Very happy to announce that my very first paper just came out in PNAS.
“Neuronal circuits overcome imbalance in excitation and inhibition by adjusting connection numbers”
pnas.org/content/118/12… #tweeprint below (1/7)
The paper is a result of a collaboration between @uni_tue @MPICybernetics and @WeizmannScience. A joint effort of @SelfOrgAnna, Moses lab, and Segal labs.
(2/7)
Hippocampal and cortical networks typically have about 20-30% of inhibitory neurons. But would they work with the other percentages? We looked at the activity of networks grown using a novel protocol to precisely control E/I ratios. (3/7) Image
The networks with practically any cellular E/I ratio were active and developed network bursting. Most features of the bursting activity were different only in cultures with extreme E/I ratios. Next, we wanted to see which mechanism do they use to main the bursting dynamics. (4/7) Image
Using patch clamp, we identified that the networks adjust the number of excitatory connections such that they stay proportional to the number of excitatory neurons. (5/7) Image
Finally, to link the changes in connections and bursting dynamics, we fit a network model using ABC. The results showed that the networks can preserve the bursting behavior by maintaining the total number of E and I inputs to each cell nearly balanced. (6/7) Image
Under the blockage of inhibition, the bursts became larger and less frequent, which was consistent with the behavior of the model. That also helped us to identify that the spike-frequency adaptation together with inhibition determines the network bursting. (7/7) Image

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Oleg Vinogradov

Oleg Vinogradov Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!