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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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A Computational Framework to Study Hierarchical Processing in Visual Narratives.

Aditya Upadhyayula1, Neil Cohn2

  • 1Department of Psychological & Brain Sciences, Washington University in St. Louis.

Cognitive Science
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PubMed
Summary
This summary is machine-generated.

This study introduces a computational framework to explore hierarchical structures in visual narrative comprehension. Findings suggest that human processing aligns with hierarchical grammar, unlike flattened models.

Keywords:
Computational psycholinguisticsHidden Markov modelsHierarchical grammarLanguage modelsProbabilistic Earley parserVisual narratives

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Area of Science:

  • Cognitive Science
  • Computational Linguistics
  • Psycholinguistics

Background:

  • Theories of visual narrative comprehension often propose hierarchical grammar-based mechanisms.
  • Empirical investigation into the hierarchical properties of visual narratives remains limited.

Purpose of the Study:

  • To develop and test a computational framework for analyzing hierarchy in visual narratives.
  • To compare computational models with behavioral data to infer cognitive processing mechanisms.

Main Methods:

  • A computational framework inspired by psycholinguistics was developed.
  • A segmentation task was used to collect behavioral data on visual narrative boundaries.
  • Three models (Earley parser, Hidden Markov Model, n-gram) were employed to predict segmentation preferences.

Main Results:

  • Participant segmentation preferences were significantly predicted by visual narrative grammar.
  • The Earley parser, utilizing hierarchical grammar with recursion, better matched behavioral data than flattened grammar models (HMM, n-gram).

Conclusions:

  • Human visual narrative comprehension appears to involve hierarchical processing, consistent with grammatical structures.
  • This research opens new avenues for understanding the cognitive architecture of mental representations beyond linguistic systems.