AI, Robot Neuroscientist: Reimagining Hypothesis Generation

Published: 28 Oct 2023, Last Modified: 08 Dec 2023NeurIPS2023-AI4Science PosterEveryoneRevisionsBibTeX
Keywords: Neuroscience, Hypothesis Generation, Structure Learning, Representation Learning, Symbolic Regression
TL;DR: We spotlight the potential of AI to generate hypotheses from neuroscience data.
Abstract: Neuroscience has long relied on human-conceived hypotheses, yet the brain's complexity fundamentally challenges this epistemology. Modern technologies and the large-scale data collection they enable throw this challenge into sharp relief. We champion the potential of AI for neuroscience exploration. We highlight both implicit, 'uninterpretable' models as aids in hypothesis formulation and symbolic regression for explicit hypothesis generation. For researchers from non-neuroscience backgrounds, we discuss domain-specific considerations in integrating AI into neuroscience research. By spotlighting the underexplored avenues for AI to accelerate neuroscience, we aim to induce both communities toward these exciting research opportunities.
Submission Track: Attention
Submission Number: 82