Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

Christian Pozzorini, Skander Mensi, Olivier Hagens, Richard Naud, Christof Koch, Wulfram Gerstner, Jonathan W. Pillow
2015 PLoS Computational Biology  
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 Integrateand-Fire model can be accurately fitted with a limited amount of data. The model is capable of predicting both the spiking activity and the
more » ... 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.
doi:10.1371/journal.pcbi.1004275 pmid:26083597 pmcid:PMC4470831 fatcat:n2sna4rjxndujdvaa3mhl2bxne