diff --git a/README.md b/README.md
index 293a693bb..fa5faf4b0 100644
--- a/README.md
+++ b/README.md
@@ -7,6 +7,10 @@ Human Brain Project
hjorth@kth.se
## Funding
+Simulations were also performed on resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) at PDC KTH partially funded by the Swedish Research Council through grant agreement no. 2022-06725.
+
+The study was supported by the Swedish Research Council (VR-M-2020-01652), Swedish e-Science Research Centre (SeRC), Science for Life Lab, EU/Horizon 2020 no. 945539 (HBP SGA3) and No. 101147319 (EBRAINS 2.0 Project), European Union's Research and Innovation Program Horizon Europe under grant agreement No 101137289 (the Virtual Brain Twin Project), and KTH Digital Futures.
+
Horizon 2020 Framework Programme (785907, HBP SGA2); Horizon 2020 Framework Programme (945539, HBP SGA3); Vetenskapsrådet (VR-M-2017-02806, VR-M-2020-01652); Swedish e-science Research Center (SeRC); KTH Digital Futures. The computations are enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at PDC KTH partially funded by the Swedish Research Council through grant agreement no. 2018-05973. We acknowledge the use of Fenix Infrastructure resources, which are partially funded from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858. Snudda is supported and featured on EBRAINS.
## Citation
diff --git a/examples/notebooks/neuromodulation/data/JSON/reaction_diffusion_D1.json b/examples/notebooks/neuromodulation/data/JSON/reaction_diffusion_D1.json
index 7988f0df2..7c016e181 100644
--- a/examples/notebooks/neuromodulation/data/JSON/reaction_diffusion_D1.json
+++ b/examples/notebooks/neuromodulation/data/JSON/reaction_diffusion_D1.json
@@ -1,215 +1,215 @@
{
"species": {
- "AC5": {
- "initial_concentration": 700.0,
+ "GaolfGDP": {
+ "initial_concentration": 0.0100831208954662,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 700.0,
+ "concentration": 0.0100831208954662,
"boundary_condition": false
},
- "AC5_ATP": {
- "initial_concentration": 0.0,
+ "Gbgolf": {
+ "initial_concentration": 29.8851246006536,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 29.8851246006536,
"boundary_condition": false
},
- "AC5_Ca": {
- "initial_concentration": 0.0,
+ "GaolfGTP": {
+ "initial_concentration": 0.00891348109605658,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 0.00891348109605658,
"boundary_condition": false
},
- "AC5_Ca_ATP": {
- "initial_concentration": 0.0,
+ "D1RDAGolf": {
+ "initial_concentration": 2.00890216216344,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 2.00890216216344,
"boundary_condition": false
},
- "AC5_Ca_GaolfGTP": {
- "initial_concentration": 0.0,
+ "Golf": {
+ "initial_concentration": 1453.07257228221,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 1453.07257228221,
"boundary_condition": false
},
- "AC5_Ca_GaolfGTP_ATP": {
- "initial_concentration": 0.0,
+ "D1RGolf": {
+ "initial_concentration": 515.033400954975,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 515.033400954975,
"boundary_condition": false
},
- "AC5_GaolfGTP": {
- "initial_concentration": 0.0,
+ "D1RDA": {
+ "initial_concentration": 5.95922532787641,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 5.95922532787641,
"boundary_condition": false
},
- "AC5_GaolfGTP_ATP": {
- "initial_concentration": 0.0,
+ "D1R": {
+ "initial_concentration": 1476.99847155499,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 1476.99847155499,
"boundary_condition": false
},
- "AMP": {
- "initial_concentration": 0.0,
+ "cAMP": {
+ "initial_concentration": 38.1860143351998,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
- "boundary_condition": true
+ "concentration": 38.1860143351998,
+ "boundary_condition": false
},
- "ATP": {
- "initial_concentration": 5000000.0,
+ "AC5": {
+ "initial_concentration": 2.66944644058834,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 5000000.0,
- "boundary_condition": true
+ "concentration": 2.66944644058834,
+ "boundary_condition": false
},
- "B56PP2A": {
- "initial_concentration": 2000.0,
+ "AC5GaolfGTP": {
+ "initial_concentration": 0.118090407078866,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 2000.0,
+ "concentration": 0.118090407078866,
"boundary_condition": false
},
- "B56PP2A_D32p75": {
- "initial_concentration": 0.0,
+ "PDE4": {
+ "initial_concentration": 1506.80848289944,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 1506.80848289944,
"boundary_condition": false
},
- "B56PP2A_pARPP21": {
- "initial_concentration": 0.0,
+ "PKA": {
+ "initial_concentration": 1157.14133868944,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 1157.14133868944,
"boundary_condition": false
},
- "B56PP2Ap": {
- "initial_concentration": 0.0,
+ "PKAcAMP2": {
+ "initial_concentration": 3.2824343126378,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 3.2824343126378,
"boundary_condition": false
},
- "B56PP2Ap_D32p75": {
- "initial_concentration": 0.0,
+ "PKAcAMP4": {
+ "initial_concentration": 0.0867374139319834,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 0.0867374139319834,
"boundary_condition": false
},
- "B56PP2Ap_pARPP21": {
- "initial_concentration": 0.0,
+ "PKAreg": {
+ "initial_concentration": 39.489489583994,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 39.489489583994,
"boundary_condition": false
},
- "B72PP2A": {
- "initial_concentration": 2000.0,
+ "PKAc": {
+ "initial_concentration": 3.66078057924366,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 2000.0,
+ "concentration": 3.66078057924366,
"boundary_condition": false
},
- "B72PP2A_D32p34": {
- "initial_concentration": 0.0,
+ "PP1": {
+ "initial_concentration": 2927.34258198642,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 2927.34258198642,
"boundary_condition": false
},
- "B72PP2A_D32p75": {
- "initial_concentration": 0.0,
+ "DA": {
+ "initial_concentration": 20.0,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 20.0,
"boundary_condition": false
},
- "B72PP2A_pARPP21": {
+ "AMP": {
"initial_concentration": 0.0,
"diffusion_constant": 0,
"charge": 0,
@@ -218,2256 +218,435 @@
"dend_internal"
],
"concentration": 0.0,
- "boundary_condition": false
+ "boundary_condition": true
},
- "B72PP2A_Ca_D32p34": {
- "initial_concentration": 0.0,
+ "PDE4_cAMP": {
+ "initial_concentration": 493.191517100561,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 493.191517100561,
"boundary_condition": false
},
- "B72PP2A_Ca_D32p75": {
- "initial_concentration": 0.0,
+ "PDE10c": {
+ "initial_concentration": 0.578101285574062,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 0.578101285574062,
"boundary_condition": false
},
- "B72PP2A_Ca": {
- "initial_concentration": 0.0,
+ "PDE10": {
+ "initial_concentration": 396.456253552482,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 396.456253552482,
"boundary_condition": false
},
- "B72PP2A_Ca_pARPP21": {
- "initial_concentration": 0.0,
+ "PDE10_cAMP": {
+ "initial_concentration": 302.781683628694,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 302.781683628694,
"boundary_condition": false
},
- "Ca": {
- "initial_concentration": 60.0,
+ "PDE10c_cAMP": {
+ "initial_concentration": 0.183961533250013,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 60.0,
- "boundary_condition": true
+ "concentration": 0.183961533250013,
+ "boundary_condition": false
},
- "CaM": {
- "initial_concentration": 9000.0,
+ "ATP": {
+ "initial_concentration": 5000000.0,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 9000.0,
- "boundary_condition": false
+ "concentration": 5000000.0,
+ "boundary_condition": true
},
- "CaM_Ca2": {
- "initial_concentration": 0.0,
+ "AC5GaolfGTP_ATP": {
+ "initial_concentration": 29.7480375915836,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 29.7480375915836,
"boundary_condition": false
},
- "CaM_Ca4": {
- "initial_concentration": 0.0,
+ "AC5_ATP": {
+ "initial_concentration": 667.46442556075,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 667.46442556075,
"boundary_condition": false
},
- "CaM_Ca4_pARPP21": {
