Changeset 124

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Timestamp:
07/05/07 16:27:08 (1 year ago)
Author:
apdavison
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This version printed out in A0 format for CNS

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  • doc/CNS2007/poster_cns2007.py

    r122 r124  
    476476           ("Where can I download PyNN?", "http://neuralensemble.org/PyNN"), 
    477477           ("What other solutions are there for developing simulator-independent models?", "<b>NeuroML</b> (http://neuroml.org) is a standard for model specification in XML. <b>NeuroConstruct</b> (http://neuroconstruct.org) is a tool for developing network models, using a graphical interface, that can then be exported as either NEURON or GENESIS code. There is also some overlap with <b>Neurospaces</b> (http://www.neurospaces.org/), a framework for modular construction of computational neuroscience simulators."), 
    478            ("What are your future plans for PyNN?", "We are currently working on: (i) support for NEST version 2, which adds support for distributed (parallel) simulations (distributed simulations in NEURON and PCSIM are already supported); (ii) support for import/export of network models specified in NeuroML; (iii) various improvements/extensions to the API, (iv) general performance improvements."), 
     478           ("What are your future plans for PyNN?", "We are currently working on: (i) support for NEST version 2, which adds support for distributed (parallel) simulations (distributed simulations in NEURON and PCSIM are already supported); (ii) support for the VLSI analog spiking network hardware being developed within the FACETS project (iii) support for import/export of network models specified in NeuroML; (iv) various improvements/extensions to the API, (v) general performance improvements."), 
    479479           ("Why shouldn't I use PyNN?", "(i) If your work does not involve network modelling; (ii) if you prefer to use a graphical interface to develop your simulations."), 
    480480           ("Who is using PyNN now?", "PyNN was first developed within the FACETS project, an EC-funded consortium of fifteen or so European research groups including seven groups doing computational neuroscience, using six simulators between them. In the absence of agreement that everyone should use the same simulator, a tool to make it easier to share models between groups was needed, and PyNN was born. Within FACETS, PyNN is being used for simulations of large-scale models of primary visual cortex and of generic cortical circuits with synaptic plasticity. We would like to encourage wider use, and anyone interested in using or developing PyNN should check out http://neuralensemble.org.") 
     
    486486        'VAbenchmark_CUBA_exc.png': """<b>Results of running the CUBA benchmark script</b> (see Box: 'Example'), written in PyNN, with three different simulators (from left to right: NEURON, NEST, PCSIM). 
    487487         
    488         The <b><i>top row</i></b> shows the membrane potential traces for two of the excitatory neurons in the network. 
    489         The <b><i>second row</i></b> shows the raster plots for the first 320 excitatory neurons in the network (total network size 3200 excitatory and 800 inhibitory neurons). Each dot represents one spike. Each row is a different cell. 
    490         The <b><i>third row</i></b> shows histograms of interspike intervals (ISIs) for the excitatory and inhibitory sub-populations. 
    491         The <b><i>bottom row</i></b> shows histograms of the coefficient of variation (CV) of the ISI
     488        The <b><i>top row</i></b> shows the <b><i>membrane potential traces</i></b> for two of the excitatory neurons in the network. 
     489        The <b><i>second row</i></b> shows the <b><i>raster plots</i></b> for the first 320 excitatory neurons in the network (total network size 3200 excitatory and 800 inhibitory neurons). Each dot represents one spike. Each row is a different cell. 
     490        The <b><i>third row</i></b> shows histograms of <b><i>interspike intervals</i></b> (ISIs) for the excitatory and inhibitory sub-populations. 
     491        The <b><i>bottom row</i></b> shows histograms of the <b><i>coefficient of variation (CV) of the ISI</i></b>
    492492         
    493493        For NEST and NEURON, the same sequence of random numbers was used to generate the network connectivity (using a PyNN <font face="Courier">NumpyRNG</font> object. For PCSIM, the random numbers were generated within the simulator (represented in PyNN with a <font face="Courier">NativeRNG</font> object). 
    494494         
    495         Even when using exactly the same connectivity pattern, the membrane potential trajectories diverge after about the first 100 ms, although the pattern of mean activity across the network is well preserved between simulators. 
     495        <b>Even when using exactly the same connectivity pattern, the membrane potential trajectories diverge<b> after about the first 100 ms, although the <b>pattern of mean activity</b> across the network is <b>well preserved</b> between simulators. 
    496496         
    497         With a different random connectivity (but with the same connection probability), there is no similarity in detailed activity patterns, but the statistical behaviour of the network in terms of spike train variability is the same.""" 
     497        With a different random connectivity (but with the same connection probability), there is no similarity in detailed activity patterns, but the <b>statistical behaviour of the network</b> in terms of spike train variability <b>is the same</b>.""" 
    498498    } 
    499499         
     
    521521     
    522522    poster.setFillColor(colors.white) 
    523     #poster.setStrokeColor(colors.white) 
     523    poster.setStrokeColor(colors.white) 
    524524  
    525     paint_background('white') #'seagreen' 'whitesmoke' 'oldlace 
    526      
    527     #paint_background('flickr_fortinbras_10182754_cfc533d350.jpg', photo_credit="Background image: 'Pine bough', from http://www.flickr.com/photos/fortinbras") 
     525    #paint_background('white') #'seagreen' 'whitesmoke' 'oldlace 
     526     
     527    paint_background('flickr_fortinbras_10182754_cfc533d350.jpg', photo_credit="Background image: 'Pine bough', from http://www.flickr.com/photos/fortinbras") 
    528528     
    529529    #paint_background('flickr_blmurch_144285136_a7116060ed_o.jpg', photo_credit="Background image: 'Pine cones' by Beatrice Murch (http://www.flickr.com/people/blmurch/)") 
     
    553553    make_deflist_frame(getStyleSheet(36, 72),QA, margins['left'], title_bottom, x_ex-margins['left']-colsep, colheight, DEBUG) 
    554554 
    555     poster.setFillColor(colors.black) # white works better with a background image 
     555    #poster.setFillColor(colors.black) # white works better with a background image 
    556556    poster.setFont("Helvetica", 24)   # bold works better with a background image 
    557557    poster.drawCentredString(margins['left']+pagewidth/2.0, 0.2*margins['bottom'], ACKNOWLEDGEMENTS)