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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 6th to Friday, August 9th, 2024.

Calls for Submissions

Submission are Open. See the pages below for submission instructions.

Call for Papers: The primary way to submit to this conference is through 2-page paper submissions. New this year is that we will do double blind reviewing. Submissions due Friday, April 12. Paper Submissions Deadline Extended through Friday, April 19.

Call for Keynotes & Tutorials and Call for Generative Adversarial Collaborative (GAC): As in previous years we have calls for community-driven content for Keynote talks with accompanying method tutorials, and our GAC symposia which aim to engage scientists around a topic over which there is debate or differing views. Proposals due Friday, April 5.

Call for Community Events: New this year, we also have a flexible submission type to enable creative community-driven programming where the format and style of the event is up to you. Proposals due Friday, April 5.

Confirmed Speakers for CCN 2024

  • Matthias Bethge, Universität Tübingen
  • Michael C. Frank, Stanford University
  • Leyla Isik, Johns Hopkins University
  • Been Kim, Google Brain
  • Nicole Rust, University of Pennsylvania
  • Andrew Saxe, University College London

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