Olfactory bulb coding of odors, mixtures and sniffs is a linear sum of odor time profiles

Gupta, Priyanka; Albeanu, Dinu F.; Bhalla, Upinder S.

doi:10.1038/nn.3913

Cited by 61 publications

(91 citation statements)

References 48 publications

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“…Similarly, we found that MT spike rates -and mean membrane potential -at higher inhalation frequencies were poorly predicted from the inhalation-triggered response at 1 Hz,inconsistent with recent reports of a linear relationship between unitary MT spiking responses and odor stimulus profiles (Gupta et al, 2015). These changes occurred also during 'playback' of sniff bouts recorded from awake mice, strengthening the conclusion that inhalation frequency drives diverse and nonlinear changes in MT excitability in a bottom-up manner during active odor sampling.…”

Section: Discussioncontrasting

confidence: 97%

“…At the same time -and in agreement with the results of Gupta et al (Gupta et al, 2015) we found that, with respect to the temporal patterning of MT responses within an inhalation cycle, subthreshold response patterns at higher frequencies (3 and 5 Hz) were, in general, well predicted from those measured at 1 Hz. Simple linear convolution of 1 Hz response patterns could account for substantial transformations of the subthreshold response -including, for example, a shortening of response duration (e.g., Fig.…”

Section: Discussionsupporting

confidence: 92%

“…Two general predictions from these studies are that high-frequency sniffing increases the reliability and temporal precision of MT cell firing relative to the respiratory cycle and enhances the signal-to-noise ratio of odorant-evoked MT cell responses (Balu et al, 2004;Hayar et al, 2004;Wachowiak and Shipley, 2006;Shao et al, 2013). In vivo tests of these hypotheses have so far consisted of extracellular MT cell recordings and have reported conflicting results, with some studies reporting a temporal sharpening of MT cell responses and reduced MT cell excitation (Bathellier et al, 2008;Carey and Wachowiak, 2011) and others reporting response patterns that are consistent with a simple linear extrapolation of unitary, low-frequency responses (Gupta et al, 2015).…”

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confidence: 99%

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Inhalation frequency controls reformatting of mitral/tufted cell odor representations in the olfactory bulb

Díaz-Quesada

Youngstrom

Tsuno

et al. 2018

Preprint

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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.. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/242784 doi: bioRxiv preprint first posted online 3 Significance statementOlfactory 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.

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Section: Discussioncontrasting

confidence: 97%

Section: Discussionsupporting

confidence: 92%

mentioning

confidence: 99%

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Inhalation frequency controls reformatting of mitral/tufted cell odor representations in the olfactory bulb

Díaz-Quesada

Youngstrom

Tsuno

et al. 2018

Preprint

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“…This surprisingly high frequency is consistent with recent findings that the olfactory bulb circuitry not only enables highly precise odour responses (Cury and Uchida, 2010;Shusterman et al, 2011) but also enables detection of optogenetically evoked inputs with a precision of 10-30 ms (Rebello et al, 2014;Smear et al, 2011). While behavioural and physiological responses to precisely timed odour stimuli have been observed in insects (Brown et al, 2005;Geffen et al, 2009;Nagel et al, 2015;Riffell et al, 2014;Szyszka et al, 2014;Vickers et al, 2001), in mammals the complex structure of the nasal cavity was generally thought to "wash-out" any temporal structure of the incoming odour plume ((Kepecs et al, 2006) see however (Gupta et al, 2015)). Our results show that on the contrary mice can readily make use of information in odour stimuli fluctuating at frequencies of up to 40 Hz.…”

