881 resultados para Neuronal Plasticity


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A series of laboratory-scale T-bar penetrometer tests have been conducted on a clay bed virgin consolidated from reconstituted high plasticity marine clay. This investigation was mainly concerned with the effects on the penetration resistance of rate of penetration and the presence of free water on the surface of the clay bed. The rate of penetration varied between 0.005mm/s and 50mm/s. The results showed that the nature of soil resistance was 'undrained' over the range of speeds studied, and the resistance showed a marked viscous rate effect. The virgin consolidated clay bed exhibited an increase in penetration resistance by up to 35% for a factor 10 increase in rate of penetration much larger than values previously reported for kaolin. The presence of water on the surface of clay bed had a profound impact on penetration resistance, particularly on the remoulded strength obtained by taking the T-bar through successive penetration and extraction cycles. This was true even when the remoulding cycles were conducted without the T-bar breaking through the clay surface.

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A small strain two-dimensional discrete dislocation plasticity framework coupled to vacancy diffusion is developed wherein the motion of edge dislocations is by a combination of glide and climb. The dislocations are modelled as line defects in a linear elastic medium and the mechanical boundary value problem is solved by the superposition of the infinite medium elastic fields of the dislocations and a complimentary non-singular solution that enforces the boundary conditions. Similarly, the climbing dislocations are modelled as line sources/sinks of vacancies and the vacancy diffusion boundary value problem is also solved by a superposition of the fields of the line sources/sinks in an infinite medium and a complementary non-singular solution that enforces the boundary conditions. The vacancy concentration field along with the stress field provides the climb rate of the dislocations. Other short-range interactions of the dislocations are incorporated via a set of constitutive rules. We first employ this formulation to investigate the climb of a single edge dislocation in an infinite medium and illustrate the existence of diffusion-limited and sink-limited climb regimes. Next, results are presented for the pure bending and uniaxial tension of single crystals oriented for single slip. These calculations show that plasticity size effects are reduced when dislocation climb is permitted. Finally, we contrast predictions of this coupled framework with an ad hoc model in which dislocation climb is modelled by a drag-type relation based on a quasi steady-state solution. © 2013 Elsevier Ltd. All rights reserved.

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Interactions between dislocations and grain boundaries play an important role in the plastic deformation of polycrystalline metals. Capturing accurately the behaviour of these internal interfaces is particularly important for applications where the relative grain boundary fraction is significant, such as ultra fine-grained metals, thin films and microdevices. Incorporating these micro-scale interactions (which are sensitive to a number of dislocation, interface and crystallographic parameters) within a macro-scale crystal plasticity model poses a challenge. The innovative features in the present paper include (i) the formulation of a thermodynamically consistent grain boundary interface model within a microstructurally motivated strain gradient crystal plasticity framework, (ii) the presence of intra-grain slip system coupling through a microstructurally derived internal stress, (iii) the incorporation of inter-grain slip system coupling via an interface energy accounting for both the magnitude and direction of contributions to the residual defect from all slip systems in the two neighbouring grains, and (iv) the numerical implementation of the grain boundary model to directly investigate the influence of the interface constitutive parameters on plastic deformation. The model problem of a bicrystal deforming in plane strain is analysed. The influence of dissipative and energetic interface hardening, grain misorientation, asymmetry in the grain orientations and the grain size are systematically investigated. In each case, the crystal response is compared with reference calculations with grain boundaries that are either 'microhard' (impenetrable to dislocations) or 'microfree' (an infinite dislocation sink). © 2013 Elsevier Ltd. All rights reserved.

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BACKGROUND: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. RESULTS: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. CONCLUSIONS: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

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Phenotypic plasticity widely exists in the external morphology of animals as well as the internal traits of organs. In the present study, we studied the gut length plasticity of planktivorous filter-feeding silver carp under different food resources in large-net cage experiments in Meiliang Bay of Lake Taihu in 2004 and 2005. There was a significant difference in stocking density between these 2 years. Under a low stocking density and abundant food resources, silver carp increased their energy intake by feeding on more zooplankton. Meanwhile, silver carp adjusted their gut length to match the digestive requirements of food when exposed to different food resources. In the main growth seasons (from April to October), silver carp significantly increased their relative gut length when feeding on more phytoplankton in 2005 (p < 0.01, 9.23 +/- 1.80 in 2004 and 10.77 +/- 2.05 in 2005, respectively). There was a nearly significant negative correlation between zooplankton proportion in the diet and the relative gut length when silver carp were stocked in a high density (p = 0.112). It appears that silver carp might have evolved plasticity to change their gut length rapidly to facilitate efficient utilization of food resources. Such resource polymorphisms in the gut may be a good indication of temporal adaptation to resource conditions. Our work provided field evidence for understanding the functional basis of resource polymorphisms and the evolution of phenotypic plasticity in planktivorous filter-feeding fish.

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It has long been recognised that statistical dependencies in neuronal activity need to be taken into account when decoding stimuli encoded in a neural population. Less studied, though equally pernicious, is the need to take account of dependencies between synaptic weights when decoding patterns previously encoded in an auto-associative memory. We show that activity-dependent learning generically produces such correlations, and failing to take them into account in the dynamics of memory retrieval leads to catastrophically poor recall. We derive optimal network dynamics for recall in the face of synaptic correlations caused by a range of synaptic plasticity rules. These dynamics involve well-studied circuit motifs, such as forms of feedback inhibition and experimentally observed dendritic nonlinearities. We therefore show how addressing the problem of synaptic correlations leads to a novel functional account of key biophysical features of the neural substrate.

