The rules linking odor perception to odorant structure are unknown. No scientist nor perfumer can predict an odor based on its molecular structure, or decipher a molecular structure based on its smell. It is this puzzle we aim to solve. In vision and audition coding was probed by linking critical physical stimulus dimensions (wavelength/frequency) to patterns of neural activity. But what are the critical physical dimensions in olfaction? Scientists have probed this by linking restricted physico-chemical aspects of the stimulus, e.g., carbon chain-length, to neural activity. However, the olfactory system did not evolve to decode carbon chain-length, but rather to encode the world around us as revealed in olfactory perception. With this in mind we developed a novel perception-based olfactory space with tangible olfactory axes, based on statistical dimension-reduction of perceptual estimates obtained from humans. In Aim 1 we will test the hypothesis that our generated space predicts olfactory perception in humans. In Aim 2 we will test the hypothesis that our generated space predicts odorant-induced neural activity in olfactory cortex (using fMRI) and epithelium (using novel methods for measurement from human neurons in vivo, methods then further explored as a potential diagnostic tool for Alzheimer's disease). In Aim 3 we will test the hypothesis that our generated space explains neural activity previously measured in the olfactory system across species. In Aim 4 we will use this framework to tune an artificial nose for medical diagnostics. In vision and audition scientists can probe the system within agreed dimensions (color/wavelength; pitch/frequency). Similarly, our proposal generates an olfactory space where one can systematically probe molecular receptor tuning-curves, cellular spatial and temporal coding schemes, as well as higher-order perception. In other words, we propose a common framework for olfaction research.