Yetişkin Hipokampal Nörogenezinin Yarı-stokastik Nümerik Bir Modeli

Dentat girusta (DG) görülen yetişkin nörogenezinin hipokampal bellek ağlarındaki işleve önemli bir katkı sunduğu kabul edilmektedir. Sunulan ayrık sayısal model DG'de bulunan nöral progenitör hücre (NPH) popülasyonlarında ve bu süreçlerin ürünlerindeki (immatür nöron, astrosit ve oligodendrosit popülasyonları) temporal değişimleri modellemeyi amaçlamaktadır. Süreçler toplam hacimde bir limitin olmadığı ve nörogenezi yönlendiren tüm kimyasal ve fiziksel düzenleyicilerin devamlı ulaşılabilir olduğu ideal bir ortamda tanımlanmıştır. Sistem üç temel seviyede bağımsız olarak çalışmaktadır. Her seviye nörogenez süreçlerindeki bir aşama olarak tanımlanmıştır ve popülasyonlar üç temel hücre tipinden oluşmaktadır: Tip I (radyal glia), tip II (geçici çoğalan hücre) ve tip III (nöroblast). Hücre kaderi, her hücre tipi için bir popülasyon limiti olan yarı-stokastik bir süreç (bir seçim) olarak sisteme eklenmiştir. Sunulan model, ayrık süreçlere dayanmasına ve basitleştirilmiş bir yaklaşım izlemesine rağmen, yetişkin nörogenezinin sayısal bir taslağını başarılı şekilde üretmektedir ve farklı modülasyonlarla bir hipokampal trisinaptik devre ağına yerleştirilebilir.

Anahtar Kelimeler:

Yetişkin nörogenezi, Subgranüler zon, Hesaplamalı model

A Semi-stochastic Numerical Model of Adult Hippocampal Neurogenesis

Adult neurogenesis in dentate gyrus (DG) is a prominent contributor in the dynamics of hippocampal memory networks. This discrete model aims to estimate the temporal changes in the neural progenitor cell (NPC) populations in DG, together with the products of differentiation – immature neurons, astrocytes and oligodendrocytes. The dynamics are described in an ideal environment, where there is no limit for the total volume and all required chemical and physical cues that direct neurogenesis are continuously available. The system works independently on three levels. Each level is defined as the dynamics in a stage of neurogenesis with three types of NPCs: type I cell (radial glia), type II cell (transiently amplifying cells) and type III cell (neuroblasts). Cell fate was introduced as a semi-stochastic process (a choice) with a population limit for each cell type. Although it is based on discrete processes and has a rather simplistic approach, the simulations successfully provide a numerical template for adult neurogenesis, which can be further modified and implemented in a hippocampal trisynaptic loop network.

Keywords:

Adult neurogenesis, Subgranular zone, Computational model,

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