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Alain Destexhe
English version

La recherche réalisée dans le laboratoire d’Alain Destexhe se situe à l’interface entre plusieurs disciplines, comme la biophysique, la physique, l’informatique et les neurosciences. Ce type de recherche est possible seulement grâce à des collaborations très étroites avec les expérimentateurs au niveau neuronal (enregistrements intracellulaires) et au niveau réseaux (enregistrements EEG, MEG, LFP et imagerie optique). Nous collaborons activement avec des groupes expérimentaux en Europe, aux USA et au sein de l’ICN. Nous encourageons les étudiants à suivre des projets de recherche mixtes, qui combinent des composantes expérimentales et théoriques ou computationnelles.

Possibilités de doctorat, post-doctorat et chercheur permanent à l’ICN



Notre groupe s’est également activement impliqué dans la création et l’animation du European Institute for Theoretical Neuroscience (EITN) à Paris et Gif sur Yvette. Cet institut est financé conjointement par le Human Brain Project et le CNRS. L’EITN a pour but de servir d’incubateur d’idées en neurosciences théoriques, sous forme d’organisation de conférences et accueil de visiteurs, postdocs ou étudiants.

Pour plus d’informations, contactez: Alain Destexhe, CNRS, Institut des Neurosciences de Paris-Saclay (NeuroPSI)

bâtiment 151, Route de la Rotonde, 91400 Saclay, France Tel: 33-1-69-82-34-35, Fax: 33-1-69-82-34-27

Picture illustrating the combination of computational models (color snapshots) with in vivo intracellular recordings (yellow trace) to study the oscillatory behavior generated in a neuronal structure (see A model of spindle rhythmicity in the isolated thalamic reticular nucleus, Journal of Neurophysiology 72: 803-818, 1994).

[su_accordion] [su_spoiler class=”my-custom-spoiler” open=”yes” title=”RERCHECHE” style=”font-size:7px;”] Recherche subventionnée par le CNRS (Centre National de la Recherche Scientifique), l’ANR (Agence Nationale de la Recherche), la CE (Commission Européenne), les NIH (National Institutes of Health) et le HFSP (Human Frontier Science Program); cliquez ici pour les détails de ces projets.

Description des axes de recherches actuels, ainsi que des liens vers une information plus détaillée.

Read more: Research themes of the laboratory and overview of publications

The research conducted in this laboratory stands at the interface between several disciplines, such as biophysics, physics and neuroscience. The themes investigated (see below) range from the microscopic (single neurons) to the macroscopic (networks or populations of neurons) aspects of the central nervous system function. We use theoretical methods and computer-based simulation techniques to explore the complex behavior of single neurons and understand their basic integrative properties (see The integrative properties of cortical neurons in vivo, The integrative properties of thalamic neurons). This task requires to integrate details about experimental measurements of these neurons, their morphology, their biophysical properties, as well as the properties of their synaptic inputs (see Biophysical models of synaptic transmission). There is also a need for a constant and continuous exchange with experimentalists recording single cells (intracellular measurements).

At the network level, we try to understand the collective behavior of neuronal populations, which in many cases cannot be simply deduced from single-cell behavior. In cerebral cortex and thalamus, neurons are characterized by complex intrinsic properties (see above) and also influence each-other through many different types of synaptic interactions involving different classes of receptors. These networks are therefore highly complex and computational methods can be particularly pertinent in predicting their behavior. This approach was followed for the case of oscillatory behavior in thalamus and cortex (see Network models of thalamic oscillations and Network models of thalamocortical oscillations). Models can also be used to understand the genesis of pathological behavior such as epileptic seizures (see Network models of epileptic discharges). Here again, a tight relation with experimental data is needed.

A lot of attention has been focused recently on the population level modeling of large cortical networks. To do this, one needs to design population level models, using mean-field techniques (see Mean-field models of neuronal populations). This type of model is appropriate to investigate large scales, such as for example the propagating waves seen over millimeter distances in primary visual cortex, or slow-wave dynamics over centimeter distances in the whole human brain. The mean-field models can integrate biophysical features like the synaptic conductances, spike-frequency adaptation, the different cell types and their excitability, and even the heterogeneity of neurons in cortex. It can also include the differential gain of excitatory and inhibitory neurons, and its emergent properties at the mesoscopic or macroscopic scale.

