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Cortical Columns, Models of

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Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

Auke Ijspeert, Sébastien Gay, José Santos-Victor

In this paper we present a framework to learn a model-free feedback controller for locomotion and balance control of a compliant quadruped robot walking on rough terrain. Having designed an open-loop gait encoded in a Central Pattern Generator (CPG), we us ...

2013

Neural networks as mechanisms to regulate division of labor

Dario Floreano, Laurent Keller, Pawel Lichocki

In social insects, workers perform a multitude of tasks such as foraging, nest construction and brood rearing without central control of how work is allocated among individuals. It has been suggested that workers choose a task by responding to stimuli gath ...

2012

Power Efficient Hardware Implementation of a Fuzzy Neural Network

Rafal Tomasz Dlugosz

This paper presents a digital, transistor level implemented neo-fuzzy neural network. This type of neural network is particularly well suited for real-time applications like those encountered in signal processing and nonlinear system identification. We con ...

Technical University of Lodz2010

Cyber-workstation for computational neuroscience

Babak Mahmoudi

A Cyber-Workstation (CW) to study in vivo, real-time interactions between computational models and large-scale brain subsystems during behavioral experiments has been designed and implemented. The design philosophy seeks to directly link the in vivo neurop ...

2010

Perceptual learning: why mice do not play backgammon

Elisa Tartaglia

Perceptual learning is the ability to modify perception through practice. As a form of brain plasticity, perceptual learning has been studied for more than thirty years in different fields including psychology, neurophysiology and computational neuroscienc ...

EPFL2009

Neural modeling of the cortical processes underlying imitative behaviors

Eric Sauser

Imitation is the ability to recognize, learn and reproduce the actions of others. In addition to facilitating the transmission of knowledge and skills, it has been suggested that this fundamental cognitive capacity is at the origin of other human faculties ...

EPFL2008

Grouping in the shine-through effect

Michael Herzog

How the elements of a visual scene are grouped into objects is one of the most fundamental but still poorly understood questions in visual neuroscience. Most investigations of perceptual grouping focus on static stimuli, neglecting temporal aspects. Using ...

Springer-Verlag2008

Evolving Neuromodulatory Topologies for Reinforcement Learning-like Problems

Dario Floreano, Claudio Mattiussi, Peter Dürr, Andrea Soltoggio

Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advantage. Recent studies suggest that neuromodulatory dynamics are a key factor in reg ...

IEEE Press2007

Neuroevolution with Analog Genetic Encoding

Dario Floreano, Claudio Mattiussi, Peter Dürr

The evolution of artificial neural networks (ANNs) is often used to tackle difficult control problems. There are different approaches to the encoding of neural networks in artificial genomes. Analog Genetic Encoding (AGE) is a new implicit method derived f ...

2006

Computational Models for Generic Cortical Microcircuits

Henry Markram

The human nervous system processes a continuous stream of multi-modal input from a rapidly changing environment. A key challenge for neural modeling is to explain how the neural microcircuits (columns, minicolumns, etc.) in the cerebral cortex whose anatom ...

Chapman & Hall/CRC2004