---
abstract: |
  Feedback connections are a prominent feature of cortical anatomy and are likely
  to have 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.
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creators_name:
  - family: Spratling
    given: M W
    honourific: ''
    lineage: ''
  - family: Johnson
    given: M H
    honourific: ''
    lineage: ''
date: 2004
date_type: published
datestamp: 2004-04-06
department: ~
dir: disk0/00/00/35/42
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eprint_status: archive
eprintid: 3542
fileinfo: /style/images/fileicons/application_pdf.png;/3542/1/cog_neurosci.pdf
full_text_status: public
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keywords: ~
lastmod: 2011-03-11 08:55:30
latitude: ~
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metadata_visibility: show
note: ~
number: 2
pagerange: 219-237
pubdom: FALSE
publication: Journal of Cognitive Neuroscience
publisher: ~
refereed: TRUE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 12
series: ~
source: ~
status_changed: 2007-09-12 16:51:33
subjects:
  - neuro-mod
  - comp-neuro-sci
  - comp-sci-neural-nets
  - percep-cog-psy
succeeds: ~
suggestions: ~
sword_depositor: ~
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thesistype: ~
title: A feedback model of visual attention
type: journalp
userid: 1040
volume: 16
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