Finally, another aspect of computational neuroscience is to directly provide methods to analyze experimental data. Single- or multi-electrode recordings often reveal complex behavior which may not be easy to analyze. Such complex signals can be analyzed in many different ways with the help of theoretical approaches (see Spatiotemporal analysis of electrophysiological data). In some cases, the theory can help analyzing complex, apparently random signals. This is the case for intracellular recordings of “synaptic noise”, from which many useful information can be extracted (see Stochastic analysis of synaptic noise).

These different approaches have been summarized in the following review papers by Destexhe’s group

Destexhe, A. Intracellular and computational evidence for a dominant role of internal network activity in cortical computations. Current Opinion in Neurobiology 21: 717-725, 2011. Abstract, DOI: 10.1016/j.conb.2011.06.002 Destexhe, A., Hughes, S., Rudolph, M. and Crunelli, V. Are corticothalamic ‘up’ states fragments of wakefulness? Trends in Neurosciences 30: 334-342, 2007. Abstract, DOI: 10.1016/j.tins.2007.04.006 Destexhe, A. and Contreras, D. Neuronal computations with stochastic network states. Science 314: 85-90, 2006. Abstract, DOI: 10.1126/science.1127241 Destexhe, A., Rudolph, M. and Paré, D. The high-conductance state of neocortical neurons in vivo. Nature Reviews Neuroscience 4: 739-751, 2003. Abstract, DOI: 10.1038/nrn1198 Destexhe, A. and Marder, E. Plasticity in single neuron and circuit computations. Nature 431: 789-795, 2004. Abstract, DOI: 10.1038/nature03011 Destexhe, A. and Sejnowski, T.J. Interactions between membrane conductances underlying thalamocortical slow-wave oscillations. Physiological Reviews 83: 1401-1453, 2003. Abstract, DOI: 10.1152/physrev.00012.2003

See also the Research Grants page for more details about current funding and on-going research projects, as well as possible PhD or postdoc opportunities.

Read more: Research themes of the laboratory and overview of publications.

[/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”DEMOS” style=”font-size:7px;”] Demos et code source des programmes de simulation qui ont généré certaines des figures des articles publiés. Ces demos sont associées au simulateur NEURON (accès public), PYTHON ou MATLAB. Elles peuvent être utilisées comme tutorials pour apprendre à utiliser NEURON, comme outil didactique, ou comme outil d’enseignement.
Database of NEURON, PYTHON and MATLAB codes, demos and tutorials

Schematic diagram of the kinetic schemes used for modeling ion channels and synaptic transmission. Different processes essential for modeling neuronal behavior can be described by similar type of equations. Voltage dependence, transmitter release, binding and gating of receptors, second messenger action, and neuromodulation can be all described by the same kinetic formalism (see Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism, Journal of Computational Neuroscience 1: 195-230, 1994).

