Christophe Pouzat

• November 15 2024, the manuscript written with Morgan André A Quasi-Stationary Approach to Metastability in a System of Spiking Neurons with Synaptic Plasticity has been accepted by Mathematical Neuroscience and Applications.
• October 17 2024, the book Probabilistic Spiking Neuronal Nets. Neuromathematics for the Computer Era, by Antonio Galves, Eva Löcherbach and Christophe Pouzat, published by Springer in the book series: Lecture Notes on Mathematical Modelling in the Life Sciences is out!
• May 2024, The brand new MOOC Reproducible Research II: Practices and tools for managing computations and data is out!
• 2023 IHP program Random processes in the brain: From experimental data to Math and back, from February 27 to April 7. If you cannot join us in Paris, follow it from its home page (link LIVE! in the upper right of the page).
• January 2023 the project Simulation Based Network Structure Inference Constrained by Observed Spike Trains: SIMBADNESTICOST ANR-22-CE45-0027 starts.

• I am currently a CNRS researcher of the Intitut de Recherche Mathématique Avancée (IRMA) of the University of Strasbourg.
• Between January 2012 and August 2020 I was a CNRS researcher of the MAP5 the Applied Maths Laboratory of the Paris-Descartes University.
• I have been for 11 years (Jan 2001 - Dec 2011) member of the Laboratory of Brain Physiology of the same University.
• I did a two years post-doc (Jan 1999 - Dec 2000) in the laboratory of Gilles Laurent at the California Institute of Technology.
• I did my PhD at the Max Planck Institute for Biophysical Chemistry under the supervision of Alain Marty (Feb 1995 - Dec 1998).

Having a background in experimental neurophysiology, I mainly work on the analysis of data produced in this field. This work can be split into three broad categories – with associated keywords linking the task to specific statistical methodologies :

• Spike sorting – dimension-reduction, clustering, classification, Gaussian mixture models, EM algorithm, MCMC. All that is now explained in a short film on YouTube.
• Spike train analysis – point process / counting process, conditional intensity estimation, nonparametric estimation, smoothing spline, goodness of fit tests, Donsker theorem.
• Calcium imaging – Poisson regression, variance stabilization, parametric / nonparametric models, image segmentation.

In every project I try to implement what is now commonly called the Reproducible research paradigm – that I prefer to call the reproducible data analysis paradigm. I am not a developer of the tools making the implementation of the paradigm possible but a daily user of them.

My main current project is: Simulation Based Network Structure Inference Constrained by Observed Spike Trains: SIMBADNESTICOST ANR-22-CE45-0027.

• Peter Kloppenburg from Cologne University (Germany), my main "data provider".
• Antonio Galves (NeuroMat at the University of São Paulo) and Eva Löcherbach (Université Paris-1) on stochastic models for neuronal networks.
• Céline Duval (Painlevé lab., Lille University) and Éric Luçon (MAP5, Université Paris-Descartes / Université de Paris) on Hawkes process models for neural networks.

• The most recent versions of my codes can now be found on my GitHub page, GitLab page and PlmLab page.

My five latest publications:

• Antonio Galves, Eva Löcherbach and Christophe Pouzat (2024) Probabilistic Spiking Neuronal Nets. Neuromathematics for the Computer Era, Springer, book series: Lecture Notes on Mathematical Modelling in the Life Sciences. The companion website describes and documents the codes simulating the models introduced in the book.
• Céline Duval, Éric Luçon, Christophe Pouzat (2022) Interacting Hawkes processes with multiplicative inhibition, Stochastic Processes and their Applications, 148: 180-226, DOI: 10.1016/j.spa.2022.02.008.
• Haeger Alexa, Pouzat Christophe, Luecken Volker, N’Diaye Karim, Elger Christian, Kennerknecht Ingo, Axmacher Nikolai and Dinkelacker Vera (2021) Face Processing in Developmental Prosopagnosia: Altered Neural Representations in the Fusiform Face Area. Frontiers in Behavioral Neuroscience, 15: 283, DOI: 10.3389/fnbeh.2021.744466. Supplementary material available on GitHub: haeger-et-al-face-processing-in-developmental-prosopagnosia.
• Simon Hess, Christophe Pouzat, Peter Kloppenburg (2021) A simple method for getting standard error on the ratiometric calcium estimator. MethoodsX, 8: 101548, DOI: 10.1016/j.mex.2021.101548.
• Simon Hess, Christophe Pouzat, Lars Paeger, Andreas Pippow and Peter Kloppenburg (2021) Analysis of neuronal Ca2+ handling properties by combining perforated patch clamp recordings and the added buffer approach. Cell Calcium, 97: 102411, DOI: 10.1016/j.ceca.2021.102411.