- "initial_concentration": 0.0,
+ "PP1_Target1p": {
+ "initial_concentration": 73.6574180095066,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 73.6574180095066,
"boundary_condition": false
},
- "CaMKII": {
- "initial_concentration": 20000.0,
+ "Target1p": {
+ "initial_concentration": 377.428073140956,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 20000.0,
+ "concentration": 377.428073140956,
"boundary_condition": false
},
- "CaMKII_CaM_Ca4": {
- "initial_concentration": 0.0,
+ "PKAc_Target1": {
+ "initial_concentration": 36.8287090047503,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 36.8287090047503,
"boundary_condition": false
},
- "CaMKII_CaM": {
- "initial_concentration": 0.0,
+ "Target1": {
+ "initial_concentration": 2515.08579984072,
"diffusion_constant": 0,
"charge": 0,
"regions": [
"soma_internal",
"dend_internal"
],
- "concentration": 0.0,
+ "concentration": 2515.08579984072,
"boundary_condition": false
- },
- "CaMKII_CaM_Ca2": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ }
+ },
+ "reactions": {
+ "revreaction_1": {
+ "reactants": "D1RGolf + DA",
+ "products": "D1RDAGolf",
+ "forward_rate": 0.05,
+ "backward_rate": 250.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "CaMKII_CaM_Ca2_psd": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_2": {
+ "reactants": "D1R + DA",
+ "products": "D1RDA",
+ "forward_rate": 0.05,
+ "backward_rate": 250.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "CaMKII_CaM_psd": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_3": {
+ "reactants": "D1R + Golf",
+ "products": "D1RGolf",
+ "forward_rate": 0.06,
+ "backward_rate": 250.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "CaMKII_CaM_Ca4_psd": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_4": {
+ "reactants": "Golf + D1RDA",
+ "products": "D1RDAGolf",
+ "forward_rate": 0.06,
+ "backward_rate": 250.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "CaMKII_psd": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_5": {
+ "reactants": "AC5 + GaolfGTP",
+ "products": "AC5GaolfGTP",
+ "forward_rate": 10.0,
+ "backward_rate": 1.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "cAMP": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_6": {
+ "reactants": "AC5GaolfGTP + ATP",
+ "products": "AC5GaolfGTP_ATP",
+ "forward_rate": 0.00255,
+ "backward_rate": 1.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "Substrate": {
- "initial_concentration": 3000.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_7": {
+ "reactants": "AC5 + ATP",
+ "products": "AC5_ATP",
+ "forward_rate": 0.0001,
+ "backward_rate": 1.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 3000.0,
- "boundary_condition": false
+ ]
},
- "CDK5": {
- "initial_concentration": 1800.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_8": {
+ "reactants": "GaolfGTP + AC5_ATP",
+ "products": "AC5GaolfGTP_ATP",
+ "forward_rate": 10.0,
+ "backward_rate": 1.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 1800.0,
- "boundary_condition": false
+ ]
},
- "CDK5_D32": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_9": {
+ "reactants": "cAMP + PDE4",
+ "products": "PDE4_cAMP",
+ "forward_rate": 0.03,
+ "backward_rate": 1.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "D1R": {
- "initial_concentration": 2000.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_10": {
+ "reactants": "PDE10 + 2 * cAMP",
+ "products": "PDE10c",
+ "forward_rate": 1e-06,
+ "backward_rate": 1.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 2000.0,
- "boundary_condition": false
+ ]
},
- "D1R_DA": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_11": {
+ "reactants": "cAMP + PDE10",
+ "products": "PDE10_cAMP",
+ "forward_rate": 0.1,
+ "backward_rate": 2.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "D1R_Golf_DA": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_12": {
+ "reactants": "cAMP + PDE10c",
+ "products": "PDE10c_cAMP",
+ "forward_rate": 0.1,
+ "backward_rate": 2.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "D1R_Golf": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_13": {
+ "reactants": "cAMP + PKA",
+ "products": "PKAcAMP2",
+ "forward_rate": 0.026,
+ "backward_rate": 350.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "D32p34": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_14": {
+ "reactants": "cAMP + PKAcAMP2",
+ "products": "PKAcAMP4",
+ "forward_rate": 0.0346,
+ "backward_rate": 50.0,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "D32p75": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "revreaction_15": {
+ "reactants": "PKAcAMP4",
+ "products": "PKAc + PKAreg",
+ "forward_rate": 50.0,
+ "backward_rate": 0.03,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "D32": {
- "initial_concentration": 50000.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "irrevreaction_1": {
+ "reactants": "D1RDAGolf",
+ "products": "Gbgolf + D1RDA + GaolfGTP",
+ "forward_rate": 15.0,
+ "backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 50000.0,
- "boundary_condition": false
+ ]
},
- "DA": {
- "initial_concentration": 20.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "irrevreaction_2": {
+ "reactants": "GaolfGTP",
+ "products": "GaolfGDP",
+ "forward_rate": 30.0,
+ "backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 20.0,
- "boundary_condition": false
+ ]
},
- "GaolfGDP": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "irrevreaction_3": {
+ "reactants": "GaolfGDP + Gbgolf",
+ "products": "Golf",
+ "forward_rate": 100.0,
+ "backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "GaolfGTP": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
+ "irrevreaction_4": {
+ "reactants": "AC5GaolfGTP_ATP",
+ "products": "cAMP + AC5GaolfGTP",
+ "forward_rate": 50.0,
+ "backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
+ ]
},
- "Gbgolf": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
- "regions": [
- "soma_internal",
- "dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
- },
- "Golf": {
- "initial_concentration": 2000.0,
- "diffusion_constant": 0,
- "charge": 0,
- "regions": [
- "soma_internal",
- "dend_internal"
- ],
- "concentration": 2000.0,
- "boundary_condition": false
- },
- "pCaMKII": {
- "initial_concentration": 0.0,
- "diffusion_constant": 0,
- "charge": 0,
- "regions": [
- "soma_internal",
- "dend_internal"
- ],
- "concentration": 0.0,
- "boundary_condition": false
- },
- "pCaMKII_CaM_Ca4": {
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- "ReactionFlux28": {
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- "ReactionFlux29": {
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- "reactants": "D32p75 + B56PP2A",
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- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux32": {
- "reactants": "B72PP2A_Ca_D32p34",
- "products": "B72PP2A_Ca + D32",
- "forward_rate": 0.00299999999999998,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux33": {
- "reactants": "B72PP2A_D32p34",
- "products": "D32 + B72PP2A",
- "forward_rate": 0.00299999999999998,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux34": {
- "reactants": "D32p34 + B72PP2A_Ca",
- "products": "B72PP2A_Ca_D32p34",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux35": {
- "reactants": "D32p34 + B72PP2A",
- "products": "B72PP2A_D32p34",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux36": {
- "reactants": "PP2Bc_D32p34",
- "products": "D32 + PP2Bc",
- "forward_rate": 0.00119999999999999,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux37": {
- "reactants": "B56PP2Ap",
- "products": "B56PP2A",
- "forward_rate": 7.99999999999994e-06,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux38": {
- "reactants": "cAMP + PKA",
- "products": "PKA_Ca2MP",
- "forward_rate": 2.60000000000001e-05,
- "backward_rate": 0.35,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux39": {
- "reactants": "cAMP + PKA_Ca2MP",
- "products": "PKA_Ca4MP",
- "forward_rate": 3.46000000000003e-05,
- "backward_rate": 0.0500000000000001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux40": {