supporting

confidence: 87%

Mammalian olfaction is a high temporal bandwidth sense

Erskine

Ackels

Dasgupta

et al. 2019

Preprint

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Odours are transported in turbulent plumes resulting locally in highly fluctuating odour concentration (Celani et al., 2014;Murlis et al., 1992;Mylne and Mason, 1991;Shraiman and Siggia, 2000). Yet, whether mammals can make use of the ensuing temporal structure (Celani et al., 2014;Crimaldi and Koseff, 2001;Murlis et al., 1992;Mylne and Mason, 1991;Schmuker et al., 2016;Vickers, 2000) to extract information about the olfactory environment remains unknown. Here, we use dual-energy photoionisation recording with >300 Hz bandwidth to simultaneously determine odour concentrations of two odours in air. We show that temporal correlation of odour concentrations reliably predicts whether odorants emerge from the same or different sources in normal turbulent environments outside and in laboratory conditions. To replicate natural odour dynamics in a reproducible manner we developed a multichannel odour delivery device allowing presentation of several odours with 10 ms temporal resolution. Integrating this device in an automated operant conditioning system we demonstrate that mice can reliably discriminate the correlation structure of odours at frequencies of up to 40 Hz. Consistent with this finding, output neurons in the olfactory bulb show segregated responses depending on the correlation of odour stimuli with populations of 10s of neurons sufficient to reach behavioural performance. Our work thus demonstrates that mammals can perceive temporal structure in odour stimuli at surprisingly fast timescales. This in turn might be useful for key behavioural challenges (Jacobs, 2012) such as odour source separation (Hopfield, 1991), figure-ground separation (Rokni et al., 2014) or odour localisation (Vergassola et al., 2007;Vickers, 2000). Main TextThe turbulent nature of air as well as water flow results in complex temporal fluctuations of odour concentrations that depend on the distance and direction of odour sources (Atema, 1995;Baker et al.

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“…404 Such a system could explain that the response dynamics in experiment depend on the 405 task [60,61]. Generally, a better understanding of the temporal structure of the 406 olfactory code [8,[62][63][64][65][66] might allow to derive more detailed models. These could rely 407 on attractor dynamics that are guided by the excitations and thus respond stronger to 408 the early and large excitations [67,68].…”

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confidence: 99%

Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned

Zwicker

2018

Preprint

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The olfactory system faces the difficult task of identifying an enormous variety of odors independent of their intensity. Primacy coding, where the odor identity is encoded by the receptor types that respond earliest, is one possible representation that can facilitate this task. So far, it is unclear whether primacy coding facilitates typical olfactory tasks and what constraints it implies for the olfactory system. In this paper, we develop a simple model of primacy coding, which we simulate numerically and analyze using a statistical description. We show that the encoded information depends strongly on the number of receptor types included in the primacy representation, but only weakly on the size of the receptor repertoire. The representation is independent of the odor intensity and the transmitted information is useful to perform typical olfactory tasks, like detecting a target odor or discriminating similar mixtures, with close to experimentally measured performance. Interestingly, we find situations in which a smaller receptor repertoire is advantageous for identifying a target odor. The model also suggests that overly sensitive receptor types could dominate the entire response and make the whole array useless, which allows us to predict how receptor arrays need to adapt to stay useful during environmental changes. By quantifying the information transmitted using primacy coding, we can thus connect microscopic characteristics of the olfactory system to its overall performance. Author summaryHumans can identify odors independent of their intensity. Experimental data suggest that this is accomplished by representing the odor identity by the earliest responding receptor types. Using theoretical modeling, we here show that such a primacy code allows discriminating odors with close to experimentally measured performance. This performance depends strongly on the number of receptors considered in the primacy code, but the receptor repertoire size is less important. The model also suggests a strong evolutionary pressure on the receptor sensitivities, which could explain observed receptor copy number adaptations. Taken together, the model connects detailed molecular measurements to large-scale psycho-physical measurements, which will contribute to our understanding of the olfactory system. July 9, 2018 1/22 1 The olfactory system identifies and discriminates odors for solving vital tasks like 2 navigating the environment, identifying food, and engaging in social interactions. These 3 tasks are complicated by the enormous variety of odors, which vary in composition and 4 in the concentrations of their individual molecules. In particular, the olfactory system 5 needs to separately recognize the odor identity (what is there?) and the odor intensity 6 (how much is there?). For instance, the identity is required to decide whether to 7 approach or avoid an odor source, whereas the intensity information is important for 8 localizing it. It is unclear how these two odor properties are separated. 9Odors are sensed by olfactor...

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Olfactory bulb coding of odors, mixtures and sniffs is a linear sum of odor time profiles

Cited by 61 publications

References 48 publications

Inhalation frequency controls reformatting of mitral/tufted cell odor representations in the olfactory bulb

Inhalation frequency controls reformatting of mitral/tufted cell odor representations in the olfactory bulb

Mammalian olfaction is a high temporal bandwidth sense

Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned

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