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Improving the Recall Performance of a Brain Mimetic Microcircuit Model

  • Vassilis CutsuridisEmail author
Article

Abstract

The recall performance of a well-established canonical microcircuit model of the hippocampus, a region of the mammalian brain that acts as a short-term memory, was systematically evaluated. All model cells were simplified compartmental models with complex ion channel dynamics. In addition to excitatory cells (pyramidal cells), four types of inhibitory cells were present: axo-axonic (axonic inhibition), basket (somatic inhibition), bistratified cells (proximal dendritic inhibition) and oriens lacunosum-moleculare (distal dendritic inhibition) cells. All cells’ firing was timed to an external theta rhythm paced into the model by external reciprocally oscillating inhibitory inputs originating from the medial septum. Excitatory input to the model originated from the region CA3 of the hippocampus and provided context and timing information for retrieval of previously stored memory patterns. Model mean recall quality was tested as the number of stored memory patterns was increased against selectively modulated feedforward and feedback excitatory and inhibitory pathways. From all modulated pathways, simulations showed recall performance was best when feedforward inhibition from bistratified cells to pyramidal cell dendrites is dynamically increased as stored memory patterns is increased with or without increased pyramidal cell feedback excitation to bistratified cells. The study furthers our understanding of how memories are retrieved by a brain microcircuit. The findings provide fundamental insights into the inner workings of learning and memory in the brain, which may lead to potential strategies for treatments in memory-related disorders.

Keywords

Hippocampus Inhibition Excitation Bistratified cell Schaffer collateral Medial septum 

Notes

Compliance with Ethical Standards

Conflict of Interest

The author declares that he has no competing interests.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

12559_2019_9658_MOESM1_ESM.doc (3.4 mb)
ESM 1 (DOC 3513 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Computer Science, Brayford PoolUniversity of LincolnLincolnUK

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