P183 Biophysically detailed neuron models with genetically defined ion channels
DarshanMandge*1,2, Rajnish Ranjan2, Emmanuelle Logette2, Tanguy Damart2, Aurélien Tristan Jaquier2, Lida Kanari2, Daniel Keller2, Yann Roussel2, Stijn van Dorp2, Werner Van Geit1, and Henry Markram2 1Open Brain Institute,1005,Lausanne,Switzerland 2Blue Brain Project, Écolepolytechniquefédéralede Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland *Email: darshan.mandge@openbraininsititute.org Introduction
Cortical neurons can be classified into different electrical firing types (e-types). A common approachtomodellingthesee-types involvesthecreationofdetailed electrical models (e-models) using generic ion channel currents such as transient and persistent sodium, potassium channels, and high- and low-voltage activated calcium channels[1]. While this approach accurately captures a neuron's electricalbehaviour, it does notestablisha link between specificion channels andobservedelectrophysiological properties. Methods We now havemade47 homomeric ion channel modelscorresponding to various potassium[2], sodium, calcium, and hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels. These genetic ion channel models were based on independent experimental data from the heterologous expression of the corresponding genes. The genetic channels along with some generic ion channelswereused in this study to construct cortical e-type modelsfromdetailed morphological reconstructions and electrophysiological datacollected inthe rat somatosensory cortex. Webuilt aPython-basedpipeline calledBluePyEModel[3] tobuild such e-models. Results The optimized e-modelsreproduce firing propertiesobservedinin vitrorecordings. Electrical features of the optimized e-models were found to be within 3–5 standard deviations of the corresponding mean experimental recordings. Discussion These biophysically detailed modelsenablea better understanding of the electrical activity in normal and pathological states of neurons.Inthefuture, wewillmake these e-models available on the Open Brain Institute (OBI)platform,https://openbraininstitute.org/. The OBIplatformprovidesa comprehensive repository of digital brain models andstandardisedcomputational modelling services to enableusers to conduct realistic brain simulations, test hypotheses, and explore the complexitiesatvarious modelling levels– Subcellular, Cellular, Circuit andSystems.
Acknowledgements This study was supported by funding to the Blue Brain Project, a researchcenterof the Écolepolytechniquefédéralede Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
