Biochemically detailed model of LTP and LTD in a cortical spine (Maki-Marttunen et al 2020)

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Accession:260971
"Signalling pathways leading to post-synaptic plasticity have been examined in many types of experimental studies, but a unified picture on how multiple biochemical pathways collectively shape neocortical plasticity is missing. We built a biochemically detailed model of post-synaptic plasticity describing CaMKII, PKA, and PKC pathways and their contribution to synaptic potentiation or depression. We developed a statistical AMPA-receptor-tetramer model, which permits the estimation of the AMPA-receptor-mediated maximal synaptic conductance based on numbers of GluR1s and GluR2s predicted by the biochemical signalling model. We show that our model reproduces neuromodulator-gated spike-timing-dependent plasticity as observed in the visual cortex and can be fit to data from many cortical areas, uncovering the biochemical contributions of the pathways pinpointed by the underlying experimental studies. Our model explains the dependence of different forms of plasticity on the availability of different proteins and can be used for the study of mental disorder-associated impairments of cortical plasticity."
Reference:
1 . Mäki-Marttunen T, Iannella N, Edwards AG, Einevoll GT, Blackwell KT (2020) A unified computational model for cortical post-synaptic plasticity. Elife [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex spiking regular (RS) neuron;
Channel(s): I Calcium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Glutamate; Norephinephrine; Acetylcholine;
Simulation Environment: NEURON; NeuroRD;
Model Concept(s): Long-term Synaptic Plasticity;
Implementer(s): Maki-Marttunen, Tuomo [tuomomm at uio.no];
Search NeuronDB for information about:  I Calcium; Acetylcholine; Norephinephrine; Glutamate;
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synaptic
L23PC
L23_PC_cADpyr229_1
hoc_recordings
mechanisms
morphology
python_recordings
synapses
README *
biophysics.hoc *
cellinfo.json *
CHANGELOG *
constants.hoc *
creategui.hoc *
createsimulation.hoc *
createsimulation_nogui.hoc
current_amps.dat *
init.hoc *
init_nogui.hoc
LICENSE *
morphology.hoc *
mosinit.hoc *
ringplot.hoc *
run.py *
run_hoc.sh *
run_py.sh *
run_RmpRiTau.py *
run_RmpRiTau_py.sh *
template.hoc
template_nosyn.hoc
VERSION *
                            
//cp init.hoc init_nogui.hoc

load_file("stdlib.hoc")
load_file("stdrun.hoc")
load_file("constants.hoc")

load_file("import3d.hoc")
load_file("morphology.hoc")
load_file("biophysics.hoc")
load_file("template_nosyn.hoc")

objref cell
objref time, voltage
objref step_stimulus
cell = new cADpyr229_L23_PC_5ecbf9b163(0)
voltage = new Vector()
time = new Vector()

access cell.soma
time.record(&t, 0.1)
voltage.record(&v(0.5), 0.1)

step_stimulus = new IClamp(0.5)
step_stimulus.dur = 2000
step_stimulus.del = 700
step_stimulus.amp = 0.18
cell.soma step_stimulus

tstop = 2000
init()
run()


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