More…

• Morgan André, Christophe Pouzat (2024) A Quasi-Stationary Approach to Metastability in a System of Spiking Neurons with Synaptic Plasticity, hal-04439827, a significantly revised version of the next item of this list; the associated simulation and analysis codes are available from the following GitLab repository: Metastability in a System of Spiking Neurons with Synaptic Plasticity.
• Morgan André, Christophe Pouzat (2021) Metastability in a System of Spiking Neurons with Synaptic Plasticity, hal-03281732, the associated simulation and analysis codes are available from the following GitLab repository: Metastability in a System of Spiking Neurons with Synaptic Plasticity.
• Céline Duval, Éric Luçon, Christophe Pouzat (2021) Interacting Hawkes processes with multiplicative inhibition, arXiv:2105.10597, the associated simulation codes with detailed explanations are available from the following PlmLab repository: hawkes-x-hawkes.
• Antonio Galves, Eva Löcherbach and Christophe Pouzat (2021) Probabilistic spiking neuronal nets - Neuromathematics for the computer era, roughly the first third of a book we are currently working on.
• Simon Hess, Christophe Pouzat, Peter Kloppenburg (2020) A Simple Method for Getting Standard Error on the Ratiometric Calcium Estimator on BioRxiv. This is the appendix of the previous manuscript, expanded at the request of the editor. As usual, codes, data, etc, are available on GitLab.
• Simon Hess, Christophe Pouzat, Lars Paeger, Andreas Pippow, Peter Kloppenburg (2020) Analysis of neuronal Ca2+ handling properties by combining perforated patch clamp recordings and the added buffer approach on bioRxiv; the data and code are available on zenodo as well as on GitHub.
• Antonio Galves, Eva Löcherbach, Christophe Pouzat, Errico Presutti (2019) A system of interacting neurons with short term synaptic facilitation (arXiv:1903.01270); a GitLab repository with the code (in C and Python) doing the simulations and the figures (in gnuplot) is available on PlmLab.

Recent talks:

• Cell Physics Master, Strasbourg University, November 21 2024: Quantitative Analysis of Fluorescence Data. You can get the slides with the overview and the "in depth" document with all the "nasty details" using Python, as well as the slide material in a chapter form.
• A Quasi-Stationary Approach to Metastability in a System of Spiking Neurons with Synaptic Plasticity, a seminar given at the Institut Neuromod, Nice Sophia-Antipolis, on October 17 2024. This is a joint work with Morgan André (USP, Sao Paulo, Brasil). A pre-print describing this work is available on HAL; the code doing the simulations and figures, etc. is on GitLab.
• Biological neural networks a seminar given at the DU IRMA++ with Eva Löcherbach on October 10 2024.
• A talk on reproducible research and a short practical given at the the workshop: "Open science, research integrity and science in society", September 23-24, Brussels. There is also an associated GitLab repository.
• Quantitative Analysis of Fluorescence Data, a lecture part of the Summer School | Advanced tools for data analysis in neuroscience held in Strasbourg, September 16-21. The same material is available in a Book chapter form. There is an associated GitLab repository.
• My course material for the Master Modeling for Neuronal and Cognitive Systems bootcamp, Université Côte d'Azur, 2024, is in the GitLab repository neuromod-bootcamp.
• A Quasi-Stationary Approach to Metastability in a System of Spiking Neurons with Synaptic Plasticity, joint work with Morgan André: an Invited Lecture given at LASCON IX, on January 22 2024 in the Special Session in Honor of Antonio Galves. The talk is available on YouTube.
• Course material for LASCON 2024 (USP, January 2024).
• What to do with extracellular recordings? A proposal. A talk given at the Eurandom's Stochastic Models in Life Science workshop on September 6 2023.
• What to do when you have to estimate a function? Nonparametric regression techniques. A lecture given at the summer school Advanced tools for data analysis in Neuroscience Aug 31 - Sept 9, 2023. An easy to read and print version of the lecture is available. The GitLab repository contains the PDF source files as well as the Python script (regressogram.py in the code folder) doing the analysis and the figures presented in the first part (on functional data analysis). The codes doing the job for the second part (on variance stabilization) are available in several languages: Python, R (the description is in French) and C.
• Neuronal network structure inference by simulation, MoMA seminar, Dipartimento di Matematica, Sapienza, Università di Roma, May 19 2023.
• IHP first lecture on Stochastic modeling of neural networks (March 20 2023). I reuse the material of my first two lectures at LASCON 2020: sta_lecture_1.pdf and sta_lecture_2.pdf that can be found on the dedicated PlmLab repository; a "properly written" version of this material is also available from the same location in file spike_train_analysis.pdf.
• IHP talk Data: Where Do They Come From? How to Interpret Them? (March 17 2023).
• IHP scratch course on Basic neurobiology for mathematicians (March 1st 2023). More mathematical details can be found in Chapter 1 and Appendix 1 in the almost finished book: Probabilistic Spiking Neuronal Nets – Data, Models and Theorems.
• Course material for the Advanced tools for data analysis in Neuroscience - 2022 summer school in Strasbourg, September 5-10: Spike sorting: The prehistory (PDF file of introduction to spike sorting); the sorting tutorial, Spike Sorting the 'Do It Yourself' way is available in PDF and HTML; the PDF and the HTML versions of the afternoon lecture, Spike trains analysis basics, are available as well; if you want more material on the statistical aspects of PSTH, etc, check last year course in folder spike_trains_statics in my dedicated repository.

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The datasets used in my publications are available in HDF5 format from zenodo. You are welcome to do what you want with them–including publishing with them without having to "invite" me to sign your publication–just cite your source (the DOI are given bellow):

• Tetrode recording from the antennal lobe of a locust (Schistocerca americana) (doi: 10.5281/zenodo.14607).
• Dataset from "Matthieu Delescluse and Christophe Pouzat (2006) Efficient spike-sorting of multi-state neurons using inter-spike intervals information Journal of Neuroscience Methods 150: 16-29." (doi: 10.5281/zenodo.15228).
• Data set from Pouzat and Chaffiol (2009) Journal of Neuroscience Methods 181:119.(doi: 10.5281/zenodo.14281).
• All my postdoc extracellular recordings from the locust olfactory pathway are now available –a third of the data has been lost due to CD corruption after 14 years!– (doi: 10.5281/zenodo.21589). There are roughly 15 GB of data from 14 experiments. A detailed description of the sorting of these data set is available on GitHub.

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