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Simulation Environments for Neuroscience. به نام خداوند بخشنده مهربان. Presented by Ali Nadalizadeh – IPM – Summer 2009. Simulation Environments. NEURON GENESIS NEST NeoCortical Simulator (NCS) Circuit Simulator (Csim) SPLIT XPPAUT (Discussed before) . NEURON - Introduction. - PowerPoint PPT Presentation
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Simulation Environments for Neuroscience
Presented by Ali Nadalizadeh – IPM – Summer 2009
به نام خداوند بخشنده مهربان
Simulation Environments
NEURON GENESIS NEST NeoCortical Simulator (NCS) Circuit Simulator (Csim) SPLIT XPPAUT (Discussed before)
NEURON - Introduction
Historically, NEURON’s primary domain of application was in simulating empirically−based models of biological neurons with extended geometry and biophysical mechanisms that are spatially nonuniform and kinetically complex. (COBA Models)
COBA – Stands for Complex Branched Anatomy
NEURON - Introduction
COBA Models may include : Extracellular potential near the membrane Multiple channel types Inhomogeneous channel distribution Ionic accumulation and diffusion Second messengers
NEURON can now simulate artificial models too, like integrate and fire or any combination of COBA and Artificial networks.
NEURON – How it works ?
We'll approximate the continuous system of neuron into a discrete system in both time and space
Every cell is constructed using connected Sections Every section is an unbranched, continuous cable
whose anatomical and biophysical properties can vary continuously along its length
Note that Sections differ from Compartments Neuron can do both Clock-Driven and Event Based
simulations
NEURON - Other Features
Different Integrate & Fire neuron choices Different Integration methods that will result in a
tradeoff between speed and accuracy. Ability to define new biophysical mechanism.
NMODL syntax → Compiled to C → Compiled to Native Machine code to be used by NEURON
Runs under Windows,MacOSX,Linux Freely available plus extensive documentation
NEURON – Creating and using models
Models should be written in an interpreted language named HOC
NMODL language for new biophysic mechanisms
A powerful GUI for conveniently building and using models
ModelDB : Online model collection that are ready to use.
NEURON - Parallel Computing
NEURON Supports 3 types of parallel computing Multiple Simulations on multiple processors Distributed Network models with gap junctions Distributed models of individual cells
NEURON Uses MPI (Message Passing Interface) for parallel computing
GENESIS - Introduction
Stands for General Neural Simulation System was given its name because it was designed, at the
outset, be an extensible general simulation system for the realistic modeling of neural and biological systems (Bower and Beeman 1998)
Typical GENESIS Models are multicompartment models with HH-type voltage/calcium dependent conductances
Parallel Genesis (PGENESIS) is an extension for it, which supports MPI and PVM for parallel computing.
GENESIS – How it works ?
Object-Oriented simulation system Message Passing Self-Knowledge (variables and actions)
Neuron Component Examples Compartments Variable conductance ion channels Synaptic connections to other neurons
Model Neuron into compartmentsand compartments into circuits
Model Neuron into compartmentsand compartments into circuits
Purkinje Cell ModelWith 4550 Compartments and 8021 channels
GENESIS - GUI
GENESIS - GUI
NEST
Simulating neural networks of biologically realistic size and complexity
Implementing a mathematically correct simulator by novices in a few days ?
Reproducing the results of ad hoc simulations ! The NEST initiative was founded as a long term
project to address these problems. Free/Open License with Extra conditions
NEST
Easily copes with a threshold network size of 105 neurons with natural number of synapses
No GUI (Network generation is usually procedural)
NeuroML Project
A step toward making standard formats for neuron/network specifications.
Current Standard Formats MorphML (specification of neuroanatomy) ChannelML (specification of models of ion channels and
receptors) Biophysics (specification of compartmental cell models,
building on MorphML and ChannelML) NetworkML (specification of cell positions and connections in
a network.)
Common syntax of these specifications is XML
Python Integration
What is python ? PyNEURON, PyGenesis, PyNEST, PyNN Benefits
Standard Scripting Syntax Script Readability NeuroML Integration Ability to use current scientific tools (such as scipy)
References
http://www.open-mpi.org/
http://en.wikipedia.org/wiki/Parallel_Virtual_Machine
http://www.neuron.yale.edu/neuron/
http://www.wam-bamm.org/Tutorials/genesis-intro/genesis-intro.html
http://www.python.org/doc/essays/blurb.html
http://en.wikipedia.org/wiki/Purkinje_cell
Michael L. Hines, Andrew P Davison, Eilif MullerNEURON and Python
Romain Brette · Michelle Rudolph · Ted Carnevale and other friends !Simulation of networks of spiking neurons: A review of tools and strategies