Categorization Goals Modulate the Use of Natural Scene Statistics
Andrea De Cesarei1, Shari Cavicchi1, Antonia Micucci1
1University of Bologna.
Journal of Cognitive Neuroscience
|September 7, 2018
Summary
Categorization goals influence early visual processing of natural scenes, affecting how we perceive scene statistics. This impacts not only target identification but also fundamental perception, as shown by event-related potentials (ERPs).
Area of Science:
- Cognitive Neuroscience
- Visual Perception
- Computational Neuroscience
Background:
- Natural scene understanding relies on both bottom-up sensory input and top-down cognitive control.
- The interplay between these processes during scene categorization remains unclear.
- Event-related potentials (ERPs) offer a temporal window into neural dynamics.
Purpose of the Study:
- To investigate how categorization goals interact with bottom-up and top-down processes in natural scene perception.
- To determine the temporal dynamics of this interaction using electrophysiological and behavioral measures.
Main Methods:
- Participants categorized natural scenes based on different questions (e.g., object type, environment, element count).
- Behavioral responses and event-related potentials (ERPs) were recorded.
- Computational modeling was employed to analyze scene statistics and neural data.
Main Results:
- ERP differences between target and non-target scenes emerged at 250 ms, unaffected by categorization questions.
- Category-specific ERP differences (e.g., animal vs. vehicle) related to scene statistics appeared earlier.
- From 180 ms, these category-specific ERPs were modulated by the specific categorization question asked.
Conclusions:
- Categorization goals influence not only late decision-making stages but also early perceptual processing of scene statistics.
- Top-down influences dynamically shape visual perception at multiple temporal stages.
- This suggests a more integrated interaction between perception and cognition than previously assumed.
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