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NEST Simulator Documentation Release 1.0.0 NEST Simulator Documentation Release 1.0.0 NEST Developer Community Sep 09, 2019 CONTENTS 1 Welcome to the NEST simulator documentation!1 1.1 How the documentation is organized..................................1 1.2 Contribute................................................1 2 Download NEST 3 2.1 Download the current version of NEST here:..............................3 2.2 Download the NEST Live Media for Virtual Machines.........................3 2.3 Previous Releases............................................3 3 Installation Instructions 5 3.1 Install NEST with Conda (Linux and macOS) - BETA.........................5 3.2 Ubuntu/Debian Installation........................................6 3.3 Installation on macOS..........................................9 3.4 High Performance Computer Systems Installation........................... 11 3.5 NEST LIVE MEDIA Installation.................................... 14 3.6 Configuration Options.......................................... 15 3.7 Compiling for Apple OSX/macOS.................................... 18 4 Getting Started 21 4.1 A quick overview of simulating neural networks............................ 21 4.2 How do I use NEST?........................................... 21 4.3 Physical units in NEST.......................................... 22 4.4 Next Steps................................................ 23 5 Tutorials 25 5.1 Part 1: Neurons and simple neural networks............................... 25 5.2 Part 2: Populations of neurons...................................... 35 5.3 Part 3: Connecting networks with synapses............................... 40 5.4 Part 4: Topologically structured networks................................ 45 5.5 Introduction to the MUSIC Interface.................................. 51 5.6 Connect two NEST simulations using MUSIC............................. 54 5.7 MUSIC Connections in C++ and Python................................ 57 5.8 The pymusic interface.......................................... 62 5.9 Practical Tips............................................... 64 5.10 Video Tutorial Series........................................... 65 6 Model Directory 67 7 NEST Example Networks 69 7.1 One neuron example........................................... 69 7.2 One neuron with noise.......................................... 70 i 7.3 Two neuron example........................................... 71 7.4 Balanced neuron example........................................ 72 7.5 IAF Neuron example........................................... 74 7.6 Repeated Stimulation........................................... 75 7.7 Multimeter to file example........................................ 76 7.8 Sensitivity to perturbation........................................ 78 7.9 Plot weight matrices example...................................... 81 7.10 IF curve example............................................. 83 7.11 Pulse packet example........................................... 86 7.12 Correlospinmatrix detector example................................... 90 7.13 Auto- and crosscorrelation functions for spike trains.......................... 91 7.14 Campbell & Siegert approximation example.............................. 93 7.15 Spike synchronization through subthreshold oscillation......................... 96 7.16 Example using Hodgkin-Huxley neuron................................. 97 7.17 Numerical phase-plane analysis of the Hodgkin-Huxley neuron.................... 98 7.18 Structural Plasticity example....................................... 101 7.19 Gap Junctions: Two neuron example.................................. 106 7.20 Gap Junctions: Inhibitory network example............................... 107 7.21 Population of GIF neuron model with oscillatory behavior....................... 110 7.22 Population rate model of generalized integrate-and-fire neurons.................... 111 7.23 Testing the adapting exponential integrate and fire model in NEST (Brette and Gerstner Fig 2C)... 118 7.24 Testing the adapting exponential integrate and fire model in NEST (Brette and Gerstner Fig 3D)... 119 7.25 Multi-compartment neuron example................................... 120 7.26 Tsodyks depressing example....................................... 122 7.27 Tsodyks facilitating example....................................... 124 7.28 Example of the tsodyks2_synapse in NEST............................... 127 7.29 Example for the quantal_stp_synapse.................................. 128 7.30 Intrinsic currents spiking......................................... 131 7.31 Intrinsic currents subthreshold...................................... 134 7.32 Network of linear rate neurons...................................... 137 7.33 Rate neuron decision making...................................... 139 7.34 Comparing precise and grid-based neuron models........................... 141 7.35 Sinusoidal poisson generator example.................................. 143 7.36 Sinusoidal gamma generator example.................................. 145 7.37 Clopath Rule: Spike pairing experiment................................. 150 7.38 Clopath Rule: Bidirectional connections................................. 152 7.39 Random balanced network (alpha synapses) connected with NumPy.................. 156 7.40 Random balanced network (alpha synapses) connected with NEST.................. 160 7.41 Random balanced network (delta synapses)............................... 165 7.42 Mean-field theory for random balanced network............................ 169 7.43 Random balanced network (exp synapses, multiple time constants).................. 172 7.44 Use evolution strategies to find parameters for a random balanced network (alpha synapses)..... 176 7.45 Using CSA for connection setup..................................... 186 7.46 Using CSA with Topology layers.................................... 187 7.47 Random balanced network HPC benchmark............................... 189 8 Microcircuit Example 197 8.1 Description................................................ 197 9 MUSIC example 223 9.1 Requirements............................................... 223 9.2 Instructions................................................ 223 10 Topology 225 ii 10.1 Topology User Manual.......................................... 225 10.2 Topology Tutorial with Hill Tononi Model............................... 260 10.3 Examples using Topology........................................ 274 11 Guides 283 11.1 Connection Management......................................... 283 11.2 Running simulations........................................... 294 11.3 Guide to parallel computing....................................... 298 11.4 Random numbers............................................. 303 11.5 Analog recording with multimeter.................................... 310 11.6 Simulations with gap junctions..................................... 312 11.7 Simulations with precise spike times.................................. 313 11.8 Using NEST with MUSIC........................................ 315 12 Getting Help 323 12.1 Have a specific question or problem with NEST?............................ 323 12.2 Getting help on the command line interface............................... 323 12.3 Set up the integrated helpdesk...................................... 324 13 Reference Material 325 14 NEST Community 327 14.1 Mailing List............................................... 327 14.2 Contributing to NEST.......................................... 327 14.3 Reporting bugs.............................................. 327 14.4 Become a NEST member........................................ 327 15 License 329 15.1 GNU GENERAL PUBLIC LICENSE.................................. 329 15.2 Preamble................................................. 329 15.3 GNU GENERAL PUBLIC LICENSE.................................. 330 Index 333 iii iv CHAPTER ONE WELCOME TO THE NEST SIMULATOR DOCUMENTATION! Download Install NEST is a simulator for spiking neural network models, ideal for networks of any size, for example: 1. Models of information processing e.g. in the visual or auditory cortex of mammals, 2. Models of network activity dynamics, e.g. laminar cortical networks or balanced random networks, 3. Models of learning and plasticity. New to NEST? Start here at our Getting Started page Have an idea of the type of model you need? Click on one of the images to access our model directory: Create complex networks using the Topology Module or the Microcircuit Model: Need a different model? Check out how you can create you own model here. Have a question or issue with NEST? See our Getting Help page. 1.1 How the documentation is organized • Tutorials show you step by step instructions using NEST. If you haven’t used NEST before, the PyNEST tutorial is a good place to start. • Example Networks demonstrate the use of dozens of the neural network models implemented in NEST. • Topical Guides provide deeper insight into several topics and concepts from Parallel Computing to handling Gap Junction Simulations and setting up a topological network. • Reference Material provides a quick look up of definitions, functions and terms. 1.2 Contribute • Have you used NEST in an article or presentation? Let us know and we will add it to our list of publications. Find out how to cite NEST in your work. • If you have any comments or suggestions, please share them on our Mailing List. • Want to contribute code? Check out our Developer Space to get started! • For more info about our larger community and the history of NEST
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