Publications that appeared as articles in journals
Citekey | Title |
Adams12 | Smooth Pursuit and Visual Occlusion: Active Inference and Oculomotor Control in Schizophrenia |
Barthelemy07 | Dynamics of distributed 1D and 2D motion representations for short-latency ocular following |
Bogadhi10 | Pursuing motion illusions: a realistic oculomotor framework for Bayesian inference |
Cessac07 | Topics in Dynamical Neural Networks: From Large Scale Neural Networks to Motor Control and Vision |
Chemla19 | Suppressive waves disambiguate the representation of long-range apparent motion in awake monkey V1 |
CristobalPerrinetKeil15bicv_chap1 | Introduction |
CristobalPerrinetKeil15bicv | Biologically Inspired Computer Vision |
Damasse18 | Reinforcement effects in anticipatory smooth eye movements |
Daucé10 | Computational Neuroscience, from Multiple Levels to Multi-level |
Davison08 | PyNN: A common interface for neuronal network simulators |
Fischer07cv | Self-invertible 2D log-Gabor wavelets |
Fischer07 | Sparse approximation of images inspired from the functional architecture of the primary visual areas |
Friston12 | Perceptions as Hypotheses: Saccades as Experiments |
Kaplan13 | Anisotropic connectivity implements motion-based prediction in a spiking neural network |
KaplanKhoei14 | Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network |
Khoei13jpp | Role of motion-based prediction in motion extrapolation |
KhoeiMassonPerrinet17 | The flash-lag effect as a motion-based predictive shift |
Kremkow10jcns | Functional consequences of correlated excitatory and inhibitory conductances in cortical networks |
Kremkow16 | Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1 |
Masson12 | The behavioral receptive field underlying motion integration for primate tracking eye movements |
Montagnini07 | Bayesian modeling of dynamic motion integration |
Montagnini15bicv | Visual motion processing and human tracking behavior |
Nava13 | Advances in Texture Analysis for Emphysema Classification |
Perrinet02sparse | Sparse spike coding in an asynchronous feed-forward multi-layer neural network using Matching Pursuit |
Perrinet02stdp | Coherence detection in a spiking neuron via hebbian learning |
Perrinet03ieee | Coding static natural images using spiking event times : do neurons cooperate? |
Perrinet03 | Emergence of filters from natural scenes in a sparse spike coding scheme |
Perrinet04nc | Finding Independent Components using spikes : a natural result of hebbian learning in a sparse spike coding scheme |
Perrinet04tauc | Feature detection using spikes : the greedy approach |
Perrinet06 | Dynamical Neural Networks: modeling low-level vision at short latencies |
Perrinet07neurocomp | Modeling spatial integration in the ocular following response using a probabilistic framework |
Perrinet10shl | Role of homeostasis in learning sparse representations |
Perrinet12pred | Motion-based prediction is sufficient to solve the aperture problem |
Perrinet15bicv | Sparse Models for Computer Vision |
Perrinet15eusipco | Sparse coding of natural images using a prior on edge co-occurences |
Perrinet16EUVIP | Biologically-inspired characterization of sparseness in natural images |
PerrinetAdamsFriston14 | Active Inference, tracking eye movements and oculomotor delays |
PerrinetBednar15 | Edge co-occurrences can account for rapid categorization of natural versus animal images |
Sanz12 | Motion Clouds: Model-based stimulus synthesis of natural-like random textures for the study of motion perception |
Simoncini12 | More is not always better: dissociation between perception and action explained by adaptive gain control |
Taouali15 | Testing the Odds of Inherent versus Observed Overdispersion in Neural Spike Counts |
Voges10neurocomp | Phase space analysis of networks based on biologically realistic parameters |
Voges12 | Complex dynamics in recurrent cortical networks based on spatially realistic connectivities |