endemic area and preventing the high morbidity of severe AVL cases.

A practical approach to assess depression risk and to guide risk reduction strategies in later life

Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.

Circulating levels of brain-derived neurotrophic factor: correlation with mood, cognition and motor function

Brain-derived neurotrophic factor (BDNF) is the most widely distributed neurotrophin in the CNS, where it plays several pivotal roles in synaptic plasticity and neuronal survival. As a consequence, BDNF has become a key target in the physiopathology of several neurological and psychiatric diseases. Recent studies have consistently reported altered levels of BDNF in the circulation (i.e., serum or plasma) of patients with major depression, bipolar disorder, Alzheimer`s disease, Huntington`s disease and Parkinson`s disease. Correlations between serum BDNF levels and affective, cognitive and motor symptoms have also been described. BDNF appears to be an unspecific biomarker of neuropsychiatric disorders characterized by neurodegenerative changes.