We present the case for a role of biologically plausible neural network modeling in bridging
the gap between physiology and behavior. We argue that spiking-level networks can allow …

The ability to notice relevant visual information has been assumed to be determined both by
the relative salience of relevant information compared with distracters within a given display …

Several models of attention explain how a priori knowledge about stimulus characteristics
results in modulations of neural activity at the time of stimulus presentation and, in turn …

Computational models of visual attention have become popular over the past decade, we
believe primarily for two reasons: First, models make testable predictions that can be …

We present new simulation results, in which a computational model of interacting visual
neurons simultaneously predicts the modula (cid: 173) tion of spatial vision thresholds by …

Cognitive behaviour requires complex context-dependent processing of information that
emerges from the links between attentional perceptual processes, working memory and …

With modern neurophysiological methods able to record neural activity throughout the visual
pathway in the context of arbitrarily complex visual stimulation, our understanding of visual …

Interest in the modeling of visual attention and cognition is strong with the number of models
growing quickly. It thus becomes important to try to consolidate what all this activity has …

Neuroscience is inherently interdisciplinary, rapidly expanding beyond its roots in biological
sciences to many areas of the social and physical sciences. This expansion has led to more …

Attentional processes have been studied using all the methods of cognitive neuroscience.
Brain imaging in humans and single-cell electrophysiology in macaque monkeys offer …