Posts about sciblog (old posts, page 11)

2013-03-06 setting some conventions common in Bibdesk (to work with bibtex, citeUlike)

  • I found this set useful to collaborate:
    • citekey  %a1%y%u0 
    • rangement semi-automatique papiers:  %f{Cite Key}%n0%e 
    • Topic = use citekey of related papers
    • Comment (instead annote) to put... comments (as annote gets printed in the manuscript that would use the entry)
  • to do that automatically, one may use this tricks:
    defaults write edu.ucsd.cs.mmccrack.bibdesk "Cite Key Format" -string "%a1%y%u0"¬
    defaults write edu.ucsd.cs.mmccrack.bibdesk BDSKLocalFileFormatKey -string "%f{Cite Key}%n0%e"
  • this is included in this script @ https://github.com/laurentperrinet/dotfiles/blob/master/init/install_tex_live.sh

2013-02-04 WP5 Year 2 report: contribution of CNRS-INT (Institut de Neurosciences de la Timone)

During the first year of BrainScaleS, we have concentrated on disseminating our work on the role of motion-based prediction in motion detection. This led to a publication on the hypothesis that this prior expectation may explain some phenomena explained otherwise by complex arrangements of mechanisms, namely that motion-based prediction is sufficient to solve the aperture problem (Perrinet and Masson, 2012). During the second year, we extended this hypothesis to other types of problems linked to the detection of motion. In particular, we focused on the case were the stimulus is transiently and unexpectedly blanked, a physiologically very relevant constraint occurring for instances during blinks of the eye. For this, we have used the same theoretical framework based on a Bayesian formulation and implemented using a particle filtering scheme, but used a different experimental protocol inspired by behavioral experiments conducted in the laboratory by CNRS-INT (Bogadhi, 2012). This is an important aspect as it allows to better understand the dynamics of the neural representation without sensory input and more generally to understand the interaction of the sensory flow with an internal neural representation of the environment.

Role of motion-based prediction in motion extrapolation
Role of motion-based prediction in motion extrapolation. We show here the results of simulation of the motion-based prediction compared to velocity prediction (no position prediction). These models were tested for a dot moving in a straight trajectory but blanked (as given by the vertical bars) whether at the early stage (top panel) or in the late phase (bottom panel). This shows that compared to a control (condition with no blank), the system simply resumes the convergence to the veridical position at reappearance of the dot. In motion-based prediction, the systems catches up the trajectory and recovers more quickly to the response with no blank.

Our results indicate that motion-based prediction is sufficient to predict eye responses during the blank and ---more importantly--- the dynamics of eye movements at the reappearance of the object. We compared simulations of the motion-based predictive framework to a dot moving in a straight trajectory which is transiently blanked, with a framework where prediction is limited to the velocity domain but is not anisotropically transported also in the position domain. This comparison allowed to show that at the reappearance of the object, instead of just resuming, the estimation of the position and velocity in the motion-based prediction framework catches-up the error that may have accumulated during the blank (see Figure). We have put in evidence that this phenomenon is only present when the system converged to a "tracking state", a phase transition that we first saw in our first study (Perrinet and Masson, 2012) and that we studied systematically here. Furthermore, we give some predictions as how the oculomotor response should respond to the same protocol when visual input is perturbed by noise, an experiment that has still not been performed behaviorally, and that could confirm the validity of our probabilistic framework. These results have been submitted for publication (Khoei, Masson and Perrinet).

From this novel step, we wish to further study the role of prediction on focusing on the neural implementation of these processes. Indeed, the framework that we used so far used an abstract, probabilistic framework. However, it is known to map well to a neural architecture such as those developed in BrainScaleS at the modeling and hardware levels. Such a venture was initiated in collaboration between CNRS-INT and KTH by Bernhard Kaplan and we could give a sufficient large-scale network of spiking neurons that could efficiently implement such algorithms. Our plan is to resume this work in more generic conditions. One objective is to apply it to different modalities,for instance to the somatosensory system (collaboration with Dan Shulz, CNRS-UNIC). Also, we wish to implement a model which is specifically more realistically accounting for the properties of the primary visual cortex of primates and the interaction this area may have with higher order areas. A post-doctoral student was selected in year 2 to work on that issue in Years 3 and 4. The ultimate goal of this work will be to have a pyNN-compatible network that implements a realistic model of motion detection. This network will be tested in light of the synthetic textures that we have generated (Sanz et al. 2012, see WP4 task 1) and that we recently used to disentangle the different read-outs that may be used by perception or action (Simoncini et al., 2012). The use of neuromorphic hardware will then be crucial to explore the configuration space of such large-scale networks implementing motion detection.

