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How the Stroop Effect Arises from Optimal Response Times in Laterally Connected Self-Organizing Maps (2025)
Divya Prabhakaran
,
Uli Grasemann
,
Swathi Kiran
,
Risto Miikkulainen
The Stroop effect refers to cognitive interference in a color-naming task: When the color and the word do not match, the response is slower and more likely to be incorrect. The Stroop task is used to assess cognitive flexibility, selective attention, and executive function. This paper implements the Stroop task with self-organizing maps (SOMs): Target color and the competing word are inputs for the semantic and lexical maps, associative connections bring color information to the lexical map, and lateral connections combine their effects over time. The model achieved an overall accuracy of 84.2%, with significantly fewer errors and faster responses in congruent compared to no-input and incongruent conditions. The model's effect is a side effect of optimizing response times, and can thus be seen as a cost associated with overall efficient performance. The model can further serve studying neurologically-inspired cognitive control and related phenomena.
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Citation:
arXiv:2502.02831
, 2025.
Bibtex:
@article{prabhakaran:arxiv25, title={How the Stroop Effect Arises from Optimal Response Times in Laterally Connected Self-Organizing Maps}, author={Divya Prabhakaran and Uli Grasemann and Swathi Kiran and Risto Miikkulainen}, journal={arXiv:2502.02831}, month={ }, url="http://nn.cs.utexas.edu/?prabhakaran:arxiv25", year={2025} }
People
Uli Grasemann
Postdoctoral Alumni
uli [at] cs utexas edu
Swathi Kiran
Collaborator
kirans [at] bu edu
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Divya Prabhakaran
Ph.D. Student
divyapr [at] cs utexas edu
Projects
Computational and Behavioral Evidence for Bilingual Aphasia Rehabilitation
2008 - 2011
Software/Data
BiLex
Download at GitHub
.
A self-organizing map model of bilingual aphasia. ...
2021
Areas of Interest
Natural Language Processing (Cognitive)
Control
Cognitive Science
Brain and Cognitive Disorders
Computational Neuroscience