Global cognitive graph properties dynamics of hippocampal formation
Konstantin Sorokin, Andrey Zaitsew, Aleksandr Levin, German Magai,, Maxim Beketov, Vladimir Sotskov

TL;DR
This study constructs and analyzes dynamic neural connection graphs in the rodent hippocampus, revealing continuous memory updates during exploration despite overall network stability.
Contribution
It introduces new methods for building and analyzing dynamic cognitive neural graphs, highlighting how neural relations evolve during spatial exploration.
Findings
Neural connections constantly change during exploration.
Global hippocampal network remains relatively stable.
Memory is dynamically updated even in familiar environments.
Abstract
In the present study we have used a set of methods and metrics to build a graph of relative neural connections in a hippocampus of a rodent. A set of graphs was built on top of time-sequenced data and analyzed in terms of dynamics of a connection genesis. The analysis has shown that during the process of a rodent exploring a novel environment, the relations between neurons constantly change which indicates that globally memory is constantly updated even for known areas of space. Even if some neurons gain cognitive specialization, the global network though remains relatively stable. Additionally we suggest a set of methods for building a graph of cognitive neural network.
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Taxonomy
TopicsCognitive Science and Mapping · Neural Networks and Applications · Fractal and DNA sequence analysis
