Neural Simulation Language NSL

1
Neural Simulation LanguageNSL
2
Overview

• Introduction
• NSLM
• Example (Max Selector)
• NSLS
• Downloading and installing NSL

3
Introduction

• NSL is a platform for
• Building neural architectures (modeling)
• NSLM
• NSLJ NSLC
• Executing them (simulation).
• NSLS
• NSL provides tools for modeling complex neural
  systems - especially (but not only) when the
  neurons are modeled as leaky integrator neurons.

4
Methodology

• The general methodology for making a complex
  neural model of brain function is to combine
  different modules corresponding to different
  brain regions.
• To model a particular brain region, we divide it
  anatomically or physiologically into different
  neural arrays.
• Each brain region is then modeled as a set of
  neuron arrays, where each neuron is described for
  example by the leaky integrator, a
  single-compartment model of membrane potential
  and firing rate.

5
Levels of abstraction

• A complete model in NSL requires the following
  components
• a set of modules defining the entire model
• neurons comprised in each neural module
• neural interconnections
• neural dynamics
• numerical methods to solve the differential
  equations.

6
Example of modules
7
Leaky integrator
8
Simulation
1
2
6
7
3
4
5
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Simulation Methods

• initSys
• initModule
• makeConn
• (simulation steps)
• endModule
• endSys

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Simulation Methods
initTrainEpoch initTrain simTrain endTrain endTrai
nEpoch initRunEpoch initRun simRun endRu
n endRunEpoch
train
doTrainEpochTimes
trainAndRunAll
run
doRunEpochTimes
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Model Structures

• Model
• Highest level
• Modules
• NeuralNetworks
• InModules
• OutModules
• Graphic Interfaces
• MotorModules
• Robotics
• NslClass
• Libraries
• New Canvases
• New NSLS Commands

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NSLM Types

• Primitive types
• int
• float
• double
• boolean
• char
• NslData types (0, 1, 2, 3, 4)
• NslInt
• NslFloat
• NslDouble
• NslBoolean
• NslString (0)
• Could be public, private or protected.

• NslPort types (0, 1, 2, 3, 4)
• NslDinInt
• NslDinFloat
• NslDinDouble
• NslDinBoolean
• NslDinString (0)
• NslDoutInt
• NslDoutFloat
• NslDoutDouble
• NslDoutBoolean
• NslDoutString (0)
• Ports must be public

13
Max Selector Model

• The details of this model can be found in section
  4.4 of TMB2.

The model uses competition mechanisms to obtain,
in many cases, a single winner in the network
where the input signal with the greatest strength
is propagated along to the output of the network.
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Max Selector Model (2)
15
Max Selector Model (3)
MaxSelectorModel
MaxSelector
Stimulus
Output
ULayer
VLayer
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MaxSelectorModel

• nslImport nslAllImports
• nslImport MaxSelectorStimulus
• nslImport MaxSelector
• nslImport MaxSelectorOutput
• nslModel MaxSelectorModel()
• nslConst int size 10
• private MaxSelectorStimulus stimulus(size)
• private MaxSelector maxselector(size)
• private MaxSelectorOutput output(size)
• public void initSys()
• system.setRunEndTime(10.0)
• system.nslSetRunDelta(0.1)

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MaxSelectorStimulus

• nslImport nslAllImports
• nslModule MaxSelectorStimulus(int size)
• public NslDoutDouble1 s_out(size)
• public void initRun()
• s_out0
• s_out10.5
• s_out31.0

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MaxSelectorOutput

• nslImport nslAllImports
• nslOutModule MaxSelectorOutput(int size)
• public NslDinDouble1 s_out(size)
• public NslDinDouble1 uf(size)
• private NslDouble1 up(size)
• private boolean worked false
• public void initModule()
• up.nslSetAccess('W')
• nslAddAreaCanvas(s_out,0,1)
• nslAddTemporalCanvas(up,-2.5,2.5)
• nslAddAreaCanvas(uf,0,1)
• public void simRun()
• workednslSetValue(up,"maxSelectorModel.maxs
  elector.u1.up")

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MaxSelector

• nslImport nslAllImports
• nslImport Ulayer
• nslImport Vlayer
• nslModule MaxSelector(int size)
• public NslDinDouble1 in(size)
• public NslDoutDouble1 out(size)
• private Ulayer u1(size)
• private Vlayer v1()
• public void makeConn()
• nslRelabel(this.in, u1.s_in)
• nslConnect(u1.uf, v1.u_in)
• nslConnect(v1.vf, u1.v_in)
• nslRelabel(u1.uf, this.out)

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ULayer

• nslImport nslAllImports
• nslModule Ulayer(int size)
• //inports
• public NslDinDouble1 s_in()
• public NslDinDouble0 v_in()
• //outports
• public NslDoutDouble1 uf(size)
• //variables
• private NslDouble1 up(size)
• private NslDouble0 w1()
• private NslDouble0 w2()
• private NslDouble0 h1()
• private NslDouble0 k()
• private double tau

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Ulayer(2)

