Whether leptin acts in the paraventricular nucleus (PVN) to increase sympathetic nerve activity (SNA) is unclear, since PVN leptin receptors (LepR) are sparse. We show in rats that PVN leptin slowly increases SNA to muscle and brown adipose tissue, because it induces the expression of its own receptor and synergizes with local glutamatergic neurons. PVN LepR are not expressed in astroglia and rarely in microglia; instead, glutamatergic neurons express LepR, some of which project to a key presympathetic hub, the rostral ventrolateral medulla (RVLM). In PVN slices from mice expressing GCaMP6, leptin excites glutamatergic neurons. LepR are expressed mainly in thyrotropin-releasing hormone (TRH) neurons, some of which project to the RVLM. Injections of TRH into the RVLM and dorsomedial hypothalamus increase SNA, highlighting these nuclei as likely targets. We suggest that this neuropathway becomes important in obesity, in which elevated leptin maintains the hypothalamic pituitary thyroid axis, despite leptin resistance.
All data generated and analyzed are included in the manuscript. Source data files are provided for relevant figures.
Leptin increases sympathetic nerve activity via induction of its own receptor in glutamatergic neurons in the paraventricular nucleusDryad, doi:10.5061/dryad.wwpzgmsg5.
- Virginia L Brooks
- Virginia L Brooks
- Daniel L Marks
- Andrei D Sdrulla
- Christopher J Madden
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (TR01_IP00000151) of Oregon Health & Science University. All surgery was performed under isoflurane, alpha-chloralose, or pentobarbital anesthesia, and every effort was made to minimize suffering.
- Joel K Elmquist, University of Texas Southwestern Medical Center, United States
© 2020, Shi 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.
Deciphering patterns of connectivity between neurons in the brain is a critical step toward understanding brain function. Imaging-based neuroanatomical tracing identifies area-to-area or sparse neuron-to-neuron connectivity patterns, but with limited throughput. Barcode-based connectomics maps large numbers of single-neuron projections, but remains a challenge for jointly analyzing single-cell transcriptomics. Here, we established a rAAV2-retro barcode-based multiplexed tracing method that simultaneously characterizes the projectome and transcriptome at the single neuron level. We uncovered dedicated and collateral projection patterns of ventromedial prefrontal cortex (vmPFC) neurons to five downstream targets and found that projection-defined vmPFC neurons are molecularly heterogeneous. We identified transcriptional signatures of projection-specific vmPFC neurons, and verified Pou3f1 as a marker gene enriched in neurons projecting to the lateral hypothalamus, denoting a distinct subset with collateral projections to both dorsomedial striatum and lateral hypothalamus. In summary, we have developed a new multiplexed technique whose paired connectome and gene expression data can help reveal organizational principles that form neural circuits and process information.
Blindness affects millions of people around the world. A promising solution to restoring a form of vision for some individuals are cortical visual prostheses, which bypass part of the impaired visual pathway by converting camera input to electrical stimulation of the visual system. The artificially induced visual percept (a pattern of localized light flashes, or ‘phosphenes’) has limited resolution, and a great portion of the field’s research is devoted to optimizing the efficacy, efficiency, and practical usefulness of the encoding of visual information. A commonly exploited method is non-invasive functional evaluation in sighted subjects or with computational models by using simulated prosthetic vision (SPV) pipelines. An important challenge in this approach is to balance enhanced perceptual realism, biologically plausibility, and real-time performance in the simulation of cortical prosthetic vision. We present a biologically plausible, PyTorch-based phosphene simulator that can run in real-time and uses differentiable operations to allow for gradient-based computational optimization of phosphene encoding models. The simulator integrates a wide range of clinical results with neurophysiological evidence in humans and non-human primates. The pipeline includes a model of the retinotopic organization and cortical magnification of the visual cortex. Moreover, the quantitative effects of stimulation parameters and temporal dynamics on phosphene characteristics are incorporated. Our results demonstrate the simulator’s suitability for both computational applications such as end-to-end deep learning-based prosthetic vision optimization as well as behavioral experiments. The modular and open-source software provides a flexible simulation framework for computational, clinical, and behavioral neuroscientists working on visual neuroprosthetics.