914 resultados para Collective Memory
Resumo:
Collective behavior refers to the emergence of complex migration patterns over scales larger than those of the individual elements constituting a system. It plays a pivotal role in biological systems in regulating various processes such as gastrulation, morphogenesis and tissue organization. Here, by combining experimental approaches and numerical modeling, we explore the role of cell density ('crowding'), strength of intercellular adhesion ('cohesion') and boundary conditions imposed by extracellular matrix (ECM) proteins ('constraints') in regulating the emergence of collective behavior within epithelial cell sheets. Our results show that the geometrical confinement of cells into well-defined circles induces a persistent, coordinated and synchronized rotation of cells that depends on cell density. The speed of such rotating large-scale movements slows down as the density increases. Furthermore, such collective rotation behavior depends on the size of the micropatterned circles: we observe a rotating motion of the overall cell population in the same direction for sizes of up to 200 μm. The rotating cells move as a solid body, with a uniform angular velocity. Interestingly, this upper limit leads to length scales that are similar to the natural correlation length observed for unconfined epithelial cell sheets. This behavior is strongly altered in cells that present a downregulation of adherens junctions and in cancerous cell types. We anticipate that our system provides a simple and easy approach to investigate collective cell behavior in a well-controlled and systematic manner.
Resumo:
We demonstrate how a prior assumption of smoothness can be used to enhance the reconstruction of free energy profiles from multiple umbrella sampling simulations using the Bayesian Gaussian process regression approach. The method we derive allows the concurrent use of histograms and free energy gradients and can easily be extended to include further data. In Part I we review the necessary theory and test the method for one collective variable. We demonstrate improved performance with respect to the weighted histogram analysis method and obtain meaningful error bars without any significant additional computation. In Part II we consider the case of multiple collective variables and compare to a reconstruction using least squares fitting of radial basis functions. We find substantial improvements in the regimes of spatially sparse data or short sampling trajectories. A software implementation is made available on www.libatoms.org.
Resumo:
Directed migration of groups of cells is a critical aspect of tissue morphogenesis that ensures proper tissue organization and, consequently, function. Cells moving in groups, unlike single cells, must coordinate their migratory behavior to maintain tissue integrity. During directed migration, cells are guided by a combination of mechanical and chemical cues presented by neighboring cells and the surrounding extracellular matrix. One important class of signals that guide cell migration includes topographic cues. Although the contact guidance response of individual cells to topographic cues has been extensively characterized, little is known about the response of groups of cells to topographic cues, the impact of such cues on cell-cell coordination within groups, and the transmission of nonautonomous contact guidance information between neighboring cells. Here, we explore these phenomena by quantifying the migratory response of confluent monolayers of epithelial and fibroblast cells to contact guidance cues provided by grooved topography. We show that, in both sparse clusters and confluent sheets, individual cells are contact-guided by grooves and show more coordinated behavior on grooved versus flat substrates. Furthermore, we demonstrate both in vitro and in silico that the guidance signal provided by a groove can propagate between neighboring cells in a confluent monolayer, and that the distance over which signal propagation occurs is not significantly influenced by the strength of cell-cell junctions but is an emergent property, similar to cellular streaming, triggered by mechanical exclusion interactions within the collective system.
Resumo:
Three questions have been prominent in the study of visual working memory limitations: (a) What is the nature of mnemonic precision (e.g., quantized or continuous)? (b) How many items are remembered? (c) To what extent do spatial binding errors account for working memory failures? Modeling studies have typically focused on comparing possible answers to a single one of these questions, even though the result of such a comparison might depend on the assumed answers to both others. Here, we consider every possible combination of previously proposed answers to the individual questions. Each model is then a point in a 3-factor model space containing a total of 32 models, of which only 6 have been tested previously. We compare all models on data from 10 delayed-estimation experiments from 6 laboratories (for a total of 164 subjects and 131,452 trials). Consistently across experiments, we find that (a) mnemonic precision is not quantized but continuous and not equal but variable across items and trials; (b) the number of remembered items is likely to be variable across trials, with a mean of 6.4 in the best model (median across subjects); (c) spatial binding errors occur but explain only a small fraction of responses (16.5% at set size 8 in the best model). We find strong evidence against all 6 documented models. Our results demonstrate the value of factorial model comparison in working memory.
Resumo:
A high performance ferroelectric non-volatile memory device based on a top-gate ZnO nanowire (NW) transistor fabricated on a glass substrate is demonstrated. The ZnO NW channel was spin-coated with a poly (vinylidenefluoride-co-trifluoroethylene) (P(VDF-TrFE)) layer acting as a top-gate dielectric without buffer layer. Electrical conductance modulation and memory hysteresis are achieved by a gate electric field induced reversible electrical polarization switching of the P(VDF-TrFE) thin film. Furthermore, the fabricated device exhibits a memory window of ∼16.5 V, a high drain current on/off ratio of ∼105, a gate leakage current below ∼300 pA, and excellent retention characteristics for over 104 s. © 2014 AIP Publishing LLC.