NEURON demos
The first part of this database is a series of NEURON demo programs related to various cellular and network models that were developed in the laboratory. Each demo reproduces figures of articles published in the literature, in which the models are described in detail, as well as the biological background. Some of these models also appear in the ModelDB database at Yale University. Note: the models described below were simulated using the NEURON simulator written by Michael Hines. The simulations will run straightforwardly provided the Interviews version of NEURON is installed properly. NEURON is publically available on internet via (see the NEURON homepage). For more informations about how to get NEURON and how to install it, please refer to the NEURON home page, or to Michael Hines directly. These demos can be used by anyone interested – the only condition we ask is to give appropriate citation to the original paper(s).
PYTHON demos
The second part of this database consists of PYTHON demos of some of the models and analysis procedures developed in the laboratory. PYTHON is a publically-available package in the standard LINUX distribution and is also available for Windows and Mac. These demos can be used by anyone interested – the only condition we ask is to give appropriate citation to the original paper(s).
MATLAB demos
The third part of this database consists of MATLAB demos of some of the analysis procedures developed in the laboratory. MATLAB is a commercial software produced by Mathworks and which is available for LINUX, Windows and Mac. These demos can be used by anyone interested – the only condition we ask is to give appropriate citation to the original paper(s).
Various Utilities
The third part of this database is a series of utilities of general interest, some of which were developed in the laboratory.
  • Generation of MPEG, AVI or GIF animations from NEURON (zip format)
    The package illustrates how to create animations from NEURON. The example taken generates MPEG or GIF animations of the spatial distribution of membrane potential during bursting in a model of thalamic reticular neuron, relative to the paper: Destexhe, A., Contreras, D., Steriade, M., Sejnowski, T.J. and Huguenard, J.R. In vivo, in vitro and computational analysis of dendritic calcium currents in thalamic reticular neurons. Journal of Neuroscience 16: 169-185, 1996 in which all biological/modeling details are given. The demo is for LINUX (works with Ubuntu 12.4), and requires several packages to be installed. The principle is to generate a series of GIF frames, and then build a movie file from these frames. Please see the README file for a description of the procedure.
  • Utility to collapse a dendritic tree into three equivalent compartments using NEURON (zip format)
    This demo program illustrates how to create a reduced model of a complex morphology using NEURON. The program uses a principle of conservation of the axial resistance. The collapse is made such as the collapsed dendritic structure preserves the axial resistance of the original structure. The algorithm works by merging successive pairs of dendritic branches into an equivalent branch (a branch that preserves the axial resistance of the two original branches). This merging of branches can be done according to different methods selectable in the present code (see README for details). This program has been used in the following article: Destexhe, A., Neubig, M., Ulrich, D. and Huguenard, J.R. Dendritic low-threshold calcium currents in thalamic relay cells. Journal of Neuroscience 18: 3574-3588, 1998 in which details of the method are given. More instructions are provided in a README file.
    This program translates digitized morphological descriptions of a neuron into files which can be used directly by NEURON. NTSCABLE was originally written by J.C. Wathey at the Salk Institute, and was intended to convert data files in the syntax of the Neuron Tracing System (Eutectic Electronics) into CABLE format, the predecessor of NEURON (hence the name “ntscable”). The program is now compatible with NEURON and can convert data files generated by various digitizing systems, including EUTECTIC, Douglas (2D and 3D), Nevin and NEUROLUCDIA (Microbrightfield) format for the last version (NTSCABLE 2.01). This program is public domain, works straightforwardly on UNIX or LINUX workstations and there is a relatively detailed documentation available. To access the documentation on NTSCABLE, click here and to get the last version of this package including code sources, click here.
    SCoP is a general tool for solving different types of mathematical problems and is the heart of the NEURON simulator. The NMODL language is based on SCoP, and all SCoP functions and features can be used within NMODL. SCoP features include the ability to solve differential equations, kinetic equations (or diagrams), partial differential equations, algebraic equations and more. There are many utility functions such as curve fitting, probability functions, random number generation, etc. The inclusion of SCoP is one of the features that make NEURON particularly powerful — it can solve problems that go beyond the strict framework of membrane equations (for example diffusion of compounds, etc). Description of the SCoP language (language description, all utility functions are described here) NMODL Language (1991) (please see the NEURON website for more recent versions) Unit checking utility for NMODL (please see the NEURON web site for more recent versions)

[/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”ANIMATIONS” style=”font-size:7px;”] Animations de modèles développés au laboratoire. Ces animations constituent un excellent complément aux articles publiés, et dans certains cas, elles illustrent la dynamique du système bien plus clairement que les figures d’articles traditionnels !

Database of Computer-generated Animations

This database of mpeg and avi movies and other files allows one to visualize the models and experimental data described in the articles. The movies are complementary as they describe important aspects of the dynamical behavior not apparent in static figures; they are most of the time directly related to figures of the published papers. In some cases, demo packages for simulations are also available and reproduce figures of the corresponding papers. Please refer to the database of publications for all biological details. These animations can be used by anyone interested – the only condition we ask is to give appropriate citation to the original paper(s).
These computer-generated animations should be playable on any recent LINUX distribution, or Windows (in principle, they do not require any nonstandard codec or other application to be played).
Please cite the original papers if you use these movies.
[/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”MORHOLOGIES” style=”font-size:7px;”] Morphologies cellulaires de neurones thalamiques et corticaux, pour être utilisées sous NEURON . Les articles originaux où ces cellules ont été décrites sont inclus également.
Database of Cellular Morphologies
This database provides 3-dim reconstructions of thalamic and neocortical neurons. These cells were reconstructed by Alain Destexhe from 80-micron serial sections using a computerized tracing system (Eutectic Electronics, Raleigh, NC) kindly provided by D. Amaral (University of California, Davis, CA), as well as a Neurolucida (Microbrightfield, Williston, VT) tracing system in Destexhe’s lab. The dendritic morphology and diameters were reconstructed in 3-dim using a X 100 objective and correction for tissue shrinkage was included, leading to a theoretical accuracy of 0.1 microns on dendritic diameters. The morphology and the modeling of these cells is described in detail in the attached references given below for each cell.

