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Jo Y, Liang X, Nguyen HH, Choi Y, Choi M, Bae GE, Cho Y, Woo J, Lee HJ. Selective manipulation of excitatory and inhibitory neurons in top-down and bottom-up visual pathways using ultrasound stimulation. Brain Stimul 2025; 18:848-862. [PMID: 40222665 DOI: 10.1016/j.brs.2025.04.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2024] [Revised: 02/27/2025] [Accepted: 04/08/2025] [Indexed: 04/15/2025] Open
Abstract
INTRODUCTION Techniques for precise manipulation of neurons in specific neural pathways are crucial for excitatory/inhibitory (E/I) balance and investigation of complex brain circuits. Low-intensity focused ultrasound stimulation (LIFUS) has emerged as a promising tool for noninvasive deep-brain targeting at high spatial resolution. However, there is a lack of studies that extensively investigate the modulation of top-down and bottom-up corticothalamic circuits via selective manipulation of excitatory and inhibitory neurons. Here, a comprehensive methodology using electrophysiological recording and c-Fos staining is employed to demonstrate pulse repetition frequency (PRF)-dependent E/I selectivity of ultrasound stimulation in the top-down and bottom-up corticothalamic pathways of the visual circuit in rodents. MATERIALS AND METHODS Ultrasound stimulation at various PRFs is applied to either the lateral posterior nucleus of the thalamus (LP) or the primary visual cortex (V1), and multi-channel single-unit activity is recorded from the V1 using a silicon probe. RESULTS AND CONCLUSION Our results demonstrate that high-frequency PRFs, particularly at 3 kHz and 1 kHz, are effective at activating the bidirectional corticothalamic visual pathway. In addition, brain region-specific PRFs modulate E/I cortical signals, corticothalamic projections, and synaptic neurotransmission, which is imperative for circuit-specific applications and behavioral studies.
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Affiliation(s)
- Yehhyun Jo
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Xiaojia Liang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Hong Hanh Nguyen
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Yeonseo Choi
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Minji Choi
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Ga-Eun Bae
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Yakdol Cho
- Research Animal Resource Center, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Jiwan Woo
- Research Animal Resource Center, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Hyunjoo Jenny Lee
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; KAIST Institute for Nano Century (KINC), Daejeon, 34141, Republic of Korea.
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2
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Zhang Z, Cai L, Li W, Gong H, Li A, Feng Z. SlicesMapi: An Interactive Three-Dimensional Registration Method for Serial Histological Brain Slices. Neuroinformatics 2025; 23:28. [PMID: 40240690 DOI: 10.1007/s12021-025-09724-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/05/2025] [Indexed: 04/18/2025]
Abstract
Brain slicing is a commonly used technique in brain science research. In order to study the spatial distribution of labeled information, such as specific types of neurons and neuronal circuits, it is necessary to register the brain slice images to the 3D standard brain space defined by the reference atlas. However, the registration of 2D brain slice images to a 3D reference brain atlas still faces challenges in terms of accuracy, computational throughput, and applicability. In this paper, we propose the SlicesMapi, an interactive 3D registration method for brain slice sequence. This method corrects linear and non-linear deformations in both 3D and 2D spaces by employing dual constraints from neighboring slices and corresponding reference atlas slices and guarantees precision by registering images with full resolution, which avoids the information loss of image down-sampling implemented in the deep learning based registration methods. This method was applied to deal the challenges of unknown slice angle registration and non-linear deformations between the 3D Allen Reference Atlas and slices with cytoarchitectonic or autofluorescence channels. Experimental results demonstrate Dice scores of 0.9 in major brain regions, highlighting significant advantages over existing methods. Compared with existing methods, our proposed method is expected to provide a more accurate, robust, and efficient spatial localization scheme for brain slices. Therefore, the proposed method is capable of achieving enhanced accuracy in slice image spatial positioning.
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Affiliation(s)
- Zoutao Zhang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Lingyi Cai
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Wenwei Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, 430074, China.
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China.
- State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
| | - Zhao Feng
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, 215123, China.
- State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
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Messore F, Narayanan Therpurakal R, Dufour JP, Hoerder-Suabedissen A, Guidi L, Korrell K, Mueller M, Abuelem M, Lak A, Bannerman DM, Mann EO, Molnár Z. An orexin-sensitive subpopulation of layer 6 neurons regulates cortical excitability and anxiety behaviour. Transl Psychiatry 2025; 15:147. [PMID: 40229262 PMCID: PMC11997144 DOI: 10.1038/s41398-025-03350-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Revised: 02/26/2025] [Accepted: 03/26/2025] [Indexed: 04/16/2025] Open
Abstract
Cortical layer 6 neurons are the only projection neuron population in the cortical mantle known to electrophysiologically respond to orexin-a neuropeptide involved in cortical arousal and emotive behaviour. These neurons exhibit extensive intercortical and thalamic projections, yet the exact mechanisms underlying these responses are not fully understood. We hypothesize that cortical circuits activated by orexin sensitive L6 neurons in the medial prefrontal cortex (mPFC) are responsible for detecting salient features of sensory stimuli and are therefore involved in regulating emotional states. Here, we show that Drd1a-Cre+ neurons in the mPFC are selectively sensitive to orexin and gate the activation of the prefrontal network in vivo. Moreover, we demonstrated that chronically "silencing" this subpopulation of L6 neurons (Drd1a-Cre+/+:Snap25fl/fl) across the cortical mantle from birth abolishes the orexin-induced prefrontal activation. Consequently, the chronic silencing of these neurons had strong anxiolytic effects on several anxiety-related behavioural paradigms, indicating that orexin-responsive L6 neurons modulate emotional states and may be a substrate for anxiety regulation.
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Affiliation(s)
- Fernando Messore
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
| | - Rajeevan Narayanan Therpurakal
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
- Department of Neurology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Jean-Philippe Dufour
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
| | | | - Luiz Guidi
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
| | - Kim Korrell
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
| | - Marissa Mueller
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
| | - Mohammed Abuelem
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
- National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Armin Lak
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA
| | - David M Bannerman
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Edward O Mann
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA.
| | - Zoltán Molnár
- Department of Physiology, Anatomy and Genetics University of Oxford, Oxford, USA.
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4
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Tustison NJ, Chen M, Kronman FN, Duda JT, Gamlin C, Tustison MG, Kunst M, Dalley R, Sorenson S, Wang Q, Ng L, Kim Y, Gee JC. Modular strategies for spatial mapping of diverse cell type data of the mouse brain. RESEARCH SQUARE 2025:rs.3.rs-6289741. [PMID: 40297692 PMCID: PMC12036443 DOI: 10.21203/rs.3.rs-6289741/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2025]
Abstract
Large-scale, international collaborative efforts by members of the BRAIN Initiative Cell Census Network (BICCN) consortium are aggregating the most comprehensive reference database to date for diverse cell type profiling of the mouse brain, which encompasses over 40 different multi-modal profiling techniques from more than 30 research groups. One central challenge for this integrative effort has been the need to map these unique datasets into common reference spaces such that the spatial, structural, and functional information from different cell types can be jointly analyzed. However, significant variation in the acquisition, tissue processing, and imaging techniques across data types makes mapping such diverse data a multifarious problem. Different data types exhibit unique tissue distortion and signal characteristics that precludes a single mapping strategy from being generally applicable across all cell type data. Tailored mapping approaches are often needed to address the unique barriers present in each modality. This work highlights modular atlas mapping strategies developed across separate BICCN studies using the Advanced Normalization Tools Ecosystem (ANTsX) to map spatial transcriptomic (MERFISH) and high-resolution morphology (fMOST) mouse brain data into the Allen Common Coordinate Framework (AllenCCFv3), and developmental (MRI and LSFM) data into the Developmental Common Coordinate Framework (DevCCF). We discuss common mapping strategies that can be shared across modalities and driven by specific challenges from each data type. These mapping strategies include novel open-source contributions that are made publicly available through ANTSX. These include 1) a velocity flow-based approach for continuously mapping developmental trajectories such as that characterizing the DevCCF and 2) an automated framework for determining structural morphology solely through the leveraging of publicly resources. Finally, we provide general guidance to aid investigators to tailor these strategies to address unique data challenges without the need to develop additional specialized software.
