Experimental Comparison of Two MRI-Compatible Flow Olfactometer Architectures
T.P. Nielen (TU Delft - Mechanical Engineering)
Alexandre L. Ratschat – Mentor (TU Delft - Human-Robot Interaction)
L Marchal-Crespo – Graduation committee member (TU Delft - Human-Robot Interaction)
T Horeman – Graduation committee member (TU Delft - Medical Instruments & Bio-Inspired Technology)
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Abstract
Olfactory research shows a link between olfaction and neurodegenerative diseases, such as Alzheimer’s and Parkinson’s. To study these neural mechanisms, functional Magnetic Resonance Imaging (fMRI) together with flow olfactometry is employed. This study evaluated two MRI-compatible flow olfactometer architectures; the classic air-dilution Lorig layout and a continuous flow vacuum-switch architecture, both built from the same modular base hardware. Both systems were benchmarked head-to-head under identical MRI constraints. Key performance metrics included temporal stimulus precision, stimulus shape, achievable odor vapor concentration range, cross-contamination, airflow stability at the participant interface and MRI compatibility. Air carrier flow rate was varied between 1–10 L/min, delivery tube length between 1–9m, and air dilution ratios between 2.5–90%. For the concentration measurements, undiluted isoamyl acetate was used in combination with a photo-ionization detector. The results show that the vacuum-switch cut stimulus
onset latency by 35–60% and kept it below 500ms with 9m tubing, producing the flattest square stimulus pulses and reducing residual odor to below 1.6% of the primary response. These gains came at the cost of brief flow rate dips of approximately 70% below target during valve transitions and a 20–35% lower maximum odor vapor concentration. The Lorig system delivered higher peaks and steadier flow but showed longer, tube length dependent latency and stronger cross-contamination of approximately 4%. Neither configuration reduced temporal signal-to-noise ratio (tSNR) for fMRI measurements. Together, the results provide quantitative trade-offs that allow researchers to match olfactometer design to the specific timing, intensity and comfort requirements of future olfactory fMRI studies, ultimately assisting research in uncovering the underlying neural mechanisms of human olfaction.