2020 International Conference on Mathematical Neuroscience - Digital Edition (6th-7th of July 2020)

The International Conference on Mathematical Neuroscience (ICMNS) is an
inter-disciplinary conference series, bringing together theoretical neuroscientists and mathematicians. The conferences are aimed at scientists interested in using or developing mathematical techniques for neuroscience problems.

ICMNS was launched in 2015 and has been organised 5 times to date.
Owing to the Coronavirus outbreak, the 6th edition will be held online on the 6th-7th of July 2020 at 14:00-19:00 (GMT+2, Amsterdam time).


Registration is now closed. Talks will be streamed live on YouTube, so they are publicly available following the links in the Programme below. Also, talks will be recorded and uploaded here after the conference.  

Plenary speakers

Parallel sessions

  • Cellular and sub-cellular dynamics
    Co-organiser: Krasimira Tsaneva-Atanasova (University of Exeter, UK)
    - Jonathan Rubin (University of Pittsburgh, USA)
    - James Sneyd (University of Auckland, New Zealand)
    - Yulia Timofeeva (University of Warwick, UK)
    - Kyle Wedgwood (University of Exeter, UK)
    - David Yule (University of Rochester, USA)
  • Dynamics of structured networks
    Co-organiser: Krešimir Josić (University of Houston, USA)
    - Omri Barak (Technion, Israel)
    - Robert Rosenbaum (University of Notre Dame, USA)
    - Lai-Sang Young (Courant Institute of Mathematical Sciences, USA)
    - Julijana Gjorgjieva (Max Planck Institute for Brain Research, Germany)
  • Inferring models from data
    Co-organiser: Jean-Pascal Pfister (University of Bern, Switzerland)
    - André Longtin (University of Ottawa, Canada)
    - Anqi Wu (Columbia University, New York, USA)
    - Maneesh Sahani (University College London, UK)
    - Simone Surace (University of Bern, Switzerland)
  • Mean-field methods
    Co-organiser: Eva Löcherbach (Université Paris 1, Panthéon Sorbonne, France)
    - Guilherme Ost (Federal University of Rio de Janeiro, Brazil)
    - Ernest Montbrió (Universitat Pompeu Fabra, Barcelona, Spain)
    - Valentin Schmutz (École polytechnique fédérale de Lausanne, Switzerland)
    - Delphine Salort (Sorbonne Université, Paris, France)
  • Neural fields and spatio-temporal dynamics
    Co-organiser: Áine Byrne (University College Dublin, Ireland)
    - Gustavo Deco (ICREA, Spain)
    - Axel Hutt (Inria, France)
    - James Maclaurin (New Jersey Institute of Technology, USA)
    - Bastian Pietras (Technical University Berlin, Germany)  
  • Neural coding
    Co-organiser: Vladimir Itskov (The Pennsylvania State University, USA)
    - Stefano Fusi (Columbia University, USA)
    - Benjamin Dunn (NTNU, Norway)
    - Tatyana Sharpee (Salk Institute, USA)
    - Ila Fiete (MIT, USA)
  • Numerical methods
    Co-organiser: Evelyn Buckwar (Johannes Kepler University Linz, Austria)
    - Gillian Queisser (Temple University, Philadelphia, USA)
    - Ari Stern (Washington University, St. Louis, USA)
    - Irene Tubikanec (Johannes Kepler University Linz, Austria)
    - Kevin K. Lin (University of Arizona, USA)
  • Mathematical theory of deep learning
    Co-organiser: Andrew Saxe (Oxford University, UK)
    - Mikhail Belkin (The Ohio State University, USA)
    - Sue-Yeon Chung (Columbia University, USA)
    - Suriya Gunasekar (Microsoft Research, USA)
    - Stephane Mallat (ENS Paris, France)

Virtual posters

Virtual poster submissions are now closed. The virtual poster session will take place on Monday the 6th of July at 19:30 GMT+2, Amsterdam time. This session is available only for subscribers.


Monday the 6th of July (times are GMT+2, Amsterdam time, time converter)

Opening and Plenary talk
Anne Churchland
Discovering diversity in decision making: cells, brains, and individuals
Parallel session
Inferring models from data
Parallel session
Mean-field methods
Maneesh Sahani
Chasing the light: mechanistically-informed statistical models of dynamics
Valentin Schmutz
Mean-field limit for large networks of multidimensional spiking neurons
Anqi Wu
New methods for identifying latent manifold structure from neural data
Guilherme Ost
Spatially Extended Hawkes Processes and their Connections with Neural Field Equations
Simone Surace
Striving for freedom and control in nonlinear filtering
Delphine Salort
Qualitative analysis on a PDE model of neural network
André Longtin
Gamma and Beta Bursts and E-I network inference
Ernest Montbrió
The influence of spike resetting on the collective dynamics of quadratic integrate-and-fire neurons
Parallel session
Cellular and sub-cellular dynamics
Parallel session
Neural coding
Yulia Timofeeva
Computational modelling framework to study Ca2+ activation of synaptic vesicle fusion
Stefano Fusi
The neural code of abstraction in artificial and biological neural networks
Kyle Wedgwood
Multi-spike rhythms in a delay coupled neuron
Benjamin Dunn
Toroidal topology of grid cell ensemble activity
Jonathan Rubin
The role of chloride dynamics in neuronal integration of multiple input streams
Tatyana Sharpee
Hyperbolic geometry of the olfactory space
James Sneyd and David Yule
Saliva Secretion in Living Animals: Experiments and Models
Ila Fiete
Simultaneous rigidity and flexibility through modularity in cognitive maps for navigation
Virtual posters

Tuesday the 7th of July (times are GMT+2, Amsterdam time time converter)

Plenary talk
Vivek Jayaraman
About a biological ring attractor network
Parallel session
Numerical methods
Parallel session
Dynamics of structured Networks
Irene Tubikanec
Splitting methods for the stochastic FitzHugh-Nagumo model
Julijana Gjorgjieva
Spontaneous emergence of structure in recurrent networks from a triplet STDP rule
Gillian Queisser
Numerical methods for ultrastructural 3D simulations of neuronal processes
Robert Rosenbaum
Universal properties of strongly coupled networks
Ari Stern
Structure-preserving numerical integrators for Hodgkin-Huxley-type systems
Omri Barak
Structure in the randomness of trained recurrent neural networks
Kevin Lin
Multilevel Monte Carlo Methods for Spiking Neuronal Networks
Lai-Sang Young
Dynamics of a realistic network model of the visual cortex
Parallel session
Neural fields and spatiotemporal dynamics
Parallel session
Mathematical theory of deep learning
Gustavo Deco
Turbulence in the human brain: Discovering the turbulent homogeneous isotropic functional core organisation of the human brain
Mikhail Belkin
From classical bias-variance trade-off to double descent
Bastian Pietras
A stochastic neural field model for finite numbers of renewal-type spiking neurons
Suriya Gunasekar
Kernel and rich regimes in overparameterized linear models
Axel Hutt
Coherence in unstructured networks induced by additive noise
Sue-Yeon Chung
Emergence of Separable Manifolds in Deep Neural Networks
James Maclaurin
Metastable phenomena in stochastic neural fields over long timescales
Stephane Mallat
Multiscale models for deep neural networks
Poster prize talks and closing remarks
Merav Stern
Emergence of Slow Timescales In Highly Chaotic Random Neural Networks
Man Yi Yim
Where can a place cell put its fields? Let us count the ways
Robert Gowers
Spatial structure filters the fluctuation-driven dynamic firing-rate response

Organising Committee

Scientific Committee

Social Media Managers

Advisory Board

Previous editions: