Visual attention mitigates information loss in small- and large-scale neural codes

Trends Cogn Sci. 2015 Apr;19(4):215-26. doi: 10.1016/j.tics.2015.02.005. Epub 2015 Mar 11.


The visual system transforms complex inputs into robust and parsimonious neural codes that efficiently guide behavior. Because neural communication is stochastic, the amount of encoded visual information necessarily decreases with each synapse. This constraint requires that sensory signals are processed in a manner that protects information about relevant stimuli from degradation. Such selective processing--or selective attention--is implemented via several mechanisms, including neural gain and changes in tuning properties. However, examining each of these effects in isolation obscures their joint impact on the fidelity of stimulus feature representations by large-scale population codes. Instead, large-scale activity patterns can be used to reconstruct representations of relevant and irrelevant stimuli, thereby providing a holistic understanding about how neuron-level modulations collectively impact stimulus encoding.

Keywords: information theory; neural coding.; stimulus reconstruction; vision; visual attention.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Animals
  • Attention / physiology*
  • Brain / physiology*
  • Humans
  • Information Theory*
  • Neurons / physiology*
  • Visual Perception / physiology*