  • Laurent U. Perrinet and Guillaume S. Masson. Motion-based prediction is sufficient to solve the aperture problem. Neural Computation, 24(10):2726--50, 2012
  • Mina A. Khoei, Guillaume S. Masson and Laurent U. Perrinet. Role of motion-based prediction in motion extrapolation. Submitted.
  • Paula S. Leon, Ivo Vanzetta, Guillaume S. Masson and Laurent U. Perrinet. Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception Journal of Neurophysiology, 107(11):3217--3226, 2012
  • Claudio Simoncini, Laurent U. Perrinet, Anna Montagnini, Pascal Mamassian and Guillaume S. Masson. More is not always better: dissociation between perception and action explained by adaptive gain control Nature Neuroscience, 2012

2013-02-02 How To Change Your Time Machine Backup Interval

tl;dr  sudo /usr/libexec/PlistBuddy -c 'set  :LaunchEvents:com.apple.time:"Backup Interval":Interval 86400' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist 

method 1 : vim (or any editor)

  • open the file for edition
    sudo vim /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
  • replace 36000 (one hour) by 86400 (one day), then quit:
    :%s/3600/86400/g
    :wq!

method 2 : plistbuddy

  • you can make it in one line:
    sudo /usr/libexec/PlistBuddy -c 'set  :LaunchEvents:com.apple.time:"Backup Interval":Interval 86400' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
  • this method use the PlistBuddy method to read / write the file. this utility can be used interactively
    sudo /usr/libexec/PlistBuddy  /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
  • but also directly:
    sudo /usr/libexec/PlistBuddy -c 'print  ' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
    sudo /usr/libexec/PlistBuddy -c 'print  :LaunchEvents:com.apple.time ' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
    sudo /usr/libexec/PlistBuddy -c 'print  :LaunchEvents:com.apple.time:"Backup Interval" ' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
    sudo /usr/libexec/PlistBuddy -c 'print  :LaunchEvents:com.apple.time:"Backup Interval":Interval ' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist
    sudo /usr/libexec/PlistBuddy -c 'set  :LaunchEvents:com.apple.time:"Backup Interval":Interval 3600' /System/Library/LaunchDaemons/com.apple.backupd-auto.plist

finally

  • reboot.

2013-01-16 WP4 report : NeuroTools support for the synthesis of random textured dynamical stimuli

In the context of BrainScales, we have developed a library to synthesize stimuli targeted at the characterization of motion perception. This process took the following steps:

  • creation of the library using python and linked with the development of NeuroTools,
  • documentation of this library along with a mathematical description, published in the Journal of Neurophysiology, while this stimuli were at the basis of a paper published in Nature Neuroscience (both acknowledging BrainScaleS)
  • dissemination of this tool by creating a dedicated webpage associated to the "neuralensemble organization" which also host neo and pyNN.

These steps were recently described in deliverable D4-1.1: https://brainscales.kip.uni-heidelberg.de/jss/FileStore/dI_1548/BrainScaleS_DeliverableD4-1.1.pdf (requires authentification).

2012-11-28 setting the umask to define default permissions for created files

  • the parameter to use is umask https://en.wikipedia.org/wiki/Umask
  • on a cluster I get
    $ umask
    0022
    $ touch test
    $ ls -l test
    -rw-r--r-- 1 perrinet.l invibe 0 Nov 28 11:32 test
    $ umask u=rwx,g=rwx,o=
    $ touch test2
    $ ls -l test2
    -rw-rw---- 1 perrinet.l invibe 0 Nov 28 11:33 test2
  • so I did:
    perrinet.l@frioul:~$ vim .profile
    
    # ~/.profile: executed by the command interpreter for login shells.
    # This file is not read by bash(1), if ~/.bash_profile or ~/.bash_login
    # exists.
    # see /usr/share/doc/bash/examples/startup-files for examples.
    # the files are located in the bash-doc package.
    
    # the default umask is set in /etc/profile; for setting the umask
    # for ssh logins, install and configure the libpam-umask package.
    #umask 022
    # https://en.wikipedia.org/wiki/Umask
    umask u=rwx,g=rwx,o=
    
    # if running bash
    if [ -n "$BASH_VERSION" ]; then
        # include .bashrc if it exists
        if [ -f "$HOME/.bashrc" ]; then
            . "$HOME/.bashrc"
        fi
    fi
    
