Experiments and observations on the behaviour and brain of the aging female mouse with special reference to dementia of the Alzheimer type

The objective of this research was to investigate the effects of normal aging and the additional effects of chronic exposure to two experimental diets, one enriched in aluminium, the other enriched in lecithin, on aspects of the behaviour and brain histology of the female mouse. The aluminium diet was administered in an attempt to develop a rodent model of Dementia of the Alzheimer Type (DAT). With normal aging, almost all assessed aspects of behaviour were found to be impaired. As regards cognition, selective impairments of single-trial passive avoidance and Morris place learning were observed. While all aspects of open-field behaviour were impaired, the degree of impairment was directly related to the degree of motoric complexity. Deficits were also observed on non-visual sensorimotor coordination tasks and in olfactory discrimination. Histologically, neuron loss, gliosis, vacuolation and congophilic angiopathy were observed in several of the brain regions/fibre tracts believed to contribute to the control of some of the assessed behaviours. The aluminium treatment had very selective effects on both behaviour and brain histology, inducing several features observed in DAT. Behaviourally, the treatment induced impaired spatial reference memory; reduced ambulation; disturbed olfactory function and induced the premature development of the senile pattern of swimming. Histologically, significant neuron loss and gliosis were observed in the hippocampus, entorhinal cortex, amygdala, medial septum, pyriform and pr-frontal cortex. In addition, the brain distribution of congophilic angiopathy was significantly increased by the treatment. The lecithin treatment had effects on both non-cognitive and cognitive aspects of behaviour. The effects of aging on open-field ambulation and rearing were partially ameliorated by the treatment. A similar effect was observed for single-trial passive avoidance performance. Age-dependent improvements in acquisition/retention were observed in 17-23 month mice and Morris place task performance was improved in 11 and 17 month mice. Histologically, a partial sparing of neurons in the cerebellum, hippocampus, entorhinal cortex and subiculum was observed.

No-reference image quality assessment in contourlet domain

The target of no-reference (NR) image quality assessment (IQA) is to establish a computational model to predict the visual quality of an image. The existing prominent method is based on natural scene statistics (NSS). It uses the joint and marginal distributions of wavelet coefficients for IQA. However, this method is only applicable to JPEG2000 compressed images. Since the wavelet transform fails to capture the directional information of images, an improved NSS model is established by contourlets. In this paper, the contourlet transform is utilized to NSS of images, and then the relationship of contourlet coefficients is represented by the joint distribution. The statistics of contourlet coefficients are applicable to indicate variation of image quality. In addition, an image-dependent threshold is adopted to reduce the effect of content to the statistical model. Finally, image quality can be evaluated by combining the extracted features in each subband nonlinearly. Our algorithm is trained and tested on the LIVE database II. Experimental results demonstrate that the proposed algorithm is superior to the conventional NSS model and can be applied to different distortions. © 2009 Elsevier B.V. All rights reserved.

The sensitivity of mapping methods to reference data quality:training supervised image classifications with imperfect reference data

The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.