[nengo-user] Adjusting topological connections

Omar Zahra omar.zahra at ejust.edu.eg
Mon Aug 8 14:05:32 EDT 2016 

Thank you Terry. I am really grateful.
But , unfortunately I cannot even find function as one of the parameters of
the node, do you have some examples I can follow to get better experience
with NENGO?


On Mon, Aug 8, 2016 at 8:02 PM, Terry Stewart <terry.stewart at gmail.com>
wrote:

> You should be able to do that with the node, since the return value
> from that node is the input to b. x[0] is the output of a.neurons[0],
> and so if your return value's [0] element is just based on x[0], then
> the input to b.neurons[0] will be based only on the output from
> a.neurons[0].
>
> Terry
>
> On Mon, Aug 8, 2016 at 1:56 PM, Omar Zahra <omar.zahra at ejust.edu.eg>
> wrote:
> > yes , that's exactly what I wanted to do. Using node would solve my
> problem.
> > The only remaining point is now the input to the node is some firing rate
> > (x) , I want for example b.neurons[0] to have an output depending on
> input
> > from a.neurons[0] ONLY.
> >
> > On Mon, Aug 8, 2016 at 7:45 PM, Terry Stewart <terry.stewart at gmail.com>
> > wrote:
> >>
> >> Hmm, I'm still not quite sure what you're trying to do here.  What do
> >> you mean by a "function for the rate of spikes"?  Do you mean neuron
> >> model itself (i.e. the thing that takes input current and generates
> >> spikes)?  If so, that's already part of the Ensemble and is specified
> >> by the neuron_type parameter, and you can choose from LIF, LIFRate,
> >> Izhikevich, Sigmoid, or write your own.  Or do you want to do
> >> something to the spikes after they've been generated by the neurons
> >> and before they're fed to the next group of neurons?  What sort of
> >> thing are you envisioning here?
> >>
> >> That said, in general, you can implement anything you want in Nengo by
> >> creating a Node:
> >>
> >> -------------------
> >> import nengo
> >>
> >> model = nengo.Network()
> >> with model:
> >>     a = nengo.Ensemble(n_neurons=50, dimensions=1)
> >>     b = nengo.Ensemble(n_neurons=50, dimensions=1)
> >>
> >>     def func(t, x):
> >>         # do whatever you want in here, where x is the input spikes and
> >>         # you return the output activity
> >>         return x
> >>     mynode = nengo.Node(func, size_in=50, size_out=50)
> >>
> >>     nengo.Connection(a.neurons, mynode)
> >>     nengo.Connection(mynode, b.neurons)
> >> ----------------------
> >>
> >>
> >> I'm still not sure whether that's what you're looking for, however....
> >>
> >>
> >> Terry
> >>
> >> On Mon, Aug 8, 2016 at 1:34 PM, Omar Zahra <omar.zahra at ejust.edu.eg>
> >> wrote:
> >> > This part I couldn't actually understand from the documentation well.
> I
> >> > thought that It wasn't about getting "the optimal connection weights"
> ,
> >> > I
> >> > just wanted to apply some function for the rate of spikes, and the
> >> > output
> >> > from the function would be input tp the postsynaptic.
> >> > Sorry for that misunderstanding , how then would I apply some function
> >> > to
> >> > the rate of spike ?
> >> > Thanks for your patience
> >> >
> >> > On Mon, Aug 8, 2016 at 6:04 PM, Terry Stewart <
> terry.stewart at gmail.com>
> >> > wrote:
> >> >>
> >> >> I think the problem is that you're trying to specify a function as
> >> >> well.  What function are you trying to do?
> >> >>
> >> >> The problem is that you're specifying the connection weights in two
> >> >> different ways.  When you save function=something, Nengo uses that
> >> >> function to find the optimal connection weights to approximate that
