Biological and Artificial Computation: From Neuroscience to Technology

Microcircuits in the brain.- Some reflections on the relationships between neuroscience and computation.- Different types of temporal correlations obtained in pairs of thalamic visual neurons suggest different functional patterns of connectivity.- Development of on-off and off-on receptive fields using a semistochastic model.- The classification of spatial, chromatic, and intensity features of simple visual stimuli by a network of retinal ganglion cells.- Geometric model of orientation tuning dynamics in striate neurons.- Neuronal circuitry in the medial cerebral cortex of lizards.- Interactions between environmental and hormonal oscillations induce plastic changes in a simple neuroendocrine transducer.- Current Source Density analysis as a tool to constrain the parameter space in hippocampal CA1 neuron models.- Spontaneous activity of hippocampal cells in various physiological states.- Neural network model of striatal complex.- Symmetry and self-organization of the oculomotor neural integrator.- Quantal neural mechanisms underlying movement execution and motor learning.- A model of cerebellar saccadic motor learning using qualitative reasoning.- Balance between intercellular coupling and input resistance as a necessary requirement for oscillatory electrical activity in pancreatic ?-cells.- Mechanisms of synchronization in the hippocampus and its role along development.- Analysis of synfire chains above saturation.- Allometry in the Justo Gonzalo's model of the sensorial cortex.- Systems models of retinal cells: A classical example.- A generic formulation of neural nets as a model of parallel and self-programming computation.- Using an artificial neural network for studying the interneuronal layer of a leech neuronal circuit.- Capacity and parasitic fixed pointscontrol in a recursive neural network.- The use of prior knowledge in neural network configuration and training.- A model for heterogeneous neurons and its use in configuring neural networks for classification problems.- A computation theory for orientation-selective simple cells based on the MAP estimation principle and Markov random fields.- Competition between feed-forward and lateral information processing in layered neural networks.- Computing functions with spiking neurons in temporal coding.- An introduction to Fuzzy State Automata.- Statistical analysis of regularization constant - From Bayes, MDL and NIC points of view.- Building digital libraries from paper documents, using ART based neuro-fuzzy systems.- Parallelization of connectionist models based on a symbolic formalism.- Generic neural network model and simulation toolkit.- A neural-fuzzy technique for interpolating spatial data via the use of learning curve.- Task decomposition based on class relations: A modular neural network architecture for pattern classification.- Lower bounds of computational power of a synaptic calculus.- Feed Forward Neural Network entities.- Astrocytes and slow learning in the formation of distal cortical associations.- Adaptation and other dynamic effects on neural signal transfer.- Hebbian learning in networks of spiking neurons using temporal coding.- An associative learning model for coupled neural oscillators.- Random perturbations to Hebbian synapses of associative memory using a genetic algorithm.- Phase memory in oscillatory networks.- Strategies for autonomous adaptation and learning in dynamical networks.- Modeling the parallel development of multiple featuremaps and topography in visual cortex.- Stability and hebbian learning in populations of probabilisticneurons.- Stochastic approximation techniques and circuits and systems associated tools for neural network optimization.- Recursive hetero-associative memories for translation.- Universal Binary and Multi-Valued Neurons paradigm: Conception, learning, applications.- Learning a Markov process with a synchronous Boltzmann machine.- The ?-EM algorithm: A block connectable generalized leaning tool for neural networks.- Training simple recurrent networks through gradient descent algorithms.- On simultaneous weight and architecture learning.- Evolution of structure and learning - A GP approach.- Self-organizing formation of receptive fields and competitive systems.- Optimizing a neural network architecture with an adaptive parameter genetic algorithm.- Self-organizing symbolic learned rules.- Viewing a class of neurodynamics on parameter space.- Hopfield neural network applied to optimization problems: Some theoretical and simulation results.- A genetic approach to computing Independent And Parallelism in logic programs.- Predicting toxicity of complex mixtures by artificial neural networks.- Regularisation by Convolution in Symmetric-?-Stable function networks.- Continuation of chaotic fields by RBFNN.- Improving the performance of Piecewise linear Separation incremental algorithms for practical hardware implementations.- Accurate decomposition of standard MLP classification responses into symbolic rules.- A hybrid intelligent system for the pre-processing of Fetal Heart rate signals in antenatal testing.- The pattern extraction architecture: A connectionist alternative to the von Neumann architecture.- A two-level heterogeneous hybrid model.- Interpretation of a hierarchical neural network.- Cognitive processes in social interactions - A neural networks' approach.-Adding phase to recurrent backpropagation networks: An application to binding tasks in vision.- Schema-based learning: Biologically inspired principles of dynamic organization.