Brain-Scales

Modelling the dynamics of cognitive processes: from the Bayesian brain to particles
2016-07-07 NeuroAI & Machine Learning, Theoretical Neuroscience
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Testing the odds of inherent vs. observed overdispersion in neural spike counts
The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at …
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A dynamic model for decoding direction and orientation in macaque primary visual cortex
Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …
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A dynamic model for decoding direction and orientation in macaque primary visual cortex
Natural scenes generally contain objects in motion. The local orientation of their contours and the direction of motion are two …
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Introduction
This is the introductory chapter of the book, which serves as a comprehensive but rigorous reference in the area of biologically …
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Sparse Models for Computer Vision
The representation of images in the brain is known to be sparse. That is, as neural activity is recorded in a visual area, for instance …
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Sparse Models for Computer Vision
Biologically Inspired Computer Vision
As the state-of-the-art imaging technologies became more and more advanced, yielding scientific data at unprecedented detail and …
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Biologically Inspired Computer Vision
Sparse Coding Of Natural Images Using A Prior On Edge Co-Occurences
Oriented edges in images of natural scenes tend to be aligned in co-linear or co-circular arrangements, with lines and smooth curves …
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On overdispersion in neuronal evoked activity
The repeated presentation of an identical visual stimulus in the receptive field of a neuron may evoke different spiking patterns at …
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The characteristics of microsaccadic eye movements varied with the change of strategy in a match-to-sample task
Under natural viewing conditions, large eye movements are interspace by small eye movements (microsaccade). Recent works have shown …
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Signature of an anticipatory response in area V1 as modeled by a probabilistic model and a spiking neural network
As it is confronted to inherent neural delays, how does the visual system create a coherent representation of a rapidly changing …
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A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise
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A Simple Model of Orientation Encoding Accounting For Multivariate Neural Noise
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Measuring speed of moving textures: Different pooling of motion information for human ocular following and perception
The visual system does not process information instantaneously, but rather integrates over time. Integration occurs both for stationary …
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Complex dynamics in recurrent cortical networks based on spatially realistic connectivities
Most studies on the dynamics of recurrent cortical networks are either based on purely random wiring or neighborhood couplings. …
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Complex dynamics in recurrent cortical networks based on spatially realistic connectivities
Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1
Oriented edges in images of natural scenes tend to be aligned in collinear or co-circular arrangements, with lines and smooth curves …
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2010-06-22 : CodeJamNr4
We held a CodeJam 22nd-24th June 2010, in Marseille.
2010-06-22 1 min read Computational Neuroscience, NeuroAI & Machine Learning
2010-06-22 : CodeJamNr4
NeuralEnsemble: Towards a meta-environment for network modeling and data analysis
NeuralEnsemble (https://neuralensemble.org) is a multilateral effort to coordinate and organise neuroscience software development …
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