Stay up-to-date on events organized/sponsored by or of interest to the CTCN and affiliated faculty.

Upcoming events

2024 Computational Neuroscience Next Generation Symposium

2024 Computational Neuroscience Next Generation Symposium

September 16, 2024

Graduate students and postdocs are invited to present their research at WashU. Deadline to apply is May 31, 2024.

Previous events

The CTCN Annual Public Lecture on Minds and Machines

The CTCN Annual Public Lecture on Minds and Machines

May 17, 2024 at 5 p.m.

Brains and AI

NEXTEN Conference

NEXTEN Conference

May 16-17, 2024

Envisaging theoretical and computational neuroscience for the next 10 years

NeuroAI Symposium

NeuroAI Symposium

May 15, 2024

Organized by the Incubator for Transdisciplinary Futures at Washington University in St. Louis

CTCN Seminar Series: Roxana Zeraati

CTCN Seminar Series: Roxana Zeraati

May 7, 2024 at 4 p.m.

Mechanistic understanding of adaptive timescales in brain and behavior

Physics Colloquium: Anqi Wu, PhD

Physics Colloquium: Anqi Wu, PhD

April 3, 2024 at 2:45 p.m.

Addressing challenges in modeling and understanding neural connectivity with generalized linear models

CTCN Seminar Series: Tatiana Engel, PhD

CTCN Seminar Series: Tatiana Engel, PhD

March 19, 2024 at 4 p.m.

Identifying mechanisms of cognitive computations from spikes

CTCN Seminar Series: Jeff Zacks, PhD and Tan Nguyen

CTCN Seminar Series: Jeff Zacks, PhD and Tan Nguyen

February 20, 2024 at 4 p.m.

Uncertainty-driven updating enables human-like segmentation and categorization of naturalistic activity

CTCN Seminar Series: Robert Wong

CTCN Seminar Series: Robert Wong

February 13, 2024 at 4 p.m.

Preventing data leakage in neural decoding

CTCN Seminar Series: Tom Franken, MD, PhD

CTCN Seminar Series: Tom Franken, MD, PhD

December 19, 2023 at 4 p.m.

Border ownership and grouping in primate visual cortex

CTCN / Statistics & Data Science Seminar: Robert Kass

CTCN / Statistics & Data Science Seminar: Robert Kass

December 11, 2023 at 11 a.m.

Data Analytic Identification of Interacting Neural Populations: Ideas and Issues