Dataset Information

Spatiotemporally precise optogenetic activation of sensory neurons in freely walking Drosophila.

ABSTRACT: Previous work has characterized how walking Drosophila coordinate the movements of individual limbs (DeAngelis et al., 2019). To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior. However, it has remained difficult to manipulate neural activity in individual limbs of freely moving animals. Here, we demonstrate a simple method for optogenetic stimulation with body side-, body segment-, and limb-specificity that does not require real-time tracking. Instead, we activate at random, precise locations in time and space and use post hoc analysis to determine behavioral responses to specific activations. Using this method, we have characterized limb coordination and walking behavior in response to transient activation of mechanosensitive bristle neurons and sweet-sensing chemoreceptor neurons. Our findings reveal that activating these neurons has opposite effects on turning, and that activations in different limbs and body regions produce distinct behaviors.

SUBMITTER: DeAngelis BD

PROVIDER: S-EPMC7198233 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Spatiotemporally precise optogenetic activation of sensory neurons in freely walking <i>Drosophila</i>.

DeAngelis Brian D BD Zavatone-Veth Jacob A JA Gonzalez-Suarez Aneysis D AD Clark Damon A DA

eLife 20200422

Previous work has characterized how walking <i>Drosophila</i> coordinate the movements of individual limbs (DeAngelis et al., 2019). To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior. However, it has remained difficult to manipulate neural activity in individual limbs of freely moving animals. Here, we demonstrate a simple method for optogenetic stimulation with body side-, body segment-, and limb-specificity ...[more]

PMID: 32319425

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Project description:Sleep abnormalities have widespread and costly public health consequences, yet we have only a rudimentary understanding of the events occurring at the cellular level in the brain that regulate sleep. Several key signaling molecules that regulate sleep across taxa come from the family of neuropeptide transmitters. For example, in Drosophila melanogaster, the neuropeptide Y (NPY)-related transmitter short neuropeptide F (sNPF) appears to promote sleep. In this study, we utilized optogenetic activation of neuronal populations expressing sNPF to determine the causal effects of precisely timed activity in these cells on sleep behavior. Combining sNPF-GAL4 and UAS-Chrimson transgenes allowed us to activate sNPF neurons using red light. We found that activating sNPF neurons for as little as 3 s at a time of day when most flies were awake caused a rapid transition to sleep that persisted for another 2+ hours following the stimulation. Changing the timing of red light stimulation to times of day when flies were already asleep caused the control flies to wake up (due to the pulse of light), but the flies in which sNPF neurons were activated stayed asleep through the light pulse, and then showed further increases in sleep at later points when they would have normally been waking up. Video recording of individual fly responses to short-term (0.5-20 s) activation of sNPF neurons demonstrated a clear light duration-dependent decrease in movement during the subsequent 4-min period. These results provide supportive evidence that sNPF-producing neurons promote long-lasting increases in sleep, and show for the first time that even brief periods of activation of these neurons can cause changes in behavior that persist after cessation of activation. We have also presented evidence that sNPF neuron activation produces a homeostatic sleep drive that can be dissipated at times long after the neurons were stimulated. Future studies will determine the specific roles of sub-populations of sNPF-producing neurons, and will also assess how sNPF neurons act in concert with other neuronal circuits to control sleep.

Project description:The lack of a deeper understanding of how olfactory sensory neurons (OSNs) encode odors has hindered the progress in understanding the olfactory signal processing in higher brain centers. Here we employ methods of system identification to investigate the encoding of time-varying odor stimuli and their representation for further processing in the spike domain by Drosophila OSNs. In order to apply system identification techniques, we built a novel low-turbulence odor delivery system that allowed us to deliver airborne stimuli in a precise and reproducible fashion. The system provides a 1% tolerance in stimulus reproducibility and an exact control of odor concentration and concentration gradient on a millisecond time scale. Using this novel setup, we recorded and analyzed the in-vivo response of OSNs to a wide range of time-varying odor waveforms. We report for the first time that across trials the response of OR59b OSNs is very precise and reproducible. Further, we empirically show that the response of an OSN depends not only on the concentration, but also on the rate of change of the odor concentration. Moreover, we demonstrate that a two-dimensional (2D) Encoding Manifold in a concentration-concentration gradient space provides a quantitative description of the neuron's response. We then use the white noise system identification methodology to construct one-dimensional (1D) and two-dimensional (2D) Linear-Nonlinear-Poisson (LNP) cascade models of the sensory neuron for a fixed mean odor concentration and fixed contrast. We show that in terms of predicting the intensity rate of the spike train, the 2D LNP model performs on par with the 1D LNP model, with a root mean-square error (RMSE) increase of about 5 to 10%. Surprisingly, we find that for a fixed contrast of the white noise odor waveforms, the nonlinear block of each of the two models changes with the mean input concentration. The shape of the nonlinearities of both the 1D and the 2D LNP model appears to be, for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

Dataset Information

Spatiotemporally precise optogenetic activation of sensory neurons in freely walking Drosophila.

Publications

Spatiotemporally precise optogenetic activation of sensory neurons in freely walking <i>Drosophila</i>.

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