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Affiliation(s)
- Nicholas J. Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA
| | - Min Chen
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | - Fae N. Kronman
- Department of Neural and Behavioral Sciences, Penn State University, Hershey, PA
| | - Jeffrey T. Duda
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
| | | | - Mia G. Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
- Department of Neural and Behavioral Sciences, Penn State University, Hershey, PA
- Allen Institute for Brain Science, Seattle, WA
| | | | | | | | | | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA
| | - Yongsoo Kim
- Department of Neural and Behavioral Sciences, Penn State University, Hershey, PA
| | - James C. Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA
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5
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Hsu CH, Hsu YY, Chang BM, Raffensperger K, Kadden M, Ton HT, Ette EA, Lin S, Brooks J, Burke MW, Lee YJ, Wang PC, Shoykhet M, Tu TW. StainAI: quantitative mapping of stained microglia and insights into brain-wide neuroinflammation and therapeutic effects in cardiac arrest. Commun Biol 2025; 8:462. [PMID: 40114030 PMCID: PMC11926354 DOI: 10.1038/s42003-025-07926-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 03/11/2025] [Indexed: 03/22/2025] Open
Abstract
Microglia, the brain's resident macrophages, participate in development and influence neuroinflammation, which is characteristic of multiple brain pathologies. Diverse insults cause microglia to alter their morphology from "resting" to "activated" shapes, which vary with stimulus type, brain location, and microenvironment. This morphologic diversity commonly restricts microglial analyses to specific regions and manual methods. We introduce StainAI, a deep learning tool that leverages 20x whole-slide immunohistochemistry images for rapid, high-throughput analysis of microglial morphology. StainAI maps microglia to a brain atlas, classifies their morphology, quantifies morphometric features, and computes an activation score for any region of interest. As a proof of principle, StainAI was applied to a rat model of pediatric asphyxial cardiac arrest, accurately classifying millions of microglia across multiple slices, surpassing current methods by orders of magnitude, and identifying both known and novel activation patterns. Extending its application to a non-human primate model of simian immunodeficiency virus infection further demonstrated its generalizability beyond rodent datasets, providing new insights into microglial responses across species. StainAI offers a scalable, high-throughput solution for microglial analysis from routine immunohistochemistry images, accelerating research in microglial biology and neuroinflammation.
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Affiliation(s)
- Chao-Hsiung Hsu
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA
| | - Yi-Yu Hsu
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA
- Miin Wu School of Computing, National Cheng Kung University, Tainan City, Taiwan
| | - Be-Ming Chang
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA
| | - Katherine Raffensperger
- Center for Neuroscience Research, Children's National Research Institute, Washington, DC, USA
| | - Micah Kadden
- Center for Neuroscience Research, Children's National Research Institute, Washington, DC, USA
- Pediatric Critical Care Medicine, Children's National Hospital, Washington, DC, USA
| | - Hoai T Ton
- Center for Neuroscience Research, Children's National Research Institute, Washington, DC, USA
| | - Essiet-Adidiong Ette
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA
| | - Stephen Lin
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA
| | - Janiya Brooks
- Department of Physiology and Biophysics, Howard University, Washington, DC, USA
| | - Mark W Burke
- Department of Physiology and Biophysics, Howard University, Washington, DC, USA
| | - Yih-Jing Lee
- School of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
| | - Paul C Wang
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA
- Department of Physics, Fu-Jen Catholic University, New Taipei City, Taiwan
| | - Michael Shoykhet
- Center for Neuroscience Research, Children's National Research Institute, Washington, DC, USA
- Pediatric Critical Care Medicine, Children's National Hospital, Washington, DC, USA
- Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Tsang-Wei Tu
- Molecular Imaging Laboratory, Department of Radiology, Howard University, Washington, DC, USA.
- Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
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6
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Tieze SM, Esqueda A, McAllister R, Lagator M, Yücel B, Sun E, Lam TT, Lockyer N, Gupta K, Chandra SS. Molecular elucidation of brain lipofuscin in aging and Neuronal Ceroid Lipofuscinosis. RESEARCH SQUARE 2025:rs.3.rs-6010379. [PMID: 40166029 PMCID: PMC11957193 DOI: 10.21203/rs.3.rs-6010379/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Lipofuscin is an autofluorescent material that accrues in brain tissues with age and in Neuronal Ceroid Lipofuscinosis (NCL), a neurodegenerative disease with pediatric onset. The distribution, composition, and organellar origin of lipofuscin have remained unclear despite its widespread presence in aged tissues and involvement in neurodegeneration. Here, we elucidate lipofuscin composition and report the spatiotemporal dynamics of lipofuscin accumulation in aging and NCL on a neuroanatomical atlas. Multimodal mass spectrometry, ultrastructural analyses, and assays of metabolic flux identify a primary role of the lysosomal-mitochondrial axis in lipofuscin formation. Dissection of implicated molecular pathways reveals protein S-acylation and lipid homeostasis as central processes involved in aging and NCL.
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Affiliation(s)
- Sofia Massaro Tieze
- Departments of Neurology & Neuroscience, Yale University, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Alexander Esqueda
- Departments of Neurology & Neuroscience, Yale University, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | | | - Matija Lagator
- Photon Science Institute, Department of Chemistry, University of Manchester, Manchester, UK
- Rosalind Franklin Institute, Rutherford Appleton Laboratory, Didcot, Oxfordshire, UK
| | - Betül Yücel
- Departments of Neurology & Neuroscience, Yale University, New Haven, CT, USA
| | - Eric Sun
- Yale College, Yale University, New Haven, CT, USA
| | - TuKiet T. Lam
- Departments of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
- Keck Mass Spectrometry & Proteomics Resource, W.M. Keck Biotechnology Resource Laboratory, New Haven, CT, USA
| | - Nicholas Lockyer
- Photon Science Institute, Department of Chemistry, University of Manchester, Manchester, UK
| | - Kallol Gupta
- Department of Cell Biology, Yale University, New Haven, CT, USA
| | - Sreeganga S. Chandra
- Departments of Neurology & Neuroscience, Yale University, New Haven, CT, USA
- Senior author
- Lead contact
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7
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Jin M, Ogundare SO, Lanio M, Sorid S, Whye AR, Santos SL, Franceschini A, Denny CA. A SMARTTR workflow for multi-ensemble atlas mapping and brain-wide network analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.07.12.603299. [PMID: 39071434 PMCID: PMC11275872 DOI: 10.1101/2024.07.12.603299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
In the last decade, activity-dependent strategies for labelling multiple immediate early gene (IEG) ensembles in mice have generated unprecedented insight into the mechanisms of memory encoding, storage, and retrieval. However, few strategies exist for brain-wide mapping of multiple ensembles, including their overlapping population, and none incorporate capabilities for downstream network analysis. Here, we introduce a scalable workflow to analyze traditionally coronally-sectioned datasets produced by activity-dependent tagging systems. Intrinsic to this pipeline is simple multi-ensemble atlas registration and statistical testing in R (SMARTTR), an R package which wraps mapping capabilities with functions for statistical analysis and network visualization, and support for import of external datasets. We demonstrate the versatility of SMARTTR by mapping the ensembles underlying the acquisition and expression of learned helplessness (LH), a robust stress model. Applying network analysis, we find that exposure to inescapable shock (IS), compared to context training (CT), results in decreased centrality of regions engaged in spatial and contextual processing and higher influence of regions involved in somatosensory and affective processing. During LH expression, the substantia nigra emerges as a highly influential region which shows a functional reversal following IS, indicating a possible regulatory function of motor activity during helplessness. We also report that IS results in a robust decrease in reactivation activity across a number of cortical, hippocampal, and amygdalar regions, indicating suppression of ensemble reactivation may be a neurobiological signature of LH. These results highlight the emergent insights uniquely garnered by applying our analysis approach to multiple ensemble datasets and demonstrate the strength of our workflow as a hypothesis-generating toolkit.
