Hi,
Right, in that case I would switch the order when assigning :
W_EE = np.zeros([len(E_neurons), len(E_neurons)]) W_IE = np.zeros([len(E_neurons), len(I_neurons)]) W_EI = np.zeros([len(I_neurons), len(E_neurons)]) W_II = np.zeros([len(I_neurons), len(I_neurons)])
So it would give a hint of the convention (at least for me), but as you said it is a convention, and indeed I was confused by it.
Thanks a lot.
From: Renato Duarte rcfduarte@gmail.com Sent: Tuesday, 19 January 2021 13:04 To: NEST User Mailing List users@nest-simulator.org Subject: [NEST Users] Re: Plot weight matrices example
Hello,
The use of "post-pre" notation when referring to synaptic connections is common practice in computational neuroscience. It does often give rise to some confusion, but it is common, for example, to refer to a synaptic connection from neuron j to neuron i as ij (post<-pre). This is the notation used in this example, where we refer to the connection from inhibitory to excitatory neurons (I->E) as EI (post-pre) and connections from excitatory to inhibitory neurons (E->I) as IE (post-pre). It is just a matter of convention.
Best regards, Renato Duarte
On Jan 19 2021, at 12:43 pm, Ing Jyh Tsang <ingjyh.tsang@uantwerpen.bemailto:ingjyh.tsang@uantwerpen.be> wrote: HI,
I may be mistaken, but isn't the EI and IE index switched (https://nest-simulator.readthedocs.io/en/stable/auto_examples/plot_weight_ma...) ?
a_EI = nest.GetConnections(I_neurons, E_neurons) c_EI = nest.GetStatus(a_EI, keys='weight') a_IE = nest.GetConnections(E_neurons, I_neurons) c_IE = nest.GetStatus(a_IE, keys='weight')
for idx, n in enumerate(a_EI): W_EI[n[0] - min(I_neurons), n[1] - min(E_neurons)] += c_EI[idx] for idx, n in enumerate(a_IE): W_IE[n[0] - min(E_neurons), n[1] - min(I_neurons)] += c_IE[idx]
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