Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 83,578 bioRxiv papers from 360,137 authors.
Most downloaded bioRxiv papers, since beginning of last month
in category neuroscience
14,555 results found. For more information, click each entry to expand.
14,964 downloads neuroscience
David Brann, Tatsuya Tsukahara, Caleb Weinreb, Marcela Lipovsek, Koen Van den Berge, Boying Gong, Rebecca Chance, Iain C Macaulay, Hsin-jung Chou, Russell Fletcher, Diya Das, Kelly Street, Hector Roux de Bézieux, Yoon-Gi Choi, Davide Risso, Sandrine Dudoit, Elizabeth Purdom, Jonathan C Mill, Ralph Abi Hachem, Hiroaki Matsunami, Darren W. Logan, Bradley Goldstein, Matthew S. Grubb, John Ngai, Sandeep Robert Datta
Altered olfactory function is a common symptom of COVID-19, but its etiology is unknown. A key question is whether SARS-CoV-2 (CoV-2) - the causal agent in COVID-19 - affects olfaction directly by infecting olfactory sensory neurons or their targets in the olfactory bulb, or indirectly, through perturbation of supporting cells. Here we identify cell types in the olfactory epithelium and olfactory bulb that express SARS-CoV-2 cell entry molecules. Bulk sequencing revealed that mouse, non-human primate and human olfactory mucosa expresses two key genes involved in CoV-2 entry, ACE2 and TMPRSS2. However, single cell sequencing and immunostaining demonstrated ACE2 expression in support cells, stem cells, and perivascular cells; in contrast, neurons in both the olfactory epithelium and bulb did not express ACE2 message or protein. These findings suggest that CoV-2 infection of non-neuronal cell types leads to anosmia and related disturbances in odor perception in COVID-19 patients. ### Competing Interest Statement DL is an employee of Mars, Inc. None of the other authors have competing interests to declare.
13,193 downloads neuroscience
Brain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant package.
2,765 downloads neuroscience
A decade after the first successful attempt to decode speech directly from human brain signals, accuracy and speed remain far below that of natural speech or typing. Here we show how to achieve high accuracy from the electrocorticogram at natural-speech rates, even with few data (on the order of half an hour of spoken speech). Taking a cue from recent advances in machine translation and automatic speech recognition, we train a recurrent neural network to map neural signals directly to word sequences (sentences). In particular, the network first encodes a sentence-length sequence of neural activity into an abstract representation, and then decodes this representation, word by word, into an English sentence. For each participant, training data consist of several spoken repeats of a set of some 30-50 sentences, along with the corresponding neural signals at each of about 250 electrodes distributed over peri-Sylvian speech cortices. Average word error rates across a validation (held-out) sentence set are as low as 7% for some participants, as compared to the previous state of the art of greater than 60%. Finally, we show how to use transfer learning to overcome limitations on data availability: Training certain components of the network under multiple participants' data, while keeping other components (e.g., the first hidden layer) "proprietary," can improve decoding performance--despite very different electrode coverage across participants.
2,251 downloads neuroscience
Daniel Witvliet, Ben Mulcahy, James K. Mitchell, Yaron Meirovitch, Daniel R. Berger, Yuelong Wu, Yufang Liu, Wan Xian Koh, Rajeev Parvathala, Douglas Holmyard, Richard L. Schalek, Nir Shavit, Andrew D. Chisholm, Jeff W. Lichtman, Aravinthan Samuel, Mei Zhen
From birth to adulthood, an animal's nervous system changes as its body grows and its behaviours mature. However, the extent of circuit remodelling across the connectome is poorly understood. Here, we used serial-section electron microscopy to reconstruct the brain of eight isogenic C. elegans individuals at different ages to learn how an entire wiring diagram changes with maturation. We found that the overall geometry of the nervous system is preserved from birth to adulthood, establishing a constant scaffold upon which synaptic change is built. We observed substantial connectivity differences among individuals that make each brain partly unique. We also observed developmental connectivity changes that are consistent between animals but different among neurons, altering the strengths of existing connections and creating additional connections. Collective synaptic changes alter information processing of the brain. Across maturation, the decision-making circuitry is maintained whereas sensory and motor pathways are substantially remodelled, and the brain becomes progressively more modular and feedforward. These synaptic changes reveal principles that underlie brain maturation. ### Competing Interest Statement The authors have declared no competing interest.
