Improving the Recall Performance of a Brain Mimetic Microcircuit Model

Cutsuridis, Vassilis (2019) Improving the Recall Performance of a Brain Mimetic Microcircuit Model. Cognitive Computation, 11 (5). pp. 644-655. ISSN 1866-9956

Full content URL:

Improving the Recall Performance of a Brain Mimetic Microcircuit Model
Published PDF

Request a copy
[img] PDF
Cutsuridis2019_Article_ImprovingTheRecallPerformanceO.pdf - Whole Document
Restricted to Repository staff only

Item Type:Article
Item Status:Live Archive


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, Computational neuroscience, Inhibition, Excitation, Bistratified cell, Schaffer collateral, Medial septum
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
B Subjects allied to Medicine > B140 Neuroscience
Divisions:College of Science > School of Computer Science
ID Code:36141
Deposited On:10 Jun 2019 13:05

Repository Staff Only: item control page