@article {70407, title = {0064 STK32A Links Sleep Homeostasis to Suppression of Sensory and Motor Systems}, journal = {Sleep}, volume = {49}, year = {2026}, month = {2026 May 08}, pages = {A28-A29}, abstract = {

Sleep is regulated by a homeostatic process and associated with an increased arousal threshold, but the genetic and neuronal mechanisms that implement these essential features of sleep remain poorly understood.To address these fundamental questions, we performed a zebrafish genetic screen informed by human genome-wide association studies.We found that mutation of serine/threonine kinase 32a (stk32a) results in increased sleep and impaired sleep homeostasis in both zebrafish and mice, and that stk32a acts downstream of neurotensin signaling and the serotonergic raphe in zebrafish. stk32a mutation reduces phosphorylation of neurofilament proteins, which are co-expressed with stk32a in neurons that regulate motor activity and in lateral line hair cells that detect environmental stimuli, and ablating these cells phenocopies stk32a mutation. Neurotensin signaling inhibits specific sensory and motor populations, and blocks stimulus-evoked responses of neurons that relay sensory information from hair cells to the brain.Our work thus shows that stk32a is an evolutionarily conserved sleep regulator that links neuropeptidergic and neuromodulatory systems to homeostatic sleep drive and changes in arousal threshold, which are implemented through suppression of specific sensory and motor systems.

}, issn = {0161-8105}, doi = {10.1093/sleep/zsag091.0064}, url = {https://doi.org/10.1093/sleep/zsag091.0064}, author = {Tran, Steven and Emtage, Jasmine and Zhang, Chaodong and Liu, Xiaoyao and Lecoeuche, Marina and Oikonomou, Grigorios and Narayan, Sujatha and Ahrens, Misha and Chou, Tsui-Fen and Xu, Min and Liu, Qinghua and Prober, David} } @article {70427, title = {Whole brain mapping of spinal-projecting neurons in larval zebrafish}, journal = {bioRxiv}, year = {2026}, month = {2026 May 25}, abstract = {

To elicit voluntary movements and integrative reflexes underlying behavior, the brain sends command signals to the spinal cord via specialized long-range descending neurons, known as spinal-projecting neurons (SPNs). The vast and widespread distribution of SPNs, combined with their complex long-distance connectivity, poses a significant challenge for mapping their anatomical organization and associating specific populations with distinct functions. Here we took advantage of the transparency and genetic accessibility of larval zebrafish to uncover the fundamental principles of SPN anatomical organization in a Teleost. Using an optical backfilling method relying on photoactivable GFP, we generate a whole-brain map of all neurons sending axons towards the spinal cord. This approach reveals far more SPNs than previously described through conventional strategies, offering an unparalleled opportunity to revisit distinct spinal-projecting nuclei distributed across hindbrain, midbrain, and diencephalic structures. Combining information on cell location, morphology, and projection patterns, we propose tentative homological designations for zebrafish of SPN nuclei based on established descriptions in mammals and other vertebrates.

}, doi = {10.64898/2026.05.20.726602}, url = {https://www.biorxiv.org/content/early/2026/05/25/2026.05.20.726602}, author = {Carbo-Tano, Martin and Fidelin, Kevin and Welch, Tom and Narayan, Sujatha and Ahrens, Misha and Dubuc, R{\'e}jean and Wyart, Claire} } @article {47262, title = {Simultaneous denoising, deconvolution, and demixing of calcium imaging data.}, journal = {Neuron}, volume = {89}, year = {2016}, month = {2016 Jan 20}, pages = {285-99}, abstract = {

We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in\ vitro and in\ vivo multi-neuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2015.11.037}, author = {Pnevmatikakis, Eftychios A and Soudry, Daniel and Gao, Yuanjun and Machado, Timothy A and Merel, Josh and Pfau, David and Reardon, Thomas and Mu, Yu and Lacefield, Clay and Yang, Weijian and Ahrens, Misha and Bruno, Randy and Jessell, Thomas M and Peterka, Darcy S and Yuste, Rafael and Paninski, Liam} }