Evidence map›Paper›PMID 37396602›Full record

ArticleArXiv2024

The Dynamic Sensorium competition for predicting large-scale mouse visual cortex activity from videos.

Polina Turishcheva, Paul G Fahey, Michaela Vystrčilová, Laura Hansel, Rachel Froebe, Kayla Ponder, Yongrong Qiu, Konstantin F Willeke, Mohammad Bashiri, Eric Wang and 4 more

Abstract readPreprint
In one paragraph

Article in ArXiv, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Polina TurishchevaInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Paul G FaheyDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
Michaela VystrčilováInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Laura HanselInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Rachel FroebeDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
Kayla PonderDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
Yongrong QiuInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Konstantin F WillekeInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Mohammad BashiriInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Eric WangDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
Zhiwei DingDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
Andreas S ToliasDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.
Fabian H SinzInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.
Alexander S EckerInstitute of Computer Science and Campus Institute Data Science, University of Göttingen, Germany.

Funding

Generation of novel cell type specific mouse genetic toolsU19MH114830 · NIMH · ALLEN INSTITUTE · PI ZENG, HONGKUI · 2017 to 2021
$64.7M
VISION RESEARCH CENTERP30EY002520 · NEI · BAYLOR COLLEGE OF MEDICINE · PI Samuel M Wu · 1985 to 2026
$14.8M
Designing and deploying an expanded color palette of voltage indicators engineered for multiphoton microscopyU01NS113294 · NINDS · BAYLOR COLLEGE OF MEDICINE · PI ST-PIERRE, FRANCOIS, TOLIAS, ANDREAS · 2019 to 2021
$3.7M
Simultaneous high-throughput functional, transcriptomic and connectivity profiling using FUNseqRF1MH126883 · NIMH · BAYLOR COLLEGE OF MEDICINE · PI TOLIAS, ANDREAS, ZADOR, ANTHONY M · 2022 to 2022
$2.3M
Probabilistic coding in cortical populationsR01EY026927 · NEI · BAYLOR COLLEGE OF MEDICINE · PI MA, WEI JI, TOLIAS, ANDREAS · 2017 to 2021
$1.9M
Anatomical connectivity and activity in primary visual cortex of mouseRF1MH130416 · NIMH · BAYLOR COLLEGE OF MEDICINE · PI PITKOW, ZACHARY SAMUEL, REIMER, JACOB · 2022 to 2022
$1.3M
NEI NIH HHS P30 EY002520NEI NIH HHS R01 EY026927NIMH NIH HHS RF1 MH126883NIMH NIH HHS RF1 MH130416NIMH NIH HHS U19 MH114830NINDS NIH HHS U01 NS113294
6 · The paper itself

Abstract

Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding of this system by allowing computational neuroscientists to create predictive models and bridge biological and machine vision. During the Sensorium 2022 competition, we introduced benchmarks for vision models with static input (i.e. images). However, animals operate and excel in dynamic environments, making it crucial to study and understand how the brain functions under these conditions. Moreover, many biological theories, such as predictive coding, suggest that previous input is crucial for current input processing. Currently, there is no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we propose the Sensorium 2023 Benchmark Competition with dynamic input (https://www.sensorium-competition.net/). This competition includes the collection of a new large-scale dataset from the primary visual cortex of ten mice, containing responses from over 78,000 neurons to over 2 hours of dynamic stimuli per neuron. Participants in the main benchmark track will compete to identify the best predictive models of neuronal responses for dynamic input (i.e. video). We will also host a bonus track in which submission performance will be evaluated on out-of-domain input, using withheld neuronal responses to dynamic input stimuli whose statistics differ from the training set. Both tracks will offer behavioral data along with video stimuli. As before, we will provide code, tutorials, and strong pre-trained baseline models to encourage participation. We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and beyond.

Indexed as

dynamic stimulusmouse visual cortexneural predictionsystem identification

Identifiers

PMID37396602
PMCPMC10312815

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.