Richard C. Gerkin

Odors Smell Like Their Components: A Linear Framework for Predicting Olfactory Mixture Perception

The paper shows that odor mixtures can be predicted linearly from component odorant profiles, challenging the assumption of nonlinear interactions.

A quantitative framework for predicting odor intensity across molecule and mixtures

This study develops a deep learning framework to predict odor intensity from physical properties of molecules and mixtures, overcoming limitations of traditional methods.

A Principal Odor Map Unifies Diverse Tasks in Human Olfactory Perception

The paper develops a Principal Odor Map using graph neural networks that matches human-level odor description performance and generalizes to diverse odor prediction tasks.

Metabolic activity organizes olfactory representations

The paper identifies a molecular-level representation of odors that predicts receptor, neural, and behavioral responses across species and shows metabolic relationships in odor space.

NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML

The paper introduces NeuroML-DB, a database of computational neuroscience models, enabling reuse and analysis of models through standardized NeuroML format and integration with other resources.

Pyrfume: A Window to the World's Olfactory Data

Pyrfume provides a unified framework to access and analyze diverse olfactory datasets across species and modalities, enabling novel analyses and benchmarks for machine olfaction.

A behavioral paradigm for measuring perceptual distances in mice

This paper develops a behavioral paradigm to measure perceptual distances in mice using olfaction as a model system.

Drawing the Borders of Olfactory Space

The paper develops a model to predict odorous molecules based on chemical properties and estimates the number of possible odorous compounds to be over 30 billion.

Deconstructing the mouse olfactory percept through an olfactory ethological atlas

This study creates a comprehensive mouse olfactory ethological atlas using behavioral responses to 73 odorants, revealing shared properties between mouse and human olfactory perception.

Changes in weak pair-wise correlations during running reshapes network state in the main olfactory bulb

The paper shows that running in mice changes spontaneous neural activity in the olfactory bulb, increasing population entropy and suggesting higher-order neuron interactions during locomotion.

Severe Hyposmia Distinguishes Neuropathologically Confirmed Dementia with Lewy Bodies from Alzheimer’s Disease Dementia

This study finds that severe hyposmia (reduced sense of smell) is a distinguishing feature between dementia with Lewy bodies and Alzheimer’s disease dementia, based on neuropathological confirmation.

NeuronUnit: A package for data-driven validation of neuron models using SciUnit

NeuronUnit provides a framework for validating neuron models using data from neurophysiologists and neuroanatomists, integrating with existing neuroinformatics resources.

Experience-dependent tuning of early olfactory processing in the adult brain

This study shows that reduced olfactory experience in adult honey bees leads to less developed antennal lobes, reduced inter-individual variation in glomerular responses, and impaired odor discrimination in learning assays.

Molecular Nearest Neighbors Determine Generalization of Odorant Mixtures

The paper investigates how mice generalize responses to odorant mixtures by testing models that predict perceptual similarity based on molecular nearest neighbors.

Reverse-engineering human olfactory perception from chemical features of odor molecules

The paper demonstrates that machine learning can accurately predict odor perception from molecular features, enabling reverse-engineering of smell.