The NEURON geometry of these cells are also available. Anyone is welcome to use these geometries in models. If you use them, we kindly ask you to cite the original paper in which these cells were published. The references are attached below, and copies of the papers are available in the present site.

[/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”MUSIQUE NEURONALE” style=”font-size:7px;”] Mélodies crées à partir d’enregistrements de neurones du cortex cérébral. Elles sont comparées à des mélodies obtenues à partir de processus stochastiques de Poisson.
Neuronal Music
This page provides audio files where neuronal activity is “visualized” by creating music. The music is created from neuronal spikes recorded extracellularly with multiple electrodes, either from the parietal cortex of awake and naturally-sleeping cats (taken from Destexhe et al., J. Neurosci, 1999), or from the temporal cortex of awake and naturally sleeping human subjects (taken from Peyrache et al., Proc. Natl. Acad. Sci. USA, 2012). We have made two types of neuronal music, a first “simple” type, consists of a direct translation of spike sequences into note sequences, as detailed in the Neuronal Melodies page. This type of musical animation is available for cat parietal cortex and human temporal cortex. A second attempt was made more recenty, in collaboration with Luc Foubert (CNRS). In the Spikiss Project, we have created more elaborated music based on associations with multiple and sophisticated sounds. We also explained step by step how the conversion to music was made. A third direction, is the myWaves Project. Here, we have created elaborated music based on electro-encephalogram (EEG) recordings of sleeping subjects. This makes use of a new technique called NeuroAcoustic Transduction. A startup company was created, myWaves Technologies

We are presently continuing to work on the Spikiss and myWaves projects, using respectively spike and EEG recordings

. [/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”LIENS” style=”font-size:7px;”] Liens à divers sites de Neurosciences Computationnelles et Neuroinformatique.
Computational Neuroscience & Neuroinformatics Links
For a recent list of links, see the Computational Neuroscience page in Wikipedia
Conferences and Courses
Computational Neuroscience Resources
Computational Neuroscience Projects and Consortia
List of Computational Neuroscience Laboratories

See also the ICN department of the NeuroPSI Institute (Neurosciences Intégratives & Computationnelles — Integrative & Computational Neuroscience)

[/su_spoiler] [/su_accordion]
[su_accordion] [su_spoiler class=”my-custom-spoiler” open=”no” title=”JCNS/SSNS” style=”font-size:7px;”] The Journal of Computational Neuroscience (Éditeurs-en-Chef: Alain Destexhe et Jonathan Victor) et Springer Series in Computational Neuroscience (Éditeurs: Alain Destexhe et Romain Brette)
The Journal of Computational Neuroscience
From neurons to behavior: A journal at the interface between experimental and theoretical neuroscience
The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily, theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience are also welcomed. It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience. Published by Springer Science Business Media B.V., ISSN: 0929-5313 (paper) and 1573-6873 (online).

Springer Series in Computational Neuroscience
Editors: Alain Destexhe and Romain Brette

The Springer Series in Computational Neuroscience gathers monographs and edited volumes on all aspects of computational neuroscience, including theoretical and mathematical neuroscience, biophysics of the brain, models of neurons and neural networks, and methods of data analysis (e.g. information theory). The editors welcome suggestions and projects for inclusion in the series.

[/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”PERSONNEL” style=”font-size:7px;”] Liste des membres du laboratoire, permanents, postdocs et étudiants.

Present lab members

  • Jules Bouté (PhD student)
  • Mallory Carlu (Postdoc Researcher)
  • Damien Depannemaeker (Postdoc Researcher)
  • Alain Destexhe (CNRS Research director)
  • Anton Filipchuk (Postdoc Researcher; co-supervised with Brice Bathellier, ICN)
  • Alexis Garcia (Postdoc Researcher)
  • Jennifer Goldman (Postdoc Researcher)
  • Tomasz Gorski (Postdoc Researcher; co-supervised with Thierry Bal, ICN)
  • Domenico Guarino (Postdoc Researcher)
  • Sabir Jacquir (Professor at Paris-Saclay University)
  • Mathias Peuvrier (PhD student; co-supervised with P. Salin, Univ. Lyon)
  • Amelie Soler (Programming Engineer)
  • Eduarda Susin (PhD student)
  • Federico Tesler (Postdoc Researcher)
  • Nuria Tort-Colet (Postdoc Researcher)

Administrative and technical staff

  • Yasaman Afshar (EITN secretary)
  • Tom Messier (EITN systems manager)
  • Julie Mongard (EITN communication manager)

