neurodynex.leaky_integrate_and_fire package¶
Submodules¶
neurodynex.leaky_integrate_and_fire.LIF module¶
This file implements a leaky intergrate-and-fire (LIF) model. You can inject a step current or sinusoidal current into neuron using LIF_Step() or LIF_Sinus() methods respectively.
Relevant book chapters:
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neurodynex.leaky_integrate_and_fire.LIF.LIF_Neuron(curr, simtime)[source]¶ Simple LIF neuron implemented in Brian2.
Parameters: - curr (TimedArray) – Input current injected into the neuron
- simtime (float) – Simulation time [seconds]
Returns: Brian2 StateMonitor with input current (I) and voltage (V) recorded
Return type: StateMonitor
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neurodynex.leaky_integrate_and_fire.LIF.LIF_Sinus(I_freq=0.1, I_offset=0.5, I_amp=0.5, tend=100, dt=0.1, do_plot=True)[source]¶ Run the LIF for a sinusoidal current
Parameters: - tend (float, optional) – the simulation time of the model [ms]
- I_freq (float, optional) – frequency of current sinusoidal [kHz]
- I_offset (float, optional) – DC offset of current [nA]
- I_amp (float, optional) – amplitude of sinusoidal [nA]
- do_plot (bool, optional) – plot the resulting simulation
Returns: Brian2 StateMonitor with input current (I) and voltage (V) recorded
Return type: StateMonitor
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neurodynex.leaky_integrate_and_fire.LIF.LIF_Step(I_tstart=20, I_tend=70, I_amp=1.005, tend=100, do_plot=True)[source]¶ Run the LIF and give a step current input.
Parameters: - tend (float, optional) – the simulation time of the model [ms]
- I_tstart (float, optional) – start of current step [ms]
- I_tend (float, optional) – start of end step [ms]
- I_amp (float, optional) – amplitude of current step [nA]
- do_plot (bool, optional) – plot the resulting simulation
Returns: Brian2 StateMonitor with input current (I) and voltage (V) recorded
Return type: StateMonitor