- "reactants": "PKA_Ca4MP",
- "products": "PKAc + PKAreg",
- "forward_rate": 0.0500000000000001,
- "backward_rate": 2.99999999999998e-05,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux41": {
- "reactants": "cAMP + PDE4",
- "products": "PDE4_cAMP",
- "forward_rate": 2.99999999999998e-05,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux42": {
- "reactants": "PDE4_cAMP",
- "products": "PDE4 + AMP",
- "forward_rate": 0.00250000000000001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux43": {
- "reactants": "PDE10r + 2 * cAMP",
- "products": "PDE10c",
- "forward_rate": 1e-09,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux44": {
- "reactants": "PDE10r_cAMP",
- "products": "PDE10r + AMP",
- "forward_rate": 0.00299999999999998,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux45": {
- "reactants": "cAMP + PDE10r",
- "products": "PDE10r_cAMP",
- "forward_rate": 0.0001,
- "backward_rate": 0.00199999999999999,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux46": {
- "reactants": "PDE10c_cAMP",
- "products": "PDE10c + AMP",
- "forward_rate": 0.01,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux47": {
- "reactants": "GaolfGDP + Gbgolf",
- "products": "Golf",
- "forward_rate": 0.1,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux48": {
- "reactants": "AC5_GaolfGTP + ATP",
- "products": "AC5_GaolfGTP_ATP",
- "forward_rate": 2.55000000000003e-06,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux49": {
- "reactants": "AC5 + ATP",
- "products": "AC5_ATP",
- "forward_rate": 1e-07,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux50": {
- "reactants": "AC5_Ca + ATP",
- "products": "AC5_Ca_ATP",
- "forward_rate": 7.5e-08,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux51": {
- "reactants": "AC5_Ca_GaolfGTP + ATP",
- "products": "AC5_Ca_GaolfGTP_ATP",
- "forward_rate": 1.30000000000001e-06,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux52": {
- "reactants": "GaolfGTP + AC5_ATP",
- "products": "AC5_GaolfGTP_ATP",
- "forward_rate": 0.01,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux53": {
- "reactants": "GaolfGTP + AC5_Ca_ATP",
- "products": "AC5_Ca_GaolfGTP_ATP",
- "forward_rate": 0.01,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux54": {
- "reactants": "Ca + AC5_ATP",
- "products": "AC5_Ca_ATP",
- "forward_rate": 1e-06,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux55": {
- "reactants": "AC5_GaolfGTP_ATP",
- "products": "cAMP + AC5_GaolfGTP",
- "forward_rate": 0.0500000000000001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux56": {
- "reactants": "cAMP + AC5_GaolfGTP",
- "products": "AC5_GaolfGTP_ATP",
- "forward_rate": 0.00255000000000003,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux57": {
- "reactants": "AC5_ATP",
- "products": "cAMP + AC5",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux58": {
- "reactants": "cAMP + AC5",
- "products": "AC5_ATP",
- "forward_rate": 2e-06,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux59": {
- "reactants": "AC5_Ca_ATP",
- "products": "cAMP + AC5_Ca",
- "forward_rate": 0.000500000000000001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux60": {
- "reactants": "cAMP + AC5_Ca",
- "products": "AC5_Ca_ATP",
- "forward_rate": 7.5e-07,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux61": {
- "reactants": "AC5_Ca_GaolfGTP_ATP",
- "products": "cAMP + AC5_Ca_GaolfGTP",
- "forward_rate": 0.0250000000000001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux62": {
- "reactants": "cAMP + AC5_Ca_GaolfGTP",
- "products": "AC5_Ca_GaolfGTP_ATP",
- "forward_rate": 0.000650000000000007,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux63": {
- "reactants": "AC5_GaolfGTP",
- "products": "AC5 + GaolfGDP",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux64": {
- "reactants": "AC5_Ca_GaolfGTP",
- "products": "AC5_Ca + GaolfGDP",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux65": {
- "reactants": "AC5_GaolfGTP_ATP",
- "products": "AC5_ATP + GaolfGDP",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux66": {
- "reactants": "AC5_Ca_GaolfGTP_ATP",
- "products": "AC5_Ca_ATP + GaolfGDP",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux67": {
- "reactants": "D1R + Golf",
- "products": "D1R_Golf",
- "forward_rate": 5.99999999999995e-05,
- "backward_rate": 0.25,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux68": {
- "reactants": "Golf + D1R_DA",
- "products": "D1R_Golf_DA",
- "forward_rate": 5.99999999999995e-05,
- "backward_rate": 0.25,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux69": {
- "reactants": "cAMP + PDE10c",
- "products": "PDE10c_cAMP",
- "forward_rate": 0.0001,
- "backward_rate": 0.00199999999999999,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux70": {
- "reactants": "CaMKII + CaM_Ca4",
- "products": "CaMKII_CaM_Ca4",
- "forward_rate": 0.0001,
- "backward_rate": 0.0399999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux71": {
- "reactants": "CaM_Ca2 + CaMKII",
- "products": "CaMKII_CaM_Ca2",
- "forward_rate": 0.0001,
- "backward_rate": 0.4,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux72": {
- "reactants": "CaM + CaMKII",
- "products": "CaMKII_CaM",
- "forward_rate": 0.0001,
- "backward_rate": 4.0,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux73": {
- "reactants": "CaMKII_CaM_Ca2 + Ca",
- "products": "CaMKII_CaM_Ca4",
- "forward_rate": 0.0001,
- "backward_rate": 0.1,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux74": {
- "reactants": "CaMKII_CaM + Ca",
- "products": "CaMKII_CaM_Ca2",
- "forward_rate": 5.99999999999995e-06,
- "backward_rate": 0.00199999999999999,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux75": {
- "reactants": "pCaMKII_CaM_Ca2 + Ca",
- "products": "pCaMKII_CaM_Ca4",
- "forward_rate": 0.0001,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux76": {
- "reactants": "pCaMKII_CaM + Ca",
- "products": "pCaMKII_CaM_Ca2",
- "forward_rate": 5.99999999999995e-06,
- "backward_rate": 0.00199999999999999,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux77": {
- "reactants": "pCaMKII + CaM_Ca4",
- "products": "pCaMKII_CaM_Ca4",
- "forward_rate": 0.0001,
- "backward_rate": 0.000399999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux78": {
- "reactants": "pCaMKII + CaM_Ca2",
- "products": "pCaMKII_CaM_Ca2",
- "forward_rate": 0.0001,
- "backward_rate": 0.0399999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux79": {
- "reactants": "pCaMKII + CaM",
- "products": "pCaMKII_CaM",
- "forward_rate": 0.0001,
- "backward_rate": 0.4,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux80": {
- "reactants": "ARPP21 + PKAc",
- "products": "PKAc_ARPP21",
- "forward_rate": 4.49999999999997e-05,
- "backward_rate": 0.2,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux81": {
- "reactants": "PKAc_ARPP21",
- "products": "PKAc + pARPP21",
- "forward_rate": 0.01,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux82": {
- "reactants": "pARPP21 + CaM_Ca4",
- "products": "CaM_Ca4_pARPP21",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux83": {
- "reactants": "B72PP2A_Ca_pARPP21",
- "products": "ARPP21 + B72PP2A_Ca",
- "forward_rate": 0.01,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux84": {
- "reactants": "pARPP21 + B72PP2A_Ca",
- "products": "B72PP2A_Ca_pARPP21",
- "forward_rate": 7.00000000000004e-06,
- "backward_rate": 0.1,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux85": {
- "reactants": "B72PP2A_pARPP21",
- "products": "ARPP21 + B72PP2A",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux86": {
- "reactants": "pARPP21 + B72PP2A",
- "products": "B72PP2A_pARPP21",
- "forward_rate": 3.99999999999998e-06,
- "backward_rate": 0.1,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux87": {
- "reactants": "B56PP2Ap_pARPP21",
- "products": "ARPP21 + B56PP2Ap",
- "forward_rate": 0.01,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux88": {
- "reactants": "pARPP21 + B56PP2Ap",
- "products": "B56PP2Ap_pARPP21",
- "forward_rate": 7.00000000000004e-06,
