BrainWideBench: Benchmarking large-scale pretraining and across-animal transfer in multi-region neural recordings
BrainWideBench tests whether pretrained neural representations transfer across mice, behavior, dynamics, and anatomy.
BrainWideBench is a benchmark for across-animal transfer on multi-region neural recordings, built on the International Brain Laboratory Brainwide Map from 139 mice and 276 brain regions. It evaluates whether pretrained representations support behavior decoding, prediction of masked or future neural activity, and recovery of anatomical organization, including finetuning and zero-shot transfer to unseen animals. Pretraining beats matched single-session baselines, but gains depend on alignment between pretraining and downstream tasks, and no method performs uniformly across all three suites.
- Benchmark uses IBL Brainwide Map data from 139 mice across 276 brain regions.
- Three suites test behavior decoding, neural prediction, and anatomical recovery.
- Pretraining beats single-session baselines, but no method wins all suites.
- Zero-shot transfer to unseen animals remains uneven and objective-dependent.
- Organizations
- International Brain Laboratory
From the original article
1 min read at arxiv.orgAdvances in large-scale neural recording have made it possible to collect data across many animals and distributed brain regions, raising the question of whether this scale can be exploited to learn general-purpose neural representations transferable across diverse downstream tasks. Yet, progress toward this goal has been limited by fragmented evaluation protocols and a narrow focus on individual task domains.
By Alexandre Andre · arxiv.org
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