Evolving simple models of diverse dynamics in hippocampal neuron types (Venkadesh et al 2018)


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Accession:239103
" ... we present an automated pipeline based on evolutionary algorithms to quantitatively reproduce features of various classes of neuronal spike patterns using the Izhikevich model. Employing experimental data from Hippocampome.org, a comprehensive knowledgebase of neuron types in the rodent hippocampus, we demonstrate that our approach reliably fit Izhikevich models to nine distinct classes of experimentally recorded spike patterns, including delayed spiking, spiking with adaptation, stuttering, and bursting. ..."
Reference:
1 . Venkadesh S, Komendantov AO, Listopad S, Scott EO, De Jong K, Krichmar JL, Ascoli GA (2018) Evolving Simple Models of Diverse Intrinsic Dynamics in Hippocampal Neuron Types Frontiers in Neuroinformatics 12:8
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Abstract Izhikevich neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: Java (web link to model);
Model Concept(s): Bursting; Stuttering; Delay; Spike Frequency Adaptation;
Implementer(s):
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