Literature DB >> 18763727

Emergence of preferred firing sequences in large spiking neural networks during simulated neuronal development.

Javier Iglesias1, Alessandro E P Villa.   

Abstract

Two main processes concurrently refine the nervous system over the course of development: cell death and selective synaptic pruning. We simulated large spiking neural networks (100 x 100 neurons "at birth") characterized by an early developmental phase with cell death due to excessive firing rate, followed by the onset of spike timing dependent synaptic plasticity (STDP), driven by spatiotemporal patterns of stimulation. The cell death affected the inhibitory units more than the excitatory units during the early developmental phase. The network activity showed the appearance of recurrent spatiotemporal firing patterns along the STDP phase, thus suggesting the emergence of cell assemblies from the initially randomly connected networks. Some of these patterns were detected throughout the simulation despite the activity-driven network modifications while others disappeared.

Mesh:

Year:  2008        PMID: 18763727     DOI: 10.1142/S0129065708001580

Source DB:  PubMed          Journal:  Int J Neural Syst        ISSN: 0129-0657            Impact factor:   5.866


  6 in total

1.  Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity.

Authors:  Amelia Waddington; Peter A Appleby; Marc De Kamps; Netta Cohen
Journal:  Front Comput Neurosci       Date:  2012-11-12       Impact factor: 2.380

2.  Mesoscopic segregation of excitation and inhibition in a brain network model.

Authors:  Daniel Malagarriga; Alessandro E P Villa; Jordi Garcia-Ojalvo; Antonio J Pons
Journal:  PLoS Comput Biol       Date:  2015-02-11       Impact factor: 4.475

3.  A Computational Model of Loss of Dopaminergic Cells in Parkinson's Disease Due to Glutamate-Induced Excitotoxicity.

Authors:  Vignayanandam Ravindernath Muddapu; Alekhya Mandali; V Srinivasa Chakravarthy; Srikanth Ramaswamy
Journal:  Front Neural Circuits       Date:  2019-02-25       Impact factor: 3.492

4.  An attractor-based complexity measurement for Boolean recurrent neural networks.

Authors:  Jérémie Cabessa; Alessandro E P Villa
Journal:  PLoS One       Date:  2014-04-11       Impact factor: 3.240

5.  Robust development of synfire chains from multiple plasticity mechanisms.

Authors:  Pengsheng Zheng; Jochen Triesch
Journal:  Front Comput Neurosci       Date:  2014-06-30       Impact factor: 2.380

6.  The topology of the directed clique complex as a network invariant.

Authors:  Paolo Masulli; Alessandro E P Villa
Journal:  Springerplus       Date:  2016-03-31
  6 in total

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