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Probabilistic reinforcement precludes transitive inference: A preliminary study.

Héctor O Camarena1, Óscar García-Leal2,3, Julieta Delgadillo-Orozco1

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Summary

Probabilistic reinforcement made transitive inference (TI) difficult for pigeons. Only one pigeon successfully learned TI, suggesting associative strength and positional ordering impact this cognitive process.

Keywords:
Symbolic Distance Effectassociative strengthprobabilistic reinforcementserial position effecttransitive inference

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Area of Science:

  • Cognitive Psychology
  • Animal Behavior
  • Neuroscience

Background:

  • Transitive inference (TI) is a logical reasoning process where a relationship between items can be inferred (e.g., if A>B and B>C, then A>C).
  • TI has been demonstrated in various species using simultaneous discrimination tasks, but its complexity under probabilistic reinforcement is less understood.

Purpose of the Study:

  • To investigate the effects of probabilistic reinforcement on transitive inference (TI) in pigeons (Columba Livia).
  • To determine if associative strength and positional ordering influence TI performance under uncertain reward conditions.

Main Methods:

  • Five pigeons were trained on a simultaneous discrimination task with probabilistic reinforcement (0.7 for positive stimuli, 0.3 for negative stimuli).
  • The task involved a linear series of stimuli (A>B>C>D>E), and TI was assessed by testing preferences between non-adjacent stimuli (e.g., B>D).

Main Results:

  • Only one out of five pigeons successfully reached the discrimination criterion for C+D-.
  • The pigeon that solved the C+D- discrimination was the only one capable of learning TI.
  • Correct response ratios did not predict performance on the B>D test, indicating TI was disrupted by probabilistic reinforcement.

Conclusions:

  • Probabilistic reinforcement significantly disrupts transitive inference (TI) in pigeons.
  • TI performance appears to be influenced by both associative strength and the positional ordering of stimuli.
  • Findings contribute to understanding the cognitive mechanisms underlying TI and support both associative and ordinal representation accounts.