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synapse_degradation.lua
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--------------------------------------------------------------------------------
-- This script is intended to examine the effect of synapse loss on single --
-- cell electrical signals. --
-- It solves the cable equation on a single cell including Hodgkin-Huxley- --
-- type K+ and Na+ channels and a leakage flux. --
-- Activation is realized through alpha-type synapses that are randomly --
-- distributed across the dendrites of the cell. A percentage of these --
-- synapses can be removed prior to the simulation. --
-- --
-- Authors: Markus Breit, Martin Stepniewski --
-- Date: 2015-08-19 --
--------------------------------------------------------------------------------
ug_load_script("ug_util.lua")
ug_load_script("util/load_balancing_util.lua")
-- init UG
InitUG(3, AlgebraType("CPU", 1))
AssertPluginsLoaded({"cable_neuron"})
--------------------------------------------------------------------------------
-- Settings
--------------------------------------------------------------------------------
cell = util.GetParam("-cellName", "12-L3pyr")
if not cell == "12-L3pyr" or not cell == "31o_pyr" then
exit("Cell not specified correctly. Type '12-L3pyr' or '31o_pyr'.")
end
if cell == "12-L3pyr" then
gridName = "grids/13-L3pyr-77.CNG.ugx"
gridSyn = "grids/13-L3pyr-77.CNG_syn.ugx"
gridDeg = "grids/13-L3pyr-77.CNG_syn_deg.ugx"
distro = {0.0, 0.0, 0.5, 0.5}
neededSubsets = {"soma", "axon", "dendrite", "apical_dendrite"}
dendSubsets = "dendrite, apical_dendrite"
else
gridName = "grids/31o_pyramidal19aFI.CNG.ugx"
gridSyn = "grids/31o_pyramidal19aFI.CNG_syn.ugx"
gridDeg = "grids/31o_pyramidal19aFI.CNG_syn_deg.ugx"
distro = {0.0, 1.0, 0.0}
neededSubsets = {"soma", "dendrite", "axon"}
dendSubsets = "dendrite"
end
-- parameters steering simulation
numRefs = util.GetParamNumber("-numRefs", 0)
dt = util.GetParamNumber("-dt", 1e-5) -- in s
endTime = util.GetParamNumber("-endTime", 1.0) -- in s
nSteps = util.GetParamNumber("-nSteps", endTime/dt)
pstep = util.GetParamNumber("-pstep", dt, "plotting interval")
-- synapse activity parameters
avg_start = util.GetParamNumber("-avgStart", 0.01)
avg_dur = util.GetParamNumber("-avgDur", 2.4e-3)
dev_start = util.GetParamNumber("-devStart", 0.005)
dev_dur = util.GetParamNumber("-devDur", 0.0)
num_synapses = util.GetParamNumber("-nSyn", 140)
-- specify "-verbose" to output linear solver convergence
verbose = util.HasParamOption("-verbose")
-- vtk output?
generateVTKoutput = util.HasParamOption("-vtk")
-- profiling?
