Yann Lecun

Facebook & NYU

October, 19, 2022

TBA

TBA

Julia Steinberg

Princeton University

October, 26, 2022

TBA

TBA

Alexis Dubreuil

CNRS, Bordeaux

November, 2, 2022

The role of population structure in computations through

neural dynamics

Neural computations are currently investigated using two separate approaches: sorting neurons into functional subpopulations or examining the low-dimensional dynamics of collective activity. Whether and how these two aspects interact to shape computations is currently unclear. Using a novel approach to extract computational mechanisms from networks trained on neuroscience tasks, here we show that the dimensionality of the dynamics and subpopulation structure play fundamentally com- plementary roles. Although various tasks can be implemented by increasing the dimensionality in networks with fully random population structure, flexible input–output mappings instead require a non-random population structure that can be described in terms of multiple subpopulations. Our analyses revealed that such a subpopulation structure enables flexible computations through a mechanism based on gain-controlled modulations that flexibly shape the collective dynamics. Our results lead to task-specific predictions for the structure of neural selectivity, for inactivation experiments and for the implication of different neurons in multi-tasking.

Yonatan Aljadeff

UCSD

November, 9, 2022

Shallow networks run deep:

How peripheral preprocessing facilitates odor classification

Drosophila olfactory sensory hairs ("sensilla") typically house two olfactory receptor neurons (ORNs) which can laterally inhibit each other via electrical ("ephaptic") coupling. ORN pairing is highly stereotyped and genetically determined. Thus, olfactory signals arriving in the Antennal Lobe (AL) have been pre-processed by a fixed and shallow network at the periphery. To uncover the functional significance of this organization, we developed a nonlinear phenomenological model of asymmetrically coupled ORNs responding to odor mixture stimuli. We derived an analytical solution to the ORNs’ dynamics, which shows that the peripheral network can extract the valence of specific odor mixtures via transient amplification. Our model predicts that for efficient read-out of the amplified valence signal there must exist specific patterns of downstream connectivity that reflect the organization at the periphery. Analysis of AL→Lateral Horn (LH) fly connectomic data reveals evidence directly supporting this prediction. We further studied the effect of ephaptic coupling on olfactory processing in the AL→Mushroom Body (MB) pathway. We show that stereotyped ephaptic interactions between ORNs lead to a clustered odor representation of glomerular responses. Such clustering in the AL is an essential assumption of theoretical studies on odor recognition in the MB. Together our work shows that preprocessing of olfactory stimuli by a fixed and shallow network increases sensitivity to specific odor mixtures, and aids in the learning of novel olfactory stimuli.
Work led by Palka Puri, in collaboration with Chih-Ying Su and Shiuan-Tze Wu

November, 16, 2022

Society for Neuroscience Meeting

Barbara Webb

University of Edinburgh

November, 23, 2022

TBA

TBA

Thibaud Taillefumier

The University of Texas

at Austin

November, 30, 2022

TBA

TBA

Grace Lindsey

NYU

December, 7, 2022

TBA

TBA

Vladimir Itskov

The Pennsylvania State

University

December, 14, 2022

TBA

TBA

​

DECEMBER, 21, 2022

​

Christmas Break

DECEMBER, 28, 2022

​

Happy New Year

Haim Sompolinsky

The Hebrew University

and Harvard

January, 4, 2023

TBA

TBA

Laureline Laugiaco

MIT

January, 11, 2023

TBA

TBA

TBA

January, 18, 2023

TBA

TBA

Alessandro Sanzeni

Universita Bocconi

Milano

January, 25, 2023

TBA

TBA

Soledad Gonzalo Cogno

NTNU,Trondheim

February, 1, 2023

TBA

TBA

TBA

February, 8, 2023

TBA

TBA

German Mato

CONICET, Bariloche

February, 15, 2023

TBA

TBA

TBA

February, 22, 2023

TBA

TBA

Richard Naud

University of Ottawa

March, 1st , 2023

TBA

TBA

TBA

March, 8 , 2023

TBA

TBA

TBA

March, 15 , 2023

TBA

TBA

TBA

March, 22 , 2023

TBA

TBA

TBA

March, 29 , 2023

TBA

TBA