Concept

Psychophysique

Publications associées (78)

The effects of visual distractors on serial dependence

Attractive serial dependence occurs when perceptual decisions are attracted toward previous stimuli. This effect is mediated by spatial attention and is most likely to occur when similar stimuli are attended at nearby locations. Attention, however, also in ...

Rockville2023

Tuning perception and decisions to temporal context

David Pascucci

Recent work suggests that serial dependence, where perceptual decisions are biased toward previous stimuli, arises from the prior that sensory input is temporally correlated. However, existing studies have mostly used random stimulus sequences that do not ...

Cambridge2023

Attractive and repulsive serial dependence: The role of task relevance, the passage of time, and the number of stimuli

David Pascucci, Gizay Ceylan

Visual decisions are attracted toward features of previous stimuli. This phenomenon, termed serial dependence, has been related to a mechanism that integrates present visual input with stimuli seen up to 10 to 15 s in the past. It is believed that this mec ...

2023

Hydraulically Amplified Electrostatic Taxels (HAXELs) for Full Body Haptics

Herbert Shea, Edouard Franck Vincent Gustave Leroy

The ability to mechanically stimulate touch receptors over the entire body is a key feature for fully immersive and highly realistic virtual reality experience. Haptic stickers, flexible arrays of HAXELs (hydraulically amplified TAXels), that enable cutane ...

WILEY2023

The full-body illusion changes visual depth perception

Olaf Blanke, Bruno Herbelin, Sophie Jacqueline Andrée Betka

Knowing where objects are relative to us implies knowing where we are relative to the external world. Here, we investigated whether space perception can be influenced by an experimentally induced change in perceived self-location. To dissociate real and ap ...

2023

Learning continuous-time working memory tasks with on-policy neural reinforcement learning

Davide Zambrano

An animals' ability to learn how to make decisions based on sensory evidence is often well described by Reinforcement Learning (RL) frameworks. These frameworks, however, typically apply to event-based representations and lack the explicit and fine-grained ...

2021

Adapting Virtual Embodiment through Reinforcement Learning

Olaf Blanke, Ronan Boulic, Bruno Herbelin, Yawen Hou

In Virtual Reality, having a virtual body opens a wide range of possibilities as the participant's avatar can appear to be quite different from oneself for the sake of the targeted application (e.g. for perspective-taking). In addition, the system can part ...

2021

How crowding challenges (feedforward) convolutional neural networks

Michael Herzog, Ben Henrik Lönnqvist, Gregory Francis, Adrien Christophe Doerig, Alban Bornet, Lynn Schmittwilken

Are (feedforward) convolutional neural networks (CNNs) good models for the human visual system? Here, we used visual crowding as a well-controlled psychophysical test to probe CNNs. Visual crowding is a ubiquitous breakdown of object recognition in the hum ...

2021

Shrinking Bouma's window: How to model crowding in dense displays

Michael Herzog, Gregory Francis, Adrien Christophe Doerig, Alban Bornet

In crowding, perception of a target deteriorates in the presence of nearby flankers. Traditionally, it is thought that visual crowding obeys Bouma's law, i.e., all elements within a certain distance interfere with the target, and that adding more elements ...

PUBLIC LIBRARY SCIENCE2021

Individual differences in the perception of visual illusions are stable across eyes, time, and measurement methods

Michael Herzog, Aline Françoise Cretenoud, Lukasz Grzeczkowski

Vision scientists have tried to classify illusions for more than a century. For example, some studies suggested that there is a unique common factor for all visual illusions. Other studies proposed that there are several subclasses of illusions, such as il ...

2021

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