Your browser doesn't support javascript.
loading
Simulation of developing human neuronal cell networks.
Lenk, Kerstin; Priwitzer, Barbara; Ylä-Outinen, Laura; Tietz, Lukas H B; Narkilahti, Susanna; Hyttinen, Jari A K.
Afiliação
  • Lenk K; Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, PL100, Tampere, Finland. kerstin.lenk@tut.fi.
  • Priwitzer B; Faculty of Engineering and Computer Science, Brandenburg University of Technology Cottbus-Senftenberg, Platz der Deutschen Einheit 1, 03046, Cottbus, Germany.
  • Ylä-Outinen L; NeuroGroup, Institute of Biomedical Technology, University of Tampere, BioMediTech, PL100, Tampere, Finland.
  • Tietz LH; Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, PL100, Tampere, Finland.
  • Narkilahti S; NeuroGroup, Institute of Biomedical Technology, University of Tampere, BioMediTech, PL100, Tampere, Finland.
  • Hyttinen JA; Department of Electronics and Communications Engineering, Tampere University of Technology, BioMediTech, PL100, Tampere, Finland.
Biomed Eng Online ; 15(1): 105, 2016 Aug 30.
Article em En | MEDLINE | ID: mdl-27576323
BACKGROUND: Microelectrode array (MEA) is a widely used technique to study for example the functional properties of neuronal networks derived from human embryonic stem cells (hESC-NN). With hESC-NN, we can investigate the earliest developmental stages of neuronal network formation in the human brain. METHODS: In this paper, we propose an in silico model of maturating hESC-NNs based on a phenomenological model called INEX. We focus on simulations of the development of bursts in hESC-NNs, which are the main feature of neuronal activation patterns. The model was developed with data from developing hESC-NN recordings on MEAs which showed increase in the neuronal activity during the investigated six measurement time points in the experimental and simulated data. RESULTS: Our simulations suggest that the maturation process of hESC-NN, resulting in the formation of bursts, can be explained by the development of synapses. Moreover, spike and burst rate both decreased at the last measurement time point suggesting a pruning of synapses as the weak ones are removed. CONCLUSIONS: To conclude, our model reflects the assumption that the interaction between excitatory and inhibitory neurons during the maturation of a neuronal network and the spontaneous emergence of bursts are due to increased connectivity caused by the forming of new synapses.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Neurológicos / Rede Nervosa / Neurônios Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Revista: Biomed Eng Online Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Finlândia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Neurológicos / Rede Nervosa / Neurônios Tipo de estudo: Qualitative_research Limite: Humans Idioma: En Revista: Biomed Eng Online Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Finlândia