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Endogenous attention biases transformational apparent motion based on high-level shape representations.

Sharif Saleki1,2, Kirsten Ziman1,3, Kevin C Hartstein1,4

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Summary
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Endogenous attention influences transformational apparent motion (TAM) by operating on high-level shape representations, not low-level visual features. This suggests attention guides perceived motion based on shape identity, regardless of how the shape is defined.

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Area of Science:

  • Cognitive Neuroscience
  • Visual Perception
  • Attention Studies

Background:

  • Transformational apparent motion (TAM) describes the illusory morphing perceived when shapes connect.
  • Endogenous attention, directed voluntarily, can influence the perceived direction of TAM.
  • It remains unclear if attention operates on low-level visual features or high-level shape representations.

Purpose of the Study:

  • To investigate whether endogenous attention influences TAM via high-level, feature-independent shape representations or low-level, feature-specific ones.
  • To compare the effect of attention on TAM for first-order (luminance-defined) and second-order (texture-defined) shapes.

Main Methods:

  • Tested the influence of endogenous attention on TAM using both first-order and second-order visual displays.
  • These displays featured common shapes but differed in their defining attributes (luminance vs. texture contrast).
  • Measured the magnitude of directional bias and timing of TAM under attentional manipulation.

Main Results:

  • Endogenous attention exerted a similar influence on TAM for both first-order and second-order objects.
  • Both the magnitude of directional bias and the timing of TAM were similarly affected by attention across display types.
  • No significant difference was observed in how attention modulated TAM based on shape-defining features.

Conclusions:

  • Endogenous attention biases the perceived direction of TAM by operating on high-level shape representations.
  • These high-level representations are invariant to the low-level visual features (luminance, texture) that define the shapes.
  • Findings support a four-stage model of TAM, highlighting the role of feature-independent shape processing in visual interpolation.