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Dynamics in random NNs with multiple neuron subtypes (Pena et al 2018, Tomov et al 2014, 2016)
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Pipeline user 82
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"Spontaneous cortical population activity exhibits a multitude of oscillatory patterns, which often display synchrony during slow-wave sleep or under certain anesthetics and stay asynchronous during quiet wakefulness. The mechanisms behind these cortical states and transitions among them are not completely understood. Here we study spontaneous population activity patterns in random networks of spiking neurons of mixed types modeled by Izhikevich equations. Neurons are coupled by conductance-based synapses subject to synaptic noise. We localize the population activity patterns on the parameter diagram spanned by the relative inhibitory synaptic strength and the magnitude of synaptic noise. In absence of noise, networks display transient activity patterns, either oscillatory or at constant level. The effect of noise is to turn transient patterns into persistent ones: for weak noise, all activity patterns are asynchronous non-oscillatory independently of synaptic strengths; for stronger noise, patterns have oscillatory and synchrony characteristics that depend on the relative inhibitory synaptic strength. ..."
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Pena RFO, Zaks MA, Roque AC (2018) Show
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Tomov P, Pena RF, Roque AC, Zaks MA (2016) Show
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Tomov P, Pena RF, Zaks MA, Roque AC (2014) Show
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Rodrigo Pena, [pena at njit.edu] Show
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Petar Tomov, [tomov at mathematik.hu-berlin.de] Show
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tom.morse@yale.edu
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Rodrigo Pena, pena@njit.edu
Petar Tomov, tomov@mathematik.hu-berlin.de
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https://link.springer.com/article/10.1007/s10827-018-0688-6
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