- "backward_rate": 0.1,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux89": {
- "reactants": "B56PP2A_pARPP21",
- "products": "ARPP21 + B56PP2A",
- "forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux90": {
- "reactants": "pARPP21 + B56PP2A",
- "products": "B56PP2A_pARPP21",
- "forward_rate": 3.99999999999998e-06,
- "backward_rate": 0.1,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux91": {
- "reactants": "pSubstrate + PP1",
- "products": "PP1_pSubstrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux92": {
- "reactants": "PP1_pSubstrate",
- "products": "PP1 + Substrate",
- "forward_rate": 0.01,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux93": {
- "reactants": "Substrate + pCaMKII_psd",
- "products": "pCaMKII_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux94": {
- "reactants": "pCaMKII_psd_Substrate",
- "products": "pCaMKII_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_5": {
+ "reactants": "cAMP + AC5GaolfGTP",
+ "products": "AC5GaolfGTP_ATP",
+ "forward_rate": 2.55,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux95": {
- "reactants": "pCaMKII",
- "products": "CaMKII",
- "forward_rate": 0.0001,
+ "irrevreaction_6": {
+ "reactants": "AC5_ATP",
+ "products": "cAMP + AC5",
+ "forward_rate": 1.0,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux96": {
- "reactants": "Substrate + pCaMKII_CaM_psd",
- "products": "pCaMKII_CaM_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux97": {
- "reactants": "pCaMKII_CaM_psd_Substrate",
- "products": "pCaMKII_CaM_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_7": {
+ "reactants": "cAMP + AC5",
+ "products": "AC5_ATP",
+ "forward_rate": 0.002,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux98": {
- "reactants": "Substrate + pCaMKII_CaM_Ca2_psd",
- "products": "pCaMKII_CaM_Ca2_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux99": {
- "reactants": "pCaMKII_CaM_Ca2_psd_Substrate",
- "products": "pCaMKII_CaM_Ca2_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_8": {
+ "reactants": "AC5GaolfGTP",
+ "products": "AC5 + GaolfGDP",
+ "forward_rate": 1.0,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux100": {
- "reactants": "Substrate + pCaMKII_CaM_Ca4_psd",
- "products": "pCaMKII_CaM_Ca4_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux101": {
- "reactants": "pCaMKII_CaM_Ca4_psd_Substrate",
- "products": "pCaMKII_CaM_Ca4_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_9": {
+ "reactants": "AC5GaolfGTP_ATP",
+ "products": "AC5_ATP + GaolfGDP",
+ "forward_rate": 1.0,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux102": {
- "reactants": "Substrate + CaMKII_CaM_psd",
- "products": "CaMKII_CaM_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux103": {
- "reactants": "CaMKII_CaM_psd_Substrate",
- "products": "CaMKII_CaM_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_10": {
+ "reactants": "PDE4_cAMP",
+ "products": "PDE4 + AMP",
+ "forward_rate": 2.5,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux104": {
- "reactants": "Substrate + CaMKII_CaM_Ca2_psd",
- "products": "CaMKII_CaM_Ca2_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux105": {
- "reactants": "CaMKII_CaM_Ca2_psd_Substrate",
- "products": "CaMKII_CaM_Ca2_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_11": {
+ "reactants": "PDE10_cAMP",
+ "products": "PDE10 + AMP",
+ "forward_rate": 3.0,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux106": {
- "reactants": "Substrate + CaMKII_CaM_Ca4_psd",
- "products": "CaMKII_CaM_Ca4_psd_Substrate",
- "forward_rate": 5.00000000000001e-07,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux107": {
- "reactants": "CaMKII_CaM_Ca4_psd_Substrate",
- "products": "CaMKII_CaM_Ca4_psd + pSubstrate",
- "forward_rate": 0.01,
+ "irrevreaction_12": {
+ "reactants": "PDE10c_cAMP",
+ "products": "PDE10c + AMP",
+ "forward_rate": 10.0,
"backward_rate": null,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux108": {
- "reactants": "pCaMKII_CaM_Ca4",
- "products": "pCaMKII_CaM_Ca4_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 1e-06,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux109": {
- "reactants": "pCaMKII_CaM_Ca2",
- "products": "pCaMKII_CaM_Ca2_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 1e-06,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux110": {
- "reactants": "pCaMKII_CaM",
- "products": "pCaMKII_CaM_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 1e-06,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux111": {
- "reactants": "pCaMKII",
- "products": "pCaMKII_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 1e-06,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux112": {
- "reactants": "CaM_Ca4 + pCaMKII_psd",
- "products": "pCaMKII_CaM_Ca4_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.000399999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux113": {
- "reactants": "pCaMKII_psd + CaM_Ca2",
- "products": "pCaMKII_CaM_Ca2_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.0399999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux114": {
- "reactants": "CaM + pCaMKII_psd",
- "products": "pCaMKII_CaM_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.4,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux115": {
- "reactants": "pCaMKII_CaM_psd + Ca",
- "products": "pCaMKII_CaM_Ca2_psd",
- "forward_rate": 5.99999999999995e-06,
- "backward_rate": 0.00199999999999999,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux116": {
- "reactants": "pCaMKII_CaM_Ca2_psd + Ca",
- "products": "pCaMKII_CaM_Ca4_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.01,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux117": {
- "reactants": "pCaMKII_psd + PP1",
- "products": "PP1_pCaMKII_psd",
- "forward_rate": 7.99999999999994e-07,
- "backward_rate": 0.001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux118": {
- "reactants": "PP1_pCaMKII_psd",
- "products": "PP1 + CaMKII_psd",
+ "revreaction_17": {
+ "reactants": "PP1 + Target1p",
+ "products": "PP1_Target1p",
"forward_rate": 0.001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux119": {
- "reactants": "CaMKII_psd",
- "products": "CaMKII",
- "forward_rate": 0.000500000000000001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux120": {
- "reactants": "CaM_Ca4 + CaMKII_psd",
- "products": "CaMKII_CaM_Ca4_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.0399999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux121": {
- "reactants": "CaM_Ca2 + CaMKII_psd",
- "products": "CaMKII_CaM_Ca2_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.4,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux122": {
- "reactants": "CaM + CaMKII_psd",
- "products": "CaMKII_CaM_psd",
- "forward_rate": 0.0001,
- "backward_rate": 4.0,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux123": {
- "reactants": "CaMKII_CaM_Ca2_psd + Ca",
- "products": "CaMKII_CaM_Ca4_psd",
- "forward_rate": 0.0001,
- "backward_rate": 0.1,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux124": {
- "reactants": "CaMKII_CaM_psd + Ca",
- "products": "CaMKII_CaM_Ca2_psd",
- "forward_rate": 5.99999999999995e-06,
- "backward_rate": 0.00199999999999999,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux125": {
- "reactants": "CaMKII_CaM",
- "products": "CaMKII_CaM_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 0.000500000000000001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux126": {
- "reactants": "CaMKII_CaM_Ca2",
- "products": "CaMKII_CaM_Ca2_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 0.000500000000000001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux127": {
- "reactants": "CaMKII_CaM_Ca4",
- "products": "CaMKII_CaM_Ca4_psd",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 0.000500000000000001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux128": {
- "reactants": "CaMKII_CaM_Ca4_psd_CaMKII_CaM_Ca4_psd",
- "products": "CaMKII_CaM_Ca4_CaMKII_CaM_Ca4",
- "forward_rate": 0.000500000000000001,
- "backward_rate": 0.000500000000000001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux129": {
