Dear Pavel,
I can confirm you observation, and I share your surprise. Intuitively, one would expect that the synaptic state should return to the initial state after the long period of silence. However, after consulting the source papers (todyks_synapse: doi:10.1523/JNEUROSCI.20-01-j0003.2000, tsodyks2_synapse: doi:10.1016/S0893-6080(01)00144-7) and looking at the NEST code, I conclude that what the example shows is indeed the intended behaviour.
A key difference between tsodyks_synapse and todyks2_synapse is the order of update steps: upon arrival of the presynaptic spike, tsodyks_synapse first updates the synapse state (x,y,z,u; see lines 258-277 in tsodyks_synapse.h), and then reports the new weight (line 285 in tsodyks_synapse.h). In tsodyks2_synapse, this is reversed: first, the synaptic weight is computed based on the current (i.e., the old) synapse state (line 236 in tsodyks2_synapse.h), and then the synapse state is updated (lines 243,244 in tsodyks2_synapse.h). When the first spike of the second burst of presynaptic spikes arrives in the example (https://nest-simulator.readthedocs.io/en/stable/auto_examples/evaluate_tsody...), the recovery value of tsodyks2_synapse still is where it was at the end of the first burst of spikes (before the break). This is exactly how the model is defined in (Maass and Markram, 2002; doi:10.1016/S0893-6080(01)00144-7; see equations (1-5)). It needs one more spike to really "recover".
I hope this clarifies things a bit.
Best Tom
On 12.12.24 12:05, Pavel Haman wrote:
Hello,
I have followed the example script comparing `tsodyks_synapse` and `tsodyks2_synapse` models, which can be found here: https://nest-simulator.readthedocs.io/en/stable/auto_examples/evaluate_tsody...
Using the parameter set for depression instead of facilitation I found that `tsodyks2_synapse` model leads to weird peaks of synaptic currents (at least I would not expect that for short term depression) - during the second stimulation the weight rescaling seems to be shifted by one spike compared to tsodyks_synapse (as if parameter "u" would be updated after rescaling the weight instead of before).
Does anybody know why is there this difference between the two synapse models?
Thank you.
All the best, PH _______________________________________________ NEST Users mailing list -- users@nest-simulator.org To unsubscribe send an email to users-leave@nest-simulator.org