User’s guide

• Importing Brian
  • Precise control over importing
  • Dependency checks
• Physical units
  • Using units
  • Removing units
  • Temperatures
  • Constants
  • Importing units
  • In-place operations on quantities
• Models and neuron groups
  • Model equations
  • Noise
  • Threshold and reset
  • Refractoriness
  • State variables
  • Subgroups
  • Shared variables
  • Storing state variables
  • Linked variables
  • Time scaling of noise
• Numerical integration
  • Method choice
  • Technical notes
  • GSL stateupdaters
• Equations
  • Equation strings
  • Arithmetic operations and functions
  • Special variables
  • External references
  • Flags
  • List of special symbols
  • Event-driven equations
  • Equation objects
  • Examples of Equation objects
• Refractoriness
  • Defining the refractory period
  • Defining model behaviour during refractoriness
  • Arbitrary refractoriness
• Synapses
  • Defining synaptic models
  • Creating synapses
  • Accessing synaptic variables
  • Delays
  • Monitoring synaptic variables
  • Synaptic connection/weight matrices
  • Creating synapses with the generator syntax
  • Summed variables
  • Creating multi-synapses
  • Multiple pathways
  • Numerical integration
  • Technical notes
• Input stimuli
  • Poisson inputs
  • Spike generation
  • Explicit equations
  • Timed arrays
  • Regular operations
  • More on Poisson inputs
  • Arbitrary Python code (network operations)
• Recording during a simulation
  • Recording spikes
  • Recording variables at spike time
  • Recording variables continuously
  • Recording population rates
  • Getting all data
  • Recording values for a subset of the run
  • Freeing up memory in long recordings
  • Recording random subsets of neurons
  • Recording population averages
• Running a simulation
  • Networks
  • Setting the simulation time step
  • Progress reporting
  • Continuing/repeating simulations
  • Multiple magic runs
  • Changing the simulation time step
  • Profiling
  • Scheduling
  • Store/restore
• Multicompartment models
  • Creating a neuron morphology
  • Creating a spatially extended neuron
• Computational methods and efficiency
  • Runtime code generation
  • Standalone code generation
  • Compiler settings
• Converting from integrated form to ODEs
• How to plot functions