A feedback model of visual attention.
Feedback connections are a prominent feature of cortical anatomy and are likely to have a significant functional role in neural information processing. We present a neural network model of cortical feedback that successfully simulates neurophysiological data associated with attention. In this domain, our model can be considered a more detailed, and biologically plausible, implementation of the biased competition model of attention. However, our model is more general as it can also explain a variety of other top-down processes in vision, such as figure/ground segmentation and contextual cueing. This model thus suggests that a common mechanism, involving cortical feedback pathways, is responsible for a range of phenomena and provides a unified account of currently disparate areas of research.
Spratling
M W
MW
Center for Brain and Cognitive Development, Birkbeck College, London, UK. m.spratling @bbk.ac.uk
Johnson
M H
MH
D000465:Algorithms; D001288:Attention / Q000502:physiology*; D015350:Contrast Sensitivity / Q000502:physiology; D003463:Cues; D004594:Electrophysiology; D030141:Feedback, Psychological / Q000502:physiology*; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D017966:Pyramidal Cells / Q000502:physiology; D013569:Synapses / Q000502:physiology; D014793:Visual Cortex / Q000166:cytology / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*