Previous lab members

  • Matteo diVolo (Postdoc Researcher)
  • Luc Foubert (Postdoc Researcher)
  • Melissa Dali (Postdoc Researcher)
  • Tony Delobel (Systems Manager)
  • Diego Contreras (Visitor, University of Pennsylvania)
  • Tara Babaie (Visitor, University of Sydney)
  • Miwa Fukino (Visitor, Panasonic)
  • Michelle Rudolph-Lilith (CNRS Researcher)
  • Kuba Orlowski (PhD student; co-supervised with A. Chaillet, SupElec)
  • Maja Telenczuk (Postdoc Researcher)
  • Katherine Fregnac (Project Manager)
  • Audrey LeReun (Scientific Comm Assistant)
  • Morgane Bourdonnais (Scientific Comm Assistant); now working at the ANR
  • Tammy Bodin (EITN secretary)
  • Remi Girard (Systems Manager)
  • Bartosz Telenczuk (Postdoc Researcher); now freelance researcher
  • Trang-Anh Nghiem (Master student; now PhD student)
  • Cristiano Capone (Postdoc Researcher); now postdoc in Rome
  • Anna Bulanova (Postdoc Researcher)
  • Zahara Girones (Postdoc Researcher); now postdoc in Eugene (Oregon)
  • Romain Cazé (Postdoc Researcher)
  • Vicente Medel (Master student)
  • Alberto Romagnoni (Postdoc Researcher)
  • Davide Forcella (Postdoc Researcher)
  • Yann Zerlaut (PhD student); now postdoc at the Italian Institute of Technology (Genova)
  • Francesca Barbieri (Postdoc Researcher); now postdoc at Paris Descartes University
  • Claude Bedard (CNRS Researcher); now retired
  • Marco Brigham (PhD student); now postdoc at Polytechique
  • Mathieu Galtier (Postdoc Researcher; now working in a private company)
  • Lyle Muller (PhD student; now CNRS researcher in Marseille
  • Sarah Goethals (Master student, now PhD student)
  • Nima Dehghani (PhD student, now Postdoc at Harvard University, USA)
  • Adrien Peyrache (Postdoc Researcher), now Assistant Professor at McGill University (Canada)
  • Sami El Boustani (PhD student, now Assistant Professor at Geneva University (Switzerland)
  • Pepe Alcami (Master student, now PhD student)
  • Romain Brette (Postdoc Researcher, now Faculty member at INSERM, France)
  • Mathieu Dubois (Master student, now PhD student)
  • Jose Gomez (Postdoc Researcher), now Professor at the University of La Laguna (Spain)
  • Alexandre Guerrini (Master student, now PhD student)
  • Martin Pospischil (PhD student, now Research Engineer in Heidelberg, Germany)
  • Seraphim Rodrigues (Postdoc Researcher, now Assistant Professor at Bilbao University (Spain)
  • Quan Zou (PhD student, now Postdoc Researcher at University of Nevada Reno, USA)
[/su_spoiler] [su_spoiler class=”my-custom-spoiler” open=”no” title=”PUBLICATIONS” style=”font-size:7px;”] Publications du laboratoire. Informations à propos des travaux publiés ou sous presse, résumés des articles (abstracts) et copies complètes des articles avec figures.
Multicompartment model of a reconstructed neuron from the reticular nucleus of the thalamus of a rat. The figure shows hree snapshots of activity during a burst of spikes generated by this type of cell. The distribution of membrane potential is indicated by colors: the range from -80 to +30 mV is coded from deep blue to yellow. Calcium currents located in the dendrites have a determinant influence on the properties of these cells in vitro. Dendritic calcium currents are also essential to account for the properties of these cells seen in vivo (from: Destexhe et al., In vivo, in vitro and computational analysis of dendritic calcium currents in thalamic reticular neurons, Journal of Neuroscience 16: 169-185, 1996).

See the publications database

The references of the articles and abstracts available in this database are listed in an approximate chronological order. This work was done successively at the University of Brussels (Belgium), the Salk Institute (USA), Laval University (Canada) and at CNRS (France). The topics range from biophysical models of synaptic transmission at the main receptor types (AMPA, NMDA, GABAA, GABAB and neuromodulators), single-cell models of the electrophysiological properties of central neurons (thalamus and neocortex), as well as network models (thalamic and cortical networks). [/su_spoiler] [/su_accordion]