- "reactants": "pCaMKII_CaM_Ca4_psd_CaMKII_CaM_Ca4_psd",
- "products": "pCaMKII_CaM_Ca4_CaMKII_CaM_Ca4",
- "forward_rate": 1e-06,
- "backward_rate": 0.000500000000000001,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux130": {
- "reactants": "CaMKII_CaM_Ca4 + CaMKII_CaM_Ca4",
- "products": "CaMKII_CaM_Ca4_CaMKII_CaM_Ca4",
- "forward_rate": 3.60000000000003e-07,
- "backward_rate": 0.0229999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux131": {
- "reactants": "CaMKII_CaM_Ca4_CaMKII_CaM_Ca4",
- "products": "pCaMKII_CaM_Ca4 + CaMKII_CaM_Ca4",
- "forward_rate": 0.00390000000000001,
- "backward_rate": null,
+ "backward_rate": 10.0,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux132": {
- "reactants": "pCaMKII_CaM_Ca4 + CaMKII_CaM_Ca4",
- "products": "pCaMKII_CaM_Ca4_CaMKII_CaM_Ca4",
- "forward_rate": 1.10000000000001e-06,
- "backward_rate": 0.00540000000000002,
+ "revreaction_16": {
+ "reactants": "Target1 + PKAc",
+ "products": "PKAc_Target1",
+ "forward_rate": 0.08,
+ "backward_rate": 10.0,
"regions": [
"soma_internal",
"dend_internal"
]
},
- "ReactionFlux133": {
- "reactants": "pCaMKII_CaM_Ca4_CaMKII_CaM_Ca4",
- "products": "pCaMKII_CaM_Ca4 + pCaMKII_CaM_Ca4",
+ "irrevreaction_14": {
+ "reactants": "PKAc_Target1",
+ "products": "PKAc + Target1p",
"forward_rate": 10.0,
"backward_rate": null,
"regions": [
@@ -2475,40 +654,10 @@
"dend_internal"
]
},
- "ReactionFlux134": {
- "reactants": "CaMKII_CaM_Ca4_psd + CaMKII_CaM_Ca4_psd",
- "products": "CaMKII_CaM_Ca4_psd_CaMKII_CaM_Ca4_psd",
- "forward_rate": 3.60000000000003e-07,
- "backward_rate": 0.0229999999999998,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux135": {
- "reactants": "CaMKII_CaM_Ca4_psd_CaMKII_CaM_Ca4_psd",
- "products": "pCaMKII_CaM_Ca4_psd + CaMKII_CaM_Ca4_psd",
- "forward_rate": 0.00390000000000001,
- "backward_rate": null,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux136": {
- "reactants": "pCaMKII_CaM_Ca4_psd + CaMKII_CaM_Ca4_psd",
- "products": "pCaMKII_CaM_Ca4_psd_CaMKII_CaM_Ca4_psd",
- "forward_rate": 1.10000000000001e-06,
- "backward_rate": 0.00540000000000002,
- "regions": [
- "soma_internal",
- "dend_internal"
- ]
- },
- "ReactionFlux137": {
- "reactants": "pCaMKII_CaM_Ca4_psd_CaMKII_CaM_Ca4_psd",
- "products": "pCaMKII_CaM_Ca4_psd + pCaMKII_CaM_Ca4_psd",
- "forward_rate": 10.0,
+ "irrevreaction_15": {
+ "reactants": "PP1_Target1p",
+ "products": "PP1 + Target1",
+ "forward_rate": 5.0,
"backward_rate": null,
"regions": [
"soma_internal",
diff --git a/examples/notebooks/neuromodulation/data/JSON/robert_reaction_diffusion.json b/examples/notebooks/neuromodulation/data/JSON/robert_reaction_diffusion.json
index 843f5f128..7c016e181 100644
--- a/examples/notebooks/neuromodulation/data/JSON/robert_reaction_diffusion.json
+++ b/examples/notebooks/neuromodulation/data/JSON/robert_reaction_diffusion.json
@@ -8,7 +8,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.0100831208954662
+ "concentration": 0.0100831208954662,
+ "boundary_condition": false
},
"Gbgolf": {
"initial_concentration": 29.8851246006536,
@@ -18,7 +19,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 29.8851246006536
+ "concentration": 29.8851246006536,
+ "boundary_condition": false
},
"GaolfGTP": {
"initial_concentration": 0.00891348109605658,
@@ -28,7 +30,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.00891348109605658
+ "concentration": 0.00891348109605658,
+ "boundary_condition": false
},
"D1RDAGolf": {
"initial_concentration": 2.00890216216344,
@@ -38,7 +41,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 2.00890216216344
+ "concentration": 2.00890216216344,
+ "boundary_condition": false
},
"Golf": {
"initial_concentration": 1453.07257228221,
@@ -48,7 +52,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 1453.07257228221
+ "concentration": 1453.07257228221,
+ "boundary_condition": false
},
"D1RGolf": {
"initial_concentration": 515.033400954975,
@@ -58,7 +63,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 515.033400954975
+ "concentration": 515.033400954975,
+ "boundary_condition": false
},
"D1RDA": {
"initial_concentration": 5.95922532787641,
@@ -68,7 +74,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 5.95922532787641
+ "concentration": 5.95922532787641,
+ "boundary_condition": false
},
"D1R": {
"initial_concentration": 1476.99847155499,
@@ -78,7 +85,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 1476.99847155499
+ "concentration": 1476.99847155499,
+ "boundary_condition": false
},
"cAMP": {
"initial_concentration": 38.1860143351998,
@@ -88,7 +96,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 38.1860143351998
+ "concentration": 38.1860143351998,
+ "boundary_condition": false
},
"AC5": {
"initial_concentration": 2.66944644058834,
@@ -98,7 +107,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 2.66944644058834
+ "concentration": 2.66944644058834,
+ "boundary_condition": false
},
"AC5GaolfGTP": {
"initial_concentration": 0.118090407078866,
@@ -108,7 +118,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.118090407078866
+ "concentration": 0.118090407078866,
+ "boundary_condition": false
},
"PDE4": {
"initial_concentration": 1506.80848289944,
@@ -118,7 +129,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 1506.80848289944
+ "concentration": 1506.80848289944,
+ "boundary_condition": false
},
"PKA": {
"initial_concentration": 1157.14133868944,
@@ -128,7 +140,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 1157.14133868944
+ "concentration": 1157.14133868944,
+ "boundary_condition": false
},
"PKAcAMP2": {
"initial_concentration": 3.2824343126378,
@@ -138,7 +151,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 3.2824343126378
+ "concentration": 3.2824343126378,
+ "boundary_condition": false
},
"PKAcAMP4": {
"initial_concentration": 0.0867374139319834,
@@ -148,7 +162,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.0867374139319834
+ "concentration": 0.0867374139319834,
+ "boundary_condition": false
},
"PKAreg": {
"initial_concentration": 39.489489583994,
@@ -158,7 +173,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 39.489489583994
+ "concentration": 39.489489583994,
+ "boundary_condition": false
},
"PKAc": {
"initial_concentration": 3.66078057924366,
@@ -168,7 +184,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 3.66078057924366
+ "concentration": 3.66078057924366,
+ "boundary_condition": false
},
"PP1": {
"initial_concentration": 2927.34258198642,
@@ -178,7 +195,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 2927.34258198642
+ "concentration": 2927.34258198642,
+ "boundary_condition": false
},
"DA": {
"initial_concentration": 20.0,
@@ -188,7 +206,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 20.0
+ "concentration": 20.0,
+ "boundary_condition": false
},
"AMP": {
"initial_concentration": 0.0,
@@ -198,7 +217,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.0
+ "concentration": 0.0,
+ "boundary_condition": true
},
"PDE4_cAMP": {
"initial_concentration": 493.191517100561,
@@ -208,7 +228,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 493.191517100561
+ "concentration": 493.191517100561,
+ "boundary_condition": false
},
"PDE10c": {
"initial_concentration": 0.578101285574062,
@@ -218,7 +239,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.578101285574062
+ "concentration": 0.578101285574062,
+ "boundary_condition": false
},
"PDE10": {
"initial_concentration": 396.456253552482,
@@ -228,7 +250,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 396.456253552482
+ "concentration": 396.456253552482,
+ "boundary_condition": false
},
"PDE10_cAMP": {
"initial_concentration": 302.781683628694,
@@ -238,7 +261,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 302.781683628694
+ "concentration": 302.781683628694,
+ "boundary_condition": false
},
"PDE10c_cAMP": {
"initial_concentration": 0.183961533250013,
@@ -248,7 +272,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 0.183961533250013
+ "concentration": 0.183961533250013,
+ "boundary_condition": false
},
