Second NeuroMat Workshop - presentation slides

Nov 21, 2016

Slides of the Second NeuroMat Workshop: New Frontiers in NeuroMathematics.

Tuesday - Nov, 22

• Modeling neural nets by interacting systems of chains with memory of variable length. E Loecherbach
• Twenty projects with Galves-Locherbach stochastic elements. O Kinouchi
• Perfect simulation for Bayesian Networks. A Cerqueira
• Dissemination of the edge of science: NeuroMat's approach and challenges? FJ da Paixão and J Peschanski

Wednesday - Nov, 23

• Mind mapping with words. S Ribeiro
• NeuroMat Parkinson Network (AMPARO). A Helene
• NeuroMat Brachial Plexus Lesion Network. C Vargas
• Clinical evaluation in brachial plexus lesions (BPL) . JV Martins
• Kinematics and BPL. G Freire
• The experience of multidisciplinary databasing in traumatic brachial plexus injury. J Maia
• Targeting brain plasticity after BPL. F Torres
• Structured stochastic processes and functional data analysis for the assessment of motor learning in normal and pathological subjects. N González
• On the mathematical consequences of binning spike trains. A Le Ny
• NeuroMat Technology Transfer - Computational tools. K Braghetto

Thursday - Nov, 24

• Cluster approach for eeg analysis: predicting upcoming sensorimotor events. ML Rangel
• Simulations of cortical network models made of stochastic spiking neurons. A Roque and N Kamiji
• Synaptic plasticity in a cortical microcircuit model: different scenarios. R Shimoura
• Too much noise to sleep: Noise-induced transition from sleep to awake-like state in a spiking network model. R Pena
• Subthreshold active conductances shape the EPSPs in cortical neurons. CC Ceballos
• The Potjans-Diesmann local microcircuit model using different neuron classes for excitatory and inhibitory neurons. Kamiji NL

Friday - Nov, 25

• Neuronal rhythms: a framework for understanding interactions in the brain. S Neuenschwander
• Stochastic Ising model with plastic interactions. A Iambartsev
• On the central limit theorem in oriented percolation in two dimensions. A Tzioufas
• Estimating the jump rate of a Piecewise Deterministic Markov Process, a model for interacting neurons. P Hodara
• Computational modeling of a network of excitatory stochastic spiking neurons in the mean-field limit. G Via

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