Synaptic control of temporal processing in theDrosophilaolfactory system

Abstract

Temporal filtering of sensory stimuli is a key neural computation, but the way such filters are implemented within the brain is unclear. One potential mechanism for implementing temporal filters is short-term synaptic plasticity, which is governed in part by the expression of pre-synaptic proteins that position synaptic vesicles at different distances to calcium channels. Here we leveraged the Drosophila olfactory system to directly test the hypothesis that short-term synaptic plasticity shapes temporal filtering of sensory stimuli. We used optogenetic activation to drive olfactory receptor neuron (ORN) activity with high temporal precision and knocked down the presynaptic priming factor unc13A specifically in ORNs. We found that this manipulation specifically decreases and delays transmission of high frequencies, leading to poorer encoding of distant plume filaments. We replicate this effect using a previously-developed model of transmission at this synapse, which features two components with different depression kinetics. Finally, we show that upwind running, a key component of odor source localization, is preferentially driven by high-frequency stimulus fluctuations, and this response is reduced by unc13A knock-down in ORNs. Our work links the extraction of particular temporal features of a sensory stimulus to the expression of particular presynaptic molecules.

Novelty detection and multiple timescale integration drive Drosophila orientation dynamics in temporally diverse olfactory environments

“…Meanwhile, for a given pulse duration, mean orientation increased with frequency up to around 3Hz, before decreasing at very high frequencies. This aligns with previous studies that have shown that olfactory receptor neurons can respond to high frequencies (Fox and Nagel, 2021).…”

“…Meanwhile, for a given pulse duration, mean orientation increased with frequency up to around 3Hz, before decreasing at very high frequencies. This aligns with previous studies that have shown that olfactory receptor neurons can respond to high frequencies (Fox and Nagel, 2021). To quantify how the frequency, duration, and intermittency of odor encounters influence upwind bias, we calculated the instantaneous angular velocity as a function of orientation at each time point during the ON block (Materials and Methods) (Figure 2B).…”

Homeostatic Synaptic Plasticity Rescues Neural Coding Reliability

“…The above results suggest that high-frequency synaptic transmission is most sensitive to manipulations of ORN AZs, consistent with previous reports 49 . High firing rates usually occur at the beginning of the odor response within the first 200 ms (Figure 1B, C).…”

Sensing complementary temporal features of odor signals enhances navigation of diverse turbulent plumes

“…Given that this timescale is similar to that of the behavioral adaptation found by Álvarez-Salvado et al, 2018 , it is plausible that this modulation could improve navigation. It has also been shown that knockdown of the priming factor unc13A impedes fast components of ORN-PN synaptic transmission in Drosophila ( Fulterer et al, 2018 ; Pooryasin et al, 2021 ) and affects behavioral responses to signals at higher frequencies ( Fox and Nagel, 2021 ). It would be illuminating to test how unc13A knockdown affects navigation in complex plumes of different frequency content.…”

“…Indeed, many organisms have evolved olfactory receptor neurons (ORNs) that respond to chemical signals with high temporal precision ( Gorur-Shandilya et al, 2017 ; Jacob et al, 2017 ; Nagel and Wilson, 2011 ; Szyszka et al, 2014 ; Szyszka et al, 2012 ). ORN firing responses are strongly time-locked to the arrival time of an odor ( Gorur-Shandilya et al, 2017 ), and fast synaptic mechanisms ( Fox and Nagel, 2021 ; Martelli et al, 2013 ) allow this information to be passed quickly downstream, within milliseconds, to projection neurons (PNs) in the antennal lobe, driving rapid behavioral responses ( Bhandawat et al, 2010 ). Such precision has been suggested to allow accurate encoding of temporal features of the odor signal ( Nagel et al, 2015 ), such as the frequency of odor arrivals.…”