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Apostichopus japonicus is a common sea cucumber that undergoes seasonal inactivity phases and ceases feeding during the summer months. We used this sea cucumber species as a model in which to examine phenotypic plasticity of the digestive tract in response to food deprivation. We measured the body mass, gross gut morphology and digestive enzyme activities of A. japonicus before, during, and after the period of inactivity to examine the effects of food deprivation on the gut structure and function of this animal. Individuals were sampled semi-monthly from June to November (10 sampling intervals over 178 days) across temperature changes of more than 18 degrees C. On 5 September, which represented the peak of inactivity and lack of feeding, A. japonicus decreased its body mass, gut mass and gut length by 50%, 85%, and 70%, respectively, in comparison to values for these parameters preceding the inactive period. The activities of amylase, cellulase and lipase decreased by 77%, 98%, and 35% respectively, in comparison to mean values for these enzymes in June, whereas pepsin activity increased two-fold (luring the inactive phase. Alginase and trypsin activities were variable and did not change significantly across the 178-day experiment. With the exception of amylase and cellulase, all body size indices and digestive enzyme activities recovered and even surpassed the mean values preceding the inactive phase during the latter part of the experiment (October-November). Principal Component Analysis (PCA) utilizing the digestive enzyme activity and body size index data divided the physiological state of this cucumber into four phases: an active stage, prophase of inactivity peak inactivity, and a reversion phase. These phases are all consistent with previously suggested life stages for this species, but our data provide more defined characteristics of each phase. A. japonicus clearly exhibits phenotypic plasticity (or life-cycle staging) of the digestive tract during its annual inactive period. (C) 2008 Elsevier Inc. All rights reserved.

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This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

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Huntington’s Disease (HD) is a rare autosomal dominant neurodegenerative disease caused by the expression of a mutant Huntingtin (muHTT) protein. Therefore, preventing the expression of muHTT by harnessing the specificity of the RNA interference (RNAi) pathway is a key research avenue for developing novel therapies for HD. However, the biggest caveat in the RNAi approach is the delivery of short interfering RNA (siRNAs) to neurons, which are notoriously difficult to transfect. Indeed, despite the great advances in the field of nanotechnology, there remains a great need to develop more effective and less toxic carriers for siRNA delivery to the Central Nervous System (CNS). Thus, the aim of this thesis was to investigate the utility of modified amphiphilic β-cyclodextrins (CDs), oligosaccharide-based molecules, as non-viral vectors for siRNA delivery for HD. Modified CDs were able to bind and complex siRNAs forming nanoparticles capable of delivering siRNAs to ST14A-HTT120Q cells and to human HD fibroblasts, and reducing the expression of the HTT gene in these in vitro models of HD. Moreover, direct administration of CD.siRNA nanoparticles into the R6/2 mouse brain resulted in significant HTT gene expression knockdown and selective alleviation of rotarod motor deficits in this mouse model of HD. In contrast to widely used transfection reagents, CD.siRNA nanoparticles only induced limited cytotoxic and neuroinflammatory responses in multiple brain-derived cell-lines, and also in vivo after single direct injections into the mouse brain. Alternatively, we have also described a PEGylation-based formulation approach to further stabilise CD.siRNA nanoparticles and progress towards a systemic delivery nanosystem. Resulting PEGylated CD.siRNA nanoparticles showed increased stability in physiological saltconditions and, to some extent, reduced protein-induced aggregation. Taken together, the work outlined in this thesis identifies modified CDs as effective, safe and versatile siRNA delivery systems that hold great potential for the treatment of CNS disorders, such as HD.

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Perfusion experiments on an isolated, canine lateral saphenous vein segment preparation have shown that noradrenaline causes potent, flow dependent effects, at a threshold concentration comparable to that of plasma noradrenaline, when it stimulates the segment by diffusion from its microcirculation (vasa vasorum). The effects caused are opposite to those neuronal noradrenaline causes in vivo and that, in the light of the principle that all information is transmitted in patterns that need contrast to be detected – star patterns need darkness, sound patterns, quietness – has generated the hypothesis that plasma noradrenaline provides the obligatory contrast tissues need to detect and respond to the regulatory information encrypted in the diffusion pattern of neuronal noradrenaline. Based on the implications of that hypothesis, the controlled variable of the peripheral noradrenergic system is believed to be the maintenance of a set point balance between the contrasting effects of plasma and neuronal noradrenaline on a tissue. The hypothalamic sympathetic centres are believed to monitor that balance through the level of afferent sympathetic traffic they receive from a tissue and to correct any deviation it detects in the balance by adjusting the level of efferent sympathetic input it projects to the tissue. The failure of the centres to maintain the correct balance, for reasons intrinsic or extrinsic to themselves, is believed to be responsible for degenerative and genetic disorders. When the failure causes the balance to be polarised in favour of the effect of plasma noradrenaline that is believed to cause inflammatory diseases like dilator cardiac failure, renal hypertension, varicose veins and aneurysms; when it causes it to be polarised in favour of the effect of neuronal noradrenaline that is believed to cause genetic diseases like hypertrophic cardiopathy, pulmonary hypertension and stenoses and when, in pregnancy, a factor causes the polarity to favour plasma noradrenaline in all the maternal tissues except the uterus and conceptus, where it favours neuronal noradrenaline, that is believed to cause preeclampsia.