"ATP": {
"initial_concentration": 5000000.0,
@@ -258,7 +283,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 5000000.0
+ "concentration": 5000000.0,
+ "boundary_condition": true
},
"AC5GaolfGTP_ATP": {
"initial_concentration": 29.7480375915836,
@@ -268,7 +294,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 29.7480375915836
+ "concentration": 29.7480375915836,
+ "boundary_condition": false
},
"AC5_ATP": {
"initial_concentration": 667.46442556075,
@@ -278,7 +305,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 667.46442556075
+ "concentration": 667.46442556075,
+ "boundary_condition": false
},
"PP1_Target1p": {
"initial_concentration": 73.6574180095066,
@@ -288,7 +316,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 73.6574180095066
+ "concentration": 73.6574180095066,
+ "boundary_condition": false
},
"Target1p": {
"initial_concentration": 377.428073140956,
@@ -298,7 +327,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 377.428073140956
+ "concentration": 377.428073140956,
+ "boundary_condition": false
},
"PKAc_Target1": {
"initial_concentration": 36.8287090047503,
@@ -308,7 +338,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 36.8287090047503
+ "concentration": 36.8287090047503,
+ "boundary_condition": false
},
"Target1": {
"initial_concentration": 2515.08579984072,
@@ -318,7 +349,8 @@
"soma_internal",
"dend_internal"
],
- "concentration": 2515.08579984072
+ "concentration": 2515.08579984072,
+ "boundary_condition": false
}
},
"reactions": {
diff --git a/examples/notebooks/neuromodulation/data/SBML/Robert-MODEL_speedy_reduced2_UPDATED.xml b/examples/notebooks/neuromodulation/data/SBML/Robert-MODEL_speedy_reduced2_UPDATED.xml
new file mode 100644
index 000000000..e061f48f9
--- /dev/null
+++ b/examples/notebooks/neuromodulation/data/SBML/Robert-MODEL_speedy_reduced2_UPDATED.xml
@@ -0,0 +1,1932 @@
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diff --git a/examples/notebooks/neuromodulation/data/connectivity.json b/examples/notebooks/neuromodulation/data/connectivity.json
index 108a12360..456a59ba0 100644
--- a/examples/notebooks/neuromodulation/data/connectivity.json
+++ b/examples/notebooks/neuromodulation/data/connectivity.json
@@ -2,8 +2,28 @@
"regions": {
"Cube": {
"connectivity": {
- "neuron,neuron": {
- "DA": {
+ "dspn,dspn": {
+ "fake_glutamate": {
+ "conductance": [
+ 1e-9,
+ 1e-3
+ ],
+ "channel_parameters": {
+ "mod_file": "tmGlut",
+ "parameter_file": "data/tmglut_DA_parameters.json"
+ },
+ "cluster_size": 1,
+ "cluster_spread": null,
+ "pruning": {
+ "f1": null,
+ "soft_max": null,
+ "mu2": null,
+ "a3": null,
+ "cluster_pruning": false
+ }
+ },
+
+ "!DA": {
"conductance": [
1e-9,
1e-3
diff --git a/examples/notebooks/neuromodulation/data/convert_sbml_to_json.sh b/examples/notebooks/neuromodulation/data/convert_sbml_to_json.sh
index 20fd1f1c7..b8bab2fd7 100755
--- a/examples/notebooks/neuromodulation/data/convert_sbml_to_json.sh
+++ b/examples/notebooks/neuromodulation/data/convert_sbml_to_json.sh
@@ -1,7 +1,8 @@
# python ../../../../snudda/utils/sbml_to_snudda.py SBML/MODEL_speedy_reduced2.xml JSON/robert_reaction_diffusion.json
+python ../../../../snudda/utils/sbml_to_snudda.py SBML/Robert-MODEL_speedy_reduced2_UPDATED.xml JSON/reaction_diffusion_D1.json
-python ../../../../snudda/utils/sbml_to_snudda.py SBML/Nair_2016_optimized_UPDATED.xml JSON/reaction_diffusion_D1.json
+# python ../../../../snudda/utils/sbml_to_snudda.py SBML/Nair_2016_optimized_UPDATED.xml JSON/reaction_diffusion_D1.json
# python ../../../../snudda/utils/sbml_to_snudda.py SBML/Nair2015-D1-BIOMD0000000635_url.xml JSON/reaction_diffusion_D1.json
@@ -13,3 +14,5 @@ python ../../../../snudda/utils/sbml_to_snudda.py SBML/Nair2015-D2-BIOMD00000006
# python ../../../../snudda/utils/sbml_to_snudda.py SBML/Robert-MODEL_speedy_reduced2.xml JSON/robert_reaction_diffusion.json
+
+
diff --git a/examples/notebooks/neuromodulation/data/tmglut_DA_parameters.json b/examples/notebooks/neuromodulation/data/tmglut_DA_parameters.json
new file mode 100644
index 000000000..9f4fd28d5
--- /dev/null
+++ b/examples/notebooks/neuromodulation/data/tmglut_DA_parameters.json
@@ -0,0 +1,39 @@
+{
+ "low": {
+ "synapse": {
+ "mod_pka_g_ampa_min": 1,
+ "mod_pka_g_ampa_max": 1,
+ "mod_pka_g_ampa_half": 12.5,
+ "mod_pka_g_ampa_slope": 1,
+ "mod_pka_g_nmda_min": 1,
+ "mod_pka_g_nmda_max": 1.2,
+ "mod_pka_g_nmda_half": 12.5,
+ "mod_pka_g_nmda_slope": 1
+ }
+ },
+ "mid": {
+ "synapse": {
+ "mod_pka_g_ampa_min": 1,
+ "mod_pka_g_ampa_max": 1.15,
+ "mod_pka_g_ampa_half": 12.5,
+ "mod_pka_g_ampa_slope": 1,
+ "mod_pka_g_nmda_min": 1,
+ "mod_pka_g_nmda_max": 1.3,
+ "mod_pka_g_nmda_half": 12.5,
+ "mod_pka_g_nmda_slope": 1
+ }
+ },
+ "high": {
+ "synapse": {
+ "mod_pka_g_ampa_min": 1,
+ "mod_pka_g_ampa_max": 1.3,
+ "mod_pka_g_ampa_half": 12.5,
+ "mod_pka_g_ampa_slope": 1,
+ "mod_pka_g_nmda_min": 1,
+ "mod_pka_g_nmda_max": 1.6,
+ "mod_pka_g_nmda_half": 12.5,
+ "mod_pka_g_nmda_slope": 1
+ }
+ }
+
+}
diff --git a/examples/notebooks/neuromodulation/neuromodulation_example_anu_on_real_dspn.ipynb b/examples/notebooks/neuromodulation/neuromodulation_example_anu_on_real_dspn.ipynb
index 391548409..62f899197 100644
--- a/examples/notebooks/neuromodulation/neuromodulation_example_anu_on_real_dspn.ipynb
+++ b/examples/notebooks/neuromodulation/neuromodulation_example_anu_on_real_dspn.ipynb
@@ -91,13 +91,14 @@
"Reading SNUDDA_DATA=None from networks/neuromodulation_example_anu_with_real_dspn/network-config.json\n",
"stop_parallel disabled, to keep pool running.\n",
"\n",
- "Execution time: 0.4s\n",
+ "Execution time: 0.8s\n",
"Prune synapses\n",
"Network path: networks/neuromodulation_example_anu_with_real_dspn\n",
"No file networks/neuromodulation_example_anu_with_real_dspn/pruning_merge_info.json\n",
+ "Read 90 out of total 90 synapses\n",
"stop_parallel disabled, to keep pool running.\n",
"\n",
- "Execution time: 0.4s\n"
+ "Execution time: 0.8s\n"
]
}
],
@@ -145,13 +146,13 @@
"Writing spikes to networks/neuromodulation_example_anu_with_real_dspn/input-spikes.hdf5\n",
"stop_parallel disabled, to keep pool running.\n",
"\n",
- "Execution time: 0.5s\n"
+ "Execution time: 1.0s\n"
]
},
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 2,
@@ -167,7 +168,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 3,
"id": "d019b580-4193-4321-9ee8-9bdd3988209f",
"metadata": {},
"outputs": [
@@ -186,38 +187,37 @@
"Using logFile: networks/neuromodulation_example_anu_with_real_dspn/log/network-simulation-log.txt-0\n",
"Worker 0 : Loading network from networks/neuromodulation_example_anu_with_real_dspn/network-synapses.hdf5\n",
"Loading config file networks/neuromodulation_example_anu_with_real_dspn/network-config.json\n",
- "0 : Memory status: 82% free\n",
+ "0 : Memory status: 63% free\n",
"Distributing neurons.\n",
"Setup neurons\n",
"Node 0 - cell 0 dspn_0\n",
- "Fixing AMP concentration to constant 0.0\n",
- "Fixing AMP concentration to constant 0.0\n",
- "Fixing ATP concentration to constant 5000000.0\n",
- "Fixing ATP concentration to constant 5000000.0\n",
- "Fixing Ca concentration to constant 60.0\n",
- "Fixing Ca concentration to constant 60.0\n",
- "Fixing pSubstrate_out concentration to constant 0.0\n",
- "Fixing pSubstrate_out concentration to constant 0.0\n",
- "Fixing PP1_out concentration to constant 0.0\n",
- "Fixing PP1_out concentration to constant 0.0\n",
- "Fixing CaM_out concentration to constant 0.0\n",
- "Fixing CaM_out concentration to constant 0.0\n",
- "Fixing D32_out concentration to constant 0.0\n",
- "Fixing D32_out concentration to constant 0.0\n",
"Neuron dspn_0 (0) resting voltage = -86.0\n",
"!!! Popping extra segment from neuron -- temp fix!\n",
- "Node 0 - cell 1 dspn_0\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "NEURON: k < sizeof(long) * 8\n",
- " near line 0\n",
- "Assertion failed: file /root/nrn/src/nrnoc/eion.cpp, line 437\n",
- " {create axon[2]}\n",
- " "
+ "Node 0 - cell 1 dspn_0\n",
+ "Neuron dspn_0 (1) resting voltage = -86.0\n",
