Gap junction plasticity as a mechanism to regulate network-wide oscillations (Pernelle et al 2018)

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"Oscillations of neural activity emerge when many neurons repeatedly activate together and are observed in many brain regions, particularly during sleep and attention. Their functional role is still debated, but could be associated with normal cognitive processes such as memory formation or with pathologies such as schizophrenia and autism. Powerful oscillations are also a hallmark of epileptic seizures. Therefore, we wondered what mechanism could regulate oscillations. A type of neuronal coupling, called gap junctions, has been shown to promote synchronization between inhibitory neurons. Computational models show that when gap junctions are strong, neurons synchronize together. Moreover recent investigations show that the gap junction coupling strength is not static but plastic and dependent on the firing properties of the neurons. Thus, we developed a model of gap junction plasticity in a network of inhibitory and excitatory neurons. We show that gap junction plasticity can maintain the right amount of oscillations to prevent pathologies from emerging. Finally, we show that gap junction plasticity serves an additional functional role and allows for efficient and robust information transfer."
1 . Pernelle G, Nicola W, Clopath C (2018) Gap junction plasticity as a mechanism to regulate network-wide oscillations. PLoS Comput Biol 14:e1006025 [PubMed]
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Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Abstract Izhikevich neuron; Abstract integrate-and-fire leaky neuron;
Gap Junctions: Gap junctions;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: Python;
Model Concept(s): Gamma oscillations;
Implementer(s): Pernelle, Guillaume [g.pernelle14 at];
Search NeuronDB for information about:  Gaba; Glutamate;
This is the readme for the models associated with the paper:

Pernelle G, Nicola W, Clopath C (2018) Gap junction plasticity as a mechanism to regulate network wide oscillations PLOS Computational Biology

Please see the html files for copies of what the python notebooks looked like when successfully run.

These model files were contributed by G. Pernelle.