Search results for "Neural Networks"
showing 10 items of 599 documents
Spot compliant neuronal networks by structure optimized micro-contact printing
2001
Neuronal cell growth in vitro can be controlled with micropatterned structures of extracellular matrix proteins such as laminin. This technique is a powerful tool for studying neuronal cell function in order to increase experimental reproducibility and to specifically design innovative experimental setups. In this paper the correlation between the structural dimensions of the ECM pattern and the shape of the resulting cellular network is analyzed. The aim of the present study was to position neuronal cell bodies as precisely as possible and to induce directed cell differentiation. PCC7-MzN cells were cultured on laminin patterns. The line width, node size and gap size in-between cell adhesi…
Polysialic acid is required for dopamine D2 receptor-mediated plasticity involving inhibitory circuits of the rat medial prefrontal cortex.
2011
Decreased expression of dopamine D2 receptors (D2R), dysfunction of inhibitory neurotransmission and impairments in the structure and connectivity of neurons in the medial prefrontal cortex (mPFC) are involved in the pathogenesis of schizophrenia and major depression, but the relationship between these changes remains unclear. The polysialylated form of the neural cell adhesion molecule (PSA-NCAM), a plasticity-related molecule, may serve as a link. This molecule is expressed in cortical interneurons and dopamine, via D2R, modulates its expression in parallel to that of proteins related to synapses and inhibitory neurotransmission, suggesting that D2R-targeted antipsychotics/antidepressants…
Computation of inverse functions in a model of cerebellar and reflex pathways allows to control a mobile mechanical segment.
2003
Abstract The command and control of limb movements by the cerebellar and reflex pathways are modeled by means of a circuit whose structure is deduced from functional constraints. One constraint is that fast limb movements must be accurate although they cannot be continuously controlled in closed loop by use of sensory signals. Thus, the pathways which process the motor orders must contain approximate inverse functions of the bio-mechanical functions of the limb and of the muscles. This can be achieved by means of parallel feedback loops, whose pattern turns out to be comparable to the anatomy of the cerebellar pathways. They contain neural networks able to anticipate the motor consequences …
Cerebellar learning of bio-mechanical functions of extra-ocular muscles: modeling by artificial neural networks
2003
A control circuit is proposed to model the command of saccadic eye movements. Its wiring is deduced from a mathematical constraint, i.e. the necessity, for motor orders processing, to compute an approximate inverse function of the bio-mechanical function of the moving plant, here the bio-mechanics of the eye. This wiring is comparable to the anatomy of the cerebellar pathways. A predicting element, necessary for inversion and thus for movement accuracy, is modeled by an artificial neural network whose structure, deduced from physical constraints expressing the mechanics of the eye, is similar to the cell connectivity of the cerebellar cortex. Its functioning is set by supervised reinforceme…
Improving the accuracy of rainfall prediction using a regionalization approach and neural networks
2018
Spatial and temporal analysis of precipitation patterns has become an intense research topic in contemporary climatology. Increasing the accuracy of precipitation prediction can have valuable results for decision-makers in a specific region. Hence, studies about precipitation prediction on a regional scale are of great importance. Artificial Neural Networks (ANN) have been widely used in climatological applications to predict different meteorological parameters. In this study, a method is presented to increase the accuracy of neural networks in precipitation prediction in Chaharmahal and Bakhtiari Province in Iran. For this purpose, monthly precipitation data recorded at 42 rain gauges duri…
Ideal Chaotic Pattern Recognition is achievable: The Ideal-M-AdNN - its design and properties
2013
Published version of a chapter in the book: Transactions on Computational Collective Intelligence XI. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-41776-4_2 This paper deals with the relatively new field of designing a Chaotic Pattern Recognition (PR) system. The benchmark of such a system is the following: First of all, one must be able to train the system with a set of “training” patterns. Subsequently, as long as there is no testing pattern, the system must be chaotic. However, if the system is, thereafter, presented with an unknown testing pattern, the behavior must ideally be as follows. If the testing pattern is not one of the trained patterns, the system …
Inverse simulated annealing for the determination of amorphous structures
2013
We present a new and efficient optimization method to determine the structure of disordered systems in agreement with available experimental data. Our approach permits the application of accurate electronic structure calculations within the structure optimization. The new technique is demonstrated within density functional theory by the calculation of a model of amorphous carbon.
Non-exponential relaxation in disordered materials: Phenomenological correlations and spectrally selective experiments
1998
Abstract In most glass-forming materials external perturbations are relaxed in a non-exponential fashion. It is shown that the degree of non-exponentiality is phenomenologically correlated with the departure from simple thermally activated behavior as measured by the fragility index m. In model glass formers such as the Ge-As-Se ternary alloy, and to some degree for amorphous materials in general, the correlations with these properties are observed also for other characteristic features. These include the specific heat step and the aging kinetics in the glass transformation range. While phenomenological correlations have proven very useful for rationalizing the properties of many glass form…
Stochastic models for wind speed forecasting
2011
Abstract This paper is concerned with the problem of developing a general class of stochastic models for hourly average wind speed time series. The proposed approach has been applied to the time series recorded during 4 years in two sites of Sicily, a region of Italy, and it has attained valuable results in terms both of modelling and forecasting. Moreover, the 24 h predictions obtained employing only 1-month time series are quite similar to those provided by a feed-forward artificial neural network trained on 2 years data.
Disorder and interactions in systems out of equilibrium : the exact independent-particle picture from density functional theory
2017
Density functional theory (DFT) exploits an independent-particle-system construction to replicate the densities and current of an interacting system. This construction is used here to access the exact effective potential and bias of non-equilibrium systems with disorder and interactions. Our results show that interactions smoothen the effective disorder landscape, but do not necessarily increase the current, due to the competition of disorder screening and effective bias. This puts forward DFT as a diagnostic tool to understand disorder screening in a wide class of interacting disordered systems.