Stochastic Models in Neuroscience

Tentative list of Speakers


The workshop will start on monday at 9.00 and end on friday before lunch (12.30).
The schedule will be available as soon as possible.


PROVISIONAL LIST OF TALKS

BIBBONA Enrico Consistent estimates for the parameters of LIF neuronal models
BONACCORSI Stefano Evolution equation on networks with stochastic inputs
BRESSLOFF Paul On the master equation approach to stochastic neurodynamics
BRETTE Romain What is the integration time constant of neurons?
BRUNEL Nicolas Stochastic dynamics of spiking neuron models and implications for network dynamics
BUCKWAR Evelyn Effects of feedback delays on stochastic signals in extended neural populations
CARRILLO José Antonio Analysis of Integrate and Fire models
CESSAC Bruno Spikes trains statistics from a dynamical systems perspective
CORDIER Stéphane A Fokker-Planck Model for two interacting neuron populations
DECO Gustavo Stochastic dynamics as a principle of brain function
DESTEXHE Alain How much stochastic is neuronal activity ?
DITLEVSEN Susanne The Morris Lecar neuron model gives rise to the Ornstein-Uhlenbeck leaky integrate-and-fire model
FAUGERAS Olivier Inter Spike Intervals probability distribution and Double Integral Processes
GERSTNER Wulfram Drift-Diffusion for Feature Fusion: The power and limits of stochastic models of decision making
GOLLO Leonardo Active dendrites stochastic neuronal model
HÖPFNER Reinhard Modelization of membrane potentials and information transmission in large systems of neurons
JAHN Patrick Modeling membrane potentials in motoneurons by time-inhomogeneous diffusion leaky integrate-and-fire models
JIRSA Viktor
JOSHI Badal Coupled Poisson process model for sleep-wake cycling
KNÖSCHE Thomas
LAFITTE Olivier Stability of a nerve impulse: construction of the associated Evans function
LINDNER Benjamin Signal amplification and information transmission in neural systems
MCLAUGHLIN David
NEWHALL Katherine Synchrony in Stochastic Pulse-Coupled Neuronal Network Models
PARGA Nestor Dynamics of densely connected networks of model neurons and of cortical circuits
RICHARDSON Magnus Dynamics of populations and networks of neurons with voltage-activated and calcium-activated currents
RIEDLER Martin Modeling neuronal membranes with Piecewise Deterministic Processes
SACERDOTE Laura Copulae and network modeling
SAMSON Adeline Minimum contrast estimate for the parameters of the stochastic Morris-Lecar model
SCHWALGER Tilo Effects of noisy adaptation on neural spiking statistics
SIROVICH Roberta Signal estimation from intracellular recordings in the Feller neuronal model
TUCKWELL Henry Weak noise effects on rhythmic spiking in point and spatial models
VAN ROSSUM Mark Synaptic learning rules: a drunk man's walk to remember
WAINRIB Gilles Multiscale Analysis of Hybrid Processes and Reduction of Stochastic Neuron Models
ZAMBOTTI Lorenzo A probabilistic study of neural complexity


POSTERS

EL BOUSTANI Sami A maximum-likelihood approach based on Master equation to estimate connectivity patterns from 2D large-scale networks (Sami El Boustani, Pierre Yger, Yves Fregnac & Alain Destexhe)
GOLTSEV Alexander Stochastic cellular automata model of neural networks (A. V. Goltsev, F. V. de Abreu, S. N. Dorogovtsev, and J. F. F. Mendes.)
HOLSTEIN Detlef Simulations of stochastic neural networks with scale-free topology
JARYNOWSKI Andrzej Transion between noise and spike regime
LANDON Damien Spikes probability distribution in FitzHugh-Nagumo model
SPREKELER Henning Reward-modulated spike timing-dependent plasticity requires a reward prediction system