993 resultados para Spatial behavior
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Generalizing the dynamic field theory of spatial cognition across real and developmental time scales
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Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.
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Contamination by butyltin compounds (BTs) has been reported in estuarine environments worldwide, with serious impacts on the biota of these areas. Considering that BTs can be degraded by varying environmental conditions such as incident light and salinity, the short-term variations in such factors may lead to inaccurate estimates of BTs concentrations in nature. Therefore, the present study aimed to evaluate the possibility that measurements of BTs in estuarine sediments are influenced by different sampling conditions, including period of the day (day or night), tidal zone (intertidal or subtidal), and tides (high or low). The study area is located on the Brazilian southeastern coast, Sao Vicente Estuary, at Pescadores Beach, where BT contamination was previously detected. Three replicate samples of surface sediment were collected randomly in each combination of period of the day, tidal zone, and tide condition, from three subareas along the beach, totaling 72 samples. BTs were analyzed by GC-PFPD using a tin filter and a VF-5 column, by means of a validated method. The concentrations of tributyltin (TBT), dibutyltin (DBT), and monobutyltin (MBT) ranged from undetectable to 161 ng Sn g(-1) (d.w.). In most samples (71%), only MBT was quantifiable, whereas TBTs were measured in only 14, suggesting either an old contamination or rapid degradation processes. DBT was found in 27 samples, but could be quantified in only one. MBT concentrations did not differ significantly with time of day, zones, or tide conditions. DBT and TBT could not be compared under all these environmental conditions, because only a few samples were above the quantification limit. Pooled samples of TBT did not reveal any difference between day and night. These results indicated that, in assessing contamination by butyltin compounds, surface-sediment samples can be collected in any environmental conditions. However, the wide variation of BTs concentrations in the study area, i.e., over a very small geographic scale, illustrates the need for representative hierarchical and composite sampling designs that are compatible with the multiscalar temporal and spatial variability common to most marine systems. The use of such sampling designs will be necessary for future attempts to quantitatively evaluate and monitor the occurrence and impact of these compounds in nature
Spatial reference of black capuchin monkeys in Brazilian Atlantic Forest: egocentric or allocentric?
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Wild primates occupy large home ranges and travel long distances to reach goals. However, how primates are able to remember goal locations and travel efficiently is unclear. Few studies present consistent results regarding what reference system primates use to navigate, and what kind of spatial information they recognize. We analysed the pattern of navigation of one wild group of black capuchin monkeys, Cebus nigritus, at Atlantic Forest for 100 days in Carlos Botelho State Park (PECB), Brazil. We tested predictions based on the alternative hypotheses that black capuchin monkeys navigate using a sequence of landmarks as an egocentric reference system or an allocentric reference system, or both, depending on availability of food resources. The group location was recorded using a GPS device collecting coordinates at 5 min intervals, and route maps were generated using ArcView v9.3.1. The study group travelled through habitual routes during less than 30% of our study sample, and revisited resources from different starting points, using different paths and routes, even when prominent landmarks near feeding locations were not visible. The study group used habitual routes more frequently when high-quality foods were scarce, and navigated using different paths when revisiting food sources. Results support the hypothesis that black capuchin monkeys at PECB navigate using both egocentric and allocentric systems of reference, depending on the quality and distribution of the food resource they find. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.
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How do capuchin monkeys learn to use stones to crack open nuts? Perception-action theory posits that individuals explore producing varying spatial and force relations among objects and surfaces, thereby learning about affordances of such relations and how to produce them. Such learning supports the discovery of tool use. We present longitudinal developmental data from semifree-ranging tufted capuchin monkeys (Cebus apella) to evaluate predictions arising from Perception-action theory linking manipulative development and the onset of tool-using. Percussive actions bringing an object into contact with a surface appeared within the first year of life. Most infants readily struck nuts and other objects against stones or other surfaces from 6 months of age, but percussive actions alone were not sufficient to produce nut-cracking sequences. Placing the nut on the anvil surface and then releasing it, so that it could be struck with a stone, was the last element necessary for nut-cracking to appear in capuchins. Young chimpanzees may face a different challenge in learning to crack nuts: they readily place objects on surfaces and release them, but rarely vigorously strike objects against surfaces or other objects. Thus the challenges facing the two species in developing the same behavior (nut-cracking using a stone hammer and an anvil) may be quite different. Capuchins must inhibit a strong bias to hold nuts so that they can release them; chimpanzees must generate a percussive action rather than a gentle placing action. Generating the right actions may be as challenging as achieving the right sequence of actions in both species. Our analysis suggests a new direction for studies of social influence on young primates learning sequences of actions involving manipulation of objects in relation to surfaces.
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In this work, we employ renormalization group methods to study the general behavior of field theories possessing anisotropic scaling in the spacetime variables. The Lorentz symmetry breaking that accompanies these models are either soft, if no higher spatial derivative is present, or it may have a more complex structure if higher spatial derivatives are also included. Both situations are discussed in models with only scalar fields and also in models with fermions as a Yukawa-like model.
