Leaky Integrate and Fire Neuron Model of Context Integration (Calvin, Redish accepted)

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The maintenance of the contextual information has been shown to be sensitive to changes in excitation-inhbition (EI) balance. We constructed a multi-structure, biophysically-realistic agent that could perform context-integration as is assessed by the dot probe expectancy task. The agent included a perceptual network, a working memory network, and a decision making system and was capable of successfully performing the dot probe expectancy task. Systemic manipulation of the agent’s EI balance produced localized dysfunction of the memory structure, which resulted in schizophrenia-like deficits at context integration.
Model Information (Click on a link to find other models with that property)
Model Type: Agent-based model;
Brain Region(s)/Organism: Prefrontal cortex (PFC);
Cell Type(s): Abstract integrate-and-fire leaky neuron;
Channel(s): I Na, leak;
Gap Junctions:
Receptor(s): AMPA; NMDA; Gaba;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: Python;
Model Concept(s): Working memory; Attractor Neural Network;
Search NeuronDB for information about:  AMPA; NMDA; Gaba; I Na, leak; Gaba; Glutamate;