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Affiliation(s)
- Michelle Jin
- Medical Scientist Training Program (MSTP), Columbia University Irving Medical Center (CUIMC), New York, NY, 10032, USA
- Neurobiology and Behavior (NB&B) Graduate Program, Columbia University, New York, NY, 10027, USA
| | - Simon O. Ogundare
- Medical Scientist Training Program (MSTP), Columbia University Irving Medical Center (CUIMC), New York, NY, 10032, USA
- Columbia College, New York, NY, 10027, USA
| | - Marcos Lanio
- Medical Scientist Training Program (MSTP), Columbia University Irving Medical Center (CUIMC), New York, NY, 10032, USA
- Adult Neurology Residency Program, Stony Brook Medicine, Stony Brook, NY, 11794, USA
| | | | - Alicia R. Whye
- Columbia College, New York, NY, 10027, USA
- Tri-Institutional MD-PhD Program, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Sofia Leal Santos
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, 4710-057, Portugal
- Department of Psychiatry, Columbia University Irving Medical Center (CUIMC), New York, NY, 10032, USA
| | - Alessandra Franceschini
- Department of Psychiatry, Columbia University Irving Medical Center (CUIMC), New York, NY, 10032, USA
- European Laboratory for Non-linear Spectroscopy (LENS), University of Florence, Sesto Fiorentino, Italy
| | - Christine. A. Denny
- Department of Psychiatry, Columbia University Irving Medical Center (CUIMC), New York, NY, 10032, USA
- Division of Systems Neuroscience, Research Foundation for Mental Hygiene, Inc. (RFMH) / New York State Psychiatric Institute (NYSPI), New York, NY, 10032, USA
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8
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Groos D, Reuss AM, Rupprecht P, Stachniak T, Lewis C, Han S, Roggenbach A, Sturman O, Sych Y, Wieckhorst M, Bohacek J, Karayannis T, Aguzzi A, Helmchen F. A distinct hypothalamus-habenula circuit governs risk preference. Nat Neurosci 2025; 28:361-373. [PMID: 39779821 DOI: 10.1038/s41593-024-01856-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 11/18/2024] [Indexed: 01/11/2025]
Abstract
Appropriate risk evaluation is essential for survival in complex, uncertain environments. Confronted with choosing between certain (safe) and uncertain (risky) options, animals show strong preference for either option consistently across extended time periods. How such risk preference is encoded in the brain remains elusive. A candidate region is the lateral habenula (LHb), which is prominently involved in value-guided behavior. Here, using a balanced two-alternative choice task and longitudinal two-photon calcium imaging in mice, we identify risk-preference-selective activity in LHb neurons reflecting individual risk preference before action selection. By using whole-brain anatomical tracing, multi-fiber photometry and projection-specific and cell-type-specific optogenetics, we find glutamatergic LHb projections from the medial (MH) but not lateral (LH) hypothalamus providing behavior-relevant synaptic input before action selection. Optogenetic stimulation of MH→LHb axons evoked excitatory and inhibitory postsynaptic responses, whereas LH→LHb projections were excitatory. We thus reveal functionally distinct hypothalamus-habenula circuits for risk preference in habitual economic decision-making.
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Affiliation(s)
- Dominik Groos
- Brain Research Institute, University of Zurich, Zurich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - Anna Maria Reuss
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Peter Rupprecht
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Tevye Stachniak
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Division of Biomedical Sciences, Memorial University, St. John's, Newfoundland, Canada
| | | | - Shuting Han
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Adrian Roggenbach
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Oliver Sturman
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Yaroslav Sych
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Institute of Cellular and Integrative Neuroscience, Strasbourg, France
| | | | - Johannes Bohacek
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Theofanis Karayannis
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zurich, Switzerland
| | - Adriano Aguzzi
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Fritjof Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland.
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.
- University Research Priority Program (URPP), Adaptive Brain Circuits in Development and Learning, University of Zurich, Zurich, Switzerland.
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9
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Morningstar MD, Lopez KM, Mayfield SS, Almeida-Mancero RN, Marquez J, Flores AM, Hafer BR, Estrada E, Holtzman GA, Goranson EV, Reid NM, Aldrich AR, Ghatalia DV, Patel JR, Padilla CM, Chavez GJ, Kelly-Roman J, Bhakta PA, Valenzuela CF, Linsenbardt DN. Connectivity of the neuronal network for contextual fear memory is disrupted in a mouse model of third-trimester binge-like ethanol exposure. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2025; 49:315-331. [PMID: 39672678 DOI: 10.1111/acer.15503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Accepted: 11/18/2024] [Indexed: 12/15/2024]
Abstract
BACKGROUND In rodents, third-trimester-equivalent alcohol exposure (TTAE) produces significant deficits in hippocampal-dependent memory processes such as contextual fear conditioning (CFC). The present study sought to characterize changes in both behavior and Fos+ neurons following CFC in ethanol (EtOH)-treated versus saline-treated mice using TRAP2:Ai14 mice that permanently label Fos+ neurons following a tamoxifen injection. We hypothesized that TTAE would produce long-lasting disruptions to the networks engaged following CFC with a particular emphasis on the limbic memory system. METHODS On postnatal day 7, mice received either two injections of saline or 2.5 g/kg EtOH spaced 2 h apart. The mice were left undisturbed until they reached adulthood, at which point they underwent CFC. After context exposure on day 2, mice received a tamoxifen injection. Brain tissue was harvested. Slides were automatically imaged using a Zeiss AxioScanner. Manual counts on a priori regions of interest were conducted. Automated counts were performed on the whole brain using the QUINT 2D stitching pipeline. Last, novel network analyses were applied to identify future regions of interest. RESULTS TTAE reduced context recall on day 2 of CFC. Fos+ neural density increased in the CA1 and CA3. Fos+ counts were reduced in the anteroventral (AV) and anterodorsal thalamus. The limbic memory system showed significant hyperconnectivity in male TTAE mice, and the AV shifted affinity toward hippocampal subregions. Last, novel regions such as a subparafascicular area and basomedial amygdalar nucleus were implicated as important mediators. DISCUSSION These results suggest that CFC is mediated by the limbic memory system and is disrupted following TTAE. Given the increase in CA1 and CA3 activity, a potential hypothesis is that TTAE causes disruptions to memory encoding following day 1 conditioning. Future studies will aim to determine whether this disruption specifically affects the encoding or retrieval of fear memories.
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Affiliation(s)
- Mitchell D Morningstar
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Katalina M Lopez
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Stefanie S Mayfield
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Roberto N Almeida-Mancero
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Joshua Marquez
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Andres M Flores
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Brooke R Hafer
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Edilberto Estrada
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Gwen A Holtzman
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Emerald V Goranson
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Natalie M Reid
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Abigale R Aldrich
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Desna V Ghatalia
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Juhee R Patel
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Christopher M Padilla
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Glenna J Chavez
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Javier Kelly-Roman
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Pooja A Bhakta
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - C Fernando Valenzuela
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - David N Linsenbardt
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
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10
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Tetzlaff SK, Reyhan E, Layer N, Bengtson CP, Heuer A, Schroers J, Faymonville AJ, Langeroudi AP, Drewa N, Keifert E, Wagner J, Soyka SJ, Schubert MC, Sivapalan N, Pramatarov RL, Buchert V, Wageringel T, Grabis E, Wißmann N, Alhalabi OT, Botz M, Bojcevski J, Campos J, Boztepe B, Scheck JG, Conic SH, Puschhof MC, Villa G, Drexler R, Zghaibeh Y, Hausmann F, Hänzelmann S, Karreman MA, Kurz FT, Schröter M, Thier M, Suwala AK, Forsberg-Nilsson K, Acuna C, Saez-Rodriguez J, Abdollahi A, Sahm F, Breckwoldt MO, Suchorska B, Ricklefs FL, Heiland DH, Venkataramani V. Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing. Cell 2025; 188:390-411.e36. [PMID: 39644898 DOI: 10.1016/j.cell.2024.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 09/16/2024] [Accepted: 11/04/2024] [Indexed: 12/09/2024]
Abstract
Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain, engaging in widespread functional communication, with cholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor-cell-state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasiveness. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.
