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The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents
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Brain size does not predict learning strategies in a serial reversal learning test.

Annika Boussard1, Séverine D Buechel2, Mirjam Amcoff2

  • 1Department of Zoology/Ethology, Stockholm University, Svante Arrhenius väg 18B, 10691 Stockholm, Sweden annika.boussard@zoologi.su.se.

The Journal of Experimental Biology
|June 21, 2020
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Summary

Brain size in guppies influences learning and memory, but not efficient strategy shifts during reversal learning tasks. Larger brains improved performance but did not fully explain differences in learning strategies.

Keywords:
Behavioural flexibilityCognitive abilityMemory

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Area of Science:

  • Behavioral Ecology
  • Neuroscience
  • Evolutionary Biology

Background:

  • Reversal learning assays assess associative learning and behavioral flexibility across species.
  • Larger relative brain size is hypothesized to enhance learning ability and flexibility, explaining interspecific variation in performance.

Purpose of the Study:

  • To experimentally test the hypothesis that larger relative brain size enhances behavioral flexibility at the intraspecific level.
  • To investigate the relationship between brain size, neuron number, and performance in serial reversal learning using guppies.

Main Methods:

  • Utilized guppies (Poecilia reticulata) artificially selected for small and large relative brain sizes.
  • Assessed 96 individuals over 10 serial reversals in a binary discrimination task.
  • Measured learning performance, memory, and efficient learning strategies.

Main Results:

  • Learning performance and memory were significantly predicted by relative brain size.
  • Differences in efficient learning strategies were not explained by brain size or neuron number.
  • Intraspecific variation in brain size impacted learning and memory, but not strategy adoption.

Conclusions:

  • Variation in brain size and neuron number is crucial for differences in learning performance and memory.
  • These brain-related differences are insufficient to account for the significant variation in efficient learning strategies observed at higher taxonomic levels.