Monell Chemical Senses Center, Philadelphia, PA, USA.
Department of Neuroscience, Bates College, Lewiston, ME, USA.
Sci Data. 2024 Nov 12;11(1):1220. doi: 10.1038/s41597-024-04051-z.
Advances in theoretical understanding are frequently unlocked by access to large, diverse experimental datasets. Our understanding of olfactory neuroscience and psychophysics remain years behind the other senses, in part because rich datasets linking olfactory stimuli with their corresponding percepts, behaviors, and neural pathways remain scarce. Here we present a concerted effort to unlock and unify dozens of stimulus-linked olfactory datasets across species and modalities under a unified framework called Pyrfume. We present examples of how researchers might use Pyrfume to conduct novel analyses uncovering new principles, introduce trainees to the field, or construct benchmarks for machine olfaction.
理论认识的进步往往得益于对大量、多样化的实验数据集的访问。我们对嗅觉神经科学和心理物理学的认识仍然落后于其他感觉,部分原因是将嗅觉刺激与其相应的感知、行为和神经通路联系起来的丰富数据集仍然稀缺。在这里,我们共同努力,在一个名为 Pyrfume 的统一框架下,解锁和统一了数十个跨物种和模态的与刺激相关的嗅觉数据集。我们展示了研究人员如何使用 Pyrfume 进行新的分析,揭示新的原理,向研究人员介绍该领域,或构建机器嗅觉的基准。