Publication

What is new in perceptual learning?

Publications associées (53)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Stimulus sampling as an exploration mechanism for fast reinforcement learning

Eleni Vasilaki, Walter Senn

Reinforcement learning in neural networks requires a mechanism for exploring new network states in response to a single, nonspecific reward signal. Existing models have introduced synaptic or neuronal noise to drive this exploration. However, those types o ...

Springer Verlag2009

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

Human perceptual learning by mental imagery

Michael Herzog, Fred Mast, Elisa Tartaglia, Laura Bamert

Perceptual learning is learning to perceive. For example, a radiologist is able to easily identify anomalies in medical images only after extended training. Theoretical and psychophysical studies [1-12] suggest that such improvements of performance are acc ...

Elsevier2009

Anesthesia prevents auditory perceptual learning

Michael Herzog, Alain Farron, Elisa Tartaglia, Carl Kristoffer Aberg

BACKGROUND: An auditory perceptual learning paradigm was used to investigate whether implicit memories are formed during general anesthesia. METHODS: Eighty-seven patients who had an American Society of Anesthesiologists physical status of I-III and were s ...

Lippincott, Williams & Wilkins2009

Perceptual learning of bisection stimuli under roving: slow and largely specific

Michael Herzog, Thomas Otto

In perceptual learning, performance often improves within a short time if only one stimulus variant is presented, such as a line bisection stimulus with one outer-line-distance. However, performance stagnates if two bisection stimuli with two outer-line-di ...

Association for Research in Vision and Ophthalmology2008

When does roving disrupt perceptual learning?

Michael Herzog, Elisa Tartaglia, Carl Kristoffer Aberg

Training with one type of a visual stimulus usually improves performance. When observers train with two or more stimulus types presented in random order (so-called roving), performance improves for certain stimulus types but not for others. To understand w ...

2008

EDITORIAL: Robot Programming By Demonstration

Aude Billard, Roland Siegwart

Programming by demonstration (PbD) is a key research topic in robotics. It impacts both fundamental research and application-oriented studies.Work in that area tackles the development of robust algorithms for motor control, motor learning, gesture recognit ...

2004

A recurrent model for perceptual learning

Michael Herzog

Perceptual learning has received enhanced interest during the last years both from theoreticians and experimentalists. Recent experimental results reveal that mechanisms underlying perceptual learning are more complex than previously expected, thereby ruli ...

Optical Society of America1999

Effects of biased feedback on learning and deciding in a vernier discrimination task

Michael Herzog

We investigate the influence of biased feedback on decision and learning processes in a vernier discrimination task. Subjects adjust their decision criteria and hence their responses according to biased external feedback. However, they do not use learning ...

Elsevier1999

Learning and Evolution

Dario Floreano

In the last few years several researchers have resorted to artificial evolution (e.g. genetic algorithms) and learning techniques (e.g. neural networks) for studying the interaction between learning and evolution. These studies have been conducted for two ...

1999