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Clinical and experimental evidence suggest that estrogens have a major impact on cognition, presenting neurotrophic and neuroprotective actions in regions involved in such function. In opposite, some studies indicate that certain hormone therapy regimens may provoke detrimental effects over female cognitive and neurological function. Therefore, we decided to investigate how estrogen treatment would influence cognition and depression in different ages. For that matter, this study assessed the effects of chronic 17 beta-estradiol treatment over cognition and depressive-like behaviors of young (3 months old), adult (7 months old) and middle-aged (12 months old) reproductive female Wistar rats. These functions were also correlated with alterations in the serotonergic system, as well as hippocampal BDNF. 17 beta-Estradiol treatment did not influence animals' locomotor activity and exploratory behavior, but it was able to improve the performance of adult and middle-aged rats in the Morris water maze, the latter being more responsive to the treatment. Young and adult rats displayed decreased immobility time in the forced swimming test, suggesting an effect of 17 beta-estradiol also over such depressive-like behavior. This same test revealed increased swimming behavior, triggered by serotonergic pathway, in adult rats. Neurochemical evaluations indicated that 17 beta-estradiol treatment was able to increase serotonin turnover rate in the hippocampus of adult rats. Interestingly, estrogen treatment increased BDNF levels from animals of all ages. These findings support the notion that the beneficial effects of 17 beta-estradiol over spatial reference memory and depressive-like behavior are evident only when hormone therapy occurs at early ages and early stages of hormonal decline. (C) 2011 Elsevier B.V. All rights reserved.
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Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.
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Synthetic Biology is a relatively new discipline, born at the beginning of the New Millennium, that brings the typical engineering approach (abstraction, modularity and standardization) to biotechnology. These principles aim to tame the extreme complexity of the various components and aid the construction of artificial biological systems with specific functions, usually by means of synthetic genetic circuits implemented in bacteria or simple eukaryotes like yeast. The cell becomes a programmable machine and its low-level programming language is made of strings of DNA. This work was performed in collaboration with researchers of the Department of Electrical Engineering of the University of Washington in Seattle and also with a student of the Corso di Laurea Magistrale in Ingegneria Biomedica at the University of Bologna: Marilisa Cortesi. During the collaboration I contributed to a Synthetic Biology project already started in the Klavins Laboratory. In particular, I modeled and subsequently simulated a synthetic genetic circuit that was ideated for the implementation of a multicelled behavior in a growing bacterial microcolony. In the first chapter the foundations of molecular biology are introduced: structure of the nucleic acids, transcription, translation and methods to regulate gene expression. An introduction to Synthetic Biology completes the section. In the second chapter is described the synthetic genetic circuit that was conceived to make spontaneously emerge, from an isogenic microcolony of bacteria, two different groups of cells, termed leaders and followers. The circuit exploits the intrinsic stochasticity of gene expression and intercellular communication via small molecules to break the symmetry in the phenotype of the microcolony. The four modules of the circuit (coin flipper, sender, receiver and follower) and their interactions are then illustrated. In the third chapter is derived the mathematical representation of the various components of the circuit and the several simplifying assumptions are made explicit. Transcription and translation are modeled as a single step and gene expression is function of the intracellular concentration of the various transcription factors that act on the different promoters of the circuit. A list of the various parameters and a justification for their value closes the chapter. In the fourth chapter are described the main characteristics of the gro simulation environment, developed by the Self Organizing Systems Laboratory of the University of Washington. Then, a sensitivity analysis performed to pinpoint the desirable characteristics of the various genetic components is detailed. The sensitivity analysis makes use of a cost function that is based on the fraction of cells in each one of the different possible states at the end of the simulation and the wanted outcome. Thanks to a particular kind of scatter plot, the parameters are ranked. Starting from an initial condition in which all the parameters assume their nominal value, the ranking suggest which parameter to tune in order to reach the goal. Obtaining a microcolony in which almost all the cells are in the follower state and only a few in the leader state seems to be the most difficult task. A small number of leader cells struggle to produce enough signal to turn the rest of the microcolony in the follower state. It is possible to obtain a microcolony in which the majority of cells are followers by increasing as much as possible the production of signal. Reaching the goal of a microcolony that is split in half between leaders and followers is comparatively easy. The best strategy seems to be increasing slightly the production of the enzyme. To end up with a majority of leaders, instead, it is advisable to increase the basal expression of the coin flipper module. At the end of the chapter, a possible future application of the leader election circuit, the spontaneous formation of spatial patterns in a microcolony, is modeled with the finite state machine formalism. The gro simulations provide insights into the genetic components that are needed to implement the behavior. In particular, since both the examples of pattern formation rely on a local version of Leader Election, a short-range communication system is essential. Moreover, new synthetic components that allow to reliably downregulate the growth rate in specific cells without side effects need to be developed. In the appendix are listed the gro code utilized to simulate the model of the circuit, a script in the Python programming language that was used to split the simulations on a Linux cluster and the Matlab code developed to analyze the data.
