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Concurrent cognitive processes in rat serial pattern learning: II. Discrimination learning, rule learning, chunk length, and multiple-item memories. | LitMetric

AI Article Synopsis

  • The experiment studied how rats learn and recognize complex serial patterns with different chunk sizes.
  • Three distinct training approaches were used with varying lengths of element chunks, culminating in a violation element to test their learning.
  • Results showed that rats relied on various memory and learning processes, such as location cues, chunk recognition, and recalling multiple items, to successfully navigate these patterns.

Article Abstract

The current experiment examined the factors that determine acquisition for elements of highly structured serial patterns. Three groups of rats were trained on three patterns with parallel rule-based hierarchical structure, but with 3-, 4-, or 5-element chunks, each with a final violation element. Once rats mastered their patterns, probe patterns were introduced to answer several questions. To assess the extent to which the learned response pattern depended on intrachamber location cues for anticipating different element types, Spatial Shift Probes shifted the starting lever of patterns to locations that positioned chunk boundaries where they had never been experienced during training. To assess the extent to which a phrasing cue is necessary for rats to perform a chunk-boundary response, a Cue Removal Probe tested whether rats would produce a chunk-boundary response in the correct serial position if the phrasing cue was omitted. To assess the extent to which cues from multiple trials leading up to the violation element are required to anticipate the violation element, Multiple-Item Memory Probes required rats to make an unexpected response on one of the elements in the last two chunks of the pattern prior to the violation element. The results indicated that rats used multiple concurrent learning and memory processes to master serial patterns, including discrimination learning, rule learning, encoding of chunk length, and multiple-item memories.

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Source
http://dx.doi.org/10.1002/jeab.186DOI Listing

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