AdEx Threshold Integrator

Threshold Integration for the AdEx neuron model with noisy input

Threshold integration methods for the adaptive exponential integrate and fire (AdEx)
neuron model driven by noisy current-based (i.e., additive) input.
Author: Robert Rosenbaum
A suite or programs to approximate steady-state statistics and linear response functions
for the AdEx model defined by the Langevin equations
Cm*V'=-gL*(V-EL)+gL*DeltaT*exp((V-VT)/DeltaT)-w+muI+sqrt(2*DI)*eta
tauw*w'=-w+a*(V-EL)
with the added condition that V is reset to Vre whenever it reaches Vth.
Uses threshold integration methods from:

Richardson, M.J.E. (2008). Spike-train spectra and network response
functions for non-linear integrate-and-fire neurons. Biological
Cybernetics, 99(4-5), 381-92.

and fixed point iteration methods from:

Richardson, M. (2009). Dynamics of populations and networks of neurons with
voltage-activated and calcium-activated currents. Physical Review E, 80(2), 021928.

with the modifications and extensions described in:

Rosenbaum, R. (2016). A diffusion approximation and numerical methods for adaptive
neuron models with stochastic inputs. To appear.

Please cite these papers if you publish research that uses this code or some modification
thereof.

See that manuscript and the comments within each function for more information on the
implementation and how to call the functions.