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Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.

Rospars JP, Grémiaux A, Jarriault D, Chaffiol A, Monsempes C, Deisig N, Anton S, Lucas P, Martinez D - PLoS Comput. Biol. (2014)

Bottom Line: We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs.So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate).Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.

View Article: PubMed Central - PubMed

Affiliation: Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.

ABSTRACT
In the olfactory system of male moths, a specialized subset of neurons detects and processes the main component of the sex pheromone emitted by females. It is composed of several thousand first-order olfactory receptor neurons (ORNs), all expressing the same pheromone receptor, that contact synaptically a few tens of second-order projection neurons (PNs) within a single restricted brain area. The functional simplicity of this system makes it a favorable model for studying the factors that contribute to its exquisite sensitivity and speed. Sensory information--primarily the identity and intensity of the stimulus--is encoded as the firing rate of the action potentials, and possibly as the latency of the neuron response. We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs. Modelling showed that the increased sensitivity of PNs can be explained by the ORN-to-PN convergent architecture alone, whereas their faster response also requires cell-to-cell heterogeneity of the ORN population. So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate). Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.

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Dose-response curves of PNs are shifted to left of ORN curves and explain ORN-to-PN transfer functions.(A) Medians (circles) and quantiles 10% and 90% (vertical dashed lines) of all F measured at a given dose, as shown in Fig. 5. Dose-firing rate curves of ORN (blue) and PN (red) populations reconstructed from parameters of individual C–F curves shown in Fig. 6, based on median (solid), 10% most responsive neurons (dashed, based on quantiles 90% for FM and 10% for C1/2, n) and 90% less responsive neurons (dash-dotted). (B) Dose-latency curves of ORNs (blue) and PNs (red) based on median, 90% and 10% quantiles. Same representations as in (A) based either on pooled L (Fig. 5) or on parameters of C-L curves (Fig. 7). (C) Median transfer function for firing rates (solid, eq. 9); it can be approximated by FPN  = 62.5/(1+ (1.5/FORN)1.15); inset: detail of most nonlinear part from threshold to ED50 of ORNs. Transfer function for the 10% most responsive neurons (dashed, derived from (A) by coupling most responsive ORNs and PNs) and for the 10% least responsive ones (dash-dotted). (D) Median transfer function for latencies running from right (low doses) to left (high doses) (solid, eq. 12); inset: linear part from threshold to ED50 of ORNs. Transfer functions for the 10% fastest neurons (dashed) and for the 10% slowest neurons (dash-dot). (E) Distributions of thresholds C0 in ORNs (blue, N = 38) and PNs (red, N = 37); empirical CDFs (staircases) with fitted normal CDF (solid curve) and corresponding PDF (dashed curve); maximum contrast at C0Δ  = −1.9 log ng (dashed vertical line) with 17% ORNs and 85% PNs activated. (F) Distributions of ED50 C1/2, same N's and representation as in (E); maximum contrast at C1/2Δ  = 0 log ng (dashed vertical line) with 2% of ORNs and 98% of PNs above their C1/2.
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pcbi-1003975-g008: Dose-response curves of PNs are shifted to left of ORN curves and explain ORN-to-PN transfer functions.(A) Medians (circles) and quantiles 10% and 90% (vertical dashed lines) of all F measured at a given dose, as shown in Fig. 5. Dose-firing rate curves of ORN (blue) and PN (red) populations reconstructed from parameters of individual C–F curves shown in Fig. 6, based on median (solid), 10% most responsive neurons (dashed, based on quantiles 90% for FM and 10% for C1/2, n) and 90% less responsive neurons (dash-dotted). (B) Dose-latency curves of ORNs (blue) and PNs (red) based on median, 90% and 10% quantiles. Same representations as in (A) based either on pooled L (Fig. 5) or on parameters of C-L curves (Fig. 7). (C) Median transfer function for firing rates (solid, eq. 9); it can be approximated by FPN  = 62.5/(1+ (1.5/FORN)1.15); inset: detail of most nonlinear part from threshold to ED50 of ORNs. Transfer function for the 10% most responsive neurons (dashed, derived from (A) by coupling most responsive ORNs and PNs) and for the 10% least responsive ones (dash-dotted). (D) Median transfer function for latencies running from right (low doses) to left (high doses) (solid, eq. 12); inset: linear part from threshold to ED50 of ORNs. Transfer functions for the 10% fastest neurons (dashed) and for the 10% slowest neurons (dash-dot). (E) Distributions of thresholds C0 in ORNs (blue, N = 38) and PNs (red, N = 37); empirical CDFs (staircases) with fitted normal CDF (solid curve) and corresponding PDF (dashed curve); maximum contrast at C0Δ  = −1.9 log ng (dashed vertical line) with 17% ORNs and 85% PNs activated. (F) Distributions of ED50 C1/2, same N's and representation as in (E); maximum contrast at C1/2Δ  = 0 log ng (dashed vertical line) with 2% of ORNs and 98% of PNs above their C1/2.

