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Automatic detection of orientation variance.

Szonya Durant1, István Sulykos2, István Czigler2

  • 1Department of Psychology, Royal Holloway, University of London, Egham, TW20 OEX, UK.

Neuroscience Letters
|August 21, 2017
PubMed
Summary

Humans automatically perceive visual scene statistics, distinguishing ordered from disordered patterns. This finding, based on visual mismatch negativity (vMMN) measurements, suggests automatic encoding of scene properties in neural responses.

Keywords:
EEGERPEntropyGistMismatch negativityOrientationVisual perception

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Area of Science:

  • Cognitive Neuroscience
  • Visual Perception
  • Neuroscience

Background:

  • Rapidly extracting visual scene statistics is key to perceiving the 'gist' of an image.
  • The brain's ability to automatically detect statistical differences between scenes remains an open question.

Purpose of the Study:

  • To investigate neural evidence for automatic, unattended detection of statistical differences between visual scenes.
  • To determine if the brain processes scene 'order' versus 'disorder' categorically.

Main Methods:

  • Measured Visual Mismatch Negativity (vMMN), an early neural response.
  • Presented sequences of oriented patterns with varying orientation variance (ordered vs. disordered).
  • Used an oddball paradigm with frequent and rare stimuli to elicit vMMN.

Main Results:

  • A significant vMMN was observed when a disordered stimulus followed ordered stimuli.
  • This suggests that 'ordered' and 'disordered' visual scenes are perceived categorically.
  • The variance in pattern orientation was automatically encoded in neural responses.

Conclusions:

  • The human visual system automatically encodes statistical properties of scenes, such as orientation variance.
  • vMMN provides neural evidence for the automatic and unattended detection of scene-level statistical differences.
  • This automatic processing contributes to the rapid perception of visual 'gist'.