1,940 downloads neuroscience
The P3a is an event-related potential comprising an early fronto-central phase and a late fronto-parietal phase. It is observed after novel events and has classically been considered to reflect the attention processing of distracting stimuli. However, novel sounds can lead to behavioral facilitation as much as behavioral distraction. This illustrates the duality of the orienting response which includes both an attentional and an arousal component. Using a paradigm with visual or auditory targets to detect and irrelevant unexpected distracting sounds to ignore, we showed that the facilitation effect by distracting sounds is independent of the target modality and endures more than 1500 ms. These results confirm that the behavioral facilitation observed after distracting sounds is related to an increase in unspecific phasic arousal on top of the attentional capture. Moreover, the amplitude of the early phase of the P3a to distracting sounds positively correlated with subjective arousal ratings, contrary to other event-related potentials. We propose that the fronto-central early phase of the P3a would index the arousing properties of distracting sounds and would be linked to the arousal component of the orienting response. Finally, we discuss the relevance of the P3a as a marker of distraction.
1,928 downloads neuroscience
Zizhen Yao, Thuc Nghi Nguyen, Cindy van Velthoven, Jeff Goldy, Adriana E. Sedeño-Cortés, Fahimeh Baftizadeh, Darren Bertagnolli, Tamara Casper, Kirsten Crichton, Song-Lin Ding, Olivia Fong, Emma Garren, Alexandra Glandon, James Gray, Lucas Graybuck, Daniel Hirschstein, Matthew Kroll, Kanan Lathia, Boaz P. Levi, Delissa McMillen, Stephanie Mok, Trangthanh Pham, Qingzhong Ren, Christine Rimorin, Nadiya Shapovalova, Josef Sulc, Susan M. Sunkin, Michael Tieu, Amy Torkelson, Herman Tung, Katelyn Ward, Nick Dee, Kimberly Smith, Bosiljka Tasic, Hongkui Zeng
The isocortex and hippocampal formation are two major structures in the mammalian brain that play critical roles in perception, cognition, emotion and learning. Both structures contain multiple regions, for many of which the cellular composition is still poorly understood. In this study, we used two complementary single-cell RNA-sequencing approaches, SMART-Seq and 10x, to profile ~1.2 million cells covering all regions in the adult mouse isocortex and hippocampal formation, and derived a cell type taxonomy comprising 379 transcriptomic types. The completeness of coverage enabled us to define gene expression variations across the entire spatial landscape without significant gaps. We found that cell types are organized in a hierarchical manner and exhibit varying degrees of discrete or continuous relatedness with each other. Such molecular relationships correlate strongly with the spatial distribution patterns of the cell types, which can be region-specific, or shared across multiple regions, or part of one or more gradients along with other cell types. Glutamatergic neuron types have much greater diversity than GABAergic neuron types, both molecularly and spatially, and they define regional identities as well as inter-region relationships. For example, we found that glutamatergic cell types between the isocortex and hippocampal formation are highly distinct from each other yet possess shared molecular signatures and corresponding layer specificities, indicating their homologous relationships. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation for the first time, and begins to shed light on its underlying relationship with the development, evolution, connectivity and function of these two brain structures.
1,917 downloads neuroscience
When people are forced to be isolated from one another, do they crave social interactions in the same way a hungry person craves food? To address this question, we used functional magnetic resonance imaging (fMRI) to measure neural responses in participants (n=40) evoked by food and social cues after ten hours of mandated fasting or total social isolation. After isolation, people felt lonely and craved social interaction. Midbrain regions showed increased activation to food cues after fasting and to social cues after isolation; these responses were correlated with self-reported craving. Neural patterns in response to food cues when participants were hungry generalized to social cues after isolation. Our results support the intuitive idea that acute isolation causes social craving, similar to hunger.
