Models that contain the Neuron : Neocortex M1 interneuron basket PV GABA cell

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    Models   Description
1.  Cortical model with reinforcement learning drives realistic virtual arm (Dura-Bernal et al 2015)
We developed a 3-layer sensorimotor cortical network of consisting of 704 spiking model-neurons, including excitatory, fast-spiking and low-threshold spiking interneurons. Neurons were interconnected with AMPA/NMDA, and GABAA synapses. We trained our model using spike-timing-dependent reinforcement learning to control a virtual musculoskeletal human arm, with realistic anatomical and biomechanical properties, to reach a target. Virtual arm position was used to simultaneously control a robot arm via a network interface.
2.  Cortical network model of posttraumatic epileptogenesis (Bush et al 1999)
This simulation from Bush, Prince, and Miller 1999 shows the epileptiform response (Fig. 6C) to a brief single stimulation in a 500 cell network of multicompartment models, some of which have active dendrites. The results which I obtained under Redhat Linux is shown in result.gif. Original 1997 code from Paul Bush modified slightly by Bill Lytton to make it work with current version of NEURON (5.7.139). Thanks to Paul Bush and Ken Miller for making the code available.
3.  Perceptual judgments via sensory-motor interaction assisted by cortical GABA (Hoshino et al 2018)
"Recurrent input to sensory cortex, via long-range reciprocal projections between motor and sensory cortices, is essential for accurate perceptual judgments. GABA levels in sensory cortices correlate with perceptual performance. We simulated a neuron-astrocyte network model to investigate how top-down, feedback signaling from a motor network (Nmot) to a sensory network (Nsen) affects perceptual judgments in association with ambient (extracellular) GABA levels. In the Nsen, astrocytic transporters modulated ambient GABA levels around pyramidal cells. A simple perceptual task was implemented: detection of a feature stimulus presented to the Nsen. ..."

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