    # set PATH so it includes user's private bin if it exists
    if [ -d "$HOME/bin" ] ; then
        PATH="$HOME/bin:$PATH"
    fi
  • before loging out I have
    perrinet.l@frioul:~$ umask
    0022
  • and after
    perrinet.l@frioul:~$ logout
    Connection to frioul.int.univ-amu.fr closed.
    [11:36:49]int-users-4-058: ~/Desktop/Dropbox/TROPIQUE/demos/12-11-11_projection $ frioul
    
     ######  #####      #     ####   #    #  #
     #       #    #     #    #    #  #    #  #
     #####   #    #     #    #    #  #    #  #
     #       #####      #    #    #  #    #  #
     #       #   #      #    #    #  #    #  #
     #       #    #     #     ####    ####   ######
    
    perrinet.l@frioul:~$ umask
    0007
    perrinet.l@frioul:~$ touch test
    perrinet.l@frioul:~$ ls -l test
    -rw-rw---- 1 perrinet.l invibe 0 Nov 28 11:37 test
    perrinet.l@frioul:~$
  • Done!

2012-11-07 craac 2012

https://crac.dsi.cnrs.fr/image/logo_cnrs.gif Compte rendu annuel d'activité des chercheurs du CNRSAnnée 2011 - 2012

Identité

Nom (nom de jeune fille)

PERRINET

Prénom

Laurent

Date de naissance

23/02/1973

Grade

CR1

N° d'agent

00024609

Téléphone

04 91 32 40 44

Télécopie

04 91 32 40 56

Adresse électronique

laurent.perrinet@univ-amu.fr

Section(s) du Comité National

7

Département scientifique

Institut des sciences biologiques

Délégation régionale

Provence et Corse

Affectation

Intitulé de l'unité

Institut des Neurosciences de la Timone

Code unité

UMR7289

Directeur

Guillaume MASSON

Adresse électronique du directeur

guillaume.masson@univ-amu.fr

Adresse

INT - 27 boulevard Jean Moulin

13385 MARSEILLE CEDEX 05

France

Téléphone

04 91 32 40 10

Télécopie

Délégation

Provence et Corse

Site Web

Distinction(s)

Qualification

Habilitation à diriger des recherches

non

Doctorat d'Etat

non

Doctorat

oui

Année d'obtention

2003

Qualification "Maître de conférences"

non

Qualification "Professeur"

non

Période d'inactivité

Mobilité(s) antérieure(s)

Autre demande Au sein de mission longue Du 01/11/2010 Au 31/01/2012

Activités de recherche développées

Rattachement à(aux) activité(s) de recherche de l'unité UMR7289

Intitulé d'activité Date fin du rattachement
Inférence et Comportement visuel - InViBe

Mots clés des sections/CID du Comité national

Section 26 : Modélisation des processus cognitifs et neurosciences computationnelles

Points forts de vos activités de recherche et /ou informations complémentaires

Mon objectif de recherche est d’étendre la compréhension des modèles des facultés cognitives sous la forme de réseaux de neurones impulsionnels qui réalisent des algorithmes de perception visuelle. En effet, les brèves impulsions du potentiel de membrane se propageant au fil des neurones sont une caractéristique universelle des systèmes nerveux et permettent de construire des modèles événementiels efficaces de traitement dynamique de l’information. Dans un but fonctionnel, je désire notamment implanter dans ces modèles des stratégies d’inférence grâce à des mécanismes d’apprentissage auto-organisés fixant les relations spatio-temporelles entre les neurones. Dans le cadre du projet BrainScaleS, nous envisageons la création de nouveaux types d'algorithmes basés sur ces recherches.

Publication(s), parue(s) ou sous presse, dans des revues à comité de lecture

Référence
Amarender Bogadhi, Anna Montagnini, Pascal Mamassian, Laurent U. Perrinet, and Guillaume S. Masson. Pursuing motion illusions: a realistic oculomotor framework for bayesian inference. Vision Research, 51(8):867-80, 2011.
Claudio Simoncini, Laurent U. Perrinet, Anna Montagnini, Pascal Mamassian, Guillaume S. Masson. More is not always better: dissociation between perception and action explained by adaptive gain control. Nature Neuroscience, 2012.
Guillaume S. Masson and Laurent U. Perrinet. The behavioral receptive field underlying motion integration for primate tracking eye movements. Neuroscience and biobehavioral reviews, March 2011. http://www.ncbi.nlm.nih.gov/pubmed/21421006
Guillaume S. Masson, Laurent U. Perrinet. The behavioral receptive field underlying motion integration for primate tracking eye movements. Neuroscience and biobehavioral reviews, 2012.
Karl Friston, Rick A. Adams, Laurent Perrinet, Michael Breakspear. Perceptions as Hypotheses: Saccades as Experiments, URL . Frontiers in Psychology, 3, 2012
Laurent Perrinet. Qui créera le premier calculateur intelligent? Interstices, 2011. http://interstices.info/jcms/i_62190/qui-creera-le-premier-ordinateur-intelligent
Laurent U Perrinet et al. Motion-based prediction is sufficient to solve the aperture problem. Neural Computation 2012 24 10 2726-50
Laurent U. Perrinet, Rick A. Adams, Karl Friston. Active Inference, tracking eye movements and oculomotor delays. Submitted.
  1. Voges, L. Perrinet. Complex dynamics in recurrent cortical networks based on spatially realistic connectivities . Frontiers in Computational Neuroscience, 6, 2012
Paula Sanz Leon et al. Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. Journal of Neurophysiology 2012 107 11 3217-26
Rick A. Adams, Laurent U. Perrinet, Karl Friston. Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia, URL . PLoS ONE, 7(10):e47502+, 2012

