Publication

Perceptual learning: why mice do not play backgammon

Related publications (103)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Cortical Columns, Models of

Sean Lewis Hill

The annual Computational Neuroscience Meeting (CNS) began in 1990 as a small workshop called Analysis and Modeling of Neural Systems. The goal of the workshop was to explore the boundary between neuroscience and computation. Riding on the success of severa ...

Springer2014

Perceptual Learning With Indiscriminable Stimuli

Lukasz Grzeczkowski, Fred Mast, Elisa Tartaglia

Perceptual learning is learning to perceive. For example, in a bisection task three parallel lines are presented. The central line is slightly offset towards the right or the left outer line. Observers indicate the offset direction. Training greatly improv ...

2014

Perceptual Learning With Only One Stimulus

Michael Herzog, Lukasz Grzeczkowski, Fred Mast, Elisa Tartaglia

Perceptual learning is learning to see. For example in a bisection task, three parallel lines are presented with the central line slightly offset towards the right or the left outer line. Participants indicate the offset direction. Training gradually impro ...

2014

Mobile and Online Learning Journal: Effects on Apprentices' Reflection in Vocational Education and Training

While learning journals (LJs) have been shown to support self-regulated learning strategies, reflection and learning outcomes in academic contexts, few studies have investigated their relevance in vocational education. A mobile and online learning journal ...

Springer2014

Assistive technology for supporting learning numeracy

Calculation depends on the majority of the abilities within the domain of general intelligence (Blair et al., 2005). Most major theories of intelligence include numeracy or quantitative thinking as one aspect of general cognitive skills (Kaufman et al., 20 ...

Psychology Press2014

On the Influence of Informed Agents on Learning and Adaptation Over Networks

Ali H. Sayed

Adaptive networks consist of a collection of agents with adaptation and learning abilities. The agents interact with each other on a local level and diffuse information across the network through their collaboration. In this work, we consider two types of ...

Institute of Electrical and Electronics Engineers, Inc., 345 E. 47 th St. NY NY 10017-2394 United States2013

Real-time model learning using Incremental Sparse Spectrum Gaussian Process Regression

Novel applications in unstructured and non-stationary human environments require robots that learn from experience and adapt autonomously to changing conditions. Predictive models therefore not only need to be accurate, but should also be updated increment ...

2013

No Stress With Perceptual Learning.

Michael Herzog, Maria del Carmen Sandi Perez, Aaron Michael Clarke, Carl Kristoffer Aberg

While stress has been shown to affect higher-level cognitive learning (such as learning to remember pictures of different emotional salience), it does not affect perceptual learning. ...

2013

Design and evaluation of the computer-based training program Calcularis for enhancing numerical cognition

This article presents the design and a first pilot evaluation of the computer-based training program Calcularis for children with developmental dyscalculia (DD) or difficulties in learning mathematics. The program has been designed according to insights on ...

Frontiers Media SA2013

Perceptual learning, roving and the unsupervised bias

Michael Herzog, Wulfram Gerstner, Carl Kristoffer Aberg, Nicolas Frémaux

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervise ...

Elsevier2012