neurodynex.adex_model package¶
Submodules¶
neurodynex.adex_model.AdEx module¶
Implementation of the Adaptive Exponential Integrate-and-Fire model.
See Neuronal Dynamics Chapter 6 Section 1
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neurodynex.adex_model.AdEx.
plot_adex_state
(adex_state_monitor)[source]¶ Visualizes the state variables: w-t, v-t and phase-plane w-v
Parameters: adex_state_monitor (StateMonitor) – States of “v” and “w”
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neurodynex.adex_model.AdEx.
simulate_AdEx_neuron
(tau_m=5. * msecond, R=0.5 * Gohm, v_rest=-70. * mvolt, v_reset=-51. * mvolt, v_rheobase=-50. * mvolt, a=0.5 * nsiemens, b=7. * pamp, v_spike=-30. * mvolt, delta_T=2. * mvolt, tau_w=100. * msecond, I_stim=<brian2.input.timedarray.TimedArray object>, simulation_time=200. * msecond)[source]¶ Implementation of the AdEx model with a single adaptation variable w.
The Brian2 model equations are:
\[\begin{split}\frac{dv}{dt} = (-(v-v_rest) +delta_T*exp((v-v_rheobase)/delta_T)+ R * I_stim(t,i) - R * w)/(tau_m) : volt \\ \frac{dw}{dt} = (a*(v-v_rest)-w)/tau_w : amp\end{split}\]Parameters: - tau_m (Quantity) – membrane time scale
- R (Quantity) – membrane restistance
- v_rest (Quantity) – resting potential
- v_reset (Quantity) – reset potential
- v_rheobase (Quantity) – rheobase threshold
- a (Quantity) – Adaptation-Voltage coupling
- b (Quantity) – Spike-triggered adaptation current (=increment of w after each spike)
- v_spike (Quantity) – voltage threshold for the spike condition
- delta_T (Quantity) – Sharpness of the exponential term
- tau_w (Quantity) – Adaptation time constant
- I_stim (TimedArray) – Input current
- simulation_time (Quantity) – Duration for which the model is simulated
Returns: A b2.StateMonitor for the variables “v” and “w” and a b2.SpikeMonitor
Return type: (state_monitor, spike_monitor)