unmyelinated

class nrv.nmod.unmyelinated(y=0, z=0, d=1, L=1000, model='Rattay_Aberham', dt=0.001, Nrec=0, Nsec=1, Nseg_per_sec=0, freq=100, freq_min=0, mesh_shape='plateau_sigmoid', alpha_max=0.3, d_lambda=0.1, v_init=None, T=None, ID=0, threshold=-40, **kwarks)

Unmyelinated axon class. Automatic refinition of all neuron sections and properties. User-friendly object including model definition Inherit from axon class. see axon for further detail.

Parameters:

• y (float) – y coordinate for the axon, in um

• z (float) – z coordinate for the axon, in um

• d (float) – axon diameter, in um

• L (float) – axon length along the x axins, in um

• model (str) –

  choice of conductance based model, possibly:

  ”HH” : original squid giant axon model, warning - low temperature model, not adapted to mamalian modeling “Rattay_Aberham” : Rattay Aberham model, see [1] for details “Sundt” : Sundt model, see [1] for details “Tigerholm” : Tigerholm model, see [1] for details “Schild_94” : Schild 1994 model, see [1] for details “Schild_97” : Schild 1997 model, see [1] for details

• dt (float) – computation step for simulations, in ms. By default equal to 1 us

• Nrec (int) – Number of points along the axon to record for simulation results. Between 0 and the number of segment, if set to 0, all segments are recorded

• Nsec (int) – Number of sections in the axon, by default 1. Usefull to create umnyelinated axons with a variable segment density

• Nseg_per_sec (int) – Number of segment per section in the axon. If set to 0, the number of segment is automatically computed using d-lambda rule and following paramters. If set by user, please use odd numbers

• freq (float) – Frequency used for the d-lmbda rule, corresponding to the maximum membrane current frequency, by default set to 100 Hz

• freq_min (float) – Minimal frequency fot the d-lambda rule when using an irregular number of segment along the axon, if set to 0, all sections have the same frequency determined by the previous parameter

• mesh_shape (str) –

  Shape of the frequencial distribution for the dlmabda rule along the axon, pick between:

  ”pyramidal” -> min frequencies on both sides and linear increase up to the middle at the maximum frequency “sigmoid” -> same a befor with sigmoid increase instead of linear “plateau” -> sale as pyramidal except the max frequency is holded on a central plateau “plateau_sigmoid” -> same as previous with sigmoid increase

• alpha_max (float) – Proportion of the axon set to the maximum frequency for plateau shapes, by default set to 0.3

• d_lambda (float) – value of d-lambda for the dlambda rule,

• v_init (float) – Initial value of the membrane voltage in mV, set None to get an automatically model attributed value

• T (float) – temperature in C, set None to get an automatically model attributed value

• ID (int) – axon ID, by default set to 0,

• threshold (float) – voltage threshold in mV for further spike detection in post-processing, by defautl set to -40mV, see post-processing files for further help

Note

reference [1] corresponds to:

Pelot, N. A., Catherall, D. C., Thio, B. J., Titus, N. D., Liang, E. D., Henriquez, C. S., & Grill, W. M. (2021). Excitation properties of computational models of unmyelinated peripheral axons. Journal of neurophysiology, 125(1), 86-104.

Methods

unmyelinated.__init__([y, z, d, L, model, ...])	initialisation of an unmyelinted axon
unmyelinated.attach_extracellular_recorder(rec)	attach an extracellular recorder to the axon
unmyelinated.attach_extracellular_stimulation(stim)	attach a extracellular context of simulation for an axon
unmyelinated.change_stimulus_from_electrode(...)	Change the stimulus of the ID_elec electrods
unmyelinated.extracel_status()	Check if an extracellular context is attached to the instance
unmyelinated.get_electrodes_footprints_on_axon([...])	get electrodes footprints on each axon segment
unmyelinated.get_ionic_conductance()	get the membrane conductance at the end of simulation.
unmyelinated.get_ionic_current()	get the ionic currents at the end of simulation.
unmyelinated.get_membrane_capacitance()	get the membrane capacitance NB: [uF/cm^{2}] (see Neuron unit)
unmyelinated.get_membrane_conductance()	get the membrane voltage at the end of simulation.
unmyelinated.get_membrane_current()	get the membrane current at the end of simulation.
unmyelinated.get_membrane_voltage()	get the membrane voltage at the end of simulation.
unmyelinated.get_parameters()	Generic method returning all the atributes of an NRV_class instance
unmyelinated.get_particles_values()	get the particules values at the end of simulation.
unmyelinated.get_particules_values()
unmyelinated.insert_I_Clamp(position, ...)	Insert a I clamp stimulation
unmyelinated.insert_V_Clamp(position, stimulus)	Insert a V clamp stimulation
unmyelinated.intracel_status()	Check if an intracellular context is attached to the instance
unmyelinated.load(data[, extracel_context, ...])	Load all axon properties from a dictionary or a json file
unmyelinated.load_axon(data[, ...])
unmyelinated.plot(axes[, color, elec_color])
unmyelinated.rec_status()	Check if a recording context is attached to the instance
unmyelinated.save([save, fname, ...])	Return axon as dictionary and eventually save it as json file
unmyelinated.save_axon([save, fname, ...])
unmyelinated.set_conductance_recorders()	setup the membrane conductance recording.
unmyelinated.set_ionic_current_recorders()	setup the ionic currents recording.
unmyelinated.set_membrane_current_recorders()	setup the membrane current recording.
unmyelinated.set_membrane_voltage_recorders()	setup the membrane voltage recording.
unmyelinated.set_parameters(**kawrgs)	Generic method to set any attribute of NRV_class instance
unmyelinated.set_particules_values_recorders()	setup the particule value recording.
unmyelinated.shut_recorder_down()	Shuts down the recorder locally
unmyelinated.simulate(**kwargs)	Simulates the axon using neuron framework
unmyelinated.topology()	call the neuron topology function to plot the current topology on prompt