Simulation Functions
current_step(pop, t1=500, t2=500, a1=0, a2=100)
#
Stimulates a given population in two periods with two input currents.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pop |
str
|
population name of population, which should be stimulated with input current neuron model of population has to contain "I_app" as input current |
required |
t1 |
int
|
time in ms before current step |
500
|
t2 |
int
|
time in ms after current step |
500
|
a1 |
int
|
current amplitude before current step |
0
|
a2 |
int
|
current amplitude after current step |
100
|
Returns:
Name | Type | Description |
---|---|---|
return_dict |
dict
|
dictionary containing:
|
Source code in src/CompNeuroPy/simulation_functions.py
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|
current_stim(pop, t=500, a=100)
#
Stimulates a given population during specified period 't' with input current with amplitude 'a', after this stimulation the current is reset to initial value (before stimulation).
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pop |
str
|
population name of population, which should be stimulated with input current neuron model of population has to contain "I_app" as input current |
required |
t |
int
|
duration in ms |
500
|
a |
int
|
current amplitude |
100
|
Source code in src/CompNeuroPy/simulation_functions.py
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current_ramp(pop, a0, a1, dur, n)
#
Conducts multiple current stimulations with constantly changing current inputs. After this current_ramp stimulation the current amplitude is reset to the initial value (before current ramp).
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pop |
str
|
population name of population, which should be stimulated with input current neuron model of population has to contain "I_app" as input current |
required |
a0 |
int
|
initial current amplitude (of first stimulation) |
required |
a1 |
int
|
final current amplitude (of last stimulation) |
required |
dur |
int
|
duration of the complete current ramp (all stimulations) |
required |
n |
int
|
number of stimulations |
required |
Warning
dur/n should be divisible by the simulation time step without remainder
Returns:
Name | Type | Description |
---|---|---|
return_dict |
dict
|
dictionary containing:
|
Raises:
Type | Description |
---|---|
AssertionError
|
if resulting duration of one stimulation is not divisible by the simulation time step without remainder |
Source code in src/CompNeuroPy/simulation_functions.py
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|
increasing_current(pop, a0, da, nr_steps, dur_step)
#
Conducts multiple current stimulations with constantly increasing current inputs. After this increasing_current stimulation the current amplitude is reset to the initial value (before increasing_current).
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pop |
str
|
population name of population, which should be stimulated with input current neuron model of population has to contain "I_app" as input current |
required |
a0 |
int
|
initial current amplitude (of first stimulation) |
required |
da |
int
|
current step size |
required |
nr_steps |
int
|
number of stimulations |
required |
dur_step |
int
|
duration of one stimulation |
required |
Returns:
Name | Type | Description |
---|---|---|
return_dict |
dict
|
dictionary containing:
|
Source code in src/CompNeuroPy/simulation_functions.py
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