Modeling the influence of heavy ion beams on neurogenesis and functioning of hippocampal neural networks

Elena Kolesnikova,Aleksandr Bugay,S Bondarenko,V Burov,A Malakhov

doi:10.1051/epjconf/201920404007

Abstract

Radiation-induced impairment of hippocampal neurogenesis is one of serious factors associated with cognitive detriments after radiation therapy of brain cancers and realization of long-term manned space flights. The goal of this study is to develop a mathematical model describing radiation-induced changes in cellular populations participating in neurogenesis and how these alterations worsen the processing of information by hippocampus. Modeling results have demonstrated that heavy ions may cause non-reversible suppression of neurogenesis, which is followed by failure of pattern encoding and retrieval by hippocampal neural networks.

Highlights

Radiation-induced cognitive disfunction becomes a serious concern in hadron therapy and long-term manned space flights [1, 2]
Recovery to normal condition is more evident for NBs than immature granular cells (ImN), and the negative feedback regulation by the inflammatory response on proliferation begins to manifest at 30 days of postirradiation in NBs and at 60-90 days of postirradiation in ImNs
Neuroblasts have been found to be more sensitive to radiation treatment than NSC and ImN, the radiation-induced loss of ImN is observed at higher doses

Summary

Introduction

Radiation-induced cognitive disfunction becomes a serious concern in hadron therapy and long-term manned space flights [1, 2]. In recent years a number of neurocognitive detriments have been reported, including progressive deficits in short- and long-term memory loss, spatial orientation, visual motor processing and impaired learning. As it is well-known, hippocampus plays a key role in a short-term and long-term memory, integrating processes and plasticity of the brain. In order to predict any cognitive dysfunction, the existing models of neurogenesis need to be supplemented with functional models of neural networks reflecting the actual performance of neural cells in the process of cognition This is the goal of the present study

Objectives

Methods

Results

Conclusion