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Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision

Published online by Cambridge University Press:  06 December 2023

James J. DiCarlo Open the ORCID record for James J. DiCarlo [Opens in a new window] ,
Daniel L. K. Yamins ,
Michael E. Ferguson ,
Evelina Fedorenko ,
Matthias Bethge ,
Tyler Bonnen  and
Martin Schrimpf
James J. DiCarlo
Affiliation:
Dept. of Brain and Cognitive Sciences, Quest for Intelligence, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA dicarlo@mit.edu; https://dicarlolab.mit.edu mferg@mit.edu evelina9@mit.edu; https://evlab.mit.edu/ msch@mit.edu; https://mschrimpf.com/
Daniel L. K. Yamins
Affiliation:
Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA yamins@stanford.edu bonnen@stanford.edu; http://neuroailab.stanford.edu/research.html
Michael E. Ferguson
Affiliation:
Dept. of Brain and Cognitive Sciences, Quest for Intelligence, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA dicarlo@mit.edu; https://dicarlolab.mit.edu mferg@mit.edu evelina9@mit.edu; https://evlab.mit.edu/ msch@mit.edu; https://mschrimpf.com/
Evelina Fedorenko
Affiliation:
Dept. of Brain and Cognitive Sciences, Quest for Intelligence, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA dicarlo@mit.edu; https://dicarlolab.mit.edu mferg@mit.edu evelina9@mit.edu; https://evlab.mit.edu/ msch@mit.edu; https://mschrimpf.com/
Matthias Bethge
Affiliation:
Tübingen AI Center, University of Tübingen, Tübingen, Germany matthias.bethge@bethgelab.org; https://bethgelab.org/
Tyler Bonnen
Affiliation:
Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA yamins@stanford.edu bonnen@stanford.edu; http://neuroailab.stanford.edu/research.html
Martin Schrimpf
Affiliation:
Dept. of Brain and Cognitive Sciences, Quest for Intelligence, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA dicarlo@mit.edu; https://dicarlolab.mit.edu mferg@mit.edu evelina9@mit.edu; https://evlab.mit.edu/ msch@mit.edu; https://mschrimpf.com/ École polytechnique fédérale de Lausanne, Lausanne, Switzerland
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Abstract

In the target article, Bowers et al. dispute deep artificial neural network (ANN) models as the currently leading models of human vision without producing alternatives. They eschew the use of public benchmarking platforms to compare vision models with the brain and behavior, and they advocate for a fragmented, phenomenon-specific modeling approach. These are unconstructive to scientific progress. We outline how the Brain-Score community is moving forward to add new model-to-human comparisons to its community-transparent suite of benchmarks.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 46 , 2023 , e390
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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