8 May
2020
8 May
'20
10:39 a.m.
Dear Charl,
thank you very much for the very quick response! This device looks
indeed like what I was searching for and could be very helpful. I will
have a deeper look and then directly comment on the issue.
Thank you!
Benedikt
On 08.05.20 10:24, Charl Linssen wrote:
Dear Benedikt,
Someone has recently proposed a specialised NEST measurement device that may do exactly
what you need. We are currently still in discussion over the details and what use cases
this device is relevant for. If this device indeed does what you need, your use case would
be a very helpful contribution to the discussion. Could I ask you to review
https://github.com/nest/nest-simulator/issues/1519 (and potentially the linked PR), and,
if this is conceptually indeed what you are looking for, to post a comment in the thread
with a short thumbs up and how you would use this device in your simulation? I'm sure
this will be a boon to @sepehrmn (the author of the device) as well.
Many thanks!
Charl
On Fri, May 8, 2020, at 10:09, Benedikt Feldotto wrote:
--
Benedikt Feldotto M.Sc.
Research Assistant
Human Brain Project - Neurorobotics
Technical University of Munich
Department of Informatics
Chair of Robotics, Artificial Intelligence and Real-Time Systems
Room HB 2.02.20
Parkring 13
D-85748 Garching b. München
Tel.: +49 89 289 17628
Mail: feldotto(a)in.tum.de
https://www6.in.tum.de/en/people/benedikt-feldotto-msc/
www.neurorobotics.net
Dear all,
I am working with frequency encoded spike trains and therefore like to
observe the changing spike frequencies between different individual
connections in my network (if possible in real time). While I can record
the spike events with time using 'spike_detector' units, I couldn't find
a direct method to calculate the frequency. Is there any method
implemented or a preferred way to calculate frequencies from spike
trains over time or would this calculation be up to the user? I am also
thinking about using an indirect way by attaching a leaky integrate and
fire neuron with infinite threshold.
Thanks!
Best,
Benedikt
--
Benedikt Feldotto M.Sc.
Research Assistant
Human Brain Project - Neurorobotics
Technical University of Munich
Department of Informatics
Chair of Robotics, Artificial Intelligence and Real-Time Systems
Room HB 2.02.20
Parkring 13
D-85748 Garching b. München
Tel.: +49 89 289 17628
Mail: feldotto(a)in.tum.de
https://www6.in.tum.de/en/people/benedikt-feldotto-msc/
www.neurorobotics.net
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