Image de Raphael Nogueira

Wednesday, 5 pm CET, i.e, 11 am EST


Organized by David Hansel & Carl van Vreeswijk, CNRS,  France


About the Seminar

WWTNS is a weekly digital seminar on Zoom targeting the theoretical neuroscience community. Its aim is to be a platform to exchange ideas among theoreticians. Speakers have the occasion to talk about theoretical aspects of their work which cannot be discussed in a setting where the majority of the audience consists of experimentalists. The seminars  are 45 min long followed by a discussion and are held on Wednesdays at 5 pm in Western Europe, i.e, 11 am EST. The talks are recorded with authorization of the speaker and are available to everybody on our YouTube channel.


To participate in the seminar you need to fill out a registration form after which you will

receive an email telling you how to connect.

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A function approximation perspective on neural representations

Activity patterns of neural populations in natural and artificial neural networks constitute representations of data. The nature of these representations and how they are learned are key questions in neuroscience and deep learning. In his talk, I will describe my group's efforts  in building a theory of representations as feature maps leading to sample efficient function approximation. Kernel methods are at the heart of these developments. I will present applications to deep learning and neuronal data.


Cengiz Pehlevan

Harvard University

December, 2, 2020


Yoram Burak

Hebrew University

December, 9, 2020

Linking neural representations of space by multiple attractor networks in the entorhinal cortex and the hippocampus

In the past decade evidence has accumulated in favor of the hypothesis that multiple sub-networks in the medial entorhinal cortex (MEC) are characterized by low-dimensional, continuous attractor dynamics. Much has been learned about the joint activity of grid cells within a module (a module consists of grid cells that share a common grid spacing), but little is known about the interactions between them. Under typical conditions of spatial exploration in which sensory cues are abundant, all grid-cells in the MEC represent the animal’s position in space and their joint activity lies on a two-dimensional manifold. However, if the grid cells in a single module mechanistically constitute independent attractor networks, then under conditions in which salient sensory cues are absent, errors could accumulate in the different modules in an uncoordinated manner. Such uncoordinated errors would give rise to catastrophic readout errors when attempting to decode position from the joint grid-cell activity. I will discuss recent theoretical works from our group, in which we explored different mechanisms that could impose coordination in the different modules. One of these mechanisms involves coordination with the hippocampus and must be set up such that it operates across multiple spatial maps that represent different environments. The other mechanism is internal to the entorhinal cortex and independent of the hippocampus.  


David Hansel

I am a theoretical neuroscientist at the National Center for Scientific Research in Paris, France and visiting professor at The Hebrew University in Jerusalem, Israel. I am mainly interested in the recurrent dynamics in the cortex and 

basal ganglia.

Carl van Vreeswijk

I am a theoretical neuroscientist working at the National Center for Scientific Research in Paris, France. My main interest is the dynamics of recurrent networks of neurons in the sensory system

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