The green infrastructure of a highly-urbanized neotropical city : the role of the urban vegetation in preserving native biodiversity

The composition of the urban vegetation that comprises the green infrastructure of a highly urbanized Neotropical city was mapped and described in order to assess how it can be used to preserve and maintain urban biodiversity. Supervised classification was used, followed by Map Algebra methodology, to identify the elements that comprise the green infrastructure of the southern region of Belo Horizonte (Minas Gerais, Brazil). Species composition of the street trees community was also assessed. Almost half of the study area is occupied by 12 types of woody and herbaceous vegetation, composed mostly by urban parks and gardens. Forty-one percent of the almost 90,000 street trees is composed by 10 species from which only four are native. These results show that the green infrastructure of this urban landscape is comprised by a large amount of different types of green elements, and has a great potential for biodiversity conservation. However, management strategies are needed such as better planning of the urban afforestation process, increasing street tree species richness. This study is the first step towards a better understanding of how such urban landscape influences local biodiversity

Dissociable Modulation of Overt Visual Attention in Valence and Arousal Revealed by Topology of Scan Path

Emotional stimuli have evolutionary significance for the survival of organisms; therefore, they are attention-grabbing and are processed preferentially. The neural underpinnings of two principle emotional dimensions in affective space, valence (degree of pleasantness) and arousal (intensity of evoked emotion), have been shown to be dissociable in the olfactory, gustatory and memory systems. However, the separable roles of valence and arousal in scene perception are poorly understood. In this study, we asked how these two emotional dimensions modulate overt visual attention. Twenty-two healthy volunteers freely viewed images from the International Affective Picture System (IAPS) that were graded for affective levels of valence and arousal (high, medium, and low). Subjects' heads were immobilized and eye movements were recorded by camera to track overt shifts of visual attention. Algebraic graph-based approaches were introduced to model scan paths as weighted undirected path graphs, generating global topology metrics that characterize the algebraic connectivity of scan paths. Our data suggest that human subjects show different scanning patterns to stimuli with different affective ratings. Valence salient stimuli (with neutral arousal) elicited faster and larger shifts of attention, while arousal salient stimuli (with neutral valence) elicited local scanning, dense attention allocation and deep processing. Furthermore, our model revealed that the modulatory effect of valence was linearly related to the valence level, whereas the relation between the modulatory effect and the level of arousal was nonlinear. Hence, visual attention seems to be modulated by mechanisms that are separate for valence and arousal

Classification of Types of Stuttering Symptoms Based on Brain Activity

Among the non-fluencies seen in speech, some are more typical (MT) of stuttering speakers, whereas others are less typical (LT) and are common to both stuttering and fluent speakers. No neuroimaging work has evaluated the neural basis for grouping these symptom types. Another long-debated issue is which type (LT, MT) whole-word repetitions (WWR) should be placed in. In this study, a sentence completion task was performed by twenty stuttering patients who were scanned using an event-related design. This task elicited stuttering in these patients. Each stuttered trial from each patient was sorted into the MT or LT types with WWR put aside. Pattern classification was employed to train a patient-specific single trial model to automatically classify each trial as MT or LT using the corresponding fMRI data. This model was then validated by using test data that were independent of the training data. In a subsequent analysis, the classification model, just established, was used to determine which type the WWR should be placed in. The results showed that the LT and the MT could be separated with high accuracy based on their brain activity. The brain regions that made most contribution to the separation of the types were: the left inferior frontal cortex and bilateral precuneus, both of which showed higher activity in the MT than in the LT; and the left putamen and right cerebellum which showed the opposite activity pattern. The results also showed that the brain activity for WWR was more similar to that of the LT and fluent speech than to that of the MT. These findings provide a neurological basis for separating the MT and the LT types, and support the widely-used MT/LT symptom grouping scheme. In addition, WWR play a similar role as the LT, and thus should be placed in the LT type

Parasite fate and involvement of infected cells in the induction of CD4+ and CD8+ T cell responses to Toxoplasma gondii

During infection with the intracellular parasite Toxoplasma gondii, the presentation of parasite-derived antigens to CD4+ and CD8+ T cells is essential for long-term resistance to this pathogen. Fundamental questions remain regarding the roles of phagocytosis and active invasion in the events that lead to the processing and presentation of parasite antigens. To understand the most proximal events in this process, an attenuated non-replicating strain of T. gondii (the cpsII strain) was combined with a cytometry-based approach to distinguish active invasion from phagocytic uptake. In vivo studies revealed that T. gondii disproportionately infected dendritic cells and macrophages, and that infected dendritic cells and macrophages displayed an activated phenotype characterized by enhanced levels of CD86 compared to cells that had phagocytosed the parasite, thus suggesting a role for these cells in priming naïve T cells. Indeed, dendritic cells were required for optimal CD4+ and CD8+ T cell responses, and the phagocytosis of heat-killed or invasion-blocked parasites was not sufficient to induce T cell responses. Rather, the selective transfer of cpsII-infected dendritic cells or macrophages (but not those that had phagocytosed the parasite) to naïve mice potently induced CD4+ and CD8+ T cell responses, and conferred protection against challenge with virulent T. gondii. Collectively, these results point toward a critical role for actively infected host cells in initiating T. gondii-specific CD4+ and CD8+ T cell responses

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

Television and food in the lives of young children

Several mechanisms have been proposed behind the associations between screens and overweight including sedentary behaviour, eating while viewing, and exposure to commercials. Aspects of this association as underlying social factors and the possible confounding factors of social norms in the family that can affect children’s lifestyle have received less attention. TV commercials for food and beverages have been extensively studied and it is important to study the appearance of food in children’s TV programmes in a similar way. The general aim of this thesis is to examine the associations between young children’s screen habits, food habits and anthropometry as well as to analyse food and beverages in children’s television programmes in public service television in Sweden. Data from the European research project Identification and prevention of dietary and lifestyle-induced health effects in children and infants (IDEFICS) has been used in Papers I-III and 25 hours of children’s TV programmes have been analysed for Paper IV. The main findings indicate that children’s TV viewing and total screen time was found to be associated with their increased sweet drink consumption, BMI and waist to height ratio, according to cross-sectional and longitudinal analyses. The association between TV viewing and sweetened beverage consumption was found to be independent of parental norms regarding sweetened beverages. Exposure to commercial TV was associated with consuming sweetened beverages more frequently independently of TV viewing time. One in five foods appearing in the sample of children’s TV programmes was for high-calorie and low-nutrient foods, often appearing with children. The results indicate that it is possible to affect children’s food habits by influencing their TV habits, and that public service television has the potential to improve the way food and eating are depicted in children’s TV programmes