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Dynamics of cortical networks including long-range patchy connections
Most studies of cortical network dynamics are either based on purely random wiring or neighborhood couplings [1], focussing on a rather …
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Functional consequences of correlated excitation and inhibition on single neuron integration and signal propagation through synfire chains
Neurons receive a large number of excitatory and inhibitory synaptic inputs whose temporal interplay determines their spiking behavior. …
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Inferring monkey ocular following responses from V1 population dynamics using a probabilistic model of motion integration
Short presentation of a large moving pattern elicits an ocular following response that exhibits many of the properties attributed to …
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NeuralEnsemble: Towards a meta-environment for network modeling and data analysis
NeuralEnsemble (http://neuralensemble.org) is a multilateral effort to coordinate and organise neuroscience software development …
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Analyzing cortical network dynamics with respect to different connectivity assumptions
Based on Nicole Voges, Laurent U Perrinet (2010). Phase space analysis of networks based on biologically realistic parameters. Journal of Physiology-Paris. PDF Cite DOI see follow-up : Nicole Voges, Laurent U Perrinet (2012).
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Functional properties of feed-forward inhibition
see this subsequent paper in the Journal of Computational Neuroscience
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Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images
If modern computers are sometimes superior to cognition in some specialized tasks such as playing chess or browsing a large database, …
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Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images
Control of the temporal interplay between excitation and inhibition by the statistics of visual input: a V1 network modelling study
In the primary visual cortex (V1), single cell responses to simple visual stimuli (gratings) are usually dense but with a high …
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Decoding the population dynamics underlying ocular following response using a probabilistic framework
The machinery behind the visual perception of motion and the subsequent sensorimotor transformation, such as in Ocular Following …
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Decoding the population dynamics underlying ocular following response using a probabilistic framework
Dynamics of cortical networks based on patchy connectivity patterns
Based on Nicole Voges, Laurent U Perrinet (2010). Phase space analysis of networks based on biologically realistic parameters. Journal of Physiology-Paris. PDF Cite DOI see follow-up : Nicole Voges, Laurent U Perrinet (2012).
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Modeling spatial integration in the ocular following response to center-surround stimulation using a probabilistic framework
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What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
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What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells
Synchrony in thalamic inputs enhances propagation of activity through cortical layers
see this subsequent paper in the Journal of Computational Neuroscience
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Dynamic inference for motion tracking
When the visual information about an object’s motion differs at the local level, the visuomotor system needs to integrate …
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Neural Codes for Adaptive Sparse Representations of Natural Images
I will illustrate in this talk how computational neuroscience may inspire and be inspired by mathematical image processing. Focusing on …
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Neural Codes for Adaptive Sparse Representations of Natural Images
On efficient sparse spike coding schemes for learning natural scenes in the primary visual cortex
We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the …
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PyNN: towards a universal neural simulator API in Python
Trends in programming language development and adoption point to Python as the high-level systems integration language of choice. …
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Visual tracking of ambiguous moving objects: A recursive Bayesian model
Perceptual and oculomotor data demonstrate that, when the visual information about an object’s motion differs on the local …
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An efficiency razor for model selection and adaptation in the primary visual cortex
We describe the theoretical formulation of a learning algorithm in a model of the primary visual cortex (V1) and present results of the …
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Bayesian modeling of dynamic motion integration
The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …
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Contrast sensitivity adaptation in a virtual spiking retina and its adequation with mammalians retinas
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Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex
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Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex
Computations in a cortical column are characterized by the dynamical, event-based nature of neuronal signals and are structured by the …
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Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
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Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework
The quality of the representation of an object’s motion is limited by the noise in the sensory input as well as by an intrinsic …
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Modeling of simple cells through a sparse overcomplete gabor wavelet representation based on local inhibition and facilitation
We present a biologically plausible model of simple cortical cells as 1) a linear transform representing edges and 2) a non-linear …
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Sparse Gabor wavelets by local operations
Efficient sparse coding of overcomplete transforms remains still anopen problem. Different methods have been proposed in theliterature, …
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Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model
The integration of information is essential to measure the exact 2D motion of a surface from both local ambiguous 1D motion produced by …
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Efficient representation of natural images using local cooperation
Low-level perceptual computations may be understood in terms of efficient codes (Simoncelli and Olshausen, 2001, Annual Review of …
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Efficient Source Detection Using Integrate-and-Fire Neurons
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Efficient Source Detection Using Integrate-and-Fire Neurons
Sparse Image Coding Using an Asynchronous Spiking Neural Network
Progressive reconstruction of a static image using spikes in a Laplacian pyramid.
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Visual Strategies for Sparse Spike Coding
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Visual Strategies for Sparse Spike Coding
A generative model for Spike Time Dependent Hebbian Plasticity
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