Publication(s), parue(s) ou sous presse, dans des revues sans comité de lecture

Ouvrage(s) ou chapitre(s) d'ouvrage(s), paru(s) ou sous presse

Participation à des manifestations scientifiques

Manifestation

Atelier Neurosciences Computationnelles, 2-3 Juillet 2011

Type de manifestation

Workshop ( national )

Lieu

Khemisset, Maroc ( Maroc )

Durée

2 (jour(s))

Intervention(s)

http://www.incm.cnrs-mrs.fr/LaurentPerrinet/Presentations/11-07-02_NeuroMedTalk

Manifestation

BCCN

Type de manifestation

Conférence ( national )

Lieu

Heidelberg ( Allemagne )

Durée

3 (jour(s))

Intervention(s)

Nicole Voges and Laurent Perrinet. Variations of horizontal cortical
network structures and their corresponding state space dynamics. 2011.
par Voges
    Affiche/poster

Manifestation

CNS*2011

Type de manifestation

Conférence ( international )

Lieu

Berlin ( Allemagne )

Durée

5 (jour(s))

Intervention(s)

Mina A. Khoei, Laurent Perrinet, and Guillaume S. Masson. Motion-based
predictive coding is sufficient to solve the aperture problem. par Khoei
    Affiche/poster

Manifestation

ECVP

Type de manifestation

Conférence ( international )

Lieu

Stockholm ( Suède )

Durée

5 (jour(s))

Intervention(s)

Mina A. Khoei, Laurent U. Perrinet, Amarender R. Bogadhi, Anna
Montagnini, and Guillaume S. Masson. Role of motion inertia in dynamic
motion integration for smooth pursuit. In Ricardo Carmona and al. par
Khoei
    Affiche/poster

Manifestation

ERMITES 2011 Décomposition Parcimonieuse, Abstraction et Structuration pour l'Analyse de Scènes Complexes

Type de manifestation

Workshop ( international )

Lieu

Porquerolles ( FRANCE )

Durée

3 (jour(s))

Intervention(s)

Edge statistics in natural images versus laboratory animal
environments: implications for understanding lateral connectivity in V1
par Perrinet
    Communication orale

Manifestation

From Mathematical Image Analysis to Neurogeometry of the Brain http://www.incm.cnrs-mrs.fr/LaurentPerrinet/Presentations/10-12-17_TaucTalk

Type de manifestation

Conférence ( international )

Lieu

Paris ( FRANCE )

Durée

2 (jour(s))

Intervention(s)

Mina Aliakbari Khoei, Laurent Perrinet, and Guillaume S. Masson.
Dynamical emergence of a neural solution for motion integration. In
Proceedings of Tauc, 2010 par Khoei
    Affiche/poster

Manifestation

Société des Neurosciences

Type de manifestation

Conférence ( national )

Lieu

Marseille ( FRANCE )

Durée

4 (jour(s))

Intervention(s)

Mina A. Khoei, Laurent Perrinet, and Guillaume S. Masson. Dynamical
solution for aperture problem using motion-based predictive coding. In
10th meeting of the Société des Neurosciences par Khoei
    Affiche/poster

Manifestation

Society for Neuroscience - http://invibe.net/LaurentPerrinet/Publications/Perrinet11sfn

Type de manifestation

Conférence ( international )

Lieu

Washington ( Etats-Unis )

Durée

6 (jour(s))

Intervention(s)

Laurent Perrinet, David Fitzpatrick, and James A. Bednar. Edge
statistics in natural images versus laboratory animal environments:
implications for understanding lateral connectivity in V1. par perrinet
    Communication orale

Manifestation

Using the ESS + Neuromorphic hardware Workshop, 5th Oktober, 2011

Type de manifestation

Workshop ( international )

Lieu

TU Dresden, Germany, 2011 ( Allemagne )

Durée

4 (jour(s))

Intervention(s)

Demo 1, Task4: Implementation of models showing emergence of cortical
fields and maps,
http://invibe.net/LaurentPerrinet/Presentations/11-10-05_BrainScalesESS
par Laurent Perrinet
    Communication orale

Manifestation

Vision Science Society

Type de manifestation

Conférence ( international )

Lieu

Naples ( Etats-Unis )

Durée

6 (jour(s))

Intervention(s)

Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception. par Claudio Simoncini, Anna Montagnini, Laurent U. Perrinet, Guillaume S. Masson.

