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Cognitive Computational Neuroscience
August 6–9, 2024
Boston, Massachusetts

Join Us for CCN 2024!

The 7th annual conference on Cognitive Computational Neuroscience will be held at the Massachusetts Institute of Technology from Tuesday, August 6 through Friday, August 9, 2024.

Meeting Registration is Open

Register to Attend CCN 2024!

Hotel Reservations are Open

Book your Accommodations for Boston Now!

Poster Schedule is Now Available

See Poster Sessions for a listing of the poster assignments. See Search Papers to find a paper.

Reviewer Feedback on Submitted Papers is Now Available

Log in to your CCN Account and click 'View Reviewer Feedback'.

Keynote Lectures

Kresge Auditorium

Matthias Bethge
Universität Tübingen
Tuesday, August 6, 11:45 am

Nicole Rust
University of Pennsylvania
Wednesday, August 7, 8:30 am

Been Kim
Google DeepMind
Wednesday, August 7, 11:45 am

Michael C. Frank
Stanford University
Thursday, August 8, 11:00 am

Andrew Saxe
University College London
Friday, August 9, 8:30 am

Leyla Isik
Johns Hopkins University
Friday, August 9, 2:30 pm

About the Conference

CCN is an annual forum for discussion among researchers in cognitive science, neuroscience, and artificial intelligence, dedicated to understanding the computations that underlie complex behavior.  The conference began in 2017, with a goal to to deepen interactions between these disciplines and to discover ways that the communities can benefit one another and leverage each other’s successes, articulated in this TICS commentary paper.

The conference is primarily single-track featuring keynote speakers and oral presentations.  Paper submissions are presented as posters with a few additionally selected for oral presentations. Community-proposed programming happens in single-track and parallel sessions, including "GACs", "K&Ts", and other community events. Generative Adversarial Collaborations (GACs), are symposia designed to clarify theoretical debates and scaffold forward progress. Keynote-and-Tutorial presentations (K&Ts) foster science and skill-building, presenting cutting-edge science as a talk, followed by the code and a tutorial of how to execute those methods. Open events are designed to welcome all creative ideas for community building, skill building, science exchange, mentorship and career development.  We aspire to have an active, open, and responsive culture to the meet the needs of this dynamic growing field.

We encourage participation from experimentalists and theoreticians investigating complex brain computations in humans and animals. CCN will draw researchers that address challenges including (and not limited to):

  • Understanding brain information processing underlying real-world tasks that involve natural stimuli, rich knowledge, complex inferences, and behavior
  • Measuring and expanding the representational competencies of modern AI systems
  • Understanding commonalities and differences between biological and artificial intelligent systems
  • Using techniques from machine learning and artificial intelligence to model brain information processing, and, conversely, incorporating neurobiological principles in machine learning and artificial intelligence
  • Mechanistic interpretability of deep neural network models and the science of deep learning
  • Revealing principles of brain connectivity and dynamics at multiple scales
  • Using psychophysical techniques to relate sensory inputs to behavioral responses
  • Developing cognitive- or neural-level models of perception, cognition, emotion, and action
  • Representation learning and representational alignment
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