Presentation Details
Dopaminergic Nuclei Track the Uncertainty of Olfactory Sensory Information

Sam H.Lyons, Pao Alicea-Roman, Ludwig Zhao, Jay A.Gottfried.

University of Pennsylvania, Philadelphia, PA, USA

Abstract


Natural odors are complex mixtures that flit about in space and time, changing in concentration and quality from one second to the next. Yet the human olfactory system is remarkably good at maintaining stable olfactory representations. How does this system remain robust to the noisy statistics of natural odors? We test a solution to this question proposed by predictive coding.  Under this scheme, reliable sensory information is amplified, and noisy sensory information is suppressed. Thus, the highest quality information is prioritized for further processing. This amplification and suppression scheme is thought to be mediated by neuromodulatory systems that amplify and suppress neural representations. To test this hypothesis, we developed a noisy odor-prediction paradigm under 7-Tesla fMRI, in which participants learned noisy cue-odor associations. By employing ultra-high-resolution fMRI, we were able to examine activity in tiny neuromodulatory nuclei during this task. Using computational modelling, we discovered that the uncertainty of odor information was tracked by the functional coupling between dopaminergic nuclei and a network associated with olfactory sensory information. The strength of this coupling then predicted task performance. These results are consistent with the role of neuromodulators in predictive coding and further suggest a mechanism for robust odor perception in natural environments.

No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author.
Content Locked. Log into a registered attendee account to access this presentation.