def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2018Zang"
# ------specify cell-regions from with response are recorded-------
self.regions = {
"soma": ["v"],
"ais": ["v"],
"dend_root": ["v"],
"dend_sm": ["v"],
"dend_sp": ["v"]
}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Zang et al. 2018 model of PurkinjeCell"
self.description = "Zang et al. 2018 model of PurkinjeCell (PC) and published in 10.1016/j.celrep.2018.07.011 This is a multi-compartment modified version of the Purkinje cell from Mike Hausser (cell 2, 19.2.97). This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 243446."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2015Masoli"
# ------specify cell-regions from with response are recorded-------
self.regions = {
"soma": ["v"],
"dend": ["v"],
"axonAIS": ["v"],
"axonNOR": ["v"],
"axonNOR2": ["v"],
"axonNOR3": ["v"]
}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
# pc.name defaults to class name, i.e, PurkinjeCell
self.name = "Masoli et al. 2015 model of PurkinjeCell"
self.description = "Masoli et al. 2015 model of PurkinjeCell (PC) and published in 10.3389/fncel.2015.00047 This is general PC model unlike special Z+ or Z- models. The model is based on adult (P90 or 3 months) Guinea pig. PC in younger ones are not mature and they grow until P90. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 229585."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2011Brown"
# ------specify cell-regions from with response are recorded-------
self.regions = {
"soma": ["v"],
"dend_root": ["v"],
"dend_sm": ["v"],
"dend_sp": ["v"],
"spine_head": ["v"],
"spine_neck": ["v"]
}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Brown et al. 2011 model of PurkinjeCell"
self.description = "Brown 2011 model of PurkinjeCell (PC) and published in 10.1007/s10827-011-0317-0 This is a multi-compartment (38) model. It is a PPR (preserved path reduction) model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 126637."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def test_2_lock_and_load_model_libraries(self):
os.chdir(rootwd) # move up to ~/cerebmodels
self.assertEqual(
sm.lock_and_load_model_libraries(modelscale="cells",
modelname="DummyTest"),
"Model libraries area loaded")
os.chdir(pwd)
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "synapses"
self.modelname = "CFPCnPFPC2018Zang"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": 0.0}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Zang et al. 2018 model of CF and PF to PurkinjeCell"
self.description = "Zang et al. 2018 model of ClimbingFiber (CF) and ParallelFIber (PF) to PurkinjeCell (PC) and published in 10.1016/j.celrep.2018.07.011 This is a multi-compartment modified version of the Purkinje cell from Mike Hausser (cell 2, 19.2.97). This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 243446."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = CFPFtoPurkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "synapses"
self.modelname = "PCDCNnMFDCN2015bSudhakar"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": 0.0}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Sudhakar et al. 2015 model of PC and MF to Deep Cerebellar neuron"
self.description = "Sudhakar 2015 model of Purkinje cell (PC) and MossyFiber (MF) to Deep Cerebellar Neuron (DCN) and published in 10.1371/journal.pcbi.1004641 There are 200 incoming inhibitory connection from PC's, 100 incoming excitatory connection from MF's into a DCN. This is the 'm2' model mentioned in the paper characterized by fast rebound burst and a pause but very long prolonged rebound spiking activity. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 185513."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = PurkinjeAndMossyToDeepCerebellar()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "synapses"
self.modelname = "CFPC2019AitOuares"
# ------specify cell-regions from with response are recorded-------
self.regions = {"dend": 0.0}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Ait Ouares et al. 2019 model of Climbing fiber to Purkinje cell dendrite"
self.description = "Ait Ouares 2019 model of ClimbingFiber (CF) to PurkinjeCell (PC) and published in 10.1523/JNEUROSCI.2155-18.2018 This is the single compartment (dendrite) model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 244679."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = ClimbingPurkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "GrC2011Souza"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], }
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Souza and Schutter 2011 model of GranuleCell"
self.description = "Souza & Schutter 2011 model of GranuleCell (GrC) and published in 10.1186/2042-1001-1-7 This is a single compartment model; it is a modification of Diwakar et al. 2009 multicompartment model. It was used as the component for GrC in the network the authors constructed. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 139656."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Granule()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2010Genet"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], "dend_sm": ["v"], "dend_sp": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Genet et al. 2010 model of PurkinjeCell"
self.description = "Genet 2010 model of PurkinjeCell (PC) and published in 10.1016/j.bpj.2010.04.056 This is a multi-compartment (1088) model. It is a resonstruction of Shelton's 1985 model which has been rescaled for dimensions of a guinea pig cell. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 147218."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "GrC1994Gabbiani"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Gabbiani et al. 1994 model of GranuleCell"
self.description = "Gabbiani 1994 model of GranuleCell (GrC) and published in 10.1152/jn.1994.72.2.999 This is the single compartment model. It models a turtle cerebellar granule cell consisting of 13 compartments that represent the soma and 4 dendrites. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 19591."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Granule()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2015bForrest"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], "dend": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Forrest 2015 model of PurkinjeCell"
