title: Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference.
abstract: Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits.
authors.affiliation: Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Biomagnetic Centre, Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.
authors.forename: Vahid
authors.initials: V
authors.lastname: Rahmati
authors.affiliation: Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.
authors.forename: Knut
authors.initials: K
authors.lastname: Kirmse
authors.affiliation: Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Biomagnetic Centre, Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.|Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
authors.forename: Dimitrije
authors.initials: D
authors.lastname: Marković
authors.affiliation: Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.
authors.forename: Knut
authors.initials: K
authors.lastname: Holthoff
authors.affiliation: Department of Psychology, Technische Universität Dresden, Dresden, Germany.|Biomagnetic Centre, Hans-Berger Department of Neurology, University Hospital Jena, Jena, Germany.|Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
authors.forename: Stefan J
authors.initials: SJ
authors.lastname: Kiebel
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D001499:Bayes Theorem; D056654:CA3 Region, Hippocampal / Q000166:cytology / Q000378:metabolism; D002118:Calcium / Q000378:metabolism*; D020013:Calcium Signaling / Q000502:physiology*; D002478:Cells, Cultured; D019295:Computational Biology; D051379:Mice; D008810:Mice, Inbred C57BL; D008959:Models, Neurological; D057054:Molecular Imaging; D009474:Neurons / Q000502:physiology*
chemical_list: D002118:Calcium