Effect of paradoxical sleep deprivation and stress on passive avoidance behavior

Previous studies have shown that several types of stress can induce memory impairment. However, the memory effects of paradoxical sleep deprivation (PSD), a stressor in itself, are unclear. We therefore compared passive avoidance behavior of rats undergoing PSD and PSD stress yoked-control (PSC) using the "reversed flowerpot method." When rats were kept isolated on a PSC platform for 24 It immediately after criterion training, retention trials showed impaired aversive memory storage. When delayed for 24 h after criterion training, PSC stress did not disrupt retention performance. In rats subjected to PSD, either immediately or 24 It after criterion training, there was no disruption of aversive memory consolidation. These results suggest that, during stress, paradoxical sleep plays a role in erasing aversive memory traces, in line with the theory that we "dream in order to forget." (C) 2003 Elsevier Inc. All rights reserved.

Ketamine affects memory consolidation: Differential effects in T-maze and passive avoidance paradigms in mice

The effects of ketamine, an N-methyl-D-aspartate (NMDA) antagonist, on memory in animals have been limited to the sub-anesthetic dose given prior to training in previous studies. We evaluated the effects of post-training anesthetic doses of ketamine to se

Effects of Prenatal Exposure to a 50-Hz Magnetic Field on One-Trial Passive Avoidance Learning in 1-Day-Old Chicks

We investigated memory impairment in newly hatched chicks following in ovo exposure to a 50-Hz magnetic field (MF) of 2 mT (60 min/day) on embryonic days 12-18. Isolated and paired chicks were used to test the effect of stress during training, and memory retention was tested at 10, 30, and 120 min, following exposure to a bitter-tasting bead (100% methylanthranilate). Results showed that memory was intact at 10 min in both isolated and paired chicks with or without MF exposure. However, while isolated chicks had good memory retention levels at 30 and 120 min, those exposed to MF did not. The results suggest a potential disruption of memory formation following in ovo exposure to MF, with this effect only evident in the more stressed, isolated chicks. Bioelectromagnetics 31:150-155, 2010. (C) 2009 Wiley-Liss. Inc.

Reversible disconnection of the hippocampal-prelimbic cortical circuit impairs spatial learning but not passive avoidance learning in rats

Wistar rats, treated with the GABA(A) receptor agonist muscimol, were used to investigate the role of the hippocampal-prelimbic cortical (Hip-PLC) circuit in spatial learning in the Morris water maze task, and in passive avoidance learning in the step-thr

Phase uncertainty in calibrating microwave test fixtures

The problem of phase uncertainty arising in calibration of the test fixtures is investigated in this paper, It is shown that the problem exists no matter what kinds of calibration standards are used. It is also found that there is no need to determine the individual S-parameters of the test fixtures. In order to eliminate the problem of phase uncertainty, three different precise (known) reflection standards or one known reflection standard plus one known transmission standard should be used to calibrate symmetrical test fixtures. For the asymmetrical cases, three known standards, including at least one transmission standard, should be used. The thru-open-match (TOM) and thru-short-match (TSM) techniques are the simplest methods, and they have no bandwidth limitation. When the standards are imprecise (unknown), it is recommended to use any suitable technique, such as the thru-reflect-line, line-reflect-line, thru-short-delay, thru-open-delay,line-reflect-match, line-reflect-reflect-match, or multiline methods, to accurately determine the values of the required calibration terms and, in addition, to use the TOM or TSM method with the same imprecise standards to resolve the phase uncertainty.

Temperature variation through 2000 years in China: An uncertainty analysis of reconstruction and regional difference

Chinese Academy of Sciences [KZCX2-YW-315, KZCX2-YW-Q1-01]; National Natural Science Foundation of China [40625002, 90502009, 200905006]; Office of Science (BER), U. S. Department of Energy ; EU/FP7 [212250]

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Study of remote sensing based parameter uncertainty in Production Efficiency Models

The remote sensing based Production Efficiency Models (PEMs), springs from the concept of "Light Use Efficiency" and has been applied more and more in estimating terrestrial Net Primary Productivity (NPP) regionally and globally. However, global NPP estimates vary greatly among different models in different data sources and handling methods. Because direct observation or measurement of NPP is unavailable at global scale, the precision and reliability of the models cannot be guaranteed. Though, there are ways to improve the accuracy of the models from input parameters. In this study, five remote sensing based PEMs have been compared: CASA, GLO-PEM, TURC, SDBM and VPM. We divided input parameters into three categories, and analyzed the uncertainty of (1) vegetation distribution, (2) fraction of photosynthetically active radiation absorbed by the canopy (fPAR) and (3) light use efficiency (e). Ground measurements of Hulunbeier typical grassland and meteorology measurements were introduced for accuracy evaluation. Results show that a real-time, more accurate vegetation distribution could significantly affect the accuracy of the models, since it's applied directly or indirectly in all models and affects other parameters simultaneously. Higher spatial and spectral resolution remote sensing data may reduce uncertainty of fPAR up to 51.3%, which is essential to improve model accuracy.

Robust Learning Control for Manipulators with Uncertainty Disturbances Based on Internal Model

In this paper, a disturbance controller is designed for making robotic system behave as a decoupled linear system according to the concept of internal model. Based on the linear system, the paper presents an iterative learning control algorithm to robotic manipulators. A sufficient condition for convergence is provided. The selection of parameter values of the algorithm is simple and easy to meet the convergence condition. The simulation results demonstrate the effectiveness of the algorithm..