<div dir="ltr"><div>yes , that's exactly what I wanted to do. Using node would solve my problem.<br></div>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.<br></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Aug 8, 2016 at 7:45 PM, Terry Stewart <span dir="ltr"><<a href="mailto:terry.stewart@gmail.com" target="_blank">terry.stewart@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hmm, I'm still not quite sure what you're trying to do here. What do<br>
you mean by a "function for the rate of spikes"? Do you mean neuron<br>
model itself (i.e. the thing that takes input current and generates<br>
spikes)? If so, that's already part of the Ensemble and is specified<br>
by the neuron_type parameter, and you can choose from LIF, LIFRate,<br>
Izhikevich, Sigmoid, or write your own. Or do you want to do<br>
something to the spikes after they've been generated by the neurons<br>
and before they're fed to the next group of neurons? What sort of<br>
thing are you envisioning here?<br>
<br>
That said, in general, you can implement anything you want in Nengo by<br>
creating a Node:<br>
<br>
-------------------<br>
import nengo<br>
<span class=""><br>
model = nengo.Network()<br>
with model:<br>
a = nengo.Ensemble(n_neurons=50, dimensions=1)<br>
b = nengo.Ensemble(n_neurons=50, dimensions=1)<br>
<br>
</span> def func(t, x):<br>
# do whatever you want in here, where x is the input spikes and<br>
# you return the output activity<br>
return x<br>
mynode = nengo.Node(func, size_in=50, size_out=50)<br>
<br>
nengo.Connection(a.neurons, mynode)<br>
nengo.Connection(mynode, b.neurons)<br>
----------------------<br>
<br>
<br>
I'm still not sure whether that's what you're looking for, however....<br>
<span class="HOEnZb"><font color="#888888"><br>
<br>
Terry<br>
</font></span><div class="HOEnZb"><div class="h5"><br>
On Mon, Aug 8, 2016 at 1:34 PM, Omar Zahra <<a href="mailto:omar.zahra@ejust.edu.eg">omar.zahra@ejust.edu.eg</a>> wrote:<br>
> This part I couldn't actually understand from the documentation well. I<br>
> thought that It wasn't about getting "the optimal connection weights" , I<br>
> just wanted to apply some function for the rate of spikes, and the output<br>
> from the function would be input tp the postsynaptic.<br>
> Sorry for that misunderstanding , how then would I apply some function to<br>
> the rate of spike ?<br>
> Thanks for your patience<br>
><br>
> On Mon, Aug 8, 2016 at 6:04 PM, Terry Stewart <<a href="mailto:terry.stewart@gmail.com">terry.stewart@gmail.com</a>><br>
> wrote:<br>
>><br>
>> I think the problem is that you're trying to specify a function as<br>
>> well. What function are you trying to do?<br>
>><br>
>> The problem is that you're specifying the connection weights in two<br>
>> different ways. When you save function=something, Nengo uses that<br>
>> function to find the optimal connection weights to approximate that<br>
>> function. So you can't also manually specify the connection weights,<br>
>> since that's exactly what you've told nengo to solve for on its own!<br>
>><br>
>> Terry<br>
>><br>
>> On Mon, Aug 8, 2016 at 12:00 PM, Omar Zahra <<a href="mailto:omar.zahra@ejust.edu.eg">omar.zahra@ejust.edu.eg</a>><br>
>> wrote:<br>
>> > Hello Terry,<br>
>> ><br>
>> > Thanks for your reply. I already used this to make a connection.<br>
>> > My problem is that I cannot " nengo.Connection(a.neurons, b.neurons,<br>