1,609 downloads neuroscience
Trygve Bakken, Nikolas L. Jorstad, Qiwen Hu, Blue B Lake, Wei Tian, Brian Kalmbach, Megan Crow, Rebecca Hodge, Fenna M. Krienen, Staci A. Sorensen, Jeroen Eggermont, Zizhen Yao, Brian D. Aevermann, Andrew I. Aldridge, Anna Bartlett, Darren Bertagnolli, Tamara Casper, Rosa G. Castanon, Kirsten Crichton, L. Daigle Tanya, Rachel Dalley, Nick Dee, Nikolai Dembrow, Dinh Diep, Song-Lin Ding, Weixiu Dong, Rongxin Fang, Stephan Fischer, Melissa Goldman, Jeff Goldy, Lucas Graybuck, Brian R. Herb, Xiaomeng Hou, Jayaram Kancherla, Matthew Kroll, Kanan Lathia, Baldur van Lew, Yang Eric Li, Christine S. Liu, Hanqing Liu, Jacinta Lucero, Anup Mahurkar, Delissa McMillen, Jeremy Miller, Marmar Moussa, Joseph R. Nery, Philip R. Nicovich, Joshua Orvis, Julia K. Osteen, Scott Owen, Carter R. Palmer, Trangthanh Pham, Nongluk Plongthongkum, Olivier Poirion, Nora M. Reed, Christine Rimorin, Angeline Rivkin, William J. Romanow, Adriana E. Sedeño-Cortés, Kimberly Siletti, Saroja Somasundaram, Josef Sulc, Michael Tieu, Amy Torkelson, Herman Tung, Xinxin Wang, Fangming Xie, Anna Marie Yanny, Renee Zhang, Seth A. Ament, M. Margarita Behrens, Héctor Corrada Bravo, Jerold Chun, Alexander Dobin, Jesse Gillis, Ronna Hertzano, Patrick R. Hof, Thomas Höllt, Gregory D. Horwitz, C.Dirk Keene, Peter V. Kharchenko, Andrew L. Ko, Boudewijn P.F. Lelieveldt, Chongyuan Luo, Eran A. Mukamel, Sebastian Preissl, Aviv Regev, Bing Ren, Richard H Scheuermann, Kimberly Smith, William J. Spain, Owen R. White, Christof Koch, Michael J. Hawrylycz, Bosiljka Tasic, Evan Z. Macosko, Steven A. McCarroll, Jonathan Ting, Hongkui Zeng, Kun Zhang, Guoping Feng, Joseph Ecker, Sten Linnarsson, Ed Lein
The primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup of this region, whose similarity mirrors evolutionary distance and is consistent between the transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal types allowed the generation of a cross-species consensus cell type classification and inference of conserved cell type properties across species. Despite overall conservation, many species specializations were apparent, including differences in cell type proportions, gene expression, DNA methylation, and chromatin state. Few cell type marker genes were conserved across species, providing a short list of candidate genes and regulatory mechanisms responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human primate and human and characterization of their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.
1,578 downloads neuroscience
Anirban Nandi, Tom Chartrand, Werner van Geit, Anatoly Buchin, Zizhen Yao, Soo Yeun Lee, Yina Wei, Brian Kalmbach, Brian Lee, Ed Lein, Jim Berg, Uygar Sümbül, Christof Koch, Bosiljka Tasic, Costas Anastassiou
Identifying the cell types constituting brain circuits is a fundamental question in neuroscience and motivates the generation of taxonomies based on electrophysiological, morphological and molecular single cell properties. Establishing the correspondence across data modalities and understanding the underlying principles has proven challenging. Bio-realistic computational models offer the ability to probe cause-and-effect and have historically been used to explore phenomena at the single-neuron level. Here we introduce a computational optimization workflow used for the generation and evaluation of more than 130 million single neuron models with active conductances. These models were based on 230 in vitro electrophysiological experiments followed by morphological reconstruction from the mouse visual cortex. We show that distinct ion channel conductance vectors exist that distinguish between major cortical classes with passive and h-channel conductances emerging as particularly important for classification. Next, using models of genetically defined classes, we show that differences in specific conductances predicted from the models reflect differences in gene expression in excitatory and inhibitory cell types as experimentally validated by single-cell RNA-sequencing. The differences in these conductances, in turn, explain many of the electrophysiological differences observed between cell types. Finally, we show the robustness of the herein generated single-cell models as representations and realizations of specific cell types in face of biological variability and optimization complexity. Our computational effort generated models that reconcile major single-cell data modalities that define cell types allowing for causal relationships to be examined. ### Competing Interest Statement The authors have declared no competing interest.
