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diff --git a/docs/source/user/py/rdesigneur/rdes.rst b/docs/source/user/py/rdesigneur/rdes.rst
index 0927770023960cd502cfc01748bddf6786bf481c..cb9264279557198bfc3c58836494b52fc27c0983 100644
--- a/docs/source/user/py/rdesigneur/rdes.rst
+++ b/docs/source/user/py/rdesigneur/rdes.rst
@@ -1,9 +1,13 @@
**Rdesigneur: Building multiscale models**
==========================================
-.. Upi Bhalla
+Author: Upi Bhalla
-.. Aug 26 2016. Updated August 2018
+Date: Aug 26 2016,
+
+Last-Updated: Nov 08 2018
+
+By: Upi Bhalla
.. --------------
@@ -1377,6 +1381,83 @@ and so the reaction system is depleted and does not oscillate.
.. figure:: ../../../../images/ex7.5_a_later.png
:alt: Travelling Oscillator molecule a later.
+Controlling a reaction by a function
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+*ex7.6_func_controls_reac_rate.py*
+
+This example illustrates how a function can be used to control a reaction
+rate. This kind of calculation is appropriate when we need to link
+different kinds of physical processses with chemical reactions, for
+example, membrane curvature with molecule accumulation. The use of
+functions to modify reaction rates should be avoided in purely chemical
+systems since they obscure the underlying chemistry, and do not map
+cleanly to stochastic calculations.
+
+In this example we simply have a molecule C that controls the forward
+rate of a reaction that converts A to B. C is a function of location
+on the cylinder, and is fixed. In more elaborate computations we could
+have a function of multiple molecules, some of which could be changing and
+others could be buffered.
+
+::
+
+ import numpy as np
+ import moose
+ import pylab
+ import rdesigneur as rd
+
+
+ def makeFuncRate():
+ model = moose.Neutral( '/library' )
+ model = moose.Neutral( '/library/chem' )
+ compt = moose.CubeMesh( '/library/chem/compt' )
+ compt.volume = 1e-15
+ A = moose.Pool( '/library/chem/compt/A' )
+ B = moose.Pool( '/library/chem/compt/B' )
+ C = moose.Pool( '/library/chem/compt/C' )
+ reac = moose.Reac( '/library/chem/compt/reac' )
+ func = moose.Function( '/library/chem/compt/reac/func' )
+ func.x.num = 1
+ func.expr = "(x0/1e8)^2"
+ moose.connect( C, 'nOut', func.x[0], 'input' )
+ moose.connect( func, 'valueOut', reac, 'setNumKf' )
+ moose.connect( reac, 'sub', A, 'reac' )
+ moose.connect( reac, 'prd', B, 'reac' )
+
+ A.concInit = 1
+ B.concInit = 0
+ C.concInit = 0
+ reac.Kb = 1
+
+ makeFuncRate()
+ rdes = rd.rdesigneur(
+ turnOffElec = True,
+ #This subdivides the 50-micron cylinder into 2 micron voxels
+ diffusionLength = 2e-6,
+ cellProto = [['somaProto', 'soma', 5e-6, 50e-6]],
+ chemProto = [['chem', 'chem']],
+ chemDistrib = [['chem', 'soma', 'install', '1' ]],
+ plotList = [['soma', '1', 'dend/A', 'conc', 'A conc', 'wave'],
+ ['soma', '1', 'dend/C', 'conc', 'C conc', 'wave']],
+ )
+ rdes.buildModel()
+ C = moose.element( '/model/chem/dend/C' )
+ C.vec.concInit = [ 1+np.sin(x/5.0) for x in range( len(C.vec) ) ]
+ moose.reinit()
+ moose.start(10)
+ rdes.display()
+
+We plot the controlling molecule C and the substrate molecule A as
+functions of position, using a waveplot. C remains fixed, and A
+decreases with time and space. A is smallest at about voxel 8, where the
+reaction rate, as controlled by C, is highest.
+
+.. figure:: ../../../../images/ex7.6_C.png
+ :alt: Concentration of control molecule C
+.. figure:: ../../../../images/ex7.6_A.png
+ :alt: Concentration of substrate molecule A
+
Multiscale models: single compartment
@@ -1417,7 +1498,7 @@ so it spikes more, so more calcium enters.
['make_Ca_conc()', 'Ca_conc' ]
],
# Some changes to the default passive properties of the cell.
- passiveDistrib = [['.', 'soma', 'CM', '0.03', 'Em', '-0.06']],
+ passiveDistrib = [['soma', 'CM', '0.03', 'Em', '-0.06']],
chemDistrib = [['chem', 'soma', 'install', '1' ]],
chanDistrib = [
['Na', 'soma', 'Gbar', '300' ],
@@ -1514,9 +1595,8 @@ The arguments in the adaptorList are:
There is a handy new line to specify cellular passive properties:
-**passiveDistrib:** `['.', path, field, value, field, value, ... ]`,
+**passiveDistrib:** `[path, field, value, field, value, ... ]`,
- * '.': This is just a placeholder.
* path: String. Specifies the object whose parameters are to be changed.
* field: String. Name of the field on the object.
* value: String, that is the value has to be enclosed in quotes. The
@@ -1723,7 +1803,7 @@ and how widely to space them.
