Dear Björn and Frank,

could you reproduce the results of the following script:
https://github.com/electronicvisions/spikey_demo/blob/master/networks/stdp.py

I can follow your arguments, but, on first sight, I cannot identify  
obvious reasons for this unexpected behavior.
Due to the unknown initialization of correlations stored in the STDP  
synapses, please consider sequentially repeating your stimulation  
pattern within a single elongated emulation run?
The temporal interval between repetitions should be large enough to  
avoid learning between them.
This allows to investigate the long-term limit of weight changes.
If these results are difficult to interpret, you may consider plotting  
the synaptic weight over the length of your emulation (here, number of  
repeated identical stimulation patterns).

Cheers,

Thomas


Zitat von "Deiseroth, Bjoern" <[log in to unmask]>:

> Hello there, us again :)
>
>
>
> so we understood, that a nearest-neighbor, pair-based STDP is  
> running on spikey.
>
> Lets say a neuron "pre" is connected to a neuron "post" via a STDP synapse.
>
>
>
> Attached, we built a network such that the following spike train occurs:
>
>
>
> Pre:
>
> 0.0,15.850000381469727
>
> 0.0,20.149999618530273
>
> 0.0,24.700000762939453
>
> 0.0,29.5
>
>
>
> Post:
>
> 5.0,28.850000381469727
>
>
>
> So changes to the STDP stack should be: a_c for Dt(28,85-24,7) and  
> a_a for Dt(28,85-29,5), according to your survey "is 4-bit  
> synaptic...".
>
>
>
> Starting at weight 3, it should therefore decreased to 2, or maybe  
> remain equal if the difference is not enough, for a single iteration.
>
> Instead, it is always rises to 4.
>
>
>
> Am I missing something?
>
>
>
> Thank you :)
>
> Björn and Frank
>
>
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