1,524 downloads neuroscience
Yang Eric Li, Sebastian Preissl, Xiaomeng Hou, Ziyang Zhang, Kai Zhang, Rongxin Fang, Yunjiang Qiu, Olivier Poirion, Bin Li, Hanqing Liu, Xinxin Wang, Jee Yun Han, Jacinta Lucero, Yiming Yan, Samantha Kuan, David U. Gorkin, Michael Nunn, Eran A. Mukamel, M. Margarita Behrens, Joseph Ecker, Bing Ren
The mammalian cerebrum performs high level sensory, motor control and cognitive functions through highly specialized cortical networks and subcortical nuclei. Recent surveys of mouse and human brains with single cell transcriptomics– and high-throughput imaging technologies, have uncovered hundreds of neuronal cell types and a variety of non-neuronal cell types distributed in different brain regions, but the cell-type-specific transcriptional regulatory programs responsible for the unique identity and function of each brain cell type have yet to be elucidated. Here, we probe the accessible chromatin in >800,000 individual nuclei from 45 regions spanning the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to define 491,818 candidate cis regulatory DNA elements in 160 distinct sub-types. We link a significant fraction of them to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of non-coding risk variants associated with various neurological disease and traits in humans. To facilitate the dissemination of information, we have set up a web portal (<http://catlas.org/mousebrain>). ### Competing Interest Statement B.R. is a co-founder and consultant of Arima Genomics, Inc.. J.R.E is on the scientific advisory board of Zymo Research, Inc : #ref-1 : #ref-3 : #ref-4 : #ref-5
1,520 downloads neuroscience
By engaging angiotensin-converting enzyme 2 (ACE2 or Ace2), the novel pathogenic SARS-coronavirus 2 (SARS-CoV-2) may invade host cells in many organs, including the brain. However, the distribution of ACE2 in the brain is still obscure. Here we investigated the ACE2 expression in the brain by analyzing data from publicly available brain transcriptome databases. According to our spatial distribution analysis, ACE2 was relatively highly expressed in some important locations, such as the substantia nigra and the choroid plexus. According to our cell-type distribution analysis, nuclear expression of ACE2 was found in many neurons (both excitatory and inhibitory neurons) and some non-neuron cells (mainly astrocytes, oligodendrocytes and endothelial cells) in human middle temporal gyrus and posterior cingulate cortex. A few ACE2-expressing nuclei were found in a hippocampal dataset, and none were detected in the prefrontal cortex. Except for the additional high expression of Ace2 in the olfactory bulb areas for spatial distribution as well as in the pericytes and endothelial cells for cell-type distribution, the distribution of Ace2 in mouse brain was similar to that in the human brain. Thus, our results reveal an outline of ACE2/Ace2 distribution in the human and mouse brain, which indicates the brain infection of SARS-CoV-2 may be capable of inducing central nervous system symptoms in coronavirus disease 2019 (COVID-19) patients. ### Competing Interest Statement The authors have declared no competing interest.
1,485 downloads neuroscience
Katherine S. Matho, Dhananjay Huilgol, William Galbavy, Gukhan Kim, Miao He, Xu An, Jiangteng Lu, Priscilla Wu, Daniela J. Di Bella, Ashwin S. Shetty, Ramesh Palaniswamy, Joshua Hatfield, Ricardo Raudales, Arun Narasimhan, Eric Gamache, Jesse Levine, Jason Tucciarone, Partha Mitra, Pavel Osten, Paola Arlotta, Z. Josh Huang
Diverse types of glutamatergic pyramidal neurons (PyNs) mediate the myriad processing streams and output channels of the cerebral cortex, yet all derive from neural progenitors of the embryonic dorsal telencephalon. Here, we establish genetic strategies and tools for dissecting and fate mapping PyN subpopulations based on their developmental and molecular programs. We leverage key transcription factors and effector genes to systematically target the temporal patterning programs in progenitors and differentiation programs in postmitotic neurons. We generated over a dozen of temporally inducible mouse Cre and Flp knock-in driver lines to enable combinatorial targeting of major progenitor types and projection classes. Intersectional converter lines confer viral access to specific subsets defined by developmental origin, marker expression, anatomical location and projection targets. These strategies establish an experimental framework for multi-modal characterization of PyN subpopulations and tracking their developmental trajectories toward elucidating the organization and assembly of cortical processing networks and output channels. ### Competing Interest Statement The authors have declared no competing interest.
