Conversion of the model from Brian1 to Brian2

[mstimberg]

@serge25

Is it right to translate it as:

delay='rand*(dm+dt)'

Not quite, it should be

Cmm_weak_inh.delay = 'dm - dd + 2*dd*rand()'

or

@serge25

And how to translate this part:

connected=Cmg_AMPA.W.transpose().copy() # copy and transpose M->G connection array
        mask_connect=(connected>0)
        Cgm_GABA.connect(G,M,mask_connect*param_dict['stronginh_weight'])

Do I understand correctly that this is meant to copy the M→G connections so that G→M has the equivalent symmetric connections?
In that case, the most straightforward translation would be to exchange the source and target indices, by using:

Cgm_GABA.connect(i=Cmg_AMPA.j, j=Cmg_AMPA.i)

Another alternative would be to use a single Synapses instance with an on_pre statement to apply the spikes from M→G, and an on_post statement to apply G→M.