Computational neuroscience models can be used to understand the diminished stability and
noisy neurodynamical behaviour of prefrontal cortex networks in schizophrenia. These …

Our understanding of cortical electrophysiology and anatomy at the single-cell level has led
to the present day insight in to the function of connections linking cortical areas. This made it …

We aim to model the top-down attention of a convolutional neural network (CNN) classifier
for generating task-specific attention maps. Inspired by a top-down human visual attention …

The time course of perceptual choice is discussed in a model of gradual, leaky, stochastic,
and competitive information accumulation in nonlinear decision units. Special cases of the …

Traditional views of visual processing suggest that early visual neurons in areas V1 and V2
are static spatiotemporal filters that extract local features from a visual scene. The extracted …

According to conventional neurobiological accounts of visual attention, attention serves to
enhance extrastriate neuronal responses to a stimulus at one spatial location in the visual …

Chelazzi, Leonardo, John Duncan, Earl K. Miller, and Robert Desimone. Responses of
neurons in inferior temporal cortex during memory-guided visual search. J. Neurophysiol …

A neural theory of visual attention (NTVA) is presented. NTVA is a neural interpretation of C.
Bundesen's (1990) theory of visual attention (TVA). In NTVA, visual processing capacity is …

The authors present a theory of how relational inference and generalization can be
accomplished within a cognitive architecture that is psychologically and neurally realistic …

The derivation, exposition, and justification of the Selective Tuning model of vision and
attention. Although William James declared in 1890," Everyone knows what attention is," …