1,462 downloads neuroscience
The recent emergence of the pathogenic SARS-CoV-2 initiated a worldwide health crisis. The entry of the virus into cells is mediated by the binding of the viral Spike protein to the angiotensin-converting enzyme-2 (ACE2), followed by its priming by the TMPRSS2 serine protease, both present on the cellular membrane of the target cells. In the respiratory tract, these targets are ciliated cells. Interestingly, various reports indicate an association between SARS-CoV-2 infection and anosmia, suggesting an alteration not restricted to the respiratory tissue, but that might also include the olfactory sensory epithelium. We explored this possibility by generating RNA-seq libraries from human neuroepithelium, in which we found significant expression of ACE2 and TMPRSS2. To determine whether specific cell types of this chemosensory tissue may coexpress both of the virus entry genes, we analyzed a scRNA-seq dataset. We determined that sustentacular cells, which are in direct contact with the external world and maintain the integrity of olfactory sensory neurons, represents a prime candidate for SARS-CoV-2 infection via the nose, and possibly for SARS-CoV-2-induced anosmia.
1,273 downloads neuroscience
Machine learning-based analysis of human functional magnetic resonance imaging (fMRI) patterns has enabled the visualization of perceptual content. However, it has been limited to the reconstruction with low-level image bases or to the matching to exemplars. Recent work showed that visual cortical activity can be decoded (translated) into hierarchical features of a deep neural network (DNN) for the same input image, providing a way to make use of the information from hierarchical visual features. Here, we present a novel image reconstruction method, in which the pixel values of an image are optimized to make its DNN features similar to those decoded from human brain activity at multiple layers. We found that the generated images resembled the stimulus images (both natural images and artificial shapes) and the subjective visual content during imagery. While our model was solely trained with natural images, our method successfully generalized the reconstruction to artificial shapes, indicating that our model indeed reconstructs or generates images from brain activity, not simply matches to exemplars. A natural image prior introduced by another deep neural network effectively rendered semantically meaningful details to reconstructions by constraining reconstructed images to be similar to natural images. Furthermore, human judgment of reconstructions suggests the effectiveness of combining multiple DNN layers to enhance visual quality of generated images. The results suggest that hierarchical visual information in the brain can be effectively combined to reconstruct perceptual and subjective images.
1,271 downloads neuroscience
Kun Leng, Emmy Li, Rana Eser, Antonia Piergies, Rene Sit, Michelle Tan, Norma Neff, Song Hua Li, Roberta Diehl Rodriguez, Claudia Kimie Suemoto, Renata Elaine Paraizo Leite, Carlos A Pasqualucci, William W Seeley, Salvatore Spina, Helmut Heinsen, Lea T. Grinberg, Martin Kampmann
Alzheimer’s disease (AD) is characterized by the selective vulnerability of specific neuronal populations, the molecular signatures of which are largely unknown. To identify and characterize selectively vulnerable neuronal populations, we used single-nucleus RNA sequencing to profile the caudal entorhinal cortex and the superior frontal gyrus – brain regions where neurofibrillary inclusions and neuronal loss occur early and late in AD, respectively – from individuals spanning the neuropathological progression of AD. We identified RORB as a marker of selectively vulnerable excitatory neurons in the entorhinal cortex, and subsequently validated their depletion and selective susceptibility to neurofibrillary inclusions during disease progression using quantitative neuropathological methods. We also discovered an astrocyte subpopulation, likely representing reactive astrocytes, characterized by decreased expression of genes involved in homeostatic functions. Our characterization of selectively vulnerable neurons in AD paves the way for future mechanistic studies of selective vulnerability and potential therapeutic strategies for enhancing neuronal resilience.
1,259 downloads neuroscience
Listeners experience speech as a sequence of discrete words. However, the real input is a continuously varying acoustic signal that blends words and phonemes into one another. Here we recorded two-hour magnetoencephalograms from 21 subjects listening to stories, in order to investigate how the brain concurrently solves three competing demands: 1) processing overlapping acoustic-phonetic information while 2) keeping track of the relative order of phonemic units and 3) maintaining individuated phonetic information until successful word recognition. We show that the human brain transforms speech input, roughly at the rate of phoneme duration, along a temporally-defined representational trajectory. These representations, absent from the acoustic signal, are active earlier when phonemes are predictable than when they are surprising, and are sustained until lexical ambiguity is resolved. The results reveal how phoneme sequences in natural speech are represented and how they interface with stored lexical items.
