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Matlab 2009 vs matlab 2013
Matlab 2009 vs matlab 2013









  1. #Matlab 2009 vs matlab 2013 series
  2. #Matlab 2009 vs matlab 2013 simulator

Implementation issues in approximate methods for stochastic Hodgkin-Huxley models (Bruce 2007) Human seizures couple across spatial scales through travelling wave dynamics (Martinet et al 2017)

matlab 2009 vs matlab 2013

Hodgkin–Huxley model with fractional gating (Teka et al. Hippocampal context-dependent retrieval (Hasselmo and Eichenbaum 2005) Recordings Using a Real-Time Computational Model of the Electrode (Brette et al. Generating coherent patterns of activity from chaotic neural networks (Sussillo and Abbott 2009) Gamma and theta rythms in biophysical models of hippocampus circuits (Kopell et al. approximation of ion channel gating models (Bruce 2009)įixed point attractor (Hasselmo et al 1995) 1999a, b, c, 2000)Ĭontinuous lateral oscillations as a mechanism for taxis in Drosophila larvae (Wystrach et al 2016)ĭisrupted information processing in Fmr1-KO mouse layer 4 barrel cortex (Domanski et al 2019)ĭynamics of sleep oscillations coupled to brain temperature on multiple scales (Csernai et al 2019)ĭynaSim: a MATLAB toolbox for neural modeling and simulation (Sherfey et al 2018)Įvaluation of stochastic diff.

#Matlab 2009 vs matlab 2013 series

2011)Īctivity constraints on stable neuronal or network parameters (Olypher and Calabrese 2007)Īnalyzing neural time series data theory and practice (Cohen 2014)Īuditory nerve spontaneous rate histograms (Jackson and Carney 2005)īinocular energy model set for binocular neurons in optic lobe of praying mantis (Rosner et al 2019)īrain Dynamics Toolbox (Heitmann & Breakspear 2016, 2017, 2018)Ĭat auditory nerve model (Zilany and Bruce 2006, 2007)Ĭerebellar stellate cells: changes in threshold, latency and frequency of firing (Mitry et al 2020)Ĭochlear implant models (Bruce et al. 2009)Ī reinforcement learning example (Sutton and Barto 1998)Ī simple integrative electrophysiological model of bursting GnRH neurons (Csercsik et al.

matlab 2009 vs matlab 2013

2017)Ī CORF computational model of a simple cell that relies on LGN input (Azzopardi & Petkov 2012)Ī detailed and fast model of extracellular recordings (Camunas-Mesa & Qurioga 2013)Ī dynamic model of the canine ventricular myocyte (Hund, Rudy 2004)Ī gap junction network of Amacrine Cells controls Nitric Oxide release (Jacoby et al 2018)Ī model for focal seizure onset, propagation, evolution, and progression (Liou et al 2020)Ī neural mass model for critical assessment of brain connectivity (Ursino et al 2020)Ī neural mass model of cross frequency coupling (Chehelcheraghi et al 2017)Ī neurocomputational model of classical conditioning phenomena (Moustafa et al.

#Matlab 2009 vs matlab 2013 simulator

The open architecture makes it easy to use MATLAB and its companion products to explore data, create algorithms, and create custom tools that provide early insights and competitive advantages.)Ī cardiac cell simulator (Puglisi and Bers 2001), applied to the QT interval (Busjahn et al 2004)Ī comparison of mathematical models of mood in bipolar disorder (Cochran et al. MATLAB integrates mathematical computing, visualization, and a powerful language to provide a flexible environment for technical computing. Models that contain the Modeling Application : MATLAB (web link to model) ( )











Matlab 2009 vs matlab 2013