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The Role of Set Size and Attention in Face Ensemble Processing
Dmitry Koch1,2, Evgenia Fedorova1, Daria Kleeva3
1Cognitive Research Lab, HSE University, Moscow, Russia.
The European Journal of Neuroscience
|May 26, 2026
Summary
Face ensemble perception involves automatic sensory processing and attention-dependent comparison. Set size influences attentional demands, with larger sets requiring more focus for accurate emotional expression analysis.
Area of Science:
- Cognitive Neuroscience
- Visual Perception
Background:
- The visual system extracts statistical information from faces via ensemble representation.
- Automaticity of face ensemble encoding is debated, with theories suggesting automatic vs. attention-dependent processing.
- Set size variations (group vs. crowd) may influence attentional requirements.
Purpose of the Study:
- Investigate the automaticity of face ensemble encoding.
- Examine the role of set size and attention in processing facial statistics.
- Determine if ensemble extraction alone is sufficient for prediction.
Main Methods:
- Electroencephalography (EEG) recorded event-related potentials (ERP) from 35 participants.
- Three tasks were used: implicit (fixation), explicit (mean emotion detection), and categorization (emotion proportion).
- Analysis focused on early ERP components, P3, LPP, and theta-band oscillations.
Main Results:
- Early ERP components showed set size effects across all tasks, indicating automatic sensory processing.
- Detection of average emotional expressions required explicit attention, reflected in P3 and LPP.
- Theta-band oscillations supported findings only in the explicit condition for group-based set sizes.
- Ensemble extraction alone did not suffice for prediction formation.
Conclusions:
- Face ensemble perception integrates automatic sensory registration with attention-dependent statistical comparison.
- Attentional engagement is modulated by set size, with larger sets demanding more resources.
- Ensemble statistics processing is a complex process influenced by task demands and set characteristics.
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