We review different functions involved in visual perception that have been integrated by a model based on the biased competition hypothesis. Attentional top-down bias guides the dynamics to concentrate at a given spatial location or on given features. The model integrates, in a unifying form, the explanation of several existing types of experimental data obtained at different levels of investigation. At the microscopic level, single cell recordings are simulated. At the mesoscopic level of cortical areas, results of functional magnetic resonance imaging (fMRI) studies are reproduced. Finally, at the macroscopic level, psychophysical experiments like visual search tasks are also described by the model
The psychophysical evidence for "selective attention " originates mainly from visual searc...
AbstractThe biased competition theory of selective attention has been an influential neural theory o...
Shifting attention away from a visual stimulus reduces, but does not abolish, visual discrimination ...
We review different functions involved in visual perception that have been integrated by a model bas...
In the present work we follow a computational neuroscience approach in order to study the role of at...
A computational neuroscience framework is proposed to better understand the role and the neuronal co...
We present a physiologically constrained neural dynamical model of the visual system for the organiz...
A computational cognitive neuroscience approach was used to examine processes of visual attention in...
AbstractWe describe a model of invariant visual object recognition in the brain that incorporates fe...
When we observe our visual environment, we do not perceive all its components as being equally inter...
We present new simulation results, in which a computational model of interacting visual neurons simu...
& Feedback connections are a prominent feature of cortical anatomy and are likely to have a sign...
We use a computational neuroscience approach to study the role of feature-based attention in visual ...
Feedback connections are a prominent feature of cortical anatomy and are likely to have a significan...
A typical scene contains many different objects that compete for neural representation due to the li...
The psychophysical evidence for "selective attention " originates mainly from visual searc...
AbstractThe biased competition theory of selective attention has been an influential neural theory o...
Shifting attention away from a visual stimulus reduces, but does not abolish, visual discrimination ...
We review different functions involved in visual perception that have been integrated by a model bas...
In the present work we follow a computational neuroscience approach in order to study the role of at...
A computational neuroscience framework is proposed to better understand the role and the neuronal co...
We present a physiologically constrained neural dynamical model of the visual system for the organiz...
A computational cognitive neuroscience approach was used to examine processes of visual attention in...
AbstractWe describe a model of invariant visual object recognition in the brain that incorporates fe...
When we observe our visual environment, we do not perceive all its components as being equally inter...
We present new simulation results, in which a computational model of interacting visual neurons simu...
& Feedback connections are a prominent feature of cortical anatomy and are likely to have a sign...
We use a computational neuroscience approach to study the role of feature-based attention in visual ...
Feedback connections are a prominent feature of cortical anatomy and are likely to have a significan...
A typical scene contains many different objects that compete for neural representation due to the li...
The psychophysical evidence for "selective attention " originates mainly from visual searc...
AbstractThe biased competition theory of selective attention has been an influential neural theory o...
Shifting attention away from a visual stimulus reduces, but does not abolish, visual discrimination ...