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Affiliation(s)
- Svenja K Tetzlaff
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Ekin Reyhan
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Nikolas Layer
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - C Peter Bengtson
- Department of Neurobiology, Interdisciplinary Centre for Neurosciences (IZN), Heidelberg University, Heidelberg, Germany
| | - Alina Heuer
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Julian Schroers
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Anton J Faymonville
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | | | - Nina Drewa
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Elijah Keifert
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Julia Wagner
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Stella J Soyka
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Marc C Schubert
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Nirosan Sivapalan
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Rangel L Pramatarov
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Verena Buchert
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Tim Wageringel
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
| | - Elena Grabis
- Translational Neurosurgery, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Niklas Wißmann
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Obada T Alhalabi
- Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Michael Botz
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Jovana Bojcevski
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Joaquín Campos
- Chica and Heinz Schaller Foundation, Institute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Berin Boztepe
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jonas G Scheck
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Sascha Henry Conic
- Division of Stem Cells and Cancer, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany; Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
| | - Maria C Puschhof
- Faculty of Medicine, Heidelberg University, and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Giulia Villa
- Translational Neurosurgery, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany
| | - Richard Drexler
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Yahya Zghaibeh
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fabian Hausmann
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sonja Hänzelmann
- Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Institute of Medical Systems Biology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthia A Karreman
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix T Kurz
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Neuroradiology, University Hospital Geneva, Geneva, Switzerland
| | - Manuel Schröter
- ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland
| | - Marc Thier
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Division of Stem Cells and Cancer, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Heidelberg, Germany; Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Heidelberg, Germany
| | - Abigail K Suwala
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuropathology (B300), German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Claudio Acuna
- Chica and Heinz Schaller Foundation, Institute of Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany
| | - Julio Saez-Rodriguez
- Faculty of Medicine, Heidelberg University, and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Amir Abdollahi
- Clinical Cooperation Unit Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Sahm
- Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuropathology (B300), German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael O Breckwoldt
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bogdana Suchorska
- Department of Neurosurgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Franz L Ricklefs
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dieter Henrik Heiland
- Translational Neurosurgery, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany; Department of Neurosurgery, University Hospital Erlangen, Friedrich-Alexander University Erlangen Nuremberg, Erlangen, Germany; Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; German Cancer Consortium (DKTK), partner site Freiburg, Freiburg, Germany
| | - Varun Venkataramani
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany; Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
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11
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Yamawaki N, Login H, Feld-Jakobsen SØ, Molnar BM, Kirkegaard MZ, Moltesen M, Okrasa A, Radulovic J, Tanimura A. Endopiriform neurons projecting to ventral CA1 are a critical node for recognition memory. eLife 2025; 13:RP99642. [PMID: 39835788 PMCID: PMC11750136 DOI: 10.7554/elife.99642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2025] Open
Abstract
The claustrum complex is viewed as fundamental for higher-order cognition; however, the circuit organization and function of its neuroanatomical subregions are not well understood. We demonstrated that some of the key roles of the CLA complex can be attributed to the connectivity and function of a small group of neurons in its ventral subregion, the endopiriform (EN). We identified a subpopulation of EN neurons by their projection to the ventral CA1 (ENvCA1-proj. neurons), embedded in recurrent circuits with other EN neurons and the piriform cortex. Although the ENvCA1-proj. neuron activity was biased toward novelty across stimulus categories, their chemogenetic inhibition selectively disrupted the memory-guided but not innate responses of mice to novelty. Based on our functional connectivity analysis, we suggest that ENvCA1-proj. neurons serve as an essential node for recognition memory through recurrent circuits mediating sustained attention to novelty, and through feed-forward inhibition of distal vCA1 neurons shifting memory-guided behavior from familiarity to novelty.
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Affiliation(s)
- Naoki Yamawaki
- Department of Biomedicine, Aarhus UniversityAarhusDenmark
- PROMEMO, The Center for Proteins in Memory, Aarhus UniversityAarhusDenmark
- DANDRITE, The Danish Research Institute of Translational Neuroscience, Aarhus UniversityAarhusDenmark
| | - Hande Login
- Department of Biomedicine, Aarhus UniversityAarhusDenmark
- PROMEMO, The Center for Proteins in Memory, Aarhus UniversityAarhusDenmark
- DANDRITE, The Danish Research Institute of Translational Neuroscience, Aarhus UniversityAarhusDenmark
| | | | | | | | - Maria Moltesen
- Department of Biomedicine, Aarhus UniversityAarhusDenmark
| | | | - Jelena Radulovic
- Department of Biomedicine, Aarhus UniversityAarhusDenmark
- PROMEMO, The Center for Proteins in Memory, Aarhus UniversityAarhusDenmark
- DANDRITE, The Danish Research Institute of Translational Neuroscience, Aarhus UniversityAarhusDenmark
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of MedicineNew YorkUnited States
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of MedicineNew YorkUnited States
| | - Asami Tanimura
- Department of Biomedicine, Aarhus UniversityAarhusDenmark
- PROMEMO, The Center for Proteins in Memory, Aarhus UniversityAarhusDenmark
- DANDRITE, The Danish Research Institute of Translational Neuroscience, Aarhus UniversityAarhusDenmark
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12
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Bjerke IE, Carey H, Bjaalie JG, Leergaard TB, Kim JH. The developing mouse dopaminergic system: Cortical-subcortical shift in D1/D2 receptor balance and increasing regional differentiation. Neurochem Int 2025; 182:105899. [PMID: 39537102 DOI: 10.1016/j.neuint.2024.105899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 11/04/2024] [Accepted: 11/05/2024] [Indexed: 11/16/2024]
Abstract
The dopaminergic system of the brain is involved in complex cognitive functioning and undergoes extensive reorganization during development. Yet, these changes are poorly characterized. We have quantified the density of dopamine 1- and 2-receptor (D1 and D2) positive cells across the forebrain of male and female mice at five developmental stages using validated transgenic mice expressing green fluorescent protein in cells producing D1 or D2 mRNA. After analyzing >4,500 coronal brain images, a cortico-subcortical shift in D1/D2 balance was discovered, with increasing D1 dominance in cortical regions as a maturational pattern that occurs earlier in females. We describe postnatal trajectories of D1 and D2 cell densities across major brain regions and observe increasing regional differentiation of D1 densities through development. Our results provide the most comprehensive overview of the developing dopaminergic system to date, and an empirical foundation for further experimental and computational investigations of dopaminergic signaling.
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Affiliation(s)
- Ingvild E Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Harry Carey
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jee Hyun Kim
- IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin University, Geelong, VIC, Australia; Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia.
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13
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Katrib C, Hladky H, Timmerman K, Durieux N, Dutheil N, Bezard E, Devos D, Laloux C, Betrouni N. Magnetic resonance imaging characterization of an α-synuclein model of Parkinson's disease. Eur J Neurosci 2024; 60:7038-7057. [PMID: 39551614 DOI: 10.1111/ejn.16610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 10/28/2024] [Accepted: 11/02/2024] [Indexed: 11/19/2024]
Abstract
Parkinson's disease (PD) is primarily characterized by three histological hallmarks: dopaminergic neuronal degeneration, α-synuclein accumulation and iron deposition. Over the last years, neuroimaging, particularly magnetic resonance imaging (MRI) has provided invaluable insights into the mechanisms underlying the disease. However, no imaging method has yet been able to translate α-synuclein protein accumulation and spreading. Amongst the animal models mimicking the disease, the α-synuclein rat, generated through the injection of human α-synuclein, has been characterized in terms of behavioural and histological aspects but not thoroughly explored in MRI. The aim of this study is, therefore, to identify the radiological signature from several MRI sequences, while controlling for histological and behavioural characteristics. Rats were assessed for motor and cognitive functions over a 4-month period. During this time, three MRI sessions, including both morphological and functional sequences, were conducted. Histological studies evaluated the three main hallmarks of PD. The progressive dopaminergic neurodegeneration and the spread of human α-synuclein corresponded to the level of sensorimotor, attentional and learning deficits observed in this PD model. MRI analyses showed progressive structural abnormalities in the midbrain, diencephalon and several cortical structures, as well as a pattern of hyperconnectivity in the basal ganglia and cortical networks. The regions affected in imaging demonstrated the highest load of human α-synuclein. This model's structural and functional MRI changes could serve as indirect indicators of α-synuclein accumulation and its association with impaired non-motor functions.
