22 citations · 22 across the 4 of their papers we have counts for
3 papers · 1 filter
BrainWideBench: Benchmarking large-scale pretraining and across-animal transfer in multi-region neural recordings
Alexandre Andre, Shivashriganesh P. Mahato, Vinam Arora +39
Advances 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…
Leveraging unlabelled data for generalizable neural population decoding
Ximeng Mao, Nanda H. Krishna, Avery Hee-Woon Ryoo +2
Robust and accurate neural decoders are integral to neurotechnologies such as brain-computer interfaces and closed-loop experiments. Recent work has shown that tokenizing neural da…
A Unified, Scalable Framework for Neural Population Decoding
Mehdi Azabou, Vinam Arora, Venkataramana Ganesh +7
Our ability to use deep learning approaches to decipher neural activity would likely benefit from greater scale, in terms of both model size and datasets. However, the integration…