CNS*2024 Natal: Program

The full program for CNS 2024 is available at: cns2024.sched.com  

A summary version is provided below.

Saturday July 20th

08:00-19:00 Registration
09:00-17:20 Tutorials (details on Sched)
10:10-10:40 Coffee Break
12:10-14:00 Lunch Break
15:30-16:00 Coffee Break
17:20-18:30 Keynote 1 (details on Sched)
18:30-19:30 Welcome Reception
(Free entry for all registrants)

Sunday July 21st

08:30-19:00 Registration
09:00-10:10 Keynote 2 (details on Sched)
10:10-10:40 Coffee Break
10:40-12:30 Oral session 1
12:30-14:00 Lunch Break
14:00-15:30 Oral session 2
15:30-16:00 Coffee Break
16:00-17:20 Oral Session 3
17:20-19:20 Poster Session 1 (details on Sched)

Monday July 22nd

08:30-18:00 Registration
09:00-10:10 Keynote 3 (details on Sched)
10:10-10:40 Coffee Break
10:40-12:30 Oral session 4
12:30-14:00 Lunch Break
14:00-16:10 Oral session 5
16:10-16:40 Coffee Break
16:40-18:40 Poster Session 2 (details on Sched)
19:10 Conference Dinner

Tuesday July 23rd

08:30-18:00 Registration
09:00-12:30 Workshops (details on Sched)
10:20-10:50 Coffee Break
12:30-14:00 Lunch Break
14:00-15:20 Keynote 4 (details on Sched)
15:20 Conference Photo
15:20-15:50 Coffee Break
15:50-16:50 Members Meeting
16:50-18:50 Poster Session 3 (details on Sched)
20:10 CNS Party

Wednesday July 24th

08:30-17:00 Registration
09:00-17:50 Workshops (details on Sched)
10:20-10:50 Coffee Break
12:30-14:10 Lunch Break
15:20-15:50 Coffee Break

Accepted Tutorials

Salvador Dura-Bernal, William Lytton, Robert McDougal
Building mechanistic multiscale models using NEURON and NetPyNE to study brain function and disease (details)
Charl Linssen, Joshua Boettcher, Jasper Albers, Iiro Ahokainen, Pooja Babu, Willem Wybo, Leander Ewert
From single-cell modeling to large-scale network dynamics with NEST Simulator (details)
Pamela Illescas-Maldonaldo, Scott Rich, Alessandro Sanzemi
Modeling Cortical Networks Dynamics (details)
Padraig Gleeson, Ankur Sinha, Boris Marin, Angus Silver
Standardised, data-driven computational modelling with NeuroML using Open Source Brian (details)
Leonardo Abdala Elias, André Fabio Kohn, Renato Naville Watanabe, Ricardo Gonçalves Molinari
Understanding motor control through multiscale modeling of spinal cord neuronal circuits (details)
Cecilia Jarne, Diego Vidaurre
Implementing the Gaussian-Linear Hidden Markov model (GLHMM), with a package in Python for brain data analysis (details)
Moein Khajehnejad, Forough Habibollahi, Leonardo Novelli
Unraveling Dynamics and Connectivity from Spiking Time Series of In-Vitro Neuronal Cultures (details)
Cengiz Gunay
Single cell signal processing and data analysis in Matlab (details)
Anca Doloc-Mihu, Cengiz Gunay
Interactive Data Visualization Techniques (details)
Christopher Kim
Training recurrent spiking neural networks to generate experimentally recorded neural activities (details)

Accepted Workshops

Marie-Constance Corsi, Damien Depannemaecker, Leonardo L. Gollo, Spase Petkoski, Pierpaolo Sorrentino
Virtual Brains: From data to modeling and back (details)
James Pang, Alex Fornito
Brain Modes: Uncovering fundamental dimensions of brain structure and function (details)
César Rennó Costa, Rodrigo Wilkens
Advances in Natural Language Processing for Computational Neuroscience (details)
Daniel Takahashi, Daniel Takahashi, Fred Wolf
Social Behavior: Evolution, Ecology, Neural Circuit (details)
Ankur Sinha
Career development workshop (details)
Maurizio De Pitta, Pamela Illescas-Maldonaldo, Patricio Orio
The structure-function binomial of cortical circuits across multiple scales (details)
Antonio Roque, Riberao Preto, Christophe Pouzat, William Lytton
The Raw and the Cooked (details)
Arnd Roth, Volker Steuber
Cerebellar learning and models of learning involving the cerebellum (details)

Horacio G. Rotstein
Neuronal Oscillations: From Mechanisms to Computation (details)

Petra Ritter, Simon Lagunas
Whole Brain Network Modeling for Clinical Application (details)

Marilyn Gatica, Joseph T. Lizier, Abdullah Makkeh, Michael Wibral, Pedro Mediano
Workshop on Methods of Information Theory in Computational Neuroscience (details)

Thomas Nowotny
From Computational Neuroscience to Biomimetic Embodied AI (details)

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