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Affiliation(s)
- Chirine Katrib
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1772, LilNCog - Lille Neuroscience & Cognition, Lille University Hospital, Lille, France
| | - Hector Hladky
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1772, LilNCog - Lille Neuroscience & Cognition, Lille University Hospital, Lille, France
| | - Kelly Timmerman
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1772, LilNCog - Lille Neuroscience & Cognition, Lille University Hospital, Lille, France
| | - Nicolas Durieux
- US41-UAR2014 PLBS, Lille In vivo imaging and functional exploration platform, Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, Lille, France
| | - Nathalie Dutheil
- Univ. de Bordeaux, Institut des Maladies Neurodégénératives, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, Bordeaux, France
| | - Erwan Bezard
- Univ. de Bordeaux, Institut des Maladies Neurodégénératives, Bordeaux, France
- CNRS, Institut des Maladies Neurodégénératives, Bordeaux, France
| | - David Devos
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1772, LilNCog - Lille Neuroscience & Cognition, Lille University Hospital, Lille, France
| | - Charlotte Laloux
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1772, LilNCog - Lille Neuroscience & Cognition, Lille University Hospital, Lille, France
- US41-UAR2014 PLBS, Lille In vivo imaging and functional exploration platform, Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, Lille, France
| | - Nacim Betrouni
- Department of Medical Pharmacology, Lille University, INSERM UMRS_1772, LilNCog - Lille Neuroscience & Cognition, Lille University Hospital, Lille, France
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14
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Catanese J, Murakami TC, Catto A, Kenny PJ, Ibañez-Tallon I. Precise 3D Localization of Intracerebral Implants Using a Simple Brain Clearing Method. J Integr Neurosci 2024; 23:207. [PMID: 39613469 DOI: 10.31083/j.jin2311207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 07/24/2024] [Accepted: 08/05/2024] [Indexed: 12/01/2024] Open
Abstract
BACKGROUND Precise localization of intracerebral implants in rodent brains is required for physiological and behavioral studies, particularly if targeting deep brain nuclei. Traditional histological methods, based on manual estimation through sectioning can introduce errors and complicate data interpretation. METHODS Here, we introduce an alternative method based on recent advances in tissue-clearing techniques and light-sheet fluorescence microscopy. This method uses a simplified recipe of the Clear, Unobstructed Brain/Body Imaging Cocktails and Computational Analysis (CUBIC) method, which is a rapid clearing procedure using an aqueous-based solution compatible with fluorescence and fluorescence markers. We demonstrate the utility of this approach in anesthetized transgenic mice expressing channelrhodopsin-2 (ChR2) and enhanced yellow fluorescent fusion (EYFP) protein under the choline acetyltransferase (ChAT) promoter/enhancer regions (ChAT-ChR2-EYFP mice) with implanted linear silicon optrode probes into the midbrain interpeduncular nucleus (IPN). RESULTS By applying the red fluorescent DiD' dye (DiIC18(5) solid (1,1'-Dioctadecyl-3,3,3',3'-Tetramethylindodicarbocyanine, 4-Chlorobenzenesulfonate Salt) to the electrode surface, we precisely visualize the electrode localization in the IPN of ChAT-ChR2-EYFP mice. Three-dimensional brain videos from different orientations highlight the potential of this method. Optogenetic responses recorded from electrodes placed in the IPN validate these findings. CONCLUSIONS This method allows for precise localization of brain implantation sites in transgenic mice expressing cell-specific fluorescence markers. It enables virtual brain slicing in any orientation, making it a useful tool for functional studies in mice.
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Affiliation(s)
- Julien Catanese
- Laboratory of Molecular Biology, The Rockefeller University, New York, NY 10065, USA
| | - Tatsuya C Murakami
- Laboratory of Molecular Biology, The Rockefeller University, New York, NY 10065, USA
| | - Adam Catto
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Paul J Kenny
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ines Ibañez-Tallon
- Laboratory of Molecular Biology, The Rockefeller University, New York, NY 10065, USA
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15
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Nemeth DP, Liu X, Monet MC, Niu H, Maxey G, Schrier MS, Smirnova MI, McGovern SJ, Herd A, DiSabato DJ, Floyd T, Atluri RR, Nusstein AC, Oliver B, Witcher KG, Juste Ellis JS, Yip J, Crider AD, McKim DB, Gajewski-Kurdziel PA, Godbout JP, Zhang Q, Blakely RD, Sheridan JF, Quan N. Localization of brain neuronal IL-1R1 reveals specific neural circuitries responsive to immune signaling. J Neuroinflammation 2024; 21:303. [PMID: 39563437 PMCID: PMC11575132 DOI: 10.1186/s12974-024-03287-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2024] [Accepted: 11/04/2024] [Indexed: 11/21/2024] Open
Abstract
Interleukin-1 (IL-1) is a pro-inflammatory cytokine that exerts a wide range of neurological and immunological effects throughout the central nervous system (CNS) and is associated with the etiology of affective and cognitive disorders. The cognate receptor for IL-1, Interleukin-1 Receptor Type 1 (IL-1R1), is primarily expressed on non-neuronal cells (e.g., endothelial cells, choroidal cells, ventricular ependymal cells, astrocytes, etc.) throughout the brain. However, the presence and distribution of neuronal IL-1R1 (nIL-1R1) has been controversial. Here, for the first time, a novel genetic mouse line that allows for the visualization of IL-1R1 mRNA and protein expression (Il1r1GR/GR) was used to map all brain nuclei and determine the neurotransmitter systems which express nIL-1R1 in adult male mice. The direct responsiveness of nIL-1R1-expressing neurons to both inflammatory and physiological levels of IL-1β in vivo was tested. Neuronal IL-1R1 expression across the brain was found in discrete glutamatergic and serotonergic neuronal populations in the somatosensory cortex, piriform cortex, dentate gyrus, and dorsal raphe nucleus. Glutamatergic nIL-1R1 comprises most of the nIL-1R1 expression and, using Vglut2-Cre-Il1r1r/r mice, which restrict IL-1R1 expression to only glutamatergic neurons, an atlas of glutamatergic nIL-1R1 expression across the brain was generated. Analysis of functional outputs of these nIL-1R1-expressing nuclei, in both Il1r1GR/GR and Vglut2-Cre-Il1r1r/r mice, reveals IL-1R1+ nuclei primarily relate to sensory detection, processing, and relay pathways, mood regulation, and spatial/cognitive processing centers. Intracerebroventricular (i.c.v.) injections of IL-1 (20 ng) induces NFκB signaling in IL-1R1+ non-neuronal cells but not in IL-1R1+ neurons, and in Vglut2-Cre-Il1r1r/r mice IL-1 did not change gene expression in the dentate gyrus of the hippocampus (DG). GO pathway analysis of spatial RNA sequencing 1mo following restoration of nIL-1R1 in the DG neurons reveals IL-1R1 expression downregulates genes related to both synaptic function and mRNA binding while increasing select complement markers (C1ra, C1qb). Further, DG neurons exclusively express an alternatively spliced IL-1R Accessory protein isoform (IL-1RAcPb), a known synaptic adhesion molecule. Altogether, this study reveals a unique network of neurons that can respond directly to IL-1 via nIL-1R1 through non-autonomous transcriptional pathways; earmarking these circuits as potential neural substrates for immune signaling-triggered sensory, affective, and cognitive disorders.
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Affiliation(s)
- Daniel P Nemeth
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA.
| | - Xiaoyu Liu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Marianne C Monet
- The International Max Planck Research School (IMPRS) for Synapses and Circuits, Max Planck Florida Institute for Neuroscience Jupiter, Jupiter, FL, 33458, USA
- Department of Biological Sciences, Charles E. Schmidt College of Science, Florida Atlantic University, Jupiter, FL, 33458, USA
| | - Haichen Niu
- Department of Genetics, Xuzhou Medical University, Xuzhou, 221004, China
| | - Gabriella Maxey
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
- Wilkes Honors College, Florida Atlantic University, Jupiter, FL, 33458, USA
| | - Matt S Schrier
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Maria I Smirnova
- The International Max Planck Research School (IMPRS) for Synapses and Circuits, Max Planck Florida Institute for Neuroscience Jupiter, Jupiter, FL, 33458, USA
- Department of Biological Sciences, Charles E. Schmidt College of Science, Florida Atlantic University, Jupiter, FL, 33458, USA
| | | | - Anu Herd
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Damon J DiSabato
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Department of Neuroscience, The Ohio State University, Columbus, OH, 43210, USA
| | - Trey Floyd
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Rohit R Atluri
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- College of Medicine and Life Sciences, University of Toledo, Toledo, OH, 43614, USA
| | - Alex C Nusstein
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
| | - Braedan Oliver
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
| | - Kristina G Witcher
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Department of Neuroscience, The Ohio State University, Columbus, OH, 43210, USA
| | - Joshua St Juste Ellis
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Jasmine Yip
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Andrew D Crider
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
| | - Daniel B McKim
- Department of Animal Science, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | | | - Jonathan P Godbout
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Department of Neuroscience, The Ohio State University, Columbus, OH, 43210, USA
| | - Qi Zhang
- Stiles-Nicholson Brain Institute, Florida Atlantic University, Jupiter, FL, 33458, USA
- Department of Biological Sciences, Charles E. Schmidt College of Science, Florida Atlantic University, Jupiter, FL, 33458, USA
- Department of Chemistry and Biochemistry, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Randy D Blakely
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA
- Stiles-Nicholson Brain Institute, Florida Atlantic University, Jupiter, FL, 33458, USA
| | - John F Sheridan
- Institute for Behavioral Medicine Research, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Division of Biosciences, College of Dentistry, The Ohio State University, Columbus, OH, 43210, USA
- Department of Neuroscience, The Ohio State University, Columbus, OH, 43210, USA
| | - Ning Quan
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, 5353 Parkside Drive, Jupiter, FL, 33458, USA.