• public void initRun()
• uf 0
• up 0
• tau 1.0
• w1 1.0
• w2 1.0
• h1 0.1
• k 0.1
• public void simRun()
• //compute upup((timestep/tu)du/dt)
• up nslDiff(up, tau, -up w1uf-w2v_in - h1
  s_in)
• uf nslStep(up,k.get(),0,1.0)

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VLayer

• nslImport nslAllImports
• nslModule Vlayer()
• // ports
• public NslDinDouble1 u_in()
• // output port
• public NslDoutDouble0 vf()
• // variables
• private NslDouble0 vp() // neuron potential
• private NslDouble0 h2()
• private double tau // time constant

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Vlayer (2)

• public void initRun()
• vf0
• vp0
• tau1.0
• h2 0.5
• public void simRun()
• // vpvp((timestep/tv)dv/dt)
• vp nslDiff(vp, tau, -vp nslSum(u_in) -h2)
• vf nslRamp(vp)

24
Compilation

• One model/module per file
• The file extension must be .mod
• We recommend to clean the model directory before
  compiling with the nslclean command
• To compile the model you just have to execute the
  following command nslc modelName
• Where modelName is the Name of the file that
  contains the model structure.
• For this example we should write nslc
  MaxSelectorModel
• Note that we didnt write the file extension at
  the end of the name.

Class File
Mod File
Nlx File
Java File
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Execution

• To simulate your model you have to use the nsl
  command.
• For this example you should write nsl
  MaxSelectorModel
• Two running modes
• Text (-nodisplay)
• Graphic interface (default)
• To redirect the standard output (-stdout console)
• To redirect the standard error (-stderr console)

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Interface
27
Interface (2)
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NSLS

• To avoid re-compiling every time you modify your
  model parameters we provide the NSL script
  language known as NSLS which also provides a
  dynamic user control environment.
• NSLS provides the following functionality
• NSL model parameter assignment
• NSL input specification
• NSL simulation control
• NSL file control
• NSL graphics control
• NSLS is an extension of the well know TCL
  scripting language, thus providing NSL and TCL
  functionality.

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NSLS (2)

• NSL command syntax nsl subcommand options
• Important NSL commands
• nsl source fileName
• (i.e. nsl source hopfield.nsls)
• nsl set variable value
• (i.e. nsl set maxSelectorModel.stimulus.s_out 1
  0 0.5)
• nsl get variable
• (i.e. nsl get maxSelectorModel.stimulus.s_out)
• nsl run
• nsl train
• nsl exit

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NSLS example

• Hopfield Network
• set A
• set B
• set C
• set D
• proc memorize x
• puts "Memorizing x"
• nsl set hopfield.inModule.input x
• nsl train
• proc test x d

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NSLS example (2)

• proc initData
• global A B C D
• set A
• -1 -1 1 1 -1 -1
• -1 1 -1 -1 1 -1
• -1 1 1 1 1 -1
• -1 1 1 1 1 -1
• -1 1 -1 -1 1 -1
• -1 1 -1 -1 1 -1
• set B
• 1 1 -1 -1 -1 -1
• 1 1 -1 -1 -1 -1
• 1 1 1 1 -1 -1
• 1 1 -1 -1 1 -1
• 1 1 -1 -1 1 -1

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NSLS example (3)

• proc trainNetwork
• global A B C D
• memorize A
• memorize B
• memorize C
• memorize D
• proc NslMain
• global A B C D
• puts "Initializing"
• initData
• puts "Training"
• trainNetwork
• puts "Testing"
• for set i 10 ilt20 incr i
• puts "Testing with distortion i"
• test A i

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Downloading NSL

• First, you will need to install the latest Java
  SDK get it directly from Sun at
  http//java.sun.com/j2se/1.3/.
• Once this is setup and working, download the
  entire NSL tree from http//www-scf.usc.edu/csci5
  64/nsl.tar.gz
• Extract the archive (Winzip or Pkzip).
• Edit the file "NSL3_0_n\resume.bat" such that it
  matches your environment (you will have to
  specify the path where you installed Java, where
  you installed NSL, etc).
• Execute the resume batch file before beginning a
  NSL session.

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Downloading NSL (2)

• _at_echo off
• echo Initializing NSL environment variables
• set NSLJ_ROOTC\salvador\NSL3_0_n
• set JAVA_HOMEC\jdk1.3
• set NSL_OSwindows
• echo Updating path and classpath
• set PATHJAVA_HOME\binNSLJ_ROOTPATH
• set CLASSPATHNSLJ_ROOT.NSLJ_ROOT\nslj\src\m
  ain
• NSLJ_ROOT\nslj\src\nsls\jacl
• NSLJ_ROOT\nslj\src\nsls\tcljava
• _at_echo on

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References

• A Weitzenfeld, MA Arbib and A Alexander, 2002,
  NSL Neural Simulation Language, MIT Press (in
  press)
• An old version is at
• http//www-hbp.usc.edu/_Documentation/NSL/Book/TO
  C.htm
• For any NSL related questions and bug reports,
  please send me an email at smarmol_at_usc.edu