Literature DB >> 21076203

From network structure to network reorganization: implications for adult neurogenesis.

Casey M Schneider-Mizell1, Jack M Parent, Eshel Ben-Jacob, Michal R Zochowski, Leonard M Sander.   

Abstract

Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells.

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Year:  2010        PMID: 21076203     DOI: 10.1088/1478-3975/7/4/046008

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  8 in total

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Review 2.  Targeting Neuronal Networks with Combined Drug and Stimulation Paradigms Guided by Neuroimaging to Treat Brain Disorders.

Authors:  Carl L Faingold; Hal Blumenfeld
Journal:  Neuroscientist       Date:  2015-07-06       Impact factor: 7.519

3.  Balancing Clinical and Pathologic Relevence in the Machine Learning Diagnosis of Epilepsy.

Authors:  Wesley T Kerr; Andrew Y Cho; Ariana Anderson; Pamela K Douglas; Edward P Lau; Eric S Hwang; Kaavya R Raman; Aaron Trefler; Mark S Cohen; Stefan T Nguyen; Navya M Reddy; Daniel H Silverman
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4.  Formation and Dynamics of Waves in a Cortical Model of Cholinergic Modulation.

Authors:  James P Roach; Eshel Ben-Jacob; Leonard M Sander; Michal R Zochowski
Journal:  PLoS Comput Biol       Date:  2015-08-21       Impact factor: 4.475

5.  Perspectives for computational modeling of cell replacement for neurological disorders.

Authors:  James B Aimone; Jason P Weick
Journal:  Front Comput Neurosci       Date:  2013-11-06       Impact factor: 2.380

6.  Computational models of neuron-astrocyte interaction in epilepsy.

Authors:  Vladislav Volman; Maxim Bazhenov; Terrence J Sejnowski
Journal:  Front Comput Neurosci       Date:  2012-08-13       Impact factor: 2.380

7.  Crosstalk among Epigenetic Pathways Regulates Neurogenesis.

Authors:  Emily M Jobe; Andrea L McQuate; Xinyu Zhao
Journal:  Front Neurosci       Date:  2012-05-08       Impact factor: 4.677

8.  Complex network analysis of CA3 transcriptome reveals pathogenic and compensatory pathways in refractory temporal lobe epilepsy.

Authors:  Silvia Yumi Bando; Filipi Nascimento Silva; Luciano da Fontoura Costa; Alexandre V Silva; Luciana R Pimentel-Silva; Luiz Hm Castro; Hung-Tzu Wen; Edson Amaro; Carlos Alberto Moreira-Filho
Journal:  PLoS One       Date:  2013-11-21       Impact factor: 3.240

  8 in total

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