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inVibe

Inference in Visual Behaviours

Publications inVibe

2017



  • Chemla S., Muller L., Reynaud A., Takerkart S., Destexhe A., and Chavane F. (2017). Improving voltage-sensitive dye imaging: with a little help from computational approaches. Neurophotonics, 4: 031215.


  • Gekas N., Meso A.I., Masson G.S., and Mamassian P. (2017). A Normalization Mechanism for Estimating Visual Motion across Speeds and Scales. Current Biology, 27: 1514-1520.e3.
  • Goffart L. (2017). De la représentation cérébrale spatio-temporellement distribuée à la capture ici-et-maintenant d’un objet visuel en mouvement. Complexité / Désordre : Adaptation, Localisation, Dynamique.

  • Goffart L. (2017). Saccadic Eye Movements: Basic Neural Processes☆. Reference Module in Neuroscience and Biobehavioral Psychology.


  • Hahn G., Ponce-Alvarez A., Monier C., Benvenuti G., Kumar A., Chavane F., Deco G., and Frégnac Y. (2017). Spontaneous cortical activity is transiently poised close to criticality. PLOS Computational Biology, 13: e1005543.


  • Khoei M.A., Masson G.S., and Perrinet L.U. (2017). The Flash-Lag Effect as a Motion-Based Predictive Shift. PLOS Computational Biology, 13: e1005068.


  • Rankin J. and Chavane F. (2017). Neural field model to reconcile structure with function in primary visual cortex. PLOS Computational Biology, 13: e1005821.


  • Roux S., Gascon P., Pham P., Matonti F., and Chavane F. (2017). Clarifier l’impact fonctionnel des rétines artificielles. médecine/sciences, 33: 389-392.


  • Vidal M. (2017). Hearing flashes and seeing beeps: Timing audiovisual events. PLOS ONE, 12: e0172028.

2016



  • Bourrelly C., Quinet J., Cavanagh P., and Goffart L. (2016). Learning the trajectory of a moving visual target and evolution of its tracking in the monkey. Journal of Neurophysiology, 116: 2739-2751.


  • Chancel M., Blanchard C., Guerraz M., Montagnini A., and Kavounoudias A. (2016). Optimal visuotactile integration for velocity discrimination of self-hand movements. Journal of Neurophysiology, 116: 1522-1535.


  • Chemla S. and Chavane F. (2016). Effects of GABA kinetics on cortical population activity: computational studies and physiological confirmations. Journal of Neurophysiology, 115: 2867-2879.


  • Ego C., Bonhomme L., Orban de Xivry J.-J., Da Fonseca D., Lefèvre P., Masson G.S., and Deruelle C. (2016). Behavioral characterization of prediction and internal models in adolescents with autistic spectrum disorders. Neuropsychologia, 91: 335-345.


  • Kremkow J., Perrinet L.U., Monier C., Alonso J.-M., Aertsen A., Frégnac Y., and Masson G.S. (2016). Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1. Frontiers in Neural Circuits, 10.


  • Landelle C., Montagnini A., Madelain L., and Danion F. (2016). Eye tracking a self-moved target with complex hand-target dynamics. Journal of Neurophysiology, 116: 1859-1870.


  • Medathati N.V.K., Neumann H., Masson G.S., and Kornprobst P. (2016). Bio-inspired computer vision: Towards a synergistic approach of artificial and biological vision. Computer Vision and Image Understanding, 150: 1-30.


  • Meso A.I., Montagnini A., Bell J., and Masson G.S. (2016). Looking for symmetry: fixational eye movements are biased by image mirror symmetry. Journal of Neurophysiology, 116: 1250-1260.


  • Meso A.I., Rankin J., Faugeras O., Kornprobst P., and Masson G.S. (2016). The relative contribution of noise and adaptation to competition during tri-stable motion perception. Journal of Vision, 16: 1-24.


  • Roux S., Matonti F., Dupont F., Hoffart L., Takerkart S., Picaud S., Pham P., and Chavane F. (2016). Probing the functional impact of sub-retinal prosthesis. eLife, 5.


  • Servant M., White C., Montagnini A., and Burle B. (2016). Linking Theoretical Decision-making Mechanisms in the Simon Task with Electrophysiological Data: A Model-based Neuroscience Study in Humans. Journal of Cognitive Neuroscience, 28: 1501-1521.


  • Spotorno S., Masson G.S., and Montagnini A. (2016). Fixational saccades during grating detection and discrimination. Vision Research, 118: 105-118.


  • Taouali W., Benvenuti G., Wallisch P., Chavane F., and Perrinet L.U. (2016). Testing the odds of inherent vs. observed overdispersion in neural spike counts. Journal of Neurophysiology, 115: 434-444.

2015


  • Cristóbal G., Perrinet L.U., and Keil M.S. (2015). Biologically Inspired Computer Vision: Fundamentals and Applications. Biologically Inspired Computer Vision, 1-10.


  • Matonti F., Roux S., Denis D., Picaud S., and Chavane F. (2015). Cécité et réhabilitation visuelle. Journal Français d'Ophtalmologie, 38: 93-102.

  • Montagnini A., Perrinet L.U., and Masson G.S. (2015). Visual Motion Processing and Human Tracking Behavior. Biologically Inspired Computer Vision, 267-294.


  • Perrinet L.U. and Bednar J.A. (2015). Edge co-occurrences can account for rapid categorization of natural versus animal images. Scientific Reports, 5: 11400.

