Sniffing shapes the dynamics of olfactory bulb gamma oscillations in awake behaving rats

Abstract

Mammals actively sample the environment for relevant olfactory objects. This active sampling is revealed by rapid changes in respiratory rate that influence the olfactory input. Yet the role of sniffing in shaping the neural responses to odorants has not been elucidated. In the olfactory bulb (OB), odorant-evoked gamma oscillations reflect the synchronous activity of mitral/tufted cells, a proposed mechanism for odorant representation. Here we examined the effect of sniffing frequency on the odorant-evoked gamma oscillations in the OB. We simultaneously recorded the respiratory rate and the local field potential while rats performed a lick/no-lick olfactory discrimination task with low odorant concentrations. High-frequency sniffing (HFS) augmented the power of gamma oscillations, suggesting an increase in the sensitivity to odorants. By contrast, coupling of the gamma oscillations to the sniff cycle and the amplitude of individual bursts were not modified by the respiratory rate. However, HFS prolonged the overall response to odorants and increased the frequency of the gamma oscillations, indicating that HFS reduces the adaptation to continuous odorant stimulation. Therefore, the increase in gamma power during HFS is the result of more frequent gamma bursts and the extended response to odorants. As odorant discrimination can be performed in a single sniff, a reduction in the adaptation mediated by HFS of novel odorants may facilitate odorant memory formation for subsequent odorant identification. Finally, these results corroborate that olfactory sampling should be integrated to the study of odorant coding in behaving animals.

Beta and gamma oscillatory activities associated with olfactory memory tasks: different rhythms for different functional networks?

“…We can rule out the hypothesis that only the concentration of odorant would turn beta into gamma in some conditions as it has been reported in anesthetized preparations (Neville and Haberly, 2003) and suggested in other studies (Rosero and Aylwin, 2011). Indeed, Go/No-Go and two-alternative choice tests were in this case performed in the same laboratory, using the same apparatus and the same odorant concentrations (Beshel et al, 2007; Martin et al, 2007).…”

“…Such a learning-induced increase in beta power has been observed in several structures associated with odor processing (MOB, PCx, entorhinal cortex, and hippocampus) and for a variety of behavioral paradigms (see Table 1): Go/No-Go task (Ravel et al, 2003; Martin et al, 2004b, 2007; Gourévitch et al, 2010; Lepousez and Lledo, 2013), two-alternative choice task (Fuentes et al, 2008) and aversive learning (Chapuis et al, 2009). However, a few studies, with similar operant conditioning, report an odor evoked gamma increase instead of a change in beta activity (Beshel et al, 2007; Rosero and Aylwin, 2011). …”

“…It is likely that the rat learns the discrimination between the odors during the first session, but that further sessions are necessary for the acquisition of the sensory-motor association. In the case where gamma oscillations are recorded in the context of a Go/No-Go task, the number of trials to criterion is also elevated (close to 1000) (Rosero and Aylwin, 2011). …”

Significance of sniffing pattern during the acquisition of an olfactory discrimination task

“…Changes in sniffing patterns have a strong impact on the temporal structure of sensory input [15] and subsequent brain processing [16], [17], [18] and [19]. More precisely, OB local field potential follows the sniff cycle with high reliability at every sniff frequency in anesthetized [20], [21] and [22] and awake animals [9], [22] and [23].…”

The olfactory bulb theta rhythm follows all frequencies of diaphragmatic respiration in the freely behaving rat

“…Mammals accomplish this through sniffing, a voluntary modification of regular breathing. Sniffing motor patterns have effects on the temporal structure of sensory input (Carey et al, 2009), subsequent brain processing (Carey and Wachowiak, 2011) and gain modulation of incoming sensory signals (Verhagen et al, 2007; Courtiol et al, 2011a; Rosero and Aylwin, 2011; Esclassan et al, 2012). However, there are no systematic studies of the basal conditions of the system and its internal neural representation, close to its ecological mode of operation.…”