Normal brain aging is associated with deficits in cognitive and sensory processes, due to subtle impairment of synaptic contacts and plasticity. Impairment may be discrete in basal conditions but is revealed when cerebral plasticity is involved, such as in learning contexts. We used olfactory perceptual learning, a non-associative form of learning in which discrimination between perceptually similar odorants is improved following exposure to these odorants, to better understand the cellular bases of olfactory aging in mice.
View Article and Find Full Text PDFPleasant odorants are represented in the posterior olfactory bulb (pOB) in mice. How does this hedonic information generate odor-motivated behaviors? Using optogenetics, we report here that stimulating the representation of pleasant odorants in a sensory structure, the pOB, can be rewarding, self-motivating, and is accompanied by ventral tegmental area activation. To explore the underlying neural circuitry downstream of the olfactory bulb (OB), we use 3D high-resolution imaging and optogenetics and determine that the pOB preferentially projects to the olfactory tubercle, whose increased activity is related to odorant attraction.
View Article and Find Full Text PDFAdult olfactory neurogenesis provides waves of new neurons involved in memory encoding. However, how the olfactory bulb deals with neuronal renewal to ensure the persistence of pertinent memories and the flexibility to integrate new events remains unanswered. To address this issue, mice performed two successive olfactory discrimination learning tasks with varying times between tasks.
View Article and Find Full Text PDFOlfactory perceptual learning is defined as an improvement in the discrimination of perceptually close odorants after passive exposure to these odorants. In mice, simple olfactory perceptual learning involving the discrimination of two odorants depends on an increased number of adult-born neurons in the olfactory bulb, which refines the bulbar output. However, the olfactory environment is complex, raising the question of the adjustment of the bulbar network to multiple discrimination challenges.
View Article and Find Full Text PDFBackground: Cellular imagery using histology sections is one of the most common techniques used in Neuroscience. However, this inescapable technique has severe limitations due to the need to delineate regions of interest on each brain, which is time consuming and variable across experimenters.
New Method: We developed algorithms based on a vectors field elastic registration allowing fast, automatic realignment of experimental brain sections and associated labeling in a brain atlas with high accuracy and in a streamlined way.