2023 GAC 2
Comparing artificial and biological networks: are we limited by tools, hypotheses or data?
Organizers & Speakers at CCN 2023:
Meenakshi Khosla, Massachusetts Institute of Technology
Apurva Ratan Murty, Massachusetts Institute of Technology
Tal Golan, Ben-Gurion University of the Negev
Jenelle Feather, Flatiron Institute
Katherine Hermann, Google Research
Aran Nayebi, Massachusetts Institute of Technology
Jessica Thompson, Oxford University
Alex Williams, New York University
Rosa Cao, Stanford University
Radoslaw Martin Cichy, Freie Universitat Berlin
Bradley Love, University College London
Kalanit Grill-Spector, Stanford University
SueYeon Chung, New York University
Other contributors:
James DiCarlo, Massachusetts Institute of Technology
Abstract:
Deep neural networks have emerged as powerful models of computations underlying sensory and high-level cognitive processing. This synergistic study of computational models (AI) and neuroscience with comparative analyses is now widely used to understand the fundamental processes of cognition. Tremendous progress towards this goal has been fueled by major dataset collection and benchmark efforts. While this progress is exciting, recent developments suggest that we might be hitting a wall with our current hypotheses, tools and data for model differentiation. In modern DNNs, seemingly wide disparities in architectural mechanisms have little consequence on alignment with biological networks based on our current comparative analyses tools and data. Moreover, current models and tools cannot help distinguish the computational logic of different brain areas within a domain. This raises the question: Is this apparent model equivalence a scientifically important result, or is something amiss in terms of our current hypotheses, tools or data used for model differentiation? Our main goal in this GAC is to identify the major challenges that have hindered adjudication between competing representational models and to discuss potential solutions for making progress. As a community, we aim to agree on the tools and data that should be employed for comparative analyses.
Kickoff workshop schedule at CCN 2023 on Friday, 25th of August:
Instructions for CCN community members:
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