Predicting Synaptic Connectivity for Large-Scale Microcircuit Simulations Using Snudda

التفاصيل البيبلوغرافية
العنوان: Predicting Synaptic Connectivity for Large-Scale Microcircuit Simulations Using Snudda
المؤلفون: Hjorth, J. J. Johannes, Hellgren Kotaleski, Jeanette, Kozlov, Alexander
المصدر: Neuroinformatics. 19(4):685-701
مصطلحات موضوعية: Basal ganglia, Brain microcircuits, Large-scale simulations, Model building pipeline, Striatum, Synaptic connectivity, animal, basal ganglion, brain, computer simulation, mouse, nerve cell, software, Animals, Mice, Neurons
الوصف: Simulation of large-scale networks of neurons is an important approach to understanding and interpreting experimental data from healthy and diseased brains. Owing to the rapid development of simulation software and the accumulation of quantitative data of different neuronal types, it is possible to predict both computational and dynamical properties of local microcircuits in a ‘bottom-up’ manner. Simulated data from these models can be compared with experiments and ‘top-down’ modelling approaches, successively bridging the scales. Here we describe an open source pipeline, using the software Snudda, for predicting microcircuit connectivity and for setting up simulations using the NEURON simulation environment in a reproducible way. We also illustrate how to further ‘curate’ data on single neuron morphologies acquired from public databases. This model building pipeline was used to set up a first version of a full-scale cellular level model of mouse dorsal striatum. Model components from that work are here used to illustrate the different steps that are needed when modelling subcortical nuclei, such as the basal ganglia.
وصف الملف: print
URL الوصول: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-310619
https://doi.org/10.1007/s12021-021-09531-w
قاعدة البيانات: SwePub
الوصف
تدمد:15392791
15590089
DOI:10.1007/s12021-021-09531-w