This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may c...
International audienceNeurons in the nervous system are submitted to distinct sources of noise, such...
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For exam...
We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relatio...
Stochastic biomathematical models are becoming increasingly important as new light is shed on the ro...
This book presents and studies a class of stochastic models for biological neural nets. A biological...
A single neurons connectivity is the key to understanding the network of neurons in the brain. Howev...
The brain is a very complex system in the strong sense. It features a huge amount of individual cell...
Deciphering the working principles of brain function is of major importance from at least two perspe...
Artificial neural networks are brain-like models of parallel computations and cognitive phenomena. W...
Neuronal networks may be represented as stochastic particle systems. Every particle has an associate...
The aim of this project is to harness the research activities of a sizable group of professors and r...
We discuss the statistics of spikes trains for different types of integrate-and-fire neurons and dif...
Abstract. Artificial neural networks are brain-like models of parallel computations and cognitive ph...
This paper addresses the problem of neural computing by a fundamentally different approach to the on...
Most Artificial Neural Networks that are widely used today focus on approximating deterministic inpu...
International audienceNeurons in the nervous system are submitted to distinct sources of noise, such...
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For exam...
We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relatio...
Stochastic biomathematical models are becoming increasingly important as new light is shed on the ro...
This book presents and studies a class of stochastic models for biological neural nets. A biological...
A single neurons connectivity is the key to understanding the network of neurons in the brain. Howev...
The brain is a very complex system in the strong sense. It features a huge amount of individual cell...
Deciphering the working principles of brain function is of major importance from at least two perspe...
Artificial neural networks are brain-like models of parallel computations and cognitive phenomena. W...
Neuronal networks may be represented as stochastic particle systems. Every particle has an associate...
The aim of this project is to harness the research activities of a sizable group of professors and r...
We discuss the statistics of spikes trains for different types of integrate-and-fire neurons and dif...
Abstract. Artificial neural networks are brain-like models of parallel computations and cognitive ph...
This paper addresses the problem of neural computing by a fundamentally different approach to the on...
Most Artificial Neural Networks that are widely used today focus on approximating deterministic inpu...
International audienceNeurons in the nervous system are submitted to distinct sources of noise, such...
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. For exam...
We have briefly reviewed the occurrence of the post-synaptic potentials between neurons, the relatio...