Attention deployment in natural scenes: Higher-order scene statistics rather than semantics modulate the N2pc...

Area of Science:

• Cognitive Psychology
• Neuroscience
• Computer Vision

Background:

• Visual search in natural scenes is complex.
• Understanding scene properties influencing search difficulty is crucial.

Purpose of the Study:

• To investigate whether low-level statistics, higher-level statistics, semantics, or layout affect visual search difficulty in natural scenes.
• To determine which scene properties make natural scenes effective distractors.

Main Methods:

• Three experiments were conducted with participants searching for a Gabor patch target.
• Backgrounds varied in preserved properties: natural scenes, 1/f noise (low-level statistics), textures (low- and higher-level statistics), and inverted scenes (statistics and semantics).
• Event-related potentials (ERPs), specifically the N2pc component, were measured as a marker of attentional selection.

Main Results:

• Reaction times were faster for targets on noise backgrounds and slower on inverted scenes compared to natural scenes and textures.
• The N2pc component showed shorter latency and higher amplitude for targets in noise compared to other backgrounds.
• Backgrounds contralateral to the target influenced performance similarly to the target side, with noise facilitating faster reactions and shorter N2pc latencies.

Conclusions:

• Natural scenes are more effective distractors than noise when searching for simple targets.
• This distractor effect stems from higher-order scene statistics, rather than semantic content or spatial layout.
• Scene statistics, particularly higher-order ones, play a significant role in modulating visual search efficiency and attentional processes.