Activité éditoriale

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Revues

Informations complémentaires

IEEE TIP

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Revues

Informations complémentaires

Evolving Systems

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Autres

Informations complémentaires

Neural Computation

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Informations complémentaires

Journal of Physiology (Paris)

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Informations complémentaires

Conférence NeuroComp 2011

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Informations complémentaires

Neurocomputing

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Revues

Informations complémentaires

PLoS Computational Biology

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Revues

Informations complémentaires

Neural Networks

Type d'intervention

Rapporteur/Relecteur dans des revues

Type de document

Revues

Informations complémentaires

Circuits, Systems and Signal Processing

Séjour(s) dans d'autres laboratoires

Objet

Collaboration avec Karl Friston sur les modèles de Free energy.

Organisme

University College of London

Pays

Royaume-Uni

Unité

Wellcome Trust Centre for Neuroimaging / FIL

Durée annuelle

365 (j)

Mission(s) sur le terrain

Formation personnelle

Collaborations

Organisme partenaire

INRIA

Pays

FRANCE ( Europe )

Unité partenaire

Odyssee

Intitulé

Sophia

Cadre de la coopération

AUTRE - FACETS

Nature de l'activité

Organisme partenaire University Freiburg
Pays Allemagne ( Europe )
Unité partenaire BrainScaleS
Intitulé BrainScaleS
Cadre de la coopération AUTRE - BrainScaleS
Nature de l'activité Participation à un réseau

Organisme partenaire

University Ulm

Pays

Allemagne ( Europe )

Unité partenaire

NeuroInformatics

Intitulé

Perception of Motion

Cadre de la coopération

Nature de l'activité

Organisme partenaire Wellcome Trust Centre for Neuroimaging
Pays Royaume-Uni ( Europe )
Unité partenaire Karl Friston
Intitulé FreeMove, a free-energy approach to eye movements
Cadre de la coopération AUTRE - projet de MAD accepté scientifiquement, refusé administrativement. Remplacé par une mission longue durée.
Nature de l'activité mission longue durée

Encadrement et animation scientifique

Chercheurs

CNRS

Enseignement supérieur

Autres EPST

Autres

Total

0

0

0

1
    Thésarde en CDD sur contrat FACETS-ITN

1

Doctorants

Thèse

Doctorants étrangers

Doctorants ayant soutenu une thèse

Total

Direction

Codirection

1

2

1

0

3

IT

Stagiaires

IT CNRS

IT non CNRS

Total

Master 2

Licence, master 1

Ecole d'ingénieur

IUT

Autre

Total

0

0

0

2

0

0

0

1

3

Animation scientifique
* Projet artistique en collaboration avec Etienne Rey de la friche Belle de Mai dans le cadre de Marseille Provence capitale européenne de la culture 2013 * écriture d'articles de vulgarisation pour interstices (INRIA), docSciences (CRDP) et de traduction en arabe pour le projet NeuroMed * Participation au réseau NeuroComp.fr * Animation d'un réseau marseillais des NeuroComp * Enseignement au master Bio-Phy à Luminy

Enseignement

Valorisation et partenariat

Vulgarisation

Type d'information Intitulé Type de participation
Exposition projet "TROPIQUE", label "Marseille-Provence capitale européenne de la culture 2013" Conseil scientifique
Presse écrite Qui créera le premier calculateur intelligent? Interstices, 2011. Participation ponctuelle

Administration de la recherche

  • Management et gestion
Membre CLAS GLM de Marseille-Joseph Aiguier

2012-09-30 discover ports on MacOSX

  • the network utility GUI is useful, but you may get the same results via the command line:
$ cd /Applications/Utilities/Network\ Utility.app/Contents/Resources/
$ ./stroke nas-meduz.local 548 550
Port Scanning host: 192.168.0.5

         Open TCP Port:         548             afpovertcp
$ ./stroke shazam.dyndns.org 548 550
Port Scanning host: 82.231.23.196

         Open TCP Port:         548             afpovertcp