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, Zavatone-Veth, and Clark, 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.
Data availability
Source data were deposited on Dryad: https://doi.org/10.5061/dryad.nzs7h44nk.Analysis code is available here: https://github.com/ClarkLabCode/FlyLimbOptoCode.
-
Data from: Spatiotemporally precise optogenetic activation of sensory neurons in freely walking <em>Drosophila</em>Dryad Digital Repository, 10.5061/dryad.nzs7h44nk.
Article and author information
Author details
Funding
National Institutes of Health (EY026555)
- Brian D DeAngelis
- Damon A Clark
National Institutes of Health (EY026878)
- Brian D DeAngelis
- Damon A Clark
Chicago Community Trust (Searle Scholar Award)
- Damon A Clark
Alfred P. Sloan Foundation (Fellowship)
- Damon A Clark
National Science Foundation (GRF)
- Brian D DeAngelis
Smith Family Foundation (Scholar Award)
- Brian D DeAngelis
- Damon A Clark
National Science Foundation (IOS 1558103)
- Jacob A Zavatone-Veth
- Damon A Clark
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, DeAngelis et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 3,317
- views
-
- 386
- downloads
-
- 9
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Computational and Systems Biology
- Neuroscience
Audiovisual information reaches the brain via both sustained and transient input channels, representing signals’ intensity over time or changes thereof, respectively. To date, it is unclear to what extent transient and sustained input channels contribute to the combined percept obtained through multisensory integration. Based on the results of two novel psychophysical experiments, here we demonstrate the importance of the transient (instead of the sustained) channel for the integration of audiovisual signals. To account for the present results, we developed a biologically inspired, general-purpose model for multisensory integration, the multisensory correlation detectors, which combines correlated input from unimodal transient channels. Besides accounting for the results of our psychophysical experiments, this model could quantitatively replicate several recent findings in multisensory research, as tested against a large collection of published datasets. In particular, the model could simultaneously account for the perceived timing of audiovisual events, multisensory facilitation in detection tasks, causality judgments, and optimal integration. This study demonstrates that several phenomena in multisensory research that were previously considered unrelated, all stem from the integration of correlated input from unimodal transient channels.
-
- Neuroscience
This study investigates the functional network underlying response inhibition in the human brain, particularly the role of the basal ganglia in successful action cancellation. Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task to examine this network. We merge five such datasets, using a novel aggregatory method allowing the unification of raw fMRI data across sites. This meta-analysis, along with other recent aggregatory fMRI studies, does not find evidence for the innervation of the hyperdirect or indirect cortico-basal-ganglia pathways in successful response inhibition. What we do find, is large subcortical activity profiles for failed stop trials. We discuss possible explanations for the mismatch of findings between the fMRI results presented here and results from other research modalities that have implicated nodes of the basal ganglia in successful inhibition. We also highlight the substantial effect smoothing can have on the conclusions drawn from task-specific general linear models. First and foremost, this study presents a proof of concept for meta-analytical methods that enable the merging of extensive, unprocessed, or unreduced datasets. It demonstrates the significant potential that open-access data sharing can offer to the research community. With an increasing number of datasets being shared publicly, researchers will have the ability to conduct meta-analyses on more than just summary data.