  • Perrinet L.U. (2015). Sparse Models for Computer Vision. Biologically Inspired Computer Vision, 319-346.


  • Quinet J. and Goffart L. (2015). Does the Brain Extrapolate the Position of a Transient Moving Target? Journal of Neuroscience, 35: 11780-11790.


  • Quinet J. and Goffart L. (2015). Cerebellar control of saccade dynamics: contribution of the fastigial oculomotor region. Journal of Neurophysiology, 113: 3323-3336.


  • Servant M., White C., Montagnini A., and Burle B. (2015). Using Covert Response Activation to Test Latent Assumptions of Formal Decision-Making Models in Humans. Journal of Neuroscience, 35: 10371-10385.


  • Taouali W., Goffart L., Alexandre F., and Rougier N.P. (2015). A parsimonious computational model of visual target position encoding in the superior colliculus. Biological Cybernetics, 109: 549-559.
  • Vacher J., Meso A., Perrinet L., and Peyre G. (2015). Biologically Inspired Dynamic Textures for Probing Motion Perception. Advances in Neural Information Processing Systems, 28: 1918 - 1926.

2014


  • Boyer L., Dousset A., Roussel P., Dossetto N., Cammilleri S., Piano V., Khalfa S., Mundler O., Donnet A., and Guedj E. (2014). rTMS in fibromyalgia: a randomized trial evaluating QoL and its brain metabolic substrate. Neurology, 82: 1231-1238.

  • Devor A., Sakadžić S., Yaseen M.A., Roussakis E., Tian P., Slovin H., Vanzetta I., Teng I., Saisan P.A., Sinks L.E., Dale A.M., Vinogradov S.A., and Boas D.A. (2014). Functional Imaging of Cerebral Oxygenation with Intrinsic Optical Contrast and Phosphorescent Probes. Optical Imaging of Neocortical Dynamics, 225-253.


  • Matonti F., Meyer F., Rouhette H., Guigou S., Dumas S., Parrat E., Mérité P.-Y., and Pommier S. (2014). Pronostic anatomique et fonctionnel des décollements de rétine secondaires après chirurgie maculaire sans suture. Journal Français d'Ophtalmologie, 37: 58-63.

  • Meso A.I. and Masson G.S. (2014). Dynamic resolution of ambiguity during tri-stable motion perception. Vision Research, 107C: 113-123.

  • Muller L., Reynaud A., Chavane F., and Destexhe A. (2014). The stimulus-evoked population response in visual cortex of awake monkey is a propagating wave. Nature Communications, 5.

  • Perrinet L.U., Adams R.A., and Friston K.J. (2014). Active inference, eye movements and oculomotor delays. Biological Cybernetics, 108: 777 - 801.

  • Rankin J., Meso A.I., Masson G.S., Faugeras O., and Kornprobst P. (2014). Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration. Journal of computational neuroscience, 193-213.


  • Servant M., Montagnini A., and Burle B. (2014). Conflict tasks and the diffusion framework: Insight in model constraints based on psychological laws. Cognitive Psychology, 72: 162-195.


  • Takerkart S., Katz P., Garcia F., Roux S., Reynaud A., and Chavane F. (2014). Vobi One: a data processing software package for functional optical imaging. Frontiers in Neuroscience, 8.


  • Vidal M. and Barrès V. (2014). Hearing (rivaling) lips and seeing voices: how audiovisual interactions modulate perceptual stabilization in binocular rivalry. Frontiers in Human Neuroscience, 8.

2013



  • Bogadhi A.R., Montagnini A., and Masson G.S. (2013). Dynamic interaction between retinal and extraretinal signals in motion integration for smooth pursuit. Journal of Vision, 13: 5-5.


  • Chazalon É., Conrath J., Ridings B., and Matonti F. (2013). Artérite de Kyrieleis : présentation de deux cas et revue de la littérature. Journal Français d'Ophtalmologie, 36: 191-196.


  • Courjaret J.-C., Denis D., Hoffart L., and Matonti F. (2013). Druses papillaires compliquées d’un décollement séreux sous-rétinien sur néovascularisation choroïdienne. Journal Français d'Ophtalmologie, 36: 718-720.
  • Courjaret J.-C., Matonti F., Savoldelli M., D'Hermies F., Legeais J.-M., and Hoffart L. (2013). Corneal ectasia after intrastromal presbyopic surgery. Journal of Refractive Surgery, 29: 865-868.


  • De Saedeleer C., Vidal M., Lipshits M., Bengoetxea A., Cebolla A.M., Berthoz A., Cheron G., and McIntyre J. (2013). Weightlessness alters up/down asymmetries in the perception of self-motion. Experimental Brain Research, 226: 95-106.


  • Denis D., Girard N., Levy-Mozziconacci A., Berbis J., and Matonti F. (2013). Colobome oculaire et résultats de l’IRM cérébrale : résultats préliminaires. Journal Français d'Ophtalmologie, 36: 210-220.


  • Kaplan B.A., Lansner A., Masson G.S., and Perrinet L.U. (2013). Anisotropic connectivity implements motion-based prediction in a spiking neural network. Frontiers in Computational Neuroscience, 7.


  • Khoei M.A., Masson G.S., and Perrinet L.U. (2013). Motion-based prediction explains the role of tracking in motion extrapolation. Journal of Physiology-Paris, 107: 409-420.

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