+ "!!! Popping extra segment from neuron -- temp fix!\n",
+ "Build node cache dspn_0 (dspn_0[0])\n",
+ "Forcing rxd update...\n",
+ "Updating node data... (takes ≈ 1 microcentury)\n",
+ "RxD update completed.\n",
+ "Node cache built.\n",
+ "Build node cache dspn_0 (dspn_0[1])\n",
+ "Node cache built.\n",
+ "0 : Memory status: 68% free\n",
+ "Adding gap junctions.\n",
+ "connect_network_gap_junctions_local\n",
+ "Finding node local gap junctions...\n",
+ "Added 0.0 gap junctions to simulation (0 total)\n",
+ "Adding synapses.\n",
+ "connect_network_synapses\n",
+ "Added 90 on worker 0\n",
+ "Added 90 synapses to simulation (90 total)\n",
+ "0 : Memory status: 68% free\n",
+ "Adding external (cortical, thalamic) input from networks/neuromodulation_example_anu_with_real_dspn/input-spikes.hdf5\n",
+ "0 : Memory status: 68% free\n",
+ "0 : Memory status: 68% free\n",
+ "Time set to 0 ms. No simulation run.\n",
+ "Program run time: 3.5s\n"
]
}
],
@@ -238,7 +238,55 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
+ "id": "1dc9fba9-131c-4bff-a7dc-3fa3047452f8",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "18"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "sim.add_synapse_variable_recording(source_id=0, dest_id=1, variable=\"modulation_factor_ampa\", synapse_type=\"fake_glutamate\")\n",
+ "sim.add_synapse_variable_recording(source_id=0, dest_id=1, variable=\"modulation_factor_nmda\", synapse_type=\"fake_glutamate\")\n",
+ "sim.add_synapse_variable_recording(source_id=1, dest_id=0, variable=\"modulation_factor_ampa\", synapse_type=\"fake_glutamate\")\n",
+ "sim.add_synapse_variable_recording(source_id=1, dest_id=0, variable=\"modulation_factor_nmda\", synapse_type=\"fake_glutamate\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "ea777c3d-232f-45d4-a26c-d85d5d4bb3c5",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "18"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "sim.add_synapse_variable_recording(source_id=0, dest_id=1, variable=\"g\", synapse_type=\"fake_glutamate\")\n",
+ "sim.add_synapse_variable_recording(source_id=0, dest_id=1, variable=\"g\", synapse_type=\"fake_glutamate\")\n",
+ "sim.add_synapse_variable_recording(source_id=1, dest_id=0, variable=\"g\", synapse_type=\"fake_glutamate\")\n",
+ "sim.add_synapse_variable_recording(source_id=1, dest_id=0, variable=\"g\", synapse_type=\"fake_glutamate\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
"id": "88bf71a5-19da-4e2e-8e90-29546a56cea1",
"metadata": {},
"outputs": [],
@@ -251,7 +299,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 7,
"id": "27ec8a70-1fbc-4093-9d8c-cb73494b626e",
"metadata": {},
"outputs": [],
@@ -272,7 +320,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 8,
"id": "6b9f2c09-d17f-4848-990d-9cc9b7859c39",
"metadata": {},
"outputs": [],
@@ -285,7 +333,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 9,
"id": "4d9216d8-8a84-4370-bfc1-88f6cc496a13",
"metadata": {},
"outputs": [],
@@ -295,7 +343,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 10,
"id": "a9f436d4-4b12-4aca-87bc-1aebb9475456",
"metadata": {},
"outputs": [],
@@ -305,7 +353,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
"id": "65a75d7a-fdcb-46b0-8148-d4752a3d0748",
"metadata": {},
"outputs": [],
@@ -316,20 +364,57 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 12,
"id": "9f5f9b57-9e65-4a09-87ab-cc6da2ce332e",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Running simulation for 0.5 s\n",
+ "Running Neuron simulator 500 ms, with dt=0.025\n",
+ " 1% done. Elapsed: 1.1 s, estimated time left: 107.4 s\n",
+ " 2% done. Elapsed: 2.2 s, estimated time left: 106.4 s\n",
+ " 3% done. Elapsed: 3.3 s, estimated time left: 105.4 s\n",
+ " 4% done. Elapsed: 4.3 s, estimated time left: 104.2 s\n",
+ " 5% done. Elapsed: 5.4 s, estimated time left: 103.5 s\n",
+ " 10% done. Elapsed: 10.9 s, estimated time left: 98.1 s\n",
+ " 20% done. Elapsed: 24.0 s, estimated time left: 96.0 s\n",
+ " 30% done. Elapsed: 38.4 s, estimated time left: 89.7 s\n",
+ " 40% done. Elapsed: 50.7 s, estimated time left: 76.1 s\n",
+ " 50% done. Elapsed: 61.7 s, estimated time left: 61.7 s\n",
+ " 60% done. Elapsed: 72.8 s, estimated time left: 48.5 s\n",
+ " 70% done. Elapsed: 83.7 s, estimated time left: 35.9 s\n",
+ " 80% done. Elapsed: 94.7 s, estimated time left: 23.7 s\n",
+ " 90% done. Elapsed: 105.6 s, estimated time left: 11.7 s\n",
+ "100% done. Elapsed: 116.5 s, estimated time left: 0.0 s\n",
+ "Neuron simulation finished\n",
+ "Simulation done.\n",
+ "Simulation run time: 118.6 s\n"
+ ]
+ }
+ ],
"source": [
"sim.run(t=500)"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 13,
"id": "053125fc-9117-459b-a3e8-725ef45db53a",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Writing network output to networks/neuromodulation_example_anu_with_real_dspn/simulation/output.hdf5\n",
+ "Using sample dt = None (sample step size None)\n",
+ "Worker 1/1 writing data to networks/neuromodulation_example_anu_with_real_dspn/simulation/output.hdf5\n"
+ ]
+ }
+ ],
"source": [
"sim.record.write()"
]
@@ -344,10 +429,18 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 14,
"id": "d84ee6f3-4193-4509-ad4a-0d93dff5e3d9",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Loading networks/neuromodulation_example_anu_with_real_dspn/simulation/output.hdf5\n"
+ ]
+ }
+ ],
"source": [
"from snudda.utils import SnuddaLoadSimulation\n",
"\n",
@@ -364,7 +457,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 15,
"id": "bd0f4edf-a622-490b-b39f-18f516975737",
"metadata": {},
"outputs": [],
@@ -376,10 +469,27 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 16,
"id": "a63a7152-730e-4868-a81a-cc87fccaf9f4",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import plotly.graph_objects as go\n",
"import plotly.io as pio\n",
@@ -395,10 +505,37 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 17,
"id": "1e49669a-1e97-4e19-8586-4acff6e21d69",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/tmp/ipykernel_31133/2856066121.py:7: RuntimeWarning:\n",
+ "\n",
+ "invalid value encountered in divide\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import numpy as np\n",
"import plotly.graph_objects as go\n",
@@ -414,10 +551,41 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 18,
"id": "0b572560-b42f-4920-bdf3-6718800d01f1",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/tmp/ipykernel_31133/4119170436.py:7: RuntimeWarning:\n",
+ "\n",
+ "invalid value encountered in divide\n",
+ "\n",
+ "/tmp/ipykernel_31133/4119170436.py:7: RuntimeWarning:\n",
+ "\n",
+ "divide by zero encountered in divide\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
+ "\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import numpy as np\n",
"import plotly.graph_objects as go\n",
@@ -441,10 +609,21 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 19,
"id": "e6554026-bb50-4209-a1f7-37565af50529",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
@@ -459,20 +638,43 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 20,
"id": "3febf45e-b1a0-45ce-b791-266ed03ed741",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "array([0.99996377, 0.99996377, 0.99996377, ..., 0.75 , 0.75 ,\n",
+ " 0.75 ])"
+ ]
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"all_species_data[data_type][0][0].T[0]"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 21,
"id": "d98d057c-752c-458b-bd52-a726f42dc90a",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.figure()\n",
@@ -485,10 +687,21 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 22,
"id": "d3bda015-1674-45ae-96f0-69167fd2cc89",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.figure()\n",
@@ -501,10 +714,21 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 23,
"id": "0e281a93-c7de-45cf-9723-98f3a19bbca0",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.figure()\n",
@@ -526,10 +750,29 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 24,
"id": "d31a7d49-55b1-479c-942a-17cbd87fa412",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Loading networks/neuromodulation_example_anu_with_real_dspn/simulation/output.hdf5\n",
