Moved demos from moose to this location.

Author: aviralg

MemoryNetworks/bidirectional_plastic_switch.py

@@ -0,0 +1,93 @@
+"""bidirectional_plastic_switch.py: 
+    
+Apply sequences of random input to this switch and plot the correlation between output
+sequences.
+
+"""
+    
+__author__           = "Dilawar Singh"
+__copyright__        = "Copyright 2015, Dilawar Singh and NCBS Bangalore"
+__credits__          = ["NCBS Bangalore"]
+__license__          = "GNU GPL"
+__version__          = "1.0.0"
+__maintainer__       = "Dilawar Singh"
+__email__            = "dilawars@ncbs.res.in"
+__status__           = "Development"
+
+import moose
+import os
+import sys
+import pylab
+
+
+def applyInputPulseTrain(mooseElem, fieldName, pulseTrain):
+    """
+    Apply a train of pulse: a list of (time, value) tuples, to fieldName of
+    mooseElem.
+
+    time is incremental.
+    """
+    for (t, v) in pulseTrain:
+        moose.start(t)
+        mooseElem.setField(fieldName, v)
+
+def dumpPlots():
+    fname = 'bidirectionalPlasticity.plot'
+    if ( os.path.exists( fname ) ):
+        os.remove( fname )
+    for x in moose.wildcardFind( '/model/graphs/conc#/#,/model/moregraphs/conc#/#' ):
+        moose.element( x[0] ).xplot( fname, x[0].name )
+
+def getPlotData():
+    totR = moose.element('/model/graphs/conc1/tot_PSD_R.Co')
+    PP1 = moose.element('/model/moregraphs/conc4/PP1_dash_active.Co')
+    Ca = moose.element('/model/graphs/conc1/Ca.Co')
+    return totR.vector, PP1.vector, Ca.vector
+
+def displayPlots():
+    clock = moose.Clock( '/clock' ) # look up global clock
+    totR = moose.element( '/model/graphs/conc1/tot_PSD_R.Co' )
+    PP1 = moose.element( '/model/moregraphs/conc4/PP1_dash_active.Co' )
+    Ca = moose.element( '/model/graphs/conc1/Ca.Co' )
+    pylab.plot( pylab.linspace( 0, clock.currentTime, len( totR.vector )), totR.vector, label='membrane Receptor' )
+    pylab.plot( pylab.linspace( 0, clock.currentTime, len( PP1.vector ) ), PP1.vector, label='active PP1' )
+    pylab.plot( pylab.linspace( 0, clock.currentTime, len( Ca.vector ) ), Ca.vector, label='Ca' )
+    pylab.legend()
+    pylab.show()
+
+def main():
+    """
+    This is a toy model of synaptic bidirectional plasticity. The model has 
+    a small a bistable chemical switch, and a small set of reactions that
+    decode calcium input. One can turn the switch on with short high 
+    calcium pulses (over 2 uM for about 10 sec). One can turn it back off
+    again using a long, lower calcium pulse (0.2 uM, 2000 sec).
+    """
+    method = 'old_gssa'  # This is the Gillespie Stoichastic Systems Algorithm
+    if ( len( sys.argv ) >= 2 ):
+        method = sys.argv[1]
+    if ( method == "gsl" ):
+        method = "old_gsl"
+    if ( method == "gssa" ):
+        method = "old_gssa"
+    # Load in the model and set up to use the specified method
+    modelId = moose.loadModel( './stargazin_synapse.g', 'model', method )
+    moose.start( 1000.0 ) # Run the model for 1000 seconds.
+    Ca = moose.element( '/model/kinetics/BULK/Ca' )
+
+    applyInputPulseTrain(Ca, 'concInit'
+            , [ (1000.0, 1.0e-3)
+                , (10.0, 0.08e-3)
+                , (50.0, 1.0e-3)
+                , (10.0, 0.08e-3)
+                , (1000.0, 0.2e-3)
+                , (2000.0, 0.08e-3) 
+                ]
+            )
+    moose.start(2000.0)
+    displayPlots()
+    quit()
+
+# Run the 'main' if this script is executed standalone.
+if __name__ == '__main__':
+    main()