doProfiling = util.HasParamOption("-profile")
SetOutputProfileStats(doProfiling)
-- file handling
outPath = util.GetParam("-outName", "sol_new_clearance_1e-3")
outPath = outPath .. "/"
--------------------------------------------------------------------------------
-- Synapse distributions via plugin by Lukas Reinhardt
--------------------------------------------------------------------------------
---[[
synDistr = SynapseDistributor(gridName)
synDistr:clear() -- clear any synapses from grid
synDistr:place_synapses(distro, num_synapses, "AlphaPostSynapse")
export_succes = synDistr:export_grid(gridSyn)
print("SynapseDistributor grid export successful: " .. tostring(export_succes))
--]]
gridName = gridSyn
--------------------------------------------------------------------------------
-- Synapse degeneration
--------------------------------------------------------------------------------
---[[
deg_factor = util.GetParamNumber("-degFac", 0.0)
deg_factor = deg_factor + 0.5/num_synapses -- rounding instead of floor-ing
synDistr = SynapseDistributor(gridName)
--synDistr:print_status()
if cell == "12-L3pyr" then
synDistr:degenerate_uniform(deg_factor, 2) -- first factor means: newNumber = (1-factor)*oldNumber
synDistr:degenerate_uniform(deg_factor, 3) -- second param is the subset index
else
synDistr:degenerate_uniform(deg_factor, 1)
end
synDistr:print_status()
synDistr:export_grid(gridDeg)
gridName = gridDeg
--]]
--------------------------
-- biological settings --
--------------------------
-- settings are according to T. Branco
-- membrane conductances (in units of S/m^2)
g_k_ax = 400.0 -- axon
g_k_so = 200.0 -- soma
g_k_de = 30 -- dendrite
g_na_ax = 3.0e4
g_na_so = 1.5e3
g_na_de = 40.0
g_l_ax = 200.0
g_l_so = 1.0
g_l_de = 1.0
-- specific capacitance (in units of F/m^2)
spec_cap = 1.0e-2
-- resistivity (in units of Ohm m)
spec_res = 1.5
-- reversal potentials (in units of V)
e_k = -0.09
e_na = 0.06
e_ca = 0.14
-- equilibrium concentrations (in units of mM)
-- comment: these concentrations will not yield Nernst potentials
-- as given above; pumps will have to be introduced to achieve this
-- in the case where Nernst potentials are calculated from concentrations!
k_out = 4.0
na_out = 150.0
ca_out = 1.5
k_in = 140.0
na_in = 10.0
ca_in = 5e-5
-- equilibrium potential (in units of V)
v_eq = -0.065
-- diffusion coefficients (in units of m^2/s)
diff_k = 1.0e-9
diff_na = 1.0e-9
diff_ca = 2.2e-10
-- temperature in units of deg Celsius
temp = 37.0
--------------------------------------------------------------------------------
-- Create, Load, Refine Domain
--------------------------------------------------------------------------------
dom = util.CreateDomain(gridName, numRefs, neededSubsets)
-- check domain is acyclic
isAcyclic = is_acyclic(dom)
if not isAcyclic then
print("Domain is not acyclic!")
exit()
end
--------------------------------------------------------------------------------
-- create Approximation Space
--------------------------------------------------------------------------------
--print("Create ApproximationSpace needs to be somewhere else")
approxSpace = ApproximationSpace(dom)
approxSpace:add_fct("v", "Lagrange", 1)
approxSpace:init_levels()
approxSpace:init_surfaces()
approxSpace:init_top_surface()
approxSpace:print_layout_statistic()
approxSpace:print_statistic()
OrderCuthillMcKee(approxSpace, true)
-- cable equation
CE = CableEquation("soma, axon, " .. dendSubsets, false)
CE:set_spec_cap(spec_cap)
CE:set_spec_res(spec_res)
CE:set_rev_pot_k(e_k)
CE:set_rev_pot_na(e_na)
CE:set_rev_pot_ca(e_ca)
CE:set_k_out(k_out)
CE:set_na_out(na_out)
CE:set_ca_out(ca_out)
CE:set_diff_coeffs({diff_k, diff_na, diff_ca})
CE:set_temperature_celsius(temp)