1,204 downloads neuroscience
GABA (γ-aminobutyric acid) stimulation of the metabotropic GABAB receptor results in prolonged inhibition of neurotransmission that is central to brain physiology. GABAB belongs to the Family C of G protein-coupled receptors (GPCRs), which operate as dimers to relay synaptic neurotransmitter signals into a cellular response through the binding and activation of heterotrimeric G proteins. GABAB, however, is unique in its function as an obligate heterodimer in which agonist binding and G protein activation take place on distinct subunits. Here we show structures of heterodimeric and homodimeric full-length GABAB receptors. Complemented by cellular signaling assays and atomistic simulations, the structures reveal an essential role for the GABAB extracellular loop 2 (ECL2) in relaying structural transitions by ordering the linker connecting the extracellular ligand-binding domain to the transmembrane region. Furthermore, the ECL2 of both GABAB subunits caps and interacts with the hydrophilic head of a phospholipid occupying the extracellular half of the transmembrane domain, thereby providing a potentially crucial link between ligand binding and the receptor core that engages G protein. These results provide a starting framework to decipher mechanistic modes of signal transduction mediated by GABAB dimers and have important implications for rational drug design targeting these receptors. ### Competing Interest Statement The authors have declared no competing interest.
1,149 downloads neuroscience
The spinal cord is a fascinating structure responsible for coordinating all movement in vertebrates. Spinal motor neurons control the activity of virtually every organ and muscle throughout the body by transmitting signals that originate in the spinal cord. These neurons are remarkably heterogeneous in their activity and innervation targets. However, because motor neurons represent only a small fraction of cells within the spinal cord and are difficult to isolate, the full complement of motor neuron subtypes remains unknown. Here we comprehensively describe the molecular heterogeneity of motor neurons within the adult spinal cord. We profiled 43,890 single-nucleus transcriptomes using fluorescence-activated nuclei sorting to enrich for spinal motor neuron nuclei. These data reveal a transcriptional map of the adult mammalian spinal cord and the first unbiased characterization of all transcriptionally distinct autonomic and somatic spinal motor neuron subpopulations. We identify 16 sympathetic motor neuron subtypes that segregate spatially along the spinal cord. Many of these subtypes selectively express specific hormones and receptors, suggesting neuromodulatory signaling within the autonomic nervous system. We describe skeletal motor neuron heterogeneity in the adult spinal cord, revealing numerous novel markers that distinguish alpha and gamma motor neurons—cell populations that are specifically affected in neurodegenerative disease. We also provide evidence for a novel transcriptional subpopulation of skeletal motor neurons. Collectively, these data provide a single-cell transcriptional atlas for investigating motor neuron diversity as well as the cellular and molecular basis of motor neuron function in health and disease.
1,077 downloads neuroscience
Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well-established that it depends on pre and postsynaptic activity. However, models that rely solely on pre and postsynaptic activity for synaptic changes have, to date, not been able to account for learning complex tasks that demand hierarchical networks. Here, we show that if synaptic plasticity is regulated by high-frequency bursts of spikes, then neurons higher in the hierarchy can coordinate the plasticity of lower-level connections. Using simulations and mathematical analyses, we demonstrate that, when paired with short-term synaptic dynamics, regenerative activity in the apical dendrites, and synaptic plasticity in feedback pathways, a burst-dependent learning rule can solve challenging tasks that require deep network architectures. Our results demonstrate that well-known properties of dendrites, synapses, and synaptic plasticity are sufficient to enable sophisticated learning in hierarchical circuits.
1,051 downloads neuroscience
Imaging of large-scale circuit dynamics is crucial to gain a better understanding of brain function, but most techniques have a limited depth of field. Here we describe vfUSI, a platform for brain-wide volumetric functional ultrasound imaging of hemodynamic activity in awake head-fixed mice. We combined high-frequency 1024-channel 2D-array transducer with advanced multiplexing and high-performance computing for real-time 3D Power Doppler imaging at high spatiotemporal resolution (220×280×175-μm3 voxel size, up to 6 Hz). In addition, we developed a standardized software pipeline for registration and segmentation based on the Allen Mouse Common Coordinate Framework, allowing for temporal analysis in 268 individual brain regions. We demonstrate the high sensitivity of vfUSI in multiple experimental situations where stimulus-evoked activity can be recorded using a minimal number of trials. We also mapped neural circuits in vivo across the whole brain during optogenetic activation of specific cell-types. Moreover, we revealed the sequential activation of sensory-motor regions during a grasping water droplet task. vfUSI will become a key neuroimaging technology because it combines ease of use, reliability, and affordability. ### Competing Interest Statement Alan Urban is a founder and shareholder of AUTC.
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