>> > transform=matrix, function = func)" because it must be applied to an<br>
>> > Ensemble.<br>
>> > I hope you have some solution for this problem.<br>
>> ><br>
>> > On Mon, Aug 8, 2016 at 5:47 PM, Terry Stewart <<a href="mailto:terry.stewart@gmail.com">terry.stewart@gmail.com</a>><br>
>> > wrote:<br>
>> >><br>
>> >> Hello Omar,<br>
>> >><br>
>> >> If you want to use Nengo to do manual neuron-to-neuron connection<br>
>> >> (i.e. the sort of thing that would happen in a standard neural<br>
>> >> simulator), then you need to connection to the ens.neurons object.<br>
>> >> For example, here's a quick way to do random connections between two<br>
>> >> groups of neurons:<br>
>> >><br>
>> >> --------------<br>
>> >> import nengo<br>
>> >> import numpy as np<br>
>> >><br>
>> >> model = nengo.Network()<br>
>> >> with model:<br>
>> >> a = nengo.Ensemble(n_neurons=50, dimensions=1)<br>
>> >> b = nengo.Ensemble(n_neurons=50, dimensions=1)<br>
>> >><br>
>> >> matrix = np.random.normal(size=(50, 50))<br>
>> >> nengo.Connection(a.neurons, b.neurons, transform=matrix)<br>
>> >> -------------------------<br>
>> >><br>
>> >> Let us know if that helps for your situations!<br>
>> >><br>
>> >> Also, for future questions, we've just started up an online forum at<br>
>> >> <a href="https://forum.nengo.ai/" rel="noreferrer" target="_blank">https://forum.nengo.ai/</a><br>
>> >><br>
>> >> Terry<br>
>> >><br>
>> >> On Mon, Aug 8, 2016 at 9:13 AM, Omar Zahra <<a href="mailto:omar.zahra@ejust.edu.eg">omar.zahra@ejust.edu.eg</a>><br>
>> >> wrote:<br>
>> >> > Hello,<br>
>> >> ><br>
>> >> > I am new to NENGO and also just started using python to deal with<br>
>> >> > NENGO.<br>
>> >> > I<br>
>> >> > would like to build part of the brain by connecting some layers.<br>
>> >> > These<br>
>> >> > connections are supposed to be topological. I would like also to<br>
>> >> > apply<br>
>> >> > some<br>
>> >> > function across these connections. When I try to use connection to<br>
>> >> > the<br>
>> >> > whole<br>
>> >> > ensemble, I cannot define the connections perfectly as done in case<br>
>> >> > of<br>
>> >> > making connections neuron by neuron -using Ensemble.neurons[] -. I<br>
>> >> > tried<br>
>> >> > even increasing the dimensions of the ensemble and setting the<br>
>> >> > encoders<br>
>> >> > such<br>
>> >> > as to give seperate action for each neuron, still some unintended<br>
>> >> > response<br>
>> >> > appears.<br>
>> >> > Reply ASAP please. Thanks in advance<br>
>> >> ><br>
>> >> > --<br>
>> >> > Best Regards<br>
>> >> > Omar Ibn ElKhatab AbdAllah Zahra<br>
>> >> ><br>
>> >> > ______________________________<wbr>_________________<br>
>> >> > nengo-user mailing list<br>
>> >> > <a href="mailto:nengo-user@ctnsrv.uwaterloo.ca">nengo-user@ctnsrv.uwaterloo.ca</a><br>
>> >> > <a href="http://ctnsrv.uwaterloo.ca/mailman/listinfo/nengo-user" rel="noreferrer" target="_blank">http://ctnsrv.uwaterloo.ca/<wbr>mailman/listinfo/nengo-user</a><br>
>> >> ><br>
>> ><br>
>> ><br>
>> ><br>
>> ><br>
>> > --<br>
>> > Best Regards<br>
>> > Omar Ibn ElKhatab AbdAllah Zahra<br>
><br>
><br>
><br>
><br>
> --<br>
> Best Regards<br>
> Omar Ibn ElKhatab AbdAllah Zahra<br>
</div></div></blockquote></div><br><br clear="all"><br>-- <br><div class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr">Best Regards<div>Omar Ibn ElKhatab AbdAllah Zahra</div></div></div>
</div>