self.description = "Forrest 2015 model of PurkinjeCell (PC) and published in 10.1186/s12868-015-0162-6 This is th two compartment model, reduced from the 1088 compartment PC2015aForrest. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 180789."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2006Akemann"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"]} #"dend_sm": ["v"], "dend_sp": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Akemann and Knöpfel 2006 model of PurkinjeCell"
self.description = "Akemann & Knöpfel 006 model of PurkinjeCell (PC) and published in 10.1523/JNEUROSCI.5204-05.2006 This is a single compartment model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 80769."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2003Khaliq"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Khaliq et al. 2003 model of PurkinjeCell"
self.description = "Khaliq & Raman 2003 model of PurkinjeCell (PC) and published in 10.1523/JNEUROSCI.23-12-04899.2003 This is a single compartment model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 48332."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "GoC2007Solinas"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], "axon": ["v"]} # "dend": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Solinas et al. 2007 model of GolgiCell"
self.description = "Solinas et al. 2007 model of GolgiCell (GoC) and published in 10.3389/neuro.03.004.2007 This is a multi-compartment (131) model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 112685."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Golgi()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "DCN2011Luthman"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Luthman et al. 2011 model of DeepCerebellarNucleiCell"
self.description = "Luthman 2011 model of a neuron in Deep Cerebellar Nuclei (DCN) and published in 10.1007/s12311-011-0295-9 This is a multi-compartment (517) model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 144523."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = ExcitatoryDCNneuron()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC2001Miyasho"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], "dend_sm": ["v"], "dend_sp": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Miyasho et al. 2001 model of PurkinjeCell"
self.description = "Miyasho 2001 model of PurkinjeCell (PC) and published in 10.1016/S0006-8993(00)03206-6 This is a multi-compartment (1088) model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 17664."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "PC1997bHausser"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], "dend_root": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Hausser 20.2.1997 model of PurkinjeCell"
self.description = "Hausser 20.2.1997 model of PurkinjeCell (PC) and used by Vetter et al. 2001 for Dendritica, published in 10.1152/jn.2001.85.2.926 This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 7907."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Purkinje()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "GrC2001DAngelo"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "D'Angelo et al. 2001 model of GranuleCell"
self.description = "D'Angelo et al. 2001 model of GranuleCell (GrC) and published in 10.1523/JNEUROSCI.21-03-00759.2001 This is the single compartment model. It models the rat granule cells because the model was derived from slices taken from 20 +/- 2 days old rats. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 46839."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Granule()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def __init__(self):
### ===================== Descriptive Attributes ======================
self.modelscale = "cells"
self.modelname = "GoC2010Botta"
# ------specify cell-regions from with response are recorded-------
self.regions = {"soma": ["v"], "axon": ["v"],}# "dend": ["v"]}
self.recordingunits = {"v": "mV"}
# -----------attributed inheritance from sciunit.Model--------------
self.name = "Botta et al. 2010 model of GolgiCell"
self.description = "Botta et al. 2010 model of GolgiCell (GoC) and published in 10.1038/npp.2010.76 This is a multi-compartment (131) model modified version of the Solinas et al. 2007 model. A Na+/K+ ATPase and ionic concentration pools for Na+, K+, Ca2+ were incorporated into the soma of the model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 127021."
#
### =================== Instantiate cell template ====================
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Golgi()
os.chdir(pwd)
### ===============================================================
self.fullfilename = "nil"
self.prediction = "nil"
def choose_model(modelscale=None, modelname=None):
"""Returns instantiated model for a desired model name available in the specified model scale.
**Keyword Arguments:**
+----------------+-------------+
| Key | Value type |
+================+=============+
| ``modelscale`` | string |
+----------------+-------------+
| ``modelname`` | string |
+----------------+-------------+
*NOTE*: Currently only ``modelscale="cells"`` are supported. Future releases will include other model scales.
"""
sm.lock_and_load_model_libraries(modelscale=modelscale,
modelname=modelname)
modelmodule = importlib.import_module("models." + modelscale +
".model" + modelname)
chosenmodel = getattr(modelmodule,
uu.classesinmodule(modelmodule)[0].__name__)
return chosenmodel()
def __init__(self):
# refer Dummy.py to choose regions
self.regions = {'soma': ['v', 'i_cap'],
'axon': ['v'],
'channels': {'soma': {'pas': ['i'],
'hh': ['il', 'el']},
'axon': {'pas': ['i']}}
}
self.recordingunits = { 'v': 'mV', 'el': 'mV',
'i_cap': 'mA/cm**2',
'i': 'mA/cm**2', 'il': 'mA/cm**2' }
self.modelscale = "cells"
self.modelname = "DummyTest"
#
self.name = "Dummy Test"
self.description = "This is a dummy model for testing out the managers and their operators."
#
# instantiate
sm.lock_and_load_model_libraries(modelscale=self.modelscale,
modelname=self.modelname)
os.chdir(path_to_files)
self.cell = Dummy()
os.chdir(pwd)