Joshua S. Harvey

The paper investigates how odor identity is represented in the mouse olfactory bulb, finding that both primacy and order coding strategies contribute to odor representation.

The paper presents a data science approach to olfaction, using machine learning to classify neural responses to odors in mice and proposes a standard dataset for olfactory research.

The paper shows that low-level image features can reliably predict metallicity perception, even when objects are rotated.