+ "Saving figure to networks/neuromodulation_example_anu_with_real_dspn/figures/spike-raster.png\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"from snudda.plotting import SnuddaPlotSpikeRaster2\n",
"fig_file_raster = f\"spike-raster.png\"\n",
@@ -542,10 +785,33 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 25,
"id": "fc082055-9e38-4ed1-b842-40e166548071",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Loading network info from networks/neuromodulation_example_anu_with_real_dspn/network-synapses.hdf5\n",
+ "Loading input info from networks/neuromodulation_example_anu_with_real_dspn/input-spikes.hdf5\n",
+ "Loading networks/neuromodulation_example_anu_with_real_dspn/simulation/output.hdf5\n",
+ "Plotting traces: [0, 1]\n",
+ "Plotted 2 traces (total 2)\n",
+ "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_example_anu_with_real_dspn/figures/Network-voltage-trace--dspn-0-1.pdf\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"%matplotlib inline\n",
"\n",
@@ -559,10 +825,49 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 26,
"id": "0484dc59-0ae4-41fa-bfd5-441f8ddf6290",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Plotting traces: [0]\n",
+ "Plotted 1 traces (total 2)\n",
+ "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_example_anu_with_real_dspn/figures/Network-voltage-trace--dspn-0.pdf\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Plotting traces: [1]\n",
+ "Plotted 1 traces (total 2)\n",
+ "Saving to figure /home/hjorth/HBP/Snudda/examples/notebooks/neuromodulation/networks/neuromodulation_example_anu_with_real_dspn/figures/Network-voltage-trace--dspn-1.pdf\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"ax0 = pt.plot_traces(offset=0, time_range=(0,1),fig_size=(10,4), trace_id=0)\n",
"ax1 = pt.plot_traces(offset=0, time_range=(0,1),fig_size=(10,4), trace_id=1)"
@@ -570,10 +875,33 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 27,
"id": "dafbc17d-34f0-413e-b26a-08e51e8fff35",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Help on method plot_traces in module snudda.plotting.plot_traces:\n",
+ "\n",
+ "plot_traces(trace_id=None, offset=0.15, colours=None, skip_time=None, time_range=None, line_width=1, fig_size=None, mark_current=None, mark_current_y=None, title=None, fig_name=None, mark_depolarisation_block=True, mark_spikes=True) method of snudda.plotting.plot_traces.PlotTraces instance\n",
+ " Plot the traces of neuron trace_id\n",
+ " \n",
+ " Args:\n",
+ " trace_id (int or list) : ID of trace to show, can be integer or list\n",
+ " offset (float) : Offset between multiple traces, float or None\n",
+ " colours : What colour to plot\n",
+ " skip_time (float) : Skip portion of the start, modifies time shown\n",
+ " time_range (float, float) : Range to plot\n",
+ " mark_current (list) : List of tuples of start, end time\n",
+ " mark_current_y (float) : Y-coordinate of where to mark the current\n",
+ " title (str) : Plot title\n",
+ " fig_name (str) : Figure file to save to\n",
+ "\n"
+ ]
+ }
+ ],
"source": [
"help(pt.plot_traces)"
]
@@ -588,20 +916,42 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 28,
"id": "97789ccd-8c45-47e8-aeec-3b752b4c9942",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "19.67872706705603"
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"sim.neurons[0].icell.soma[0](0.5).naf_ms.gbar"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 29,
"id": "7b2a5b48-6450-475e-b842-478e75d2cf32",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "0.0005424674497187078"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"sim.neurons[0].icell.soma[0](0.5).pas.g"
]
diff --git a/snudda/neurons/neuron_modulation.py b/snudda/neurons/neuron_modulation.py
index 1a746c4ea..8cba32a45 100644
--- a/snudda/neurons/neuron_modulation.py
+++ b/snudda/neurons/neuron_modulation.py
@@ -3,6 +3,8 @@
# TODO: How to handle co-release?
+# TODO: Move DA species to external compartment. IMPORTANT.
+
import numpy as np
import neuron.crxd as rxd
import json
@@ -65,14 +67,8 @@ def add_species(self, species_name, diffusion_constant, initial_conc,
if comp in self.species[species_name]:
raise ValueError(f"{species_name = } already defined for {comp = }")
- # boundary_condition = False # The rxd.Parameter does not seem to work?
-
- # if species_name == "ATP":
- # import pdb
- # pdb.set_trace()
-
if boundary_condition:
- print(f"Fixing {species_name} concentration to constant {initial_conc}")
+ # print(f"Fixing {species_name} concentration to constant {initial_conc}")
# The concentration is fixed
self.species[species_name][comp] = rxd.Parameter(self.compartments[comp],
name=species_name,
diff --git a/snudda/simulate/simulate.py b/snudda/simulate/simulate.py
index 8b6481e69..3108622bd 100644
--- a/snudda/simulate/simulate.py
+++ b/snudda/simulate/simulate.py
@@ -485,8 +485,7 @@ def load_synapse_parameters(self):
# Gap junctions, skip parameters
continue
- if ("channel_parameters" in info_dict
- and info_dict["channel_parameters"] is not None):
+ if "channel_parameters" in info_dict and info_dict["channel_parameters"] is not None:
channel_param_dict = copy.deepcopy(info_dict["channel_parameters"])
mod_file = channel_param_dict["mod_file"]
@@ -519,6 +518,7 @@ def load_synapse_parameters(self):
# Save data as a list, we don't need the keys
par_data = []
for pd in par_data_dict:
+
if "synapse" in par_data_dict[pd]:
# Add channel parameters specified in network file, however
# any values in the synapse parameter file will overwrite them
@@ -527,6 +527,7 @@ def load_synapse_parameters(self):
p_dict[x] = par_data_dict[pd]["synapse"][x]
par_data.append(p_dict)
+
else:
self.write_log(f"WARNING: Old data format in parameter file {par_file}")
@@ -1737,6 +1738,63 @@ def add_membrane_recording(self, variable, neuron_id, sec_id, sec_x):
sec_id=sec_id,
sec_x=sec_x)
+ def get_internal_synapse_point_process(self, source_id, dest_id, synapse_type=None):
+
+ synapse_list = self.synapse_dict.get((source_id, dest_id), [])
+
+ channel_model_id = None
+
+ if synapse_type is not None:
+ pre_type = self.network_info["neurons"][source_id]["type"]
+ post_type = self.network_info["neurons"][dest_id]["type"]
+
+ if (pre_type, post_type) in self.network_info["connectivity_distributions"]:
+ channel_model_id = self.network_info["connectivity_distributions"][(pre_type, post_type)][synapse_type]["channel_model_id"]
+
+ s_list = [synapse_info for synapse_info in synapse_list
+ if channel_model_id is None or channel_model_id == synapse_info[2]]
+
+ return s_list, pre_type, post_type
+
+ def get_external_synapse_point_process(self, dest_id):
+
+ """ Returns point process of the external synapses on the neuron """
+
+ raise NotImplementedError("Not yet implemented.")
+
+ def add_synapse_variable_recording(self, source_id, dest_id, variable, synapse_type=None):
+
+ synapse_list, pre_type, post_type = self.get_internal_synapse_point_process(source_id=source_id,
+ dest_id=dest_id,
+ synapse_type=synapse_type)
+
+ return self.add_point_process_variable_recording(point_process_list=synapse_list,
+ variable=variable,
+ post_synaptic_id=dest_id,
+ pre_synaptic_id=source_id,
+ name=f"{pre_type}_{post_type}_{synapse_type}")
+
+ def add_point_process_variable_recording(self, point_process_list, variable,
+ post_synaptic_id, pre_synaptic_id=-1, name=""):
+
+ syn_ctr = 0
+
+ for syn, nc, synapse_type_id, sec_id in point_process_list:
+ data = self.sim.neuron.h.Vector()
+ data.record(getattr(syn, f"_ref_{variable}"))
+ seg = syn.get_segment()
+
+ self.record.register_synapse_data(neuron_id=post_synaptic_id,
+ data_type=f"{name}{'.' if len(name) > 0 else ''}{variable}", data=data,
+ synapse_type=synapse_type_id,
+ presynaptic_id=pre_synaptic_id,
+ sec_id=sec_id,
+ sec_x=seg.x,
+ cond=nc.weight[0])
+ syn_ctr += 1
+
+ return syn_ctr
+
def add_synapse_current_recording(self, source_id, dest_id):
assert (source_id, dest_id) in self.synapse_dict, f"No synapse between {source_id} and {dest_id}"