Open AccessRecurrent loops: Incorporating prediction error and semantic/episodic theories into Drosophila associative memory models
Author(s) -
Horiuchi Junjiro
Publication year - 2019
Publication title -
genes, brain and behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.315
H-Index - 91
eISSN - 1601-183X
pISSN - 1601-1848
DOI - 10.1111/gbb.12567
Subject(s) - mushroom bodies , content addressable memory , associative property , semantic memory , computer science , episodic memory , cognitive science , cognitive psychology , artificial intelligence , psychology , neuroscience , cognition , artificial neural network , biology , mathematics , drosophila melanogaster , biochemistry , pure mathematics , gene
In 2003, Martin Heisenberg et al. presented a model of how associative memories could be encoded and stored in the insect brain. This model was extremely influential in the Drosophila memory field, but did not incorporate several important mammalian concepts, including ideas of separate episodic and semantic types of memory and prediction error hypotheses. In addition, at that time, the concept of memory traces recurrently entering and exiting the mushroom bodies, brain areas where associative memories are formed and stored, was unknown. In this review, I present a simple updated model incorporating these ideas, which may be useful for future studies.