['make_Ca()', 'Ca' ],
['make_Ca_conc()', 'Ca_conc' ]
],
- passiveDistrib = [['.', 'soma', 'CM', '0.01', 'Em', '-0.06']],
+ passiveDistrib = [['soma', 'CM', '0.01', 'Em', '-0.06']],
spineDistrib = [['spine', '#dend#', '50e-6', '1e-6']],
chemDistrib = [['chem', '#', 'install', '1' ]],
chanDistrib = [
@@ -1856,7 +1936,7 @@ ramifications. There are a lot of plots, to illustrate some of these outcomes.
['make_Ca()', 'Ca' ],
['make_Ca_conc()', 'Ca_conc' ]
],
- passiveDistrib = [['.', 'soma', 'CM', '0.01', 'Em', '-0.06']],
+ passiveDistrib = [['soma', 'CM', '0.01', 'Em', '-0.06']],
spineDistrib = [['spine', '#dend#', '50e-6', '1e-6']],
chemDistrib = [['chem', '#', 'install', '1' ]],
chanDistrib = [
@@ -2346,6 +2426,51 @@ Suggestions:
name of the spine compartments is 'head#' where # is the index of the
spine.
+Place spines in a spiral along a dendrite
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+*ex9.3_spiral_spines.py*
+
+Just for fun. Illustrates how to place spines in a spiral around the dendrite.
+For good measure the spines get bigger the further they are from the soma.
+
+Note that the uniform spacing of spines is signified
+by the negative minSpacing term, the fourth argument to spineDistrib.
+
+
+::
+
+ import moose
+ import pylab
+ import rdesigneur as rd
+ rdes = rd.rdesigneur(
+ cellProto = [['ballAndStick', 'elec', 10e-6, 10e-6, 2e-6, 300e-6, 50]],
+ spineProto = [['makePassiveSpine()', 'spine']],
+ spineDistrib = [['spine', '#dend#', '3e-6', '-1e-6', '1+p*2e4', '0', 'p*6.28e7', '0']],
+ stimList = [['soma', '1', '.', 'inject', '(t>0.02) * 1e-9' ]],
+ moogList = [['#', '1', '.', 'Vm', 'Soma potential']]
+ )
+ rdes.buildModel()
+ moose.reinit()
+ rdes.displayMoogli( 0.0002, 0.025, 0.02 )
+
+Note that the uniform spacing of spines is signified
+by the negative minSpacing term, the fourth argument to spineDistrib.
+
+spineDistrib = [['spine', '#dend#', '3e-6', **'-1e-6'**, '1+p*2e4', '0', 'p*6.28e7', '0']]
+
+
+.. figure:: ../../../../images/ex9.3_spiral_spines.png
+ :alt: 3-D display of spines in a spiral
+
+ 3-D display of spines in a spiral
+
+Suggestions:
+
+ - Play with expressions for spine size and angular placement.
+ - See what happens if the segment size gets smaller than the
+ spine spacing.
+
Rdesigneur command reference
----------------------------
@@ -2726,19 +2851,19 @@ making channel prototypes:
- make_HH_Na(): Make the classical Hodgkin-Huxley Na channel, with
kinetics scaled to SI units.
- make_HH_K(): Classical HH delayed rectifier K channel.
- - make_Na(): Hippocampal pyramidal Na channel from Migliore et al.
+ - make_Na(): Hippocampal pyramidal Na channel from Traub 1991.
- make_K_DR(): Hippocampal pyramidal K delayed rectifier channel
- from Migliore et al.
- - make_K_A(): Hippocampal pyramidal A-type K channel from Migliore
- et al.
+ from Traub 1991.
+ - make_K_A(): Hippocampal pyramidal A-type K channel from Traub
+ 1991.
- make_Ca_conc(): A calcium pool with tau 13.333 ms. This is
required for the calcium dynamics of several channels.
- make_Ca(): Voltage-gated Calcium channel, based on Traub 1991. It
requires the Ca_conc.
- make_K_AHP: Voltage and calcium-gated afterhyperpolarization-
- activated K channel, from Traub. Note that this channel requires
- the presence of the Ca_conc.
- - make_K_C: Voltage and calcium-dependent K channel from Traub.
+ activated K channel, from Traub 1991. Note that this channel
+ requires the presence of the Ca_conc.
+ - make_K_C: Voltage and calcium-dependent K channel from Traub 1991.
This channel requires the presence of the Ca_conc.
- make_glu(): Glutamate receptor in the form of dual-exponential
alpha functions, with a separate opening (2ms) and closing (9ms)
@@ -2902,6 +3027,11 @@ The interpretation of the arguments is as follows:
of this expression is shown again below.
- minSpacing: The minimum spacing, and the increment along which the
Poisson samples are taken to decide if a spine should be added.
+ In case *minSpacing* is negative, the system places spines with uniform
+ *spacing* along the dendritic segment. If
+ ``segment length < 0.5 * spacing``
+ then the system falls back onto Poisson samples so that finely
+ subdivided dendrites don't miss out on spines altogether.
- size: Scale factor for size from the prototype spine. All dimension of
the spine are scaled by this number: shaft length, shaft diameter,
head length and head diameter. This is a math expression, as shown below.