Frontiers in Behavioral Neuroscience (Oct 2022)

How common is a common error term? The rules that govern associative learning in sensory preconditioning and second-order conditioning

  • Travis P. Todd,
  • Nathan M. Holmes

DOI
https://doi.org/10.3389/fnbeh.2022.954646
Journal volume & issue
Vol. 16

Abstract

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In standard (first-order) Pavlovian conditioning protocols, pairings of an initially neutral conditioned stimulus (CS) and a biologically significant unconditioned stimulus (US) result in the formation of a CS-US association. The strength of this association is theoretically regulated by prediction error: specifically, the difference between the total level of conditioning supported by the US and the degree to which it is predicted by all stimuli present (i.e., a common error term). In higher-order conditioning protocols (e.g., sensory preconditioning and second-order conditioning), a Pavlovian CS is used to condition responses to other stimuli with which it is paired. At present, it is unknown whether error-correction processes regulate associative learning in higher-order conditioning and, if so, whether these processes are the same as those that regulate formation of a CS-US association in first-order conditioning. Here we review studies that have provided findings relevant to this question: specifically, studies that have examined blocking and/or inhibitory learning in sensory preconditioning and second-order conditioning. These studies show that: (1) animals can form inhibitory associations between relatively neutral sensory stimuli; (2) the learning that occurs in sensory preconditioning and second-order conditioning can be blocked; and, finally, (3) a first-order CS can block conditioning to a second-order CS, and vice versa. The findings are taken to imply that a common error term regulates associative learning in higher-order conditioning, just as it regulates associative learning in first-order conditioning. They are discussed with respect to the nature of the error signal that underlies conditioning and future work that is needed to advance our understanding of the rules that govern different types of learning.

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