Adaptive olfactory circuitry restores function despite severe olfactory bulb degeneration.

The olfactory bulb (OB) is a critical component of mammalian olfactory neuroanatomy. Beyond being the first and sole relay station for olfactory information to the rest of the brain, it also contains elaborate stereotypical circuitry that is considered essential for olfaction. Indeed, substantial lesions of the OB in rodents lead to anosmia. Here, we examined the circuitry that underlies olfaction in a mouse model with severe developmental degeneration of the OB. These mice could perform odor-guided tasks and even responded normally to innate olfactory cues. Despite the near total loss of the OB, piriform cortices in these mice responded to odors, and its neural activity sufficed to decode odor identity. We found that sensory neurons express the full repertoire of olfactory receptors, and their axons project primarily to the rudiments of the OB but also, ectopically, to olfactory cortical regions. Within the OB, the number of principal neurons was greatly reduced, and the morphology of their dendrites was abnormal, extending over large regions within the OB. Glomerular organization was totally lost in the severe cases of OB degeneration and altered in the more conserved OBs. This study shows that olfactory functionality can be preserved despite reduced and aberrant circuitry that is missing many of the elements believed to be essential for olfaction, and it may explain reported retention of olfaction in humans with degenerated OBs.

Paradoxical relationship between speed and accuracy in olfactory figure-background segregation.

In natural settings, many stimuli impinge on our sensory organs simultaneously. Parsing these sensory stimuli into perceptual objects is a fundamental task faced by all sensory systems. Similar to other sensory modalities, increased odor backgrounds decrease the detectability of target odors by the olfactory system. The mechanisms by which background odors interfere with the detection and identification of target odors are unknown. Here we utilized the framework of the Drift Diffusion Model (DDM) to consider possible interference mechanisms in an odor detection task. We first considered pure effects of background odors on either signal or noise in the decision-making dynamics and showed that these produce different predictions about decision accuracy and speed. To test these predictions, we trained mice to detect target odors that are embedded in random background mixtures in a two-alternative choice task. In this task, the inter-trial interval was independent of behavioral reaction times to avoid motivating rapid responses. We found that increased backgrounds reduce mouse performance but paradoxically also decrease reaction times, suggesting that noise in the decision making process is increased by backgrounds. We further assessed the contributions of background effects on both noise and signal by fitting the DDM to the behavioral data. The models showed that background odors affect both the signal and the noise, but that the paradoxical relationship between trial difficulty and reaction time is caused by the added noise.