The neuropeptides tachykinin2 (Tac2) and kisspeptin (Kiss1) in hypothalamic arcuate nucleus Kiss1 (Kiss1ARH) neurons are essential for pulsatile release of GnRH and reproduction. Since 17β-estradiol (E2) decreases Kiss1 and Tac2 mRNA expression in Kiss1ARH neurons, the role of Kiss1ARH neurons during E2-driven anorexigenic states and their coordination of POMC and NPY/AgRP feeding circuits have been largely ignored. Presently, we show that E2 augmented the excitability of Kiss1ARH neurons by amplifying Cacna1g, Hcn1 and Hcn2 mRNA expression and T-type calcium and h-currents. E2 increased Slc17a6 mRNA expression and glutamatergic synaptic input to arcuate neurons, which excited POMC and inhibited NPY/AgRP neurons via metabotropic receptors. Deleting Slc17a6 in Kiss1 neurons eliminated glutamate release and led to conditioned place preference for sucrose in E2-treated KO female mice. Therefore, the E2-driven increase in Kiss1 neuronal excitability and glutamate neurotransmission may play a key role in governing the motivational drive for palatable food in females.
All data generated or analysed during this study are included in the manuscript and supporting files.
- Martin J Kelly
- Oline K Rønnekleiv
- Oline K Rønnekleiv
- Martin J Kelly
- Richard D Palmiter
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: Animal experimentation: This study was performed in strict accordance with the recommendations from the National Institutes of Health Guide for the care and use of Laboratory Animals. All animal procedures were conducted according to the approved institutional animal care and use committee (IACUC) protocols (#IP00000585; #IP00000382) at Oregon health and Science University and (#2183-02) at University of Washington. All surgeries were performed using aseptic techniques under isoflurane anesthesia, and every effort was made to minimize suffering.
- Catherine Dulac, Harvard University, United States
© 2018, Qiu 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.