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Divide and Conquer: Functional Segregation of Synaptic Inputs by Astrocytic Microdomains Could Alleviate Paroxysmal Activity Following Brain Trauma

Overview of attention for article published in PLoS Computational Biology, January 2013
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Title
Divide and Conquer: Functional Segregation of Synaptic Inputs by Astrocytic Microdomains Could Alleviate Paroxysmal Activity Following Brain Trauma
Published in
PLoS Computational Biology, January 2013
DOI 10.1371/journal.pcbi.1002856
Pubmed ID
Authors

Vladislav Volman, Maxim Bazhenov, Terrence J. Sejnowski

Abstract

Traumatic brain injury often leads to epileptic seizures. Among other factors, homeostatic synaptic plasticity (HSP) mediates posttraumatic epileptogenesis through unbalanced synaptic scaling, partially compensating for the trauma-incurred loss of neural excitability. HSP is mediated in part by tumor necrosis factor alpha (TNFα), which is released locally from reactive astrocytes early after trauma in response to chronic neuronal inactivity. During this early period, TNFα is likely to be constrained to its glial sources; however, the contribution of glia-mediated spatially localized HSP to post-traumatic epileptogenesis remains poorly understood. We used computational model to investigate the reorganization of collective neural activity early after trauma. Trauma and synaptic scaling transformed asynchronous spiking into paroxysmal discharges. The rate of paroxysms could be reduced by functional segregation of synaptic input into astrocytic microdomains. Thus, we propose that trauma-triggered reactive gliosis could exert both beneficial and deleterious effects on neural activity.

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Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 5%
France 1 3%
Unknown 34 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 9 24%
Student > Postgraduate 3 8%
Professor > Associate Professor 3 8%
Student > Master 3 8%
Other 6 16%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 30%
Medicine and Dentistry 8 22%
Neuroscience 7 19%
Psychology 2 5%
Physics and Astronomy 1 3%
Other 3 8%
Unknown 5 14%