- Stiles-Nicholson Brain Institute, Florida Atlantic University, Jupiter, FL, 33458, USA.
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16
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Øvsthus M, van Swieten MMH, Puchades MA, Tocco C, Studer M, Bjaalie JG, Leergaard TB. Spatially integrated cortico-subcortical tracing data for analyses of rodent brain topographical organization. Sci Data 2024; 11:1214. [PMID: 39532918 PMCID: PMC11557934 DOI: 10.1038/s41597-024-04060-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 11/01/2024] [Indexed: 11/16/2024] Open
Abstract
The cerebral cortex extends axonal projections to several subcortical brain regions, including the striatum, thalamus, superior colliculus, and pontine nuclei. Experimental tract-tracing studies have shown that these subcortical projections are topographically organized, reflecting the spatial organization of sensory surfaces and body parts. Several public collections of mouse- and rat- brain tract-tracing data are available, with the Allen mouse brain connectivity atlas being most prominent. There, a large body of image data can be inspected, but it is difficult to combine data from different experiments and compare spatial distribution patterns. To enable co-visualization and comparison of topographical organization in mouse brain cortico-subcortical projections across experiments, we represent axonal labelling data as point data in a common 3D brain atlas space. We here present a collection of point-cloud data representing spatial distribution of corticostriatal, corticothalamic, corticotectal, and corticopontine projections in mice and exemplify how these spatially integrated point data can be used as references for experimental investigations of topographic organization in transgenic mice, and for cross-species comparison with corticopontine projections in rats.
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Affiliation(s)
- Martin Øvsthus
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maaike M H van Swieten
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Chiara Tocco
- Université Côte d'Azur, CNRS, Inserm, iBV, Nice, France
| | | | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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17
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Martin KA, Papadoyannis ES, Schiavo JK, Fadaei SS, Issa HA, Song SC, Valencia SO, Temiz NZ, McGinley MJ, McCormick DA, Froemke RC. Vagus nerve stimulation recruits the central cholinergic system to enhance perceptual learning. Nat Neurosci 2024; 27:2152-2166. [PMID: 39284963 PMCID: PMC11932732 DOI: 10.1038/s41593-024-01767-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 08/15/2024] [Indexed: 11/07/2024]
Abstract
Perception can be refined by experience, up to certain limits. It is unclear whether perceptual limits are absolute or could be partially overcome via enhanced neuromodulation and/or plasticity. Recent studies suggest that peripheral nerve stimulation, specifically vagus nerve stimulation (VNS), can alter neural activity and augment experience-dependent plasticity, although little is known about central mechanisms recruited by VNS. Here we developed an auditory discrimination task for mice implanted with a VNS electrode. VNS applied during behavior gradually improved discrimination abilities beyond the level achieved by training alone. Two-photon imaging revealed VNS induced changes to auditory cortical responses and activated cortically projecting cholinergic axons. Anatomical and optogenetic experiments indicated that VNS can enhance task performance through activation of the central cholinergic system. These results highlight the importance of cholinergic modulation for the efficacy of VNS and may contribute to further refinement of VNS methodology for clinical conditions.
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Affiliation(s)
- Kathleen A Martin
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Eleni S Papadoyannis
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Jennifer K Schiavo
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Saba Shokat Fadaei
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Habon A Issa
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Soomin C Song
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Sofia Orrey Valencia
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
| | - Nesibe Z Temiz
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Matthew J McGinley
- Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | | | - Robert C Froemke
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY, USA.
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA.
- Department of Otolaryngology, New York University School of Medicine, New York, NY, USA.
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA.
- Center for Neural Science, New York University, New York, NY, USA.
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18
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Kim J, Choi M, Lee J, Park I, Kim K, Choe HK. Bidirectional Control of Emotional Behaviors by Excitatory and Inhibitory Neurons in the Orbitofrontal Cortex. Exp Neurobiol 2024; 33:225-237. [PMID: 39568179 PMCID: PMC11581826 DOI: 10.5607/en24021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2024] [Revised: 09/30/2024] [Accepted: 10/21/2024] [Indexed: 11/22/2024] Open
Abstract
The orbitofrontal cortex (OFC) plays a crucial role in mood disorders; however, its specific role in the emotional behaviors of mice remains unclear. This study investigates the bidirectional control of emotional behaviors using population calcium dynamics and optogenetic manipulation of OFC neurons. Fiber photometry of OFC neurons revealed that OFC excitatory neurons consistently responded to the onset and offset of aversive conditions, showing decreased activation in response to anxiogenic and stressful stimuli, including tail suspension, restraint stress, and exposure to the center of the open field. The selective activation of excitatory neurons in the OFC reduced the time spent in the center of the open field, whereas optogenetic activation of inhibitory neurons in the OFC induced the opposite behavioral changes. We also provided a brain-wide activation map for OFC excitatory and inhibitory neuron activation. Our findings demonstrate that excitatory and inhibitory neurons in the OFC play opposing roles in the regulation of emotional behaviors. These results provide new insights into the neural mechanisms underlying emotional control and suggest that targeting these specific neuronal populations may offer novel therapeutic strategies for emotional disorders.
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Affiliation(s)
- Jihoon Kim
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
- Convergence Research Advanced Centre for Olfaction, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
| | - Mijung Choi
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
- Convergence Research Advanced Centre for Olfaction, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
| | - Jimin Lee
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
| | - Inah Park
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
- Convergence Research Advanced Centre for Olfaction, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
| | - Kyungjin Kim
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
| | - Han Kyoung Choe
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
- Convergence Research Advanced Centre for Olfaction, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
- Brain Science Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea
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19
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Rubio-Teves M, Martín-Correa P, Alonso-Martínez C, Casas-Torremocha D, García-Amado M, Timonidis N, Sheiban FJ, Bakker R, Tiesinga P, Porrero C, Clascá F. Beyond Barrels: Diverse Thalamocortical Projection Motifs in the Mouse Ventral Posterior Complex. J Neurosci 2024; 44:e1096242024. [PMID: 39197940 PMCID: PMC11502235 DOI: 10.1523/jneurosci.1096-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 07/29/2024] [Accepted: 08/20/2024] [Indexed: 09/01/2024] Open
Abstract
Thalamocortical pathways from the rodent ventral posterior (VP) thalamic complex to the somatosensory cerebral cortex areas are a key model in modern neuroscience. However, beyond the intensively studied projection from medial VP (VPM) to the primary somatosensory area (S1), the wiring of these pathways remains poorly characterized. We combined micropopulation tract-tracing and single-cell transfection experiments to map the pathways arising from different portions of the VP complex in male mice. We found that pathways originating from different VP regions show differences in area/lamina arborization pattern and axonal varicosity size. Neurons from the rostral VPM subnucleus innervate trigeminal S1 in point-to-point fashion. In contrast, a caudal VPM subnucleus innervates heavily and topographically second somatosensory area (S2), but not S1. Neurons in a third, intermediate VPM subnucleus innervate through branched axons both S1 and S2, with markedly different laminar patterns in each area. A small anterodorsal subnucleus selectively innervates dysgranular S1. The parvicellular VPM subnucleus selectively targets the insular cortex and adjacent portions of S1 and S2. Neurons in the rostral part of the lateral VP nucleus (VPL) innervate spinal S1, while caudal VPL neurons simultaneously target S1 and S2. Rostral and caudal VP nuclei show complementary patterns of calcium-binding protein expression. In addition to the cortex, neurons in caudal VP subnuclei target the sensorimotor striatum. Our finding of a massive projection from VP to S2 separate from the VP projections to S1 adds critical anatomical evidence to the notion that different somatosensory submodalities are processed in parallel in S1 and S2.
