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AraiKensuke / LOST

Latent Oscillation in Spike Train (LOST)
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005596
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Some questions #2

Closed alberto-antonietti closed 5 years ago

alberto-antonietti commented 5 years ago

Hi again Ken,

I have some questions about your code. In particular, I would like to exploit only a part of its capabilities. My problem is to extract the oscillations of spike trains, extracting in a robust way the frequency of oscillations and how strong they are. I only have spike trains, but I do not have modulatory signals such as LFP or EEG. Do you think that your approach could be useful also in my case?

I have already tried simpler methods (autocorrelograms + FFT) but they are no reliable and stable.

Thank you for you support and congratulation again for the nice work that you have achieved!

Alberto

AraiKensuke commented 5 years ago

My problem is to extract the oscillations of spike trains, extracting in a robust way the frequency of oscillations and how strong they are. I only have spike trains, but I do not have modulatory signals such as LFP or EEG. Do you think that your approach could be useful also in my case?

Hi Alberto:

Yes, this is the whole point of LOST - extracting oscillations from

ONLY spiking observations. If you have LFP or EEG, then you can compare what you've extracted to those signals, and such analysis may uncover other useful information, but at its most basic, LOST only needs as input, spike train.

Ken

On Wed, Dec 12, 2018 at 10:06 AM Alberto Antonietti < notifications@github.com> wrote:

Hi again Ken,

I have some questions about your code. In particular, I would like to exploit only a part of its capabilities. My problem is to extract the oscillations of spike trains, extracting in a robust way the frequency of oscillations and how strong they are. I only have spike trains, but I do not have modulatory signals such as LFP or EEG. Do you think that your approach could be useful also in my case?

I have already tried simpler methods (autocorrelograms + FFT) but they are no reliable and stable.

Thank you for you support and congratulation again for the nice work that you have achieved!

Alberto

— You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub https://github.com/AraiKensuke/LOST/issues/2, or mute the thread https://github.com/notifications/unsubscribe-auth/AHGQnyt39Rlp25kDEqSsmoayFBO1tN_nks5u4RuEgaJpZM4ZPn6_ .

-- Kensuke Arai Postdoc @ Uri Eden Group, Boston University

alberto-antonietti commented 5 years ago

My problem is to extract the oscillations of spike trains, extracting in a robust way the frequency of oscillations and how strong they are. I only have spike trains, but I do not have modulatory signals such as LFP or EEG. Do you think that your approach could be useful also in my case? Hi Alberto: Yes, this is the whole point of LOST - extracting oscillations from ONLY spiking observations. If you have LFP or EEG, then you can compare what you've extracted to those signals, and such analysis may uncover other useful information, but at its most basic, LOST only needs as input, spike train. Ken … On Wed, Dec 12, 2018 at 10:06 AM Alberto Antonietti < @.***> wrote: Hi again Ken, I have some questions about your code. In particular, I would like to exploit only a part of its capabilities. My problem is to extract the oscillations of spike trains, extracting in a robust way the frequency of oscillations and how strong they are. I only have spike trains, but I do not have modulatory signals such as LFP or EEG. Do you think that your approach could be useful also in my case? I have already tried simpler methods (autocorrelograms + FFT) but they are no reliable and stable. Thank you for you support and congratulation again for the nice work that you have achieved! Alberto — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#2>, or mute the thread https://github.com/notifications/unsubscribe-auth/AHGQnyt39Rlp25kDEqSsmoayFBO1tN_nks5u4RuEgaJpZM4ZPn6_ . -- Kensuke Arai Postdoc @ Uri Eden Group, Boston University

Dear Ken, that is wonderful! Then you method will be very useful for my research. It is a very good opportunity for me to exploit your code (thanks for having made it public!) and, at the same time, to improve its availability and accessibility to other researchers.

I close this issue and we can continue the discussion on more technical stuff on #1