Inhalation Frequency Controls Reformatting of Mitral/Tufted Cell Odor Representations in the Olfactory Bulb

Abstract

In mammals, olfactory sensation depends on inhalation, which controls activation of sensory neurons and temporal patterning of central activity. Odor representations by mitral and tufted (MT) cells, the main output from the olfactory bulb (OB), reflect sensory input as well as excitation and inhibition from OB circuits, which may change as sniff frequency increases. To test the impact of sampling frequency on MT cell odor responses, we obtained whole-cell recordings from MT cells in anesthetized male and female mice while varying inhalation frequency via tracheotomy, allowing comparison of inhalation-linked responses across cells. We characterized frequency effects on MT cell responses during inhalation of air and odorants using inhalation pulses and also "playback" of sniffing recorded from awake mice. Inhalation-linked changes in membrane potential were well predicted across frequency from linear convolution of 1 Hz responses; and, as frequency increased, near-identical temporal responses could emerge from depolarizing, hyperpolarizing, or multiphasic MT responses. However, net excitation was not well predicted from 1 Hz responses and varied substantially across MT cells, with some cells increasing and others decreasing in spike rate. As a result, sustained odorant sampling at higher frequencies led to increasing decorrelation of the MT cell population response pattern over time. Bulk activation of sensory inputs by optogenetic stimulation affected MT cells more uniformly across frequency, suggesting that frequency-dependent decorrelation emerges from odor-specific patterns of activity in the OB network. These results suggest that sampling behavior alone can reformat early sensory representations, possibly to optimize sensory perception during repeated sampling. Olfactory sensation in mammals depends on inhalation, which increases in frequency during active sampling of olfactory stimuli. We asked how inhalation frequency can shape the neural coding of odor information by recording from projection neurons of the olfactory bulb while artificially varying odor sampling frequency in the anesthetized mouse. We found that sampling an odor at higher frequencies led to diverse changes in net responsiveness, as measured by action potential output, that were not predicted from low-frequency responses. These changes led to a reorganization of the pattern of neural activity evoked by a given odorant that occurred preferentially during sustained, high-frequency inhalation. These results point to a novel mechanism for modulating early sensory representations solely as a function of sampling behavior.

Human VMPFC encodes early signatures of confidence in perceptual decisions

“…We next sought to identify potential influences of neural confidence signals on decision-related behaviour. In particular, there is evidence that confidence, as reflected in behavioural ( Braun et al, 2018 ) and physiological ( Urai et al, 2017 ) correlates, can play a role in the modulation of history-dependent choice biases. Here, we tested whether the strength of our EEG-derived confidence signals (i.e., confidence discriminant component amplitude CONF ) on a given trial might influence the probability to repeat a choice on the immediately subsequent trial (P REPEAT ).…”

Temporal Dynamics of Inhalation-Linked Activity across Defined Subpopulations of Mouse Olfactory Bulb Neurons ImagedIn Vivo

“…To compare the dynamics of inhalation-driven activity across different OB neuron populations, we used an artificial inhalation paradigm that allowed for precise comparison of temporal response dynamics across experiments, as described previously (Wachowiak et al, 2013; Díaz-Quesada et al, 2018; Fig. 1 A ).…”

Respiration-Locking of Olfactory Receptor and Projection Neurons in the Mouse Olfactory Bulb and Its Modulation by Brain State

“…While the ability to analyze olfactory representations in a cell-type-specific manner is crucial, for some techniques such as electrophysiology in vivo , cell-type identification has remained difficult. This is especially the case when relying on morphological reconstruction, which limited sample sizes to date (Fukunaga et al, 2012 , 2014 ; Díaz-quesada et al, 2018 ; Jordan et al, 2018a ). Even though the performance of the linear classifiers is not perfect, the potential to include a far larger sample size for analyses may be advantageous when exploring cell-type-specific olfactory encoding.…”

“…To date, sniff-coupled activity in MCs and TCs has been described using both electrophysiological (Adrian, 1950 ; Cang and Isaacson, 2003 ; Margrie and Schaefer, 2003 ; Carey and Wachowiak, 2011 ; Shusterman et al, 2011 ; Smear et al, 2011 ; Fukunaga et al, 2012 , 2014 ; Igarashi et al, 2012 ; Díaz-quesada et al, 2018 ; Jordan et al, 2018a , b ) and imaging techniques (Iwata et al, 2017 ; Short and Wachowiak, 2019 ; Eiting and Wachowiak, 2020 ) in a variety of brain states. However, it is unclear how sniff-locking under wide-ranging protocols relates to each other, especially given that parameters of sniff patterns, or inputs to the olfactory system, can change drastically between anesthetized and awake states (Welker, 1964 ; Jessberger et al, 2016 ).…”