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Affiliation(s)
- Mario Rubio-Teves
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
| | - Pablo Martín-Correa
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
| | - Carmen Alonso-Martínez
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
| | - Diana Casas-Torremocha
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
| | - María García-Amado
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
| | - Nestor Timonidis
- Department of Neuroinformatics, Donders Centre for Neuroscience, Radboud University Nijmegen, Nijmegen 6525 AJ, The Netherlands
| | - Francesco J Sheiban
- NearLab, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan 20133, Italy
| | - Rembrandt Bakker
- Department of Neuroinformatics, Donders Centre for Neuroscience, Radboud University Nijmegen, Nijmegen 6525 AJ, The Netherlands
- Inst. of Neuroscience and Medicine (INM-6) and Inst. for Advanced Simulation (IAS-6) and JARA BRAIN Inst. I, Julich Research Centre, Jülich 52428, Germany
| | - Paul Tiesinga
- Department of Neuroinformatics, Donders Centre for Neuroscience, Radboud University Nijmegen, Nijmegen 6525 AJ, The Netherlands
| | - César Porrero
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
| | - Francisco Clascá
- Department of Anatomy & Neuroscience, Autónoma de Madrid University, Madrid E28029, Spain
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20
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Vadisiute A, Meijer E, Therpurakal RN, Mueller M, Szabó F, Messore F, Jursenas A, Bredemeyer O, Krone LB, Mann E, Vyazovskiy V, Hoerder-Suabedissen A, Molnár Z. Glial cells undergo rapid changes following acute chemogenetic manipulation of cortical layer 5 projection neurons. Commun Biol 2024; 7:1286. [PMID: 39384971 PMCID: PMC11464517 DOI: 10.1038/s42003-024-06994-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 09/30/2024] [Indexed: 10/11/2024] Open
Abstract
Bidirectional communication between neurons and glial cells is crucial to establishing and maintaining normal brain function. Some of these interactions are activity-dependent, yet it remains largely unexplored how acute changes in neuronal activity affect glial-to-neuron and neuron-to-glial dynamics. Here, we use excitatory and inhibitory designer receptors exclusively activated by designer drugs (DREADD) to study the effects of acute chemogenetic manipulations of a subpopulation of layer 5 cortical projection and dentate gyrus neurons in adult (Rbp4Cre) mouse brains. We show that acute chemogenetic neuronal activation reduces synaptic density, and increases microglia and astrocyte reactivity, but does not affect parvalbumin (PV+) neurons, only perineuronal nets (PNN). Conversely, acute silencing increases synaptic density and decreases glial reactivity. We show fast glial response upon clozapine-N-oxide (CNO) administration in cortical and subcortical regions. Together, our work provides evidence of fast, activity-dependent, bidirectional interactions between neurons and glial cells.
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Affiliation(s)
- Auguste Vadisiute
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom.
- St John's College, University of Oxford, St Giles', Oxford, United Kingdom.
| | - Elise Meijer
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
| | - Rajeevan Narayanan Therpurakal
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
- Department of Neurology, Düsseldorf University Hospital, Düsseldorf, Germany
| | - Marissa Mueller
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
| | - Florina Szabó
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
| | - Fernando Messore
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
| | | | - Oliver Bredemeyer
- St John's College, University of Oxford, St Giles', Oxford, United Kingdom
| | - Lukas B Krone
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Centre for Experimental Neurology, University of Bern, Bern, Switzerland
| | - Ed Mann
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
| | - Vladyslav Vyazovskiy
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
- Kavli Institute for Nanoscience Discovery, Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, United Kingdom
- Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, United Kingdom
| | - Anna Hoerder-Suabedissen
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom
- Kavli Institute for Nanoscience Discovery, Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, United Kingdom
- Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, United Kingdom
| | - Zoltán Molnár
- Department of Physiology, Anatomy and Genetics, Sherrington Building, University of Oxford, Parks Road, Oxford, OX1 3PT, United Kingdom.
- St John's College, University of Oxford, St Giles', Oxford, United Kingdom.
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21
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Dias RF, Rajan R, Baeta M, Belbut B, Marques T, Petreanu L. Visual experience reduces the spatial redundancy between cortical feedback inputs and primary visual cortex neurons. Neuron 2024; 112:3329-3342.e7. [PMID: 39137776 DOI: 10.1016/j.neuron.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 06/11/2024] [Accepted: 07/14/2024] [Indexed: 08/15/2024]
Abstract
The role of experience in the organization of cortical feedback (FB) remains unknown. We measured the effects of manipulating visual experience on the retinotopic specificity of supragranular and infragranular projections from the lateromedial (LM) visual area to layer (L)1 of the mouse primary visual cortex (V1). LM inputs were, on average, retinotopically matched with V1 neurons in normally and dark-reared mice, but visual exposure reduced the fraction of spatially overlapping inputs to V1. FB inputs from L5 conveyed more surround information to V1 than those from L2/3. The organization of LM inputs from L5 depended on their orientation preference and was disrupted by dark rearing. These observations were recapitulated by a model where visual experience minimizes receptive field overlap between LM inputs and V1 neurons. Our results provide a mechanism for the dependency of surround modulations on visual experience and suggest how expected interarea coactivation patterns are learned in cortical circuits.
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Affiliation(s)
- Rodrigo F Dias
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Radhika Rajan
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Margarida Baeta
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Beatriz Belbut
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Tiago Marques
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Leopoldo Petreanu
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
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22
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Kleven H, Schlegel U, Groenewegen HJ, Leergaard TB, Bjerke IE. Comparison of basal ganglia regions across murine brain atlases using metadata models and the Waxholm Space. Sci Data 2024; 11:1036. [PMID: 39333155 PMCID: PMC11437236 DOI: 10.1038/s41597-024-03863-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 09/04/2024] [Indexed: 09/29/2024] Open
Abstract
The murine basal ganglia regions are targets for research into complex brain functions such as motor control and habit formation. However, there are several ways to name and annotate these regions, posing challenges for interpretation and comparison of data across studies. Here, we give an overview of basal ganglia terms and boundaries in the literature and reference atlases, and describe the criteria used for annotating these regions in the Waxholm Space rat brain atlas. We go on to compare basal ganglia annotations in stereotaxic rat brain atlases and the Allen Mouse brain Common Coordinate Framework to those in the Waxholm Space rat brain atlas. We demonstrate and describe considerable differences in the terms and boundaries of most basal ganglia regions across atlases and their versions. We also register information about atlases and regions in the openMINDS metadata framework, facilitating integration of data in neuroscience databases. The comparisons of terms and boundaries across rat and mouse atlases support analysis and interpretation of existing and new data from the basal ganglia.
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Affiliation(s)
- H Kleven
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - U Schlegel
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - H J Groenewegen
- Department of Anatomy and Neurosciences, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - T B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - I E Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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23
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Sarwar A, Rue M, French L, Cross H, Chen X, Gillis J. Cross-expression analysis reveals patterns of coordinated gene expression in spatial transcriptomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.17.613579. [PMID: 39345494 PMCID: PMC11429685 DOI: 10.1101/2024.09.17.613579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Spatial transcriptomics promises to transform our understanding of tissue biology by molecularly profiling individual cells in situ. A fundamental question they allow us to ask is how nearby cells orchestrate their gene expression. To investigate this, we introduce cross-expression, a novel framework for discovering gene pairs that coordinate their expression across neighboring cells. Just as co-expression quantifies synchronized gene expression within the same cells, cross-expression measures coordinated gene expression between spatially adjacent cells, allowing us to understand tissue gene expression programs with single cell resolution. Using this framework, we recover ligand-receptor partners and discover gene combinations marking anatomical regions. More generally, we create cross-expression networks to find gene modules with orchestrated expression patterns. Finally, we provide an efficient R package to facilitate cross-expression analysis, quantify effect sizes, and generate novel visualizations to better understand spatial gene expression programs.
