Journal
PLOS COMPUTATIONAL BIOLOGY
Volume 11, Issue 6, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1004275
Keywords
-
Funding
- Swiss National Science Foundation (SNSF) [200020_132871/1, 200020_147200]
- European Community [269921]
- European Union [604102]
- EPFL
- Fonds de recherche du Quebec - Nature et technologies (FQRNT)
- Swiss National Science Foundation (SNF) [200020_132871] Funding Source: Swiss National Science Foundation (SNF)
Ask authors/readers for more resources
Single-neuron models are useful not only for studying the emergent properties of neural circuits in large-scale simulations, but also for extracting and summarizing in a principled way the information contained in electrophysiological recordings. Here we demonstrate that, using a convex optimization procedure we previously introduced, a Generalized Integrate-and-Fire model can be accurately fitted with a limited amount of data. The model is capable of predicting both the spiking activity and the subthreshold dynamics of different cell types, and can be used for online characterization of neuronal properties. A protocol is proposed that, combined with emergent technologies for automatic patch-clamp recordings, permits automated, in vitro high-throughput characterization of single neurons.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available