2025 School on Analytical Connectionism

Analytical Connectionism is a 2-week summer course on analytical tools, including methods from statistical physics and probability theory, for probing neural networks and higher-level cognition. The course brings together neuroscience, psychology and machine-learning communities, and introduces attendees to analytical methods for neural-network analysis and connectionist theories of higher-level cognition and psychology.

Connectionism, a key theoretical approach in psychology, uses neural-network models to simulate a wide range of phenomena, including perception, memory, decision-making, language, and cognitive control. However, most connectionist models remain, to a certain extent, black boxes, and we lack a mathematical understanding of their behaviors. Recent progress in theoretical neuroscience and machine learning has provided novel analytical tools that have advanced our mathematical understanding of deep neural networks, and have the potential to help make these “black boxes” more transparent.

During the School, teams of students work closely with faculty and postdoc mentors to develop research projects on topics related to analytical connectionism, presenting initial proposals during week one and interim results at the School’s conclusion. Participant projects from prior Schools have led to publications at NeurIPS.

Additionally, students are grouped based on their expertise and preferences and assigned to take notes for a specific lecturer. These notes are peer-reviewed and published in a special journal issue. Currently, lecture notes from the 2023 and 2024 editions of the school are being collected into a publication in the Proceedings of Machine Learning Research (PMLR). This initiative aims to make the content accessible to future participants and those who were unable to attend, while providing note-takers with the opportunity to contribute to a formal publication.

This course will introduce:

• mathematical methods for neural-network analysis, providing a solid overview of the analytical tools available to understand neural-network models;
• key connectionist models with links to experimental observations, which provide targets for analytical results.

During the course, you will:

• attend lectures given by leading researchers on theoretical methods and applications, key connectionist models, and experimental observations;
• participate in tutorials, Q&A sessions, and panel discussions;
• present to and engage with lecturers, organizers, and other participants during a poster session;
• work in a group with other participants on a novel research project, mentored by the course organizers and lecturers.

Target audience

This course is appropriate for graduate students, postdoctoral fellows and early-career faculty in a number of fields, including psychology, neuroscience, physics, computer science, and mathematics. Attendees are expected to have a strong background in one of these disciplines and to have made some effort to introduce themselves to a complementary discipline.

The course is limited to 40 attendees, who will be chosen to balance the representation of different fields. In circumstances where all other things are equal, priority will be given to applicants from underrepresented groups in STEM fields, using positive action under the UK Equality Act 2010 where appropriate.

Course fees

There is a course fee of 600 GBP. Attendees are expected to cover their own travel, accommodation and other subsistence expenses. Lunch and coffee/tea breaks will be provided on course days, and there will be one course dinner.

Cancellation policy:

• Within 7 days of registering/making the booking: 100% refund
• After 7 days of registering/making the booking and up to 15 days before the start of the school: 80% refund
• Less than 15 days before the start of the school: no refund

Financial assistance via travel grant may be available for successful applicants who find it difficult to take up a place for financial reasons. Applicants are asked to indicate in their application if they would like to be considered for financial aid. The amount of financial aid available will depend on the course funding from grants and sponsors.

Core lecturers

Rémi Monasson

CNRS & Ecole Normale Supérieure

Tim Rogers

University of Wisconsin-Madison

Tali Sharot

UCL & MIT

Topic lecturers

Merav Ahissar

The Hebrew University of Jerusalem

Xuechunzi Bai

University of Chicago

Marco Baity-Jesi

Eawag

Mathew Diamond

SISSA

Lasana Harris

UCL

Tiago Maia

University of Lisbon

Angela Radulescu

Icahn School of Medicine at Mt. Sinai

Levent Sagun

FAIR

Fanny Yang

ETH Zürich

This year, we are thrilled to have lecturers with expertise in the following research areas:

• analytical frameworks for understanding bias from statistical physics;
• perceptual and cognitive biases in human decision-making and belief formation;
• individual differences and deficits in learning, including atypical development and atypical cognitive processes;
• social learning and the emergence of group-level stereotypes;
• bias amplification in machine learning systems from theoretical and applied perspectives;
• clinical applications in computational psychiatry and mental health.

These components will be delivered as a set of core lectures in the first week, followed by a set of topic lectures in the second week.

Contributed posters

To be announced in July 2025.

Participant list

To be announced in July 2025.

Course organizers

Tyler Boyd-Meredith

University College London

SueYeon Chung

New York University & Flatiron Institute

Erin Grant

University College London

I-Chun Lin

University College London

Stefano Sarao Mannelli

Chalmers University of Technology & Gothenburg University

Andrew Saxe

University College London

• I need a visa to attend the programme. Will you provide the necessary documents for my visa application if I am accepted? If you require a UK Standard Visitor visa, we will provide an invitation letter to support your application once you confirm your acceptance into the programme. Please note that visa processing can take several weeks, so it’s necessary to start the application process as soon as you accept the offer.
• I am not based in London. Where can I stay during the programme? You may wish to look into UCL Summer Residences or University of London halls, both open to the general public during the student vacation period in summer. The YMCA Indian Student Hostel (if eligible) is within five minutes walking distance. London Metropolitan University also has a list of summer accommodation options on its website.
• Will I receive individual feedback if my application is not successful? Unfortunately, due to the large number of applicants, we are unable to offer individual feedback on unsuccessful applications.
• Other questions not covered in the FAQs? Contact us at admissions@gatsby.ucl.ac.uk.