Search results for "Neural"
showing 10 items of 2783 documents
The role of expert evaluation for microsleep detection
2015
Abstract Recently, it has been shown by overnight driving simulation studies that microsleep density is the only known sleepiness indicator which rapidly increases within a few seconds immediately before sleepiness related crashes. This indicator is based solely on EEG and EOG and subsequent adaptive pattern recognition. Accurate microsleep recognition is very important for the performance of this sleepiness indicator. The question is whether expensive evaluations of microsleep events by a) experts are necessary or b) non-experts provide sufficient evaluations. Based on 11,114 microsleep events in case a) and 12,787 in case b) recognition accuracies were investigated utilizing (i) artificia…
Principal Component and Neural Network Analyses of Face Images: What Can Be Generalized in Gender Classification?
1998
We present an overview of the major findings of the principal component analysis (pca) approach to facial analysis. In a neural network or connectionist framework, this approach is known as the linear autoassociator approach. Faces are represented as a weighted sum of macrofeatures (eigenvectors or eigenfaces) extracted from a cross-product matrix of face images. Using gender categorization as an illustration, we analyze the robustness of this type of facial representation. We show that eigenvectors representing general categorical information can be estimated using a very small set of faces and that the information they convey is generalizable to new faces of the same population and to a l…
DAE-GP
2020
Estimation of distribution genetic programming (EDA-GP) algorithms are metaheuristics where sampling new solutions from a learned probabilistic model replaces the standard mutation and recombination operators of genetic programming (GP). This paper presents DAE-GP, a new EDA-GP which uses denoising autoencoder long short-term memory networks (DAE-LSTMs) as probabilistic model. DAE-LSTMs are artificial neural networks that first learn the properties of a parent population by mapping promising candidate solutions to a latent space and reconstructing the candidate solutions from the latent space. The trained model is then used to sample new offspring solutions. We show on a generalization of t…
NMDA receptor antagonist treatment induces a long-lasting increase in the number of proliferating cells, PSA-NCAM-immunoreactive granule neurons and …
2001
During adulthood, neural precursors located in the subgranular zone of the dentate gyrus continue to proliferate, leading to the generation of new granule neurons. These recently generated cells transiently express the polysialylated form of the neural cell adhesion molecule, PSA-NCAM, and are supported by radial glia-like cells that are likely to play a role in neuronal migration and differentiation, or even act as their precursors. Previous reports indicate that treatment with NMDA receptor antagonists stimulates adult neurogenesis in the dentate gyrus, and because of the potential therapeutic value of this approach, we were interested in further characterizing the consequences of pharmac…
Nonlinear Relaxation in Population Dynamics
2001
We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the i-th population and on the distribution of the population and of the local field.
A Neuro-Ethological Approach for the TSP: Changing Metaphors in Connectionist Models.
1994
Biological systems often offer solutions to difficult problems which are not only original but also efficient. Connectionist models have been inspired by neural systems and successfully applied to the formulation of algorithms for solving complex problems such as the travelling salesman problem. In this paper we extend the connectionist metaphor to include an ethological account of how problems similar to the travelling salesman problem are solved by real living systems. A model is presented in which a population of neural networks with simple sensory-motor systems evolve genetically in simulated environments which represent the problem instances to be solved. Preliminary results are discu…
Cell lineage and cell fate specification in the embryonic CNS of Drosophila.
1997
The Drosophila CNS derives from a population of neural stem cells, called neuroblasts (NBs), which delaminate individually from the neurogenic region of the ectoderm. In the embryonic ventral nerve cord each NB can be uniquely identified and gives rise to a specific lineage consisting of neurons and/or glial cells. This 'NB identity' is dependent on the position of the progenitor cells in the neuroectoderm before delamination. The positional information is provided by the products of segment polarity and dorsoventral (D/V) patterning genes. Subsequently, 'cell fate genes' like huckebein (hkb) and eagle (eg) contribute to the generation of specific NB lineages. These genes act downstream of …
Localization of parvalbumin, calretinin, and calbindin D-28k in identified extraocular motoneurons and internuclear neurons of the cat
1998
Calcium-binding proteins have been shown to be excellent markers of specific neuronal populations. We aimed to characterize the expression of calcium-binding proteins in identified populations of the cat extraocular motor nuclei by means of immunohistochemistry against parvalbumin, calretinin, and calbindin D-28k. Abducens, medial rectus, and trochlear motoneurons were retrogradely labeled with horseradish peroxidase from their corresponding muscles. Oculomotor and abducens internuclear neurons were retrogradely labeled after horseradish peroxidase injection into either the abducens or the oculomotor nucleus, respectively. Parvalbumin staining produced the highest density of immunoreactive …
Shared feature representations of LiDAR and optical images: Trading sparsity for semantic discrimination
2015
This paper studies the level of complementary information conveyed by extremely high resolution LiDAR and optical images. We pursue this goal following an indirect approach via unsupervised spatial-spectral feature extraction. We used a recently presented unsupervised convolutional neural network trained to enforce both population and lifetime spar-sity in the feature representation. We derived independent and joint feature representations, and analyzed the sparsity scores and the discriminative power. Interestingly, the obtained results revealed that the RGB+LiDAR representation is no longer sparse, and the derived basis functions merge color and elevation yielding a set of more expressive…
Mortalidad por defectos del tubo neural en México, 1980-1997
2003
Objetivo. Describir la mortalidad en México por defectos del tubo neural, durante el periodo 1980-1997. Material y métodos. Las tasas anuales de mortalidad estatales y nacionales, por defectos del tubo neural, se calcularon por 10 000 nacidos vivos. La tendencia temporal fue evaluada por el porcentaje de cambio anual obtenido mediante un modelo de regresión de Poisson. Se calculó la razón de mortalidad, tomando la media nacional como referencia. Las tasas y las razones se representaron gráficamente en mapas. Resultados. Durante el periodo la tasa bruta de mortalidad por defectos del tubo neural fue de 5.8 por 10 000 nacidos vivos. La anencefalia fue el tipo de defecto más frecuente (37.7%),…