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<p>Semantic fluency tasks require participants to recall as many items as possible from a category (e.g., animals) within a fixed time. These tasks are known to produce heavy-tailed distributions of interresponse times (IRTs), a pattern also found in natural foraging. The present study examined whether long IRTs arise specifically at category transitions. Across three experiments, participants completed fluency tasks that varied in scope: recalling items from a single semantic category (animals), from two categories (animals and vegetables), or from letter-based categories (words beginning with <i>S</i> or <i>T</i>). IRTs were modeled against normal, lognormal, and power-law distributions, and transitions were identified using both behavioral ratings and algorithmic similarity measures. Results showed that lognormal distributions consistently provided the best fit at group and individual levels, confirming the heavy-tailed nature of memory search. The longest IRTs appeared immediately after, rather than during, a category switch, suggesting a brief adjustment period when participants begin exploring a new cluster of items. These findings support the view that memory retrieval operates according to principles of optimal foraging, highlighting shared dynamics across spatial, semantic, and abstract domains.</p>

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Investigating category transitions and interresponse times in fluency tasks

  • 期刊论文

  • 发表日期：

    2026年1月28日

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  • Corey M. Magaldino,
  • Eric L. Amazeen

摘要

Semantic fluency tasks require participants to recall as many items as possible from a category (e.g., animals) within a fixed time. These tasks are known to produce heavy-tailed distributions of interresponse times (IRTs), a pattern also found in natural foraging. The present study examined whether long IRTs arise specifically at category transitions. Across three experiments, participants completed fluency tasks that varied in scope: recalling items from a single semantic category (animals), from two categories (animals and vegetables), or from letter-based categories (words beginning with S or T). IRTs were modeled against normal, lognormal, and power-law distributions, and transitions were identified using both behavioral ratings and algorithmic similarity measures. Results showed that lognormal distributions consistently provided the best fit at group and individual levels, confirming the heavy-tailed nature of memory search. The longest IRTs appeared immediately after, rather than during, a category switch, suggesting a brief adjustment period when participants begin exploring a new cluster of items. These findings support the view that memory retrieval operates according to principles of optimal foraging, highlighting shared dynamics across spatial, semantic, and abstract domains.