Mentions: PNs are clearly more sensitive than ORNs. For example, the recruitment of PNs starts at lower doses as half of the PNs were activated at −3 log ng and half of the ORNs only at −0.5 log ng (not shown). PNs approach saturation at doses 3 orders of magnitude lower than ORNs. These changes testify that major transformations take place in the neural network of the cumulus when the sensory signal passes from ORN to PN. The ORN-to-PN transformations can be represented in two complementary ways: either by pairs of dose-response curves (Fig. 7A, B), or by transfer functions linking the latencies (or frequencies) of the ORNs and PNs at the same doses (Fig. 8C, D). Interestingly these curves (and the transfer functions derived from them) can be determined in two different ways, either directly from the pooled distributions of F and L at each dose (Figs. 4, 5), or from the distributions of the parameters determined on single dose-response plots (Figs. 6, 7). Both methods give practically the same results as shown here by the median and extreme values (quantiles 10% and 90%) of the firing rates (Fig. 8A) and the latencies (Fig. 8B).


Heterogeneity and convergence of olfactory first-order neurons account for the high speed and sensitivity of second-order neurons.

Rospars JP, Grémiaux A, Jarriault D, Chaffiol A, Monsempes C, Deisig N, Anton S, Lucas P, Martinez D - PLoS Comput. Biol. (2014)

