InterneuronAxon
Project description
To simulate neural network functions, it is critical to build realistic models of the functional units that are embedded in the network, The cortical neural network includes glutamatergic excitatory neurons and GABAergic inhibitory interneurons. Inhibitory interneurons have many important functions, but their high degree of diversity represents a challenge to simulate their functions in a cell type-specific manner. The goal of this project is to determine dendritic and axonal mechanism underlying synaptic activation of inhibitory interneurons, To describe interneuron synaptic integration in a quantitative manner, we build detailed cable models of rodent cortical interneurons based on subcellular patch-clamp recordings and complete morphological reconstructions [Hu et al., Science, 2010; Norenberg et al., PNAS, 20t0; Vervaeke et al., Science, 2012; Hu and fonas, Nat Neuroscience, 201,4). We are focusing on two major types of interneurons in the cortex: the parvalbuminexpressing basket cell [funded from 2016-2,020J and the Martinotti cell [grant application pending approval). We want to join the HBP to establish future collaborations and to disseminate our results to the scientific community.
Contribution to HBP
Interneurons are key elements of the cortical network, but their high degree of diversity represents a challenge to build data-driven cell type-specific interneuron cable models. Thus, our project will contribute to the HBP by providing important building blocks for constructing a detailed cortical network model. Conversely, the HBP will allow us to test our hypothesis with the powerful analytical tools developed by the HBP members, and it will give us with the opportunity to share our results with the scientific community on the HBP platform.
We will build models of inolecularly defined inhibitory cells. By providing important pieces for building the large scale network model in the Brain Simulation Platform [BSP), our project will accelerate the endeavour of reverse engineering the brain in silico.
Key facts
Time frame: 2016 to 2020
Origin: Spontaneous Application
Funding: Norwegian Research Council