- Digital connectionist hardware: Current problems and future challenges.- EpsiloNN - A specification language for the efficient parallel simulation of neural networks.- Forward-backward building blocks for evolving neural networks with intrinsic learning behaviours.- A cascade network algorithm employing Progressive RPROP.- Tight bounds on the size of neural networks for classification problems.- On the possibilities of the limited precision weights neural networks in classification problems.- A modified backpropagation algorithm to tolerate weight errors.- A high performance SOFM hardware-system.- On application incentive and constraints for neural network hardware development.- A fast Kohonen net implementation for spert-II.- Synthesis and optimization of a bit-serial pipeline kernel processor.- A hardware implementation of CNNs based on Pulse Stream Techniques.- Evaluation of the CNAPS neuro-computer for the simulation of MLPS with receptive fields.- AFAN, a tool for the automatic design of fuzzy and neural controllers.- A fully stochastic fuzzy logic controller.- Multi-Neural Networks hardware and software architecture: Application of the divide to simplify paradigm DTS.- A fuzzy controller for switching regulators with programmable control surfaces.- The Kohonen algorithm: A powerful tool for analysing and representing multidimensional quantitative and qualitative data.- Constrained neural network for estimating sensor reliability in sensors fusion.- Statistical analysis of the main parameters in the definition of Radial Basis Function networks.- Structural level comparison of two basicparadigms in neural computation.- Symmetry: Between indecision and equality of choice.- A non-convergent on-line training algorithm for neural networks.- Using classical and evolutive neural models in industrial applications: A case study for an automatic Coin Classifier.- A new type of unsupervised growing neural network for biological sequence classification that adopts the topology of a phylogenetic tree.- Classification of the onset of respiratory difficulties in ventilation assisted neonates.- A neural network approach for symbolic interpretation in critical care.- ECG beat classification with synaptic delay based artificial neural networks.- Neural network-based insulin infusion control for an insulin-pump, using discontinuous blood glucose measurements.- Infraclinic breast carcinoma: Application of neural networks techniques for the indication of radioguided biopsias.- Detection of Glaucoma by means of ANNs.- A comparative analysis of the neonatal prognosis problem using artificial neural networks, statistical techniques and certainty management techniques.- Models of visual processing derived from cortical microelectrode recordings.- Rotation invariant IR object recognition using adaptive kernel subspace projections with a neural network.- Neural networks based projectivity invariant recognition of flat patterns.- The instant laboratory: Bringing intelligence to the workfloor.- A biological front-end processing for speech recognition.- Non parametric coding of speech by means of a MLP with hints.- Gray-level object segmentation with a network of FitzHugh-Nagumo oscillators.- Multidimensional filtering inspired by retino-cortical projection: Application to texture segmentation.- A competitive neural network for blind separation of sources based on geometric properties.- A new bio-inspired algorithm for early vision edge detection and image segmentation.- Function of biological asymmetrical neural networks.- Identification of spectral features as sound localization cues in the external ear acoustics.- Phoneme recognition by means of predictive neural networks.- Shift-invariant fuzzy-morphology neural network for occluded target recognition.- A comparative study between linear and nonlinear speech prediction.- Recognition model with extension fields.- A GA-optimized neural network for classification of biological particles from electron-microscopy images.- Application of artificial neural networks to the design and implementation of electronic olfactory systems.- Application of a multilayer discrete-time CNN to deformable models.- Spoken-digit recognition using self-organizing maps with perceptual pre-processing.- Noise discrimination and autoassociative neural networks.- Modified Boltzmann machine for an efficient distributed implementation.- Simulation of MPEG video traffic using neural networks.- A continuous time structure for filtering and prediction using Hopfield Neural Networks.- Structure-adaptable neurocontrollers: A hardware-friendly approach.- A new QRS detector based on neural network.- Application of Neural Networks for local modeliation of the boiler furnace in thermal power plants.- Evolved neurocontrollers for pole-balancing.- Artificial neural networks for the computation of traffic queues.- Unsupervised neural network for forecasting alarms in hydroelectric power plant.- Motor sequence processing with an artificial learning system.- On-line continuous weld monitoring using neural networks.- Combining reinforcement learning and differential inverse kinematics for collision-free motion of multilink manipulators.- Short-term peak load forecasting: Statistical methods versus Artificial Neural Networks.- Integration of Self-Organizing Feature Maps and reinforcement learning in robotics.- Dynamic path planning with spiking neural networks.- Implementation of a basic reactive behavior in mobile robotics through artificial neural networks.- Visual probe mark inspection, using hardware implementation of artificial neural networks, in VLSI production.- Teleoreactive neural networks.