Volume 0 , Issue 1 , PP: 24-30, 2019 | Cite this article as | XML | Html | PDF | Full Length Article
Shubha Mishra 1 *
Proficient design division in dentate gyrus plays an imperative part in putting away data within the hippocampus. Current information of the structure and work of the hippocampus, entorhinal cortex, and dentate gyrus, in design partition are joined in this work. A three-layer feed-forward spiking neural network inspired by the rodent hippocampus an equipped with simplified synaptic and molecular mechanisms is developed. The aim of the study is to make a spiking neural network capable of pattern separation in imbalanced excitation/inhibition ratios caused by different levels of stimulations or network damage. This work presents a novel theory on the cellular mechanisms of robustness to damages to synapses and connectivity of neurons in dentate gyrus that results in imbalanced excitation-inhibition activity of neurons. This spiking neural network uses simplified molecular and cellular hypothetical mechanisms and demonstrates efficient storing of information in different levels of stimulation and can be implemented in cognitive robotics.
spiking neural networks , memory , dentate gyrus , pattern separation , imbalanced network , back-propagation , hippocampus
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