-- Hodgkin and Huxley channels
HH = ChannelHH("v", "axon, soma, " .. dendSubsets)
HH:set_conductances(g_k_ax, g_na_ax, "axon")
HH:set_conductances(g_k_so, g_na_so, "soma")
HH:set_conductances(g_k_de, g_na_de, dendSubsets)
CE:add(HH)
-- leakage
tmp_fct = math.pow(2.3,(temp-23.0)/10.0)
leak = ChannelLeak("v", "axon, soma, " .. dendSubsets)
leak:set_cond(g_l_ax*tmp_fct, "axon")
leak:set_rev_pot(-0.066210342630746467, "axon")
leak:set_cond(g_l_so*tmp_fct, "soma")
leak:set_rev_pot(-0.022074360525636, "soma")
leak:set_cond(g_l_de*tmp_fct, dendSubsets)
leak:set_rev_pot(-0.056314322586687, dendSubsets)
CE:add(leak)
-- synapses
syn_handler = SynapseHandler()
syn_handler:set_ce_object(CE)
syn_handler:set_activation_timing_alpha(
avg_start, -- average onset of synaptical activity in [s]
avg_dur/6.0, -- average tau of activity function in [s]
dev_start, -- deviation of onset in [s]
dev_dur/6.0, -- deviation of tau in [s]
1.2e-9) -- peak conductivity in [S]
CE:set_synapse_handler(syn_handler)
--[[
-- electrode stimulation
-- 5nA seem to enervate the pyramidal cell with uniform diameters of 1um
-- (coords for 13-L3pyr-77.CNG.ugx, current given in C/ms)
CE:set_influx(5e-9, 6.54e-05, 2.665e-05, 3.985e-05, 0.0, 0.04) -- near soma
CE:set_influx(5e-9, 3.955e-06, 1.095e-06, -3.365e-06, 0.001, 0.0025) -- 1st edge soma to dend
CE:set_influx(0.3e-9, 3.955e-06, 1.095e-06, -3.365e-06, 0.0, 0.03) -- 1st 1st edge soma to dend
CE:set_influx(0.095e-9, 0.0, 0.0, 0.0, 0.1, 0.1) -- soma center vertex
CE:set_influx(0.2e-9, 0.0, 0.0, 0.0, 0.005, 0.0005) -- soma center vertex
CE:set_influx(10.0e-9, 0.000139, 0.00020809, -2.037e-05, 0.005, 0.005) -- distal apical dendrite vertex v1
CE:set_influx(10.0e-9, -3.96e-06, 0.0002173, -5.431e-05, 0.005, 0.005) -- distal apical dendrite vertex v2
--]]
-- create domain discretization
domainDisc = DomainDiscretization(approxSpace)
domainDisc:add(CE)
assTuner = domainDisc:ass_tuner()
-- create time discretization
timeDisc = ThetaTimeStep(domainDisc)
timeDisc:set_theta(1.0)
-- create operator from discretization
linOp = AssembledLinearOperator(timeDisc)
------------------
-- solver setup --
------------------
-- debug writer
dbgWriter = GridFunctionDebugWriter(approxSpace)
dbgWriter:set_vtk_output(true)
-- linear solver --
linConvCheck = CompositeConvCheck(approxSpace, 20, 2e-26, 1e-08)
linConvCheck:set_component_check("v", 1e-21, 1e-12)
linConvCheck:set_verbose(verbose)
ilu = ILU()
cgSolver = CG()
cgSolver:set_preconditioner(ilu)
cgSolver:set_convergence_check(linConvCheck)
--cgSolver:set_debug(dbgWriter)
----------------------
-- time stepping --
----------------------
time = 0.0
-- init solution
u = GridFunction(approxSpace)
b = GridFunction(approxSpace)
u:set(0.0)
Interpolate(v_eq, u, "v")
-- file i/o setup for sample calcium concentration measurement
measFileVm = outPath.."measVm.txt"
if ProcRank() == 0 then
measOutVm = assert(io.open(measFileVm, "a"))
end
-- write start solution
if generateVTKoutput then
out = VTKOutput()
out:print(outPath.."vtk/solution", u, 0, time)
end
-- store grid function in vector of old solutions
uOld = u:clone()
solTimeSeries = SolutionTimeSeries()
solTimeSeries:push(uOld, time)
curr_dt = dt
dtred = 2
lv = 0
maxLv = 10
cb_counter = {}
cb_counter[lv] = 0
while endTime-time > 0.001*curr_dt do
-- setup time Disc for old solutions and timestep
timeDisc:prepare_step(solTimeSeries, curr_dt)
-- reduce time step if cfl < curr_dt
-- (this needs to be done AFTER prepare_step as channels are updated there)
dtChanged = false
cfl = CE:estimate_cfl_cond(solTimeSeries:latest())
print("estimated CFL condition: dt < " .. cfl)
while (curr_dt > cfl) do
curr_dt = curr_dt/dtred
if lv+1 > maxLv then
print("Time step too small.")