Dose-response curves of PNs are shifted to left of ORN curves and explain ORN-to-PN transfer functions.(A) Medians (circles) and quantiles 10% and 90% (vertical dashed lines) of all F measured at a given dose, as shown in Fig. 5. Dose-firing rate curves of ORN (blue) and PN (red) populations reconstructed from parameters of individual C–F curves shown in Fig. 6, based on median (solid), 10% most responsive neurons (dashed, based on quantiles 90% for FM and 10% for C1/2, n) and 90% less responsive neurons (dash-dotted). (B) Dose-latency curves of ORNs (blue) and PNs (red) based on median, 90% and 10% quantiles. Same representations as in (A) based either on pooled L (Fig. 5) or on parameters of C-L curves (Fig. 7). (C) Median transfer function for firing rates (solid, eq. 9); it can be approximated by FPN  = 62.5/(1+ (1.5/FORN)1.15); inset: detail of most nonlinear part from threshold to ED50 of ORNs. Transfer function for the 10% most responsive neurons (dashed, derived from (A) by coupling most responsive ORNs and PNs) and for the 10% least responsive ones (dash-dotted). (D) Median transfer function for latencies running from right (low doses) to left (high doses) (solid, eq. 12); inset: linear part from threshold to ED50 of ORNs. Transfer functions for the 10% fastest neurons (dashed) and for the 10% slowest neurons (dash-dot). (E) Distributions of thresholds C0 in ORNs (blue, N = 38) and PNs (red, N = 37); empirical CDFs (staircases) with fitted normal CDF (solid curve) and corresponding PDF (dashed curve); maximum contrast at C0Δ  = −1.9 log ng (dashed vertical line) with 17% ORNs and 85% PNs activated. (F) Distributions of ED50 C1/2, same N's and representation as in (E); maximum contrast at C1/2Δ  = 0 log ng (dashed vertical line) with 2% of ORNs and 98% of PNs above their C1/2.
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pcbi-1003975-g008: Dose-response curves of PNs are shifted to left of ORN curves and explain ORN-to-PN transfer functions.(A) Medians (circles) and quantiles 10% and 90% (vertical dashed lines) of all F measured at a given dose, as shown in Fig. 5. Dose-firing rate curves of ORN (blue) and PN (red) populations reconstructed from parameters of individual C–F curves shown in Fig. 6, based on median (solid), 10% most responsive neurons (dashed, based on quantiles 90% for FM and 10% for C1/2, n) and 90% less responsive neurons (dash-dotted). (B) Dose-latency curves of ORNs (blue) and PNs (red) based on median, 90% and 10% quantiles. Same representations as in (A) based either on pooled L (Fig. 5) or on parameters of C-L curves (Fig. 7). (C) Median transfer function for firing rates (solid, eq. 9); it can be approximated by FPN  = 62.5/(1+ (1.5/FORN)1.15); inset: detail of most nonlinear part from threshold to ED50 of ORNs. Transfer function for the 10% most responsive neurons (dashed, derived from (A) by coupling most responsive ORNs and PNs) and for the 10% least responsive ones (dash-dotted). (D) Median transfer function for latencies running from right (low doses) to left (high doses) (solid, eq. 12); inset: linear part from threshold to ED50 of ORNs. Transfer functions for the 10% fastest neurons (dashed) and for the 10% slowest neurons (dash-dot). (E) Distributions of thresholds C0 in ORNs (blue, N = 38) and PNs (red, N = 37); empirical CDFs (staircases) with fitted normal CDF (solid curve) and corresponding PDF (dashed curve); maximum contrast at C0Δ  = −1.9 log ng (dashed vertical line) with 17% ORNs and 85% PNs activated. (F) Distributions of ED50 C1/2, same N's and representation as in (E); maximum contrast at C1/2Δ  = 0 log ng (dashed vertical line) with 2% of ORNs and 98% of PNs above their C1/2.
Mentions: PNs are clearly more sensitive than ORNs. For example, the recruitment of PNs starts at lower doses as half of the PNs were activated at −3 log ng and half of the ORNs only at −0.5 log ng (not shown). PNs approach saturation at doses 3 orders of magnitude lower than ORNs. These changes testify that major transformations take place in the neural network of the cumulus when the sensory signal passes from ORN to PN. The ORN-to-PN transformations can be represented in two complementary ways: either by pairs of dose-response curves (Fig. 7A, B), or by transfer functions linking the latencies (or frequencies) of the ORNs and PNs at the same doses (Fig. 8C, D). Interestingly these curves (and the transfer functions derived from them) can be determined in two different ways, either directly from the pooled distributions of F and L at each dose (Figs. 4, 5), or from the distributions of the parameters determined on single dose-response plots (Figs. 6, 7). Both methods give practically the same results as shown here by the median and extreme values (quantiles 10% and 90%) of the firing rates (Fig. 8A) and the latencies (Fig. 8B).

Bottom Line: We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs.So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate).Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.

View Article: PubMed Central - PubMed

Affiliation: Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche 1392 Institut d'Ecologie et des Sciences de l'Environnement de Paris, Versailles, France.

ABSTRACT
In the olfactory system of male moths, a specialized subset of neurons detects and processes the main component of the sex pheromone emitted by females. It is composed of several thousand first-order olfactory receptor neurons (ORNs), all expressing the same pheromone receptor, that contact synaptically a few tens of second-order projection neurons (PNs) within a single restricted brain area. The functional simplicity of this system makes it a favorable model for studying the factors that contribute to its exquisite sensitivity and speed. Sensory information--primarily the identity and intensity of the stimulus--is encoded as the firing rate of the action potentials, and possibly as the latency of the neuron response. We found that over all their dynamic range, PNs respond with a shorter latency and a higher firing rate than most ORNs. Modelling showed that the increased sensitivity of PNs can be explained by the ORN-to-PN convergent architecture alone, whereas their faster response also requires cell-to-cell heterogeneity of the ORN population. So, far from being detrimental to signal detection, the ORN heterogeneity is exploited by PNs, and results in two different schemes of population coding based either on the response of a few extreme neurons (latency) or on the average response of many (firing rate). Moreover, ORN-to-PN transformations are linear for latency and nonlinear for firing rate, suggesting that latency could be involved in concentration-invariant coding of the pheromone blend and that sensitivity at low concentrations is achieved at the expense of precise encoding at high concentrations.

Show MeSH
Related in: MedlinePlus