How the Stroop Effect Arises from Optimal Response Times in Laterally Connected Self-Organizing Maps

Area of Science:

• Cognitive Science
• Computational Neuroscience
• Artificial Intelligence

Background:

• The Stroop effect demonstrates cognitive interference in color-naming tasks.
• It is a key tool for assessing cognitive flexibility, selective attention, and executive functions.
• Understanding this effect is crucial for modeling human cognitive processes.

Purpose of the Study:

• To implement the Stroop task using self-organizing maps (SOMs).
• To investigate how computational models can replicate and explain the Stroop effect.
• To explore the role of associative and lateral connections in cognitive control.

Main Methods:

• Utilized self-organizing maps (SOMs) as a computational framework.
• Input variables included target color and competing word for semantic and lexical maps.
• Simulated associative and lateral connections to model information processing over time.

Main Results:

• Achieved an overall accuracy of 84.2% in the implemented model.
• Demonstrated significantly fewer errors and faster responses in congruent conditions compared to incongruent and no-input conditions.
• The observed Stroop-like effect emerged as a byproduct of optimizing speed-accuracy tradeoffs.

Conclusions:

• The SOM-based model successfully replicates key aspects of the Stroop effect.
• The findings suggest that cognitive interference can be an emergent property of efficient information processing.
• This model provides a foundation for studying neurologically-inspired cognitive control mechanisms.