exit()
end
lv = lv + 1
cb_counter[lv] = 0
print("estimated CFL condition: dt < " .. cfl .. " - reducing time step to " .. curr_dt)
dtChanged = true
end
-- increase time step if cfl > curr_dt / dtred (and if time is aligned with new bigger step size)
while curr_dt*dtred < cfl and lv > 0 and cb_counter[lv] % (dtred) == 0 do
curr_dt = curr_dt*dtred
lv = lv - 1
cb_counter[lv] = cb_counter[lv] + cb_counter[lv+1]/dtred
cb_counter[lv+1] = 0
print ("estimated CFL condition: dt < " .. cfl .. " - increasing time step to " .. curr_dt)
dtChanged = true
end
print("++++++ POINT IN TIME " .. math.floor((time+curr_dt)/curr_dt+0.5)*curr_dt .. " BEGIN ++++++")
-- prepare again with new time step size
if dtChanged == true then
timeDisc:prepare_step(solTimeSeries, curr_dt)
end
-- assemble linear problem
matrixIsConst = time ~= 0.0 and dtChanged == false
assTuner:set_matrix_is_const(matrixIsConst)
AssembleLinearOperatorRhsAndSolution(linOp, u, b)
-- synchronize (for profiling)
PclDebugBarrierAll()
-- apply linear solver
ilu:set_disable_preprocessing(matrixIsConst)
if ApplyLinearSolver(linOp, u, b, cgSolver) == false then
print("Could not apply linear solver.")
exit()
end
-- log time and vm in Soma
if ProcRank() == 0 then
if cell == "12-L3pyr" then
vm_soma = EvaluateAtClosestVertex(MakeVec(0.0, 0.0, 0.0), u, "v", "soma", dom:subset_handler())
vm_axon = EvaluateAtClosestVertex(MakeVec(-3.828e-05, -0.00013166, -2.34e-05), u, "v", "axon", dom:subset_handler())
vm_dend = EvaluateAtClosestVertex(MakeVec(8.304e-05, -1.982e-05, -8.4e-06), u, "v", "dendrite", dom:subset_handler())
vm_aDend = EvaluateAtClosestVertex(MakeVec(-3.84e-06, 0.00018561, -3.947e-05), u, "v", "apical_dendrite", dom:subset_handler())
measOutVm:write(time, "\t", vm_soma, "\t", vm_axon, "\t", vm_dend, "\t", vm_aDend, "\n")
else
vm_soma = EvaluateAtClosestVertex(MakeVec(6.9e-07, 3.74e-06, -2.86e-06), u, "v", "soma", dom:subset_handler())
vm_axon = EvaluateAtClosestVertex(MakeVec(-4.05e-06, 6.736e-05, -1.341e-05), u, "v", "axon", dom:subset_handler())
vm_dend = EvaluateAtClosestVertex(MakeVec(-4.631e-05, -0.0001252, 4.62e-06), u, "v", "dendrite", dom:subset_handler())
measOutVm:write(time, "\t", vm_soma, "\t", vm_axon, "\t", vm_dend, "\t", -65, "\n")
end
end
-- update to new time
time = solTimeSeries:time(0) + curr_dt
-- vtk output
if generateVTKoutput then
if math.abs(time/pstep - math.floor(time/pstep+0.5)) < 1e-5 then
out:print(outPath.."vtk/solution", u, math.floor(time/pstep+0.5), time)
end
end
-- updte time series (reuse memory)
oldestSol = solTimeSeries:oldest()
VecScaleAssign(oldestSol, 1.0, u)
solTimeSeries:push_discard_oldest(oldestSol, time)
-- increment check-back counter
cb_counter[lv] = cb_counter[lv] + 1
print("++++++ POINT IN TIME " .. math.floor((time)/curr_dt+0.5)*curr_dt .. " END ++++++")
end
-- end timeseries, produce gathering file
if generateVTKoutput then
out:write_time_pvd(outPath.."vtk/solution", u)
end
-- close measure file
if ProcRank() == 0 then
measOutVm:close()
end
if doProfiling then
WriteProfileData(outPath .."pd.pdxml")
end