ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish

Data-driven benchmarks have led to significant progress in key scientific modeling domains including weather and structural biology. Here, we introduce the Zebrafish Activity Prediction Benchmark (ZAPBench) to measure progress on the problem of predicting cellular-resolution neural activity throughout an entire vertebrate brain. The benchmark is based on a novel dataset containing 4d light-sheet microscopy recordings of over 70,000 neurons in a larval zebrafish brain, along with motion stabilized and voxel-level cell segmentations of these data that facilitate development of a variety of forecasting methods. Initial results from a selection of time series and volumetric video modeling approaches achieve better performance than naive baseline methods, but also show room for further improvement. The specific brain used in the activity recording is also undergoing synaptic-level anatomical mapping, which will enable future integration of detailed structural information into forecasting methods.

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Publication Details

Journal
ArXiv.org
Published
2025-03-04
Citations
1
Primary Topic
Zebrafish Biomedical Research Applications
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article
Field-Weighted Citation Impact
1.15
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article

ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish

Luuk Willem Hesselink, Viren Jain, Peter H. Li, Gudrun Ihrke et al.
1 citations
ArXiv.org
Zebrafish Biomedical Research Applications
1.15
article

ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish

Luuk Willem Hesselink, Viren Jain, Peter H. Li, Gudrun Ihrke, Nirmala Iyer, Jan-Matthis Lueckmann, Alyson Petruncio, Wyatt Korff, Misha B. Ahrens, Michał Januszewski, Alexander Immer, Arun Kr Dev, Aubrey V. Weigel, Mariela D. Petkova, Alex Chen, Florian Engert, Grace Park, Jeff W. Lichtman
article en
1 citations

Abstract

Data-driven benchmarks have led to significant progress in key scientific modeling domains including weather and structural biology. Here, we introduce the Zebrafish Activity Prediction Benchmark (ZAPBench) to measure progress on the problem of predicting cellular-resolution neural activity throughout an entire vertebrate brain. The benchmark is based on a novel dataset containing 4d light-sheet microscopy recordings of over 70,000 neurons in a larval zebrafish brain, along with motion stabilized and voxel-level cell segmentations of these data that facilitate development of a variety of forecasting methods. Initial results from a selection of time series and volumetric video modeling approaches achieve better performance than naive baseline methods, but also show room for further improvement. The specific brain used in the activity recording is also undergoing synaptic-level anatomical mapping, which will enable future integration of detailed structural information into forecasting methods.

ArXiv.org
Openalex Percentile: Top 19%
Zebrafish Biomedical Research Applications
1.15
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ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish — Luuk Willem Hesselink, Viren Jain, et al. · ArXiv.org (2025) | TGRS Research Map | TGRS