Impact of cortical feedback on odor concentration change coding

University Of Oregon, Eugene OR

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Abstract

ABSTRACT Top-down feedback connections between ?higher? and ?lower? brain areas are quite common, but their functional role remains a mystery. This general principle applies to the olfactory system, in which the olfactory bulb receives dense feedback innervation from its cortical targets. Here, we propose techniques with which feedback neurons can be targeted by a viral/transgenic intersectional strategy in mice. Using this strategy, we will identify feedback neurons during electrophysiological recordings by optogenetic tagging. In addition, we will exclusively silence the feedback axons in olfactory bulb, in a way that will not affect the feedforward connections of these neurons. In the timeframe of this proposal, we will apply these techniques to determine the role of one olfactory cortical area, the anterior olfactory nucleus, in one olfactory computation: sensing odor concentration changes over time. This computation is very important to a mouse, because sensing concentration changes over time can enable a mouse to locate odor sources. We have recently reported that a substantial subset of neurons in olfactory bulb explicitly represent concentration changes. Because inhalation parses odor input into discrete, intermittent samples, computing concentration change requires a memory of stimulation during past inhalations. We hypothesize that anterior olfactory nucleus provides this putative memory signal via its feedback projection. This hypothesis predicts that responses of feedback neurons will represent the previous sniff's odor concentration, even after the stimulus has ceased. In Aim 1 of this proposal, we will test this prediction by delivering dynamic concentration stimuli to awake mice, while we record electrophysiologically from neuronal ensembles in which we can use optogenetic tagging to distinguish feedback from non-feedback neurons. Another prediction of our hypothesis is that feedback signals are essential to computing concentration changes. In Aim 2, we will test for a causal role of feedback in this computation, by silencing feedback axons in the olfactory bulb while we record the responses of olfactory bulb neurons to odor concentration dynamics. With the proposed experiments, we will determine how and whether anterior olfactory nucleus participates in concentration change sensing. In the longer term, the methods we propose here will enable us to determine the role of feedback neurons in other olfactory areas, such as piriform or lateral entorhinal cortices, in sensing concentration changes, as well as other relevant olfactory computations. Importantly, the optogenetic silencing strategy we propose is compatible with behavioral experiments, because we will selectively silence feedback axons without affecting activity in the neurons' cell bodies. Thus, feedback can be dissected from feedforward signals, which will make experimental results easier to interpret. Ultimately, the techniques established here will facilitate our big picture goal of elucidating the role of top-down feedback in neuronal computation.