Resumo:
Performance on visual working memory tasks decreases as more items need to be remembered. Over the past decade, a debate has unfolded between proponents of slot models and slotless models of this phenomenon (Ma, Husain, Bays (Nature Neuroscience 17, 347-356, 2014). Zhang and Luck (Nature 453, (7192), 233-235, 2008) and Anderson, Vogel, and Awh (Attention, Perception, Psychophys 74, (5), 891-910, 2011) noticed that as more items need to be remembered, "memory noise" seems to first increase and then reach a "stable plateau." They argued that three summary statistics characterizing this plateau are consistent with slot models, but not with slotless models. Here, we assess the validity of their methods. We generated synthetic data both from a leading slot model and from a recent slotless model and quantified model evidence using log Bayes factors. We found that the summary statistics provided at most 0.15 % of the expected model evidence in the raw data. In a model recovery analysis, a total of more than a million trials were required to achieve 99 % correct recovery when models were compared on the basis of summary statistics, whereas fewer than 1,000 trials were sufficient when raw data were used. Therefore, at realistic numbers of trials, plateau-related summary statistics are highly unreliable for model comparison. Applying the same analyses to subject data from Anderson et al. (Attention, Perception, Psychophys 74, (5), 891-910, 2011), we found that the evidence in the summary statistics was at most 0.12 % of the evidence in the raw data and far too weak to warrant any conclusions. The evidence in the raw data, in fact, strongly favored the slotless model. These findings call into question claims about working memory that are based on summary statistics.
Resumo:
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.
Resumo:
This paper proposes a novel single-electron multiple-valued memory. It is a metal-oxide-semiconductor field effect transistor (MOS)-type memory with multiple separate control gates and floating gate layer, which consists of nano-crystal grains. The electron can tunnel among the grains (floating gates) and between the floating gate layer and the MOS channel. The memory can realize operations of 'write', 'store' and 'erase' of multiple-valued signals exceeding three values by controlling the single electron tunneling behavior. We use Monte Carlo method to simulate the operation of single-electron four-valued memory. The simulation results show that it can operate well at room temperature.
Resumo:
We analyse the operation of a semiconductor nanowire-based memory cell. Large changes in the nanowire conductance result when the magnetization of a periodic array of nanoscale magnetic gates, which comprise the other key component of the memory cell, is switched between distinct configurations by an external magnetic field. The resulting conductance change provides the basis for a robust memory effect, which can be implemented in a semiconductor structure compatible with conventional semiconductor integrated circuits.
Resumo:
Zincblende Mn-rich Mn(Ga)As nanoclusters embedded in GaAs matrices are fabricated by in situ postgrowth annealing diluted magnetic semiconductor (Ga,Mn)As films with Mn concentration ranging from 2.6% to 8% at 650 degrees C. Magnetization measurements show that memory effect and slow magnetic relaxation, the typical characteristics of the spin-glass-like phase, occur below the blocking temperature of 45 K in samples with high Mn concentration, while for samples with low Mn concentration, ferromagnetic order remains up to 360 K. The behavior of low-temperature spin dynamics can be explained by the hierarchical model. (c) 2007 American Institute of Physics.
Resumo:
A time-varying controllable fault-tolerant field associative memory model and the realization algorithms are proposed. On the one hand, this model simulates the time-dependent changeability character of the fault-tolerant field of human brain's associative memory. On the other hand, fault-tolerant fields of the memory samples of the model can be controlled, and we can design proper fault-tolerant fields for memory samples at different time according to the essentiality of memory samples. Moreover, the model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. And the fault-tolerant fields of the memory samples are full of the whole real space R-n. The simulation shows that the model has the above characters and the speed of associative memory about the model is faster.
Resumo:
A design algorithm of an associative memory neural network is proposed. The benefit of this design algorithm is to make the designed associative memory model can implement the hoped situation. On the one hand, the designed model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. The result has improved the ones of some old associative memory neural network. On the other hand, the memory samples are in the centers of the fault-tolerant. In average significance the radius of the memory sample fault-tolerant field is maximum.
Resumo:
AlGaN/GaN npn heterojunction bipolar transistor structures were grown by low-pressure MOCVD. Secondary ion mass spectroscopy (SIMS) measurements were carried out to study the Mg memory effect and redistribution in the emitter-base junction. The results indicated that there is a Mg-rich film formed in the ongrowing layer after the Cp2Mg source is switched off. The Mg-rich film can be confined in the base section by switching off the Cp2Mg source for appropriate time before the end of base growth. Low temperature growth of the undoped GaN spacer suppresses the Mg redistribution from Mg rich film. The delay rate of the Mg profile in sample C with spacer growing in low temperature is about 56 nm/decade, which becomes sharper than 80 nm/decade of the samples A and B without low temperature spacer. (C) 2005 Elsevier Ltd. All rights reserved.