Inferring and validating mechanistic models of neural microcircuits based on spike-train data
It is difficult to fit mechanistic, biophysically constrained circuit models to spike train data from in vivo extracellular recordings. Here the authors present analytical methods that enable efficient parameter estimation for integrate-and-fire circuit models and inference of the underlying connect...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2019
|
| Subjects: | |
| Online Access: | https://doaj.org/article/85a037d778554f659901d36b5d3fc974 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | It is difficult to fit mechanistic, biophysically constrained circuit models to spike train data from in vivo extracellular recordings. Here the authors present analytical methods that enable efficient parameter estimation for integrate-and-fire circuit models and inference of the underlying connectivity structure in subsampled networks. |
|---|