A theoretical network model to analyse neurogenesis and synaptogenesis in the dentate gyrus
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Publication:858879
DOI10.1016/J.NEUNET.2006.07.007zbMath1102.92003OpenAlexW2006594778WikidataQ48407183 ScholiaQ48407183MaRDI QIDQ858879
Ingolf E. Dammasch, Konrad Lehmann, Markus Butz, Gertraud Teuchert-Noodt
Publication date: 11 January 2007
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.neunet.2006.07.007
apoptosiscell proliferationhippocampusnetwork modelrewiringhomoestatic plasticityneurogenesissynaptogenesis
Cites Work
- Unnamed Item
- Compensation type algorithms for neural nets: Stability and convergence
- Self-stabilization of neuronal networks. I. The compensation algorithm for synaptogenesis
- A simplified neuron model as a principal component analyzer
- ON THE PROPERTIES OF RANDOMLY CONNECTED McCULLOCH-PITTS NETWORKS: DIFFERENCES BETWEEN INPUT-CONSTANT AND INPUT-VARIANT NETWORKS
- Activity-dependent neural network development
- A logical calculus of the ideas immanent in nervous activity
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