> >> >> function.  So you can't also manually specify the connection weights,
> >> >> since that's exactly what you've told nengo to solve for on its own!
> >> >>
> >> >> Terry
> >> >>
> >> >> On Mon, Aug 8, 2016 at 12:00 PM, Omar Zahra <omar.zahra at ejust.edu.eg
> >
> >> >> wrote:
> >> >> > Hello Terry,
> >> >> >
> >> >> > Thanks for your reply. I already used this to make a connection.
> >> >> > My problem is that I cannot " nengo.Connection(a.neurons,
> b.neurons,
> >> >> > transform=matrix, function = func)" because it must be applied to
> an
> >> >> > Ensemble.
> >> >> > I hope you have some solution for this problem.
> >> >> >
> >> >> > On Mon, Aug 8, 2016 at 5:47 PM, Terry Stewart
> >> >> > <terry.stewart at gmail.com>
> >> >> > wrote:
> >> >> >>
> >> >> >> Hello Omar,
> >> >> >>
> >> >> >> If you want to use Nengo to do manual neuron-to-neuron connection
> >> >> >> (i.e. the sort of thing that would happen in a standard neural
> >> >> >> simulator), then you need to connection to the ens.neurons object.
> >> >> >> For example, here's a quick way to do random connections between
> two
> >> >> >> groups of neurons:
> >> >> >>
> >> >> >> --------------
> >> >> >> import nengo
> >> >> >> import numpy as np
> >> >> >>
> >> >> >> model = nengo.Network()
> >> >> >> with model:
> >> >> >>     a = nengo.Ensemble(n_neurons=50, dimensions=1)
> >> >> >>     b = nengo.Ensemble(n_neurons=50, dimensions=1)
> >> >> >>
> >> >> >>     matrix = np.random.normal(size=(50, 50))
> >> >> >>     nengo.Connection(a.neurons, b.neurons, transform=matrix)
> >> >> >> -------------------------
> >> >> >>
> >> >> >> Let us know if that helps for your situations!
> >> >> >>
> >> >> >> Also, for future questions, we've just started up an online forum
> at
> >> >> >> https://forum.nengo.ai/
> >> >> >>
> >> >> >> Terry
> >> >> >>
> >> >> >> On Mon, Aug 8, 2016 at 9:13 AM, Omar Zahra <
> omar.zahra at ejust.edu.eg>
> >> >> >> wrote:
> >> >> >> > Hello,
> >> >> >> >
> >> >> >> > I am new to NENGO and also just started using python to deal
> with
> >> >> >> > NENGO.
> >> >> >> > I
> >> >> >> > would like to build part of the brain by connecting some layers.
> >> >> >> > These
> >> >> >> > connections are supposed to be topological. I would like also to
> >> >> >> > apply
> >> >> >> > some
> >> >> >> > function across these connections. When I try to use connection
> to
> >> >> >> > the
> >> >> >> > whole
> >> >> >> > ensemble, I cannot define the connections perfectly as done in
> >> >> >> > case
> >> >> >> > of
> >> >> >> > making connections neuron by neuron -using Ensemble.neurons[]
> -. I
> >> >> >> > tried
> >> >> >> > even increasing the dimensions of the ensemble and setting the
> >> >> >> > encoders
> >> >> >> > such
> >> >> >> > as to give seperate action for each neuron, still some
> unintended
> >> >> >> > response
> >> >> >> > appears.
> >> >> >> > Reply ASAP please. Thanks in advance
> >> >> >> >
> >> >> >> > --
> >> >> >> > Best Regards
> >> >> >> > Omar Ibn ElKhatab AbdAllah Zahra
> >> >> >> >
> >> >> >> > _______________________________________________
> >> >> >> > nengo-user mailing list
> >> >> >> > nengo-user at ctnsrv.uwaterloo.ca
> >> >> >> > http://ctnsrv.uwaterloo.ca/mailman/listinfo/nengo-user
> >> >> >> >
> >> >> >
> >> >> >
> >> >> >
> >> >> >
> >> >> > --
> >> >> > Best Regards
> >> >> > Omar Ibn ElKhatab AbdAllah Zahra
> >> >
> >> >
> >> >
> >> >
> >> > --
> >> > Best Regards
> >> > Omar Ibn ElKhatab AbdAllah Zahra
> >
> >
> >
> >
> > --
> > Best Regards
> > Omar Ibn ElKhatab AbdAllah Zahra
>



-- 
Best Regards
Omar Ibn ElKhatab AbdAllah Zahra
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