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A broad variety of solid state NMR techniques were used to investigate the chain dynamics in several polyethylene (PE) samples, including ultrahigh molecular weight PEs (UHMW-PEs) and low molecular weight PEs (LMW-PEs). Via changing the processing history, i.e. melt/solution crystallization and drawing processes, these samples gain different morphologies, leading to different molecular dynamics. Due to the long chain nature, the molecular dynamics of polyethylene can be distinguished in local fluctuation and long range motion. With the help of NMR these different kinds of molecular dynamics can be monitored separately. In this work the local chain dynamics in non-crystalline regions of polyethylene samples was investigated via measuring 1H-13C heteronuclear dipolar coupling and 13C chemical shift anisotropy (CSA). By analyzing the motionally averaged 1H-13C heteronuclear dipolar coupling and 13C CSA, the information about the local anisotropy and geometry of motion was obtained. Taking advantage of the big difference of the 13C T1 relaxation time in crystalline and non-crystalline regions of PEs, the 1D 13C MAS exchange experiment was used to investigate the cooperative chain motion between these regions. The different chain organizations in non-crystalline regions were used to explain the relationship between the local fluctuation and the long range motion of the samples. In a simple manner the cooperative chain motion between crystalline and non-crystalline regions of PE results in the experimentally observed diffusive behavior of PE chain. The morphological influences on the diffusion motion have been discussed. The morphological factors include lamellar thickness, chain organization in non-crystalline regions and chain entanglements. Thermodynamics of the diffusion motion in melt and solution crystallized UHMW-PEs is discussed, revealing entropy-controlled features of the chain diffusion in PE. This thermodynamic consideration explains the counterintuitive relationship between the local fluctuation and the long range motion of the samples. Using the chain diffusion coefficient, the rates of jump motion in crystals of the melt crystallized PE have been calculated. A concept of "effective" jump motion has been proposed to explain the difference between the values derived from the chain diffusion coefficients and those in literatures. The observations of this thesis give a clear demonstration of the strong relationship between the sample morphology and chain dynamics. The sample morphologies governed by the processing history lead to different spatial constraints for the molecular chains, leading to different features of the local and long range chain dynamics. The knowledge of the morphological influence on the microscopic chain motion has many implications in our understanding of the alpha-relaxation process in PE and the related phenomena such as crystal thickening, drawability of PE, the easy creep of PE fiber, etc.
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In this thesis, the influence of composition changes on the glass transition behavior of binary liquids in two and three spatial dimensions (2D/3D) is studied in the framework of mode-coupling theory (MCT).The well-established MCT equations are generalized to isotropic and homogeneous multicomponent liquids in arbitrary spatial dimensions. Furthermore, a new method is introduced which allows a fast and precise determination of special properties of glass transition lines. The new equations are then applied to the following model systems: binary mixtures of hard disks/spheres in 2D/3D, binary mixtures of dipolar point particles in 2D, and binary mixtures of dipolar hard disks in 2D. Some general features of the glass transition lines are also discussed. The direct comparison of the binary hard disk/sphere models in 2D/3D shows similar qualitative behavior. Particularly, for binary mixtures of hard disks in 2D the same four so-called mixing effects are identified as have been found before by Götze and Voigtmann for binary hard spheres in 3D [Phys. Rev. E 67, 021502 (2003)]. For instance, depending on the size disparity, adding a second component to a one-component liquid may lead to a stabilization of either the liquid or the glassy state. The MCT results for the 2D system are on a qualitative level in agreement with available computer simulation data. Furthermore, the glass transition diagram found for binary hard disks in 2D strongly resembles the corresponding random close packing diagram. Concerning dipolar systems, it is demonstrated that the experimental system of König et al. [Eur. Phys. J. E 18, 287 (2005)] is well described by binary point dipoles in 2D through a comparison between the experimental partial structure factors and those from computer simulations. For such mixtures of point particles it is demonstrated that MCT predicts always a plasticization effect, i.e. a stabilization of the liquid state due to mixing, in contrast to binary hard disks in 2D or binary hard spheres in 3D. It is demonstrated that the predicted plasticization effect is in qualitative agreement with experimental results. Finally, a glass transition diagram for binary mixtures of dipolar hard disks in 2D is calculated. These results demonstrate that at higher packing fractions there is a competition between the mixing effects occurring for binary hard disks in 2D and those for binary point dipoles in 2D.
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Despite the fact that photographic stimuli are used across experimental contexts with both human and nonhuman subjects, the nature of individuals' perceptions of these stimuli is still not well understood. In the present experiments, we tested whether three orangutans and 36 human children could use photographic information presented on a computer screen to solve a perceptually corresponding problem in the physical domain. Furthermore, we tested the cues that aided in this process by pitting featural information against spatial position in a series of probe trials. We found that many of the children and one orangutan were successfully able to use the information cross-dimensionally; however, the other two orangutans and almost a quarter of the children failed to acquire the task. Species differences emerged with respect to ease of task acquisition. More striking, however, were the differences in cues that participants used to solve the task: Whereas the orangutan used a spatial strategy, the majority of children used a feature one. Possible reasons for these differences are discussed from both evolutionary and developmental perspectives. The novel results found here underscore the need for further testing in this area to design appropriate experimental paradigms in future comparative research settings.