Symmetry, Invariance and Neural Representations

Organizers

Simone Azeglio  | Institut Pasteur, France
Arianna Di Bernardo | Ecole Normale Supérieure de Paris, France

Abstract

Why does symmetry encoding matter for neuroscience? There exists an intimate relationship between how natural phenomena evolve in time and how we represent the world by measuring it with our senses. On the one hand, the best mathematical model of the world we possess, the physical laws, can be characterised on the basis of invariants, conserved quantities (Noether’s Theorem). On the other hand, in order to perceive and thus interact with the external environment, we need to create robust neural representations from the “data” collected through sensory processing.

It is therefore inevitable that neural representations, as well as the structure and dynamics of neuronal circuits, are affected by the organisational properties dictated by physics. Awareness of this fact and incorporating it in the definition of computational and deep learning models for brain function can allow for more robust learning and provide better generalisation properties. This workshop proposal aims to unify under a common framework, theories and models that consider invariant representations in vision, audition, olfaction, touch, motor control, spatial navigation and memory.

Schedule (CEST)

Tuesday, Sept 13

14:00

Introduction

14:30

Tamar Flash | Weizmann Institute of Science, Israel
Symmetries and Space-time geometries in action production and perception

15:10

t.b.a.

15:50

Alexandra Libby | Princeton University, USA
Rotational dynamics reduce interference between sensory and memory representations

16:30

30 min break

17:00

Ben Sorscher | Stanford University, USA
A unified theory for the origin of grid cells through the lens of pattern formation

17:30

Hiba Sheheitli | Aix-Marseille Université, France
Entropy, free energy, symmetry and dynamics in the brain

18:00

Round table discussion
All workshop speakers

18:30

End of first day

Wednesday, Sept 14

08:30

Introduction

08:40

Zygmunt Pizlo | UC Irvine, USA
Symmetry as an explanatory principle in human vision and problem solving

09:20

Michael A. Casey | Dartmouth College, USA
L’objet sonore: toward modeling auditory object invariances in neural data with spectro-temporal receptive fields

09:55

Tatyana Sharpee | UC San Diego & Salk Institute for Biological Studies, USA
Hyperbolic geometry in biological systems: from gene expression to human perception

10:30

30 min break

11:00

Thomas Serre | Brown University, USA
Bottom-up, horizontal and top-down processes in perceptual grouping

11:30

Sophia Sanborn | UC Berkeley & UC Santa Barbara, USA
Discovering Group Structure in Neural Data with Group Variational Auto-Encoders

12:00

Round table discussion
All workshop speakers

12:30

End