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Article Dans Une Revue Proceedings of Machine Learning Research Année : 2023

Retrospective on the SENSORIUM 2022 competition

Konstantin F Willeke
  • Fonction : Auteur
Paul G Fahey
  • Fonction : Auteur
  • PersonId : 1316010
Mohammad Bashiri
  • Fonction : Auteur
Laura Hansel
  • Fonction : Auteur
Christoph Blessing
  • Fonction : Auteur
Konstantin-Klemens Lurz
  • Fonction : Auteur
Max F Burg
  • Fonction : Auteur
Santiago A Cadena
  • Fonction : Auteur
Kaiwen Deng
  • Fonction : Auteur
Yiqin Zhu
  • Fonction : Auteur
Kaiwen Xiao
  • Fonction : Auteur
Simone Azeglio
  • Fonction : Auteur
Olivier Marre
Adrian Roggenbach
  • Fonction : Auteur
Kirill Fedyanin
  • Fonction : Auteur
Kirill Vishniakov
  • Fonction : Auteur
Maxim Panov
  • Fonction : Auteur
Subash Prakash
  • Fonction : Auteur
Kishan Naik
  • Fonction : Auteur
Kantharaju Narayanappa
  • Fonction : Auteur
Alexander S Ecker
  • Fonction : Auteur
Andreas S Tolias
  • Fonction : Auteur
Fabian H Sinz
  • Fonction : Auteur
  • PersonId : 1316011
Marco Ciccone
  • Fonction : Autre
Gustavo Stolovitzky
  • Fonction : Autre
Jacob Albrecht
  • Fonction : Autre

Résumé

The neural underpinning of the biological visual system is challenging to study experimentally, in particular as neuronal activity becomes increasingly nonlinear with respect to visual input. Artificial neural networks (ANNs) can serve a variety of goals for improving our understanding of this complex system, not only serving as predictive digital twins of sensory cortex for novel hypothesis generation in silico, but also incorporating bio-inspired architectural motifs to progressively bridge the gap between biological and machine vision. The mouse has recently emerged as a popular model system to study visual information processing, but no standardized large-scale benchmark to identify state-of-the-art models of the mouse visual system has been established. To fill this gap, we proposed the SENSORIUM benchmark competition. We collected a large-scale dataset from mouse primary visual cortex containing the responses of more than 28,000 neurons across seven mice stimulated with thousands of natural images, together with simultaneous behavioral measurements that include running speed, pupil dilation, and eye movements. The benchmark challenge ranked models based on predictive performance for neuronal responses on a held-out test set, and included two tracks for model input limited to either stimulus only (SENSORIUM) or stimulus plus behavior (SENSORIUM+). As a part of the NeurIPS 2022 competition track, we received 172 model submissions from 26 teams, with the winning teams improving our previous state-of-the-art model by more than 15%. Dataset access and infrastructure for evaluation of model predictions will remain online as an ongoing benchmark. We would like to see this as a starting point for regular challenges and data releases, and as a standard tool for measuring progress in large-scale neural system identification models of the mouse visual system and beyond.
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hal-04306603 , version 1 (25-11-2023)

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  • HAL Id : hal-04306603 , version 1

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Konstantin F Willeke, Paul G Fahey, Mohammad Bashiri, Laura Hansel, Christoph Blessing, et al.. Retrospective on the SENSORIUM 2022 competition. Proceedings of Machine Learning Research, 2023. ⟨hal-04306603⟩
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