Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos

Polina Turishcheva, Paul G. Fahey, Michaela Vystrčilová, Laura Hansel, Rachel E Froebe, Kayla Ponder, Yongrong Qiu, Konstantin Friedrich Willeke, Mohammad Bashiri, Ruslan Baikulov, Yu Zhu, Lei Ma, Shan Yu, Tiejun Huang, Bryan M. Li, Wolf De Wulf, Nina Kudryashova, Matthias H. Hennig, Nathalie Rochefort, Arno Onken et al. (5 additional authors not shown)

Keywords: benchmark, neuroscience, predictive models, visual cortex, competition retrospective

TL;DR: a large scale benchmark for dynamic predictive models of mouse visual cortex

Abstract:

Understanding how biological visual systems process information is challenging because of the nonlinear relationship between visual input and neuronal responses.
Artificial neural networks allow computational neuroscientists to create predictive models that connect biological and machine vision.
Machine learning has benefited tremendously from benchmarks that compare different models on the same task under standardized conditions.
However, there was no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system.
To address this gap, we established the SENSORIUM 2023 Benchmark Competition with dynamic input, featuring a new large-scale dataset from the primary visual cortex of ten mice.
This dataset includes responses from 78,853 neurons to 2 hours of dynamic stimuli per neuron, together with behavioral measurements such as running speed, pupil dilation, and eye movements.
The competition ranked models in two tracks based on predictive performance for neuronal responses on a held-out test set: one focusing on predicting in-domain natural stimuli and another on out-of-distribution (OOD) stimuli to assess model generalization.
As part of the NeurIPS 2023 Competition Track, we received more than 160 model submissions from 22 teams.
Several new architectures for predictive models were proposed, and the winning teams improved the previous state-of-the-art model by 50\%.
Access to the dataset as well as the benchmarking infrastructure will remain online at www.sensorium-competition.net.

NeurIPS 23 Competition Analysis Paper: NeurIPS23 Competition Analysis Paper

NeurIPS 23 Competition Name For Competition Analysis Papers Only: The Dynamic Sensorium competition for predicting large-scale mouse visual cortex activity from videos

Submission Number: 1929