2023 GAC 1

Reconciling the dichotomy between Sherringtonian and Hopfieldian views on neural computations

Organizers & Speakers at CCN 2023

Dongyan Lin, McGill University

Arna Ghosh, McGill University

Jonathan Cornford, McGill University

James Whittington, Stanford University

Tatiana Engel, Princeton University

David Barack, University of Pennsylvania

John Krakauer, John Hopkins University

Daniel Levenstein, McGill University


The development of high-density neural recordings and inability for single-cell activity to explain many cognitive phenomena has led to the emergence of a “Hopfieldian” paradigm that deals in representational spaces, in opposition to a historical “Sherringtonian” one that deals in the actions of single neurons. However, the Hopfieldian paradigm has yet to incorporate many features of the Sherringtonian paradigm, such as the diverse functionality of distinct cell types, the emergence and computational benefits of Sherringtonian tuning curves, and the (e.g. circuit) mechanisms that give rise to representational spaces. Thus, it remains unclear if the two paradigms can be merged, if the Hopfieldian paradigm should subsume the Sherringtonian one, or if they should remain as distinct but complementary perspectives for understanding the brain. Mediating these views will involve clearer specification of the modeling and analysis frameworks entailed by each paradigm, such that the neural circuit conditions that lend themselves to one or the other can be identified and ideally translatory modeling frameworks can be developed. This GAC aims to bring together researchers whose work provides different perspectives on the two paradigms, and the possibility of their reconciliation.

>>> the workshop recording can be found here <<<

Kickoff workshop schedule at CCN 2023 on Friday, 25th of August:

Instructions for CCN community members: