The role of PDF neurons in setting preferred temperature before dawn in Drosophila
- Cincinnati Children's Hospital Medical Center, United States
- University College London, United Kingdom
- Hokkaido University, Japan
- University of London, United Kingdom
- University of Cincinnati, United States
- Westfälische Wilhelms University, Germany
Abstract
Animals have sophisticated homeostatic controls. While mammalian body temperature fluctuates throughout the day, small ectotherms, such as Drosophila, achieve a body temperature rhythm (BTR) through their preference of environmental temperature. Here, we demonstrate that pigment dispersing factor (PDF) neurons play an important role in setting preferred temperature before dawn. We show that small lateral ventral neurons (sLNvs), a subset of PDF neurons, activate the dorsal neurons 2 (DN2s), the main circadian clock cells that regulate temperature preference rhythm (TPR). The number of temporal contacts between sLNvs and DN2s peak before dawn. Our data suggest that the thermosensory Anterior Cells (ACs) likely contact sLNvs via serotonin signaling. Together, the ACs-sLNs-DN2s neural circuit regulates the proper setting of temperature preference before dawn. Given that sLNvs are important for sleep and that BTR and sleep have a close temporal relationship, our data highlight a possible neuronal interaction between body temperature and sleep regulation.
Article and author information
Author details
Funding
National Institutes of Health (R01 grant GM107582)
- Fumika N Hamada
March of Dimes Foundation (Basil O'Connor Starter Scholar Research Award)
- Fumika N Hamada
Japan Science and Technology Agency (PRESTO)
- Fumika N Hamada
Biotechnology and Biological Sciences Research Council
- Ralf Stanewsky
Seventh Framework Programme
- Ralf Stanewsky
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- K VijayRaghavan, National Centre for Biological Sciences, Tata Institute of Fundamental Research, India
Version history
- Received: November 12, 2016
- Accepted: April 23, 2017
- Accepted Manuscript published: May 2, 2017 (version 1)
- Version of Record published: May 30, 2017 (version 2)
Copyright
© 2017, Tang 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
-
- 3,327
- views
-
- 644
- downloads
-
- 36
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
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)
The role of PDF neurons in setting preferred temperature before dawn in Drosophila
eLife 6:e23206.
https://doi.org/10.7554/eLife.23206
Further reading
-
- Neuroscience
Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mechanisms cost energy. We examined four such mechanisms along with the associated scaling of the energetic costs. We then embedded these energetic costs for reliability in artificial neural networks (ANNs) with trainable stochastic synapses, and trained these networks on standard image classification tasks. The resulting networks revealed a tradeoff between circuit performance and the energetic cost of synaptic reliability. Additionally, the optimised networks exhibited two testable predictions consistent with pre-existing experimental data. Specifically, synapses with lower variability tended to have (1) higher input firing rates and (2) lower learning rates. Surprisingly, these predictions also arise when synapse statistics are inferred through Bayesian inference. Indeed, we were able to find a formal, theoretical link between the performance-reliability cost tradeoff and Bayesian inference. This connection suggests two incompatible possibilities: evolution may have chanced upon a scheme for implementing Bayesian inference by optimising energy efficiency, or alternatively, energy-efficient synapses may display signatures of Bayesian inference without actually using Bayes to reason about uncertainty.
-
- Neuroscience
Resting-state brain networks (RSNs) have been widely applied in health and disease, but the interpretation of RSNs in terms of the underlying neural activity is unclear. To address this fundamental question, we conducted simultaneous recordings of whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions of rats. Our data reveal that for both recording sites, spatial maps derived from band-specific local field potential (LFP) power can account for up to 90% of the spatial variability in RSNs derived from rsfMRI signals. Surprisingly, the time series of LFP band power can only explain to a maximum of 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has minimal impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggests that electrophysiological activity alone does not fully explain the effects observed in the rsfMRI signal, implying the existence of an rsfMRI component contributed by ‘electrophysiology-invisible’ signals. These findings offer a novel perspective on our understanding of RSN interpretation.