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Affiliation(s)
- Ameer Sarwar
- Department of Cell and Systems Biology and Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Mara Rue
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Leon French
- Department of Physiology and Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Helen Cross
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Xiaoyin Chen
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jesse Gillis
- Department of Physiology and Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
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24
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Jiang Z, He M, Young C, Cai J, Xu Y, Jiang Y, Li H, Yang M, Tong Q. Dopaminergic Neurons in Zona Incerta Drives Appetitive Self-Grooming. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308974. [PMID: 39099402 PMCID: PMC11422805 DOI: 10.1002/advs.202308974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 07/07/2024] [Indexed: 08/06/2024]
Abstract
Dopaminergic (DA) neurons are known to play a key role in controlling behaviors. While DA neurons in other brain regions are extensively characterized, those in zona incerta (ZITH or A13) receive much less attention and their function remains to be defined. Here it is shown that optogenetic stimulation of these neurons elicited intensive self-grooming behaviors and promoted place preference, which can be enhanced by training but cannot be converted into contextual memory. Interestingly, the same stimulation increased DA release to periaqueductal grey (PAG) neurons and local PAG antagonism of DA action reduced the elicited self-grooming. In addition, A13 neurons increased their activity in response to various external stimuli and during natural self-grooming episodes. Finally, monosynaptic retrograde tracing showed that the paraventricular hypothalamus represents one of the major upstream brain regions to A13 neurons. Taken together, these results reveal that A13 neurons are one of the brain sites that promote appetitive self-grooming involving DA release to the PAG.
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Affiliation(s)
- Zhiying Jiang
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Michelle He
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Summer Undergraduate Research Program, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA, 02215, USA
| | - Claire Young
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Jing Cai
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- MD Anderson Cancer Center & UTHealth Graduate School for Biomedical Sciences, University of Texas Health Science at Houston, Houston, TX, 77030, USA
| | - Yuanzhong Xu
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Yanyan Jiang
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Hongli Li
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Maojie Yang
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Qingchun Tong
- The Brown Foundation Institute of Molecular Medicine for the Prevention of Human Diseases, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
- MD Anderson Cancer Center & UTHealth Graduate School for Biomedical Sciences, University of Texas Health Science at Houston, Houston, TX, 77030, USA
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25
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Choi YK, Feng L, Jeong WK, Kim J. Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity. Brain Inform 2024; 11:15. [PMID: 38833195 DOI: 10.1186/s40708-024-00228-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 05/08/2024] [Indexed: 06/06/2024] Open
Abstract
Mapping neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow aging and diseases. Developments in imaging technology, such as microscopy and labeling tools, have allowed researchers to visualize this connectivity through high-resolution brain-wide imaging. With this, image processing and analysis have become more crucial. However, despite the wealth of neural images generated, access to an integrated image processing and analysis pipeline to process these data is challenging due to scattered information on available tools and methods. To map the neural connections, registration to atlases and feature extraction through segmentation and signal detection are necessary. In this review, our goal is to provide an updated overview of recent advances in these image-processing methods, with a particular focus on fluorescent images of the mouse brain. Our goal is to outline a pathway toward an integrated image-processing pipeline tailored for connecto-informatics. An integrated workflow of these image processing will facilitate researchers' approach to mapping brain connectivity to better understand complex brain networks and their underlying brain functions. By highlighting the image-processing tools available for fluroscent imaging of the mouse brain, this review will contribute to a deeper grasp of connecto-informatics, paving the way for better comprehension of brain connectivity and its implications.
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Affiliation(s)
- Yoon Kyoung Choi
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, South Korea
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | | | - Won-Ki Jeong
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea
| | - Jinhyun Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, South Korea.
- Department of Computer Science and Engineering, Korea University, Seoul, South Korea.
- KIST-SKKU Brain Research Center, SKKU Institute for Convergence, Sungkyunkwan University, Suwon, South Korea.
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26
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Gurdon B, Yates SC, Csucs G, Groeneboom NE, Hadad N, Telpoukhovskaia M, Ouellette A, Ouellette T, O'Connell KMS, Singh S, Murdy TJ, Merchant E, Bjerke I, Kleven H, Schlegel U, Leergaard TB, Puchades MA, Bjaalie JG, Kaczorowski CC. Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model. Commun Biol 2024; 7:605. [PMID: 38769398 PMCID: PMC11106287 DOI: 10.1038/s42003-024-06242-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 04/24/2024] [Indexed: 05/22/2024] Open
Abstract
Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.
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Affiliation(s)
- Brianna Gurdon
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
| | - Sharon C Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Gergely Csucs
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Nicolaas E Groeneboom
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Niran Hadad
- The Jackson Laboratory, Bar Harbor, ME, USA
- Translational Genomics Research Institute, Phoenix, AZ, USA
| | | | - Andrew Ouellette
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
| | - Tionna Ouellette
- The Jackson Laboratory, Bar Harbor, ME, USA
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA
| | - Kristen M S O'Connell
- The Jackson Laboratory, Bar Harbor, ME, USA
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA
| | - Surjeet Singh
- The Jackson Laboratory, Bar Harbor, ME, USA
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Ingvild Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Heidi Kleven
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ulrike Schlegel
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
| | - Catherine C Kaczorowski
- The University of Maine Graduate School of Biomedical Sciences and Engineering, Orono, ME, USA.
- Tufts University Graduate School of Biomedical Sciences, Medford, MA, USA.
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA.
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27
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Yang L, Liu F, Hahm H, Okuda T, Li X, Zhang Y, Kalyanaraman V, Heitmeier MR, Samineni VK. Projection-TAGs enable multiplex projection tracing and multi-modal profiling of projection neurons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.24.590975. [PMID: 38712231 PMCID: PMC11071495 DOI: 10.1101/2024.04.24.590975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Single-cell multiomic techniques have sparked immense interest in developing a comprehensive multi-modal map of diverse neuronal cell types and their brain wide projections. However, investigating the spatial organization, transcriptional and epigenetic landscapes of brain wide projection neurons is hampered by the lack of efficient and easily adoptable tools. Here we introduce Projection-TAGs, a retrograde AAV platform that allows multiplex tagging of projection neurons using RNA barcodes. By using Projection-TAGs, we performed multiplex projection tracing of the mouse cortex and high-throughput single-cell profiling of the transcriptional and epigenetic landscapes of the cortical projection neurons. Projection-TAGs can be leveraged to obtain a snapshot of activity-dependent recruitment of distinct projection neurons and their molecular features in the context of a specific stimulus. Given its flexibility, usability, and compatibility, we envision that Projection-TAGs can be readily applied to build a comprehensive multi-modal map of brain neuronal cell types and their projections.
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Affiliation(s)
- Lite Yang
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
- Neuroscience Graduate Program, Division of Biology & Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, United States
| | - Fang Liu
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Hannah Hahm
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Takao Okuda
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Xiaoyue Li
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Yufen Zhang
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Vani Kalyanaraman
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Monique R. Heitmeier
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
| | - Vijay K. Samineni
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States
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28
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Mazo C, Baeta M, Petreanu L. Auditory cortex conveys non-topographic sound localization signals to visual cortex. Nat Commun 2024; 15:3116. [PMID: 38600132 PMCID: PMC11006897 DOI: 10.1038/s41467-024-47546-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 04/02/2024] [Indexed: 04/12/2024] Open
Abstract
Spatiotemporally congruent sensory stimuli are fused into a unified percept. The auditory cortex (AC) sends projections to the primary visual cortex (V1), which could provide signals for binding spatially corresponding audio-visual stimuli. However, whether AC inputs in V1 encode sound location remains unknown. Using two-photon axonal calcium imaging and a speaker array, we measured the auditory spatial information transmitted from AC to layer 1 of V1. AC conveys information about the location of ipsilateral and contralateral sound sources to V1. Sound location could be accurately decoded by sampling AC axons in V1, providing a substrate for making location-specific audiovisual associations. However, AC inputs were not retinotopically arranged in V1, and audio-visual modulations of V1 neurons did not depend on the spatial congruency of the sound and light stimuli. The non-topographic sound localization signals provided by AC might allow the association of specific audiovisual spatial patterns in V1 neurons.
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Affiliation(s)
- Camille Mazo
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
| | - Margarida Baeta
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal
| | - Leopoldo Petreanu
- Champalimaud Neuroscience Programme, Champalimaud Foundation, Lisbon, Portugal.
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29
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Farrell JS, Hwaun E, Dudok B, Soltesz I. Neural and behavioural state switching during hippocampal dentate spikes. Nature 2024; 628:590-595. [PMID: 38480889 PMCID: PMC11023929 DOI: 10.1038/s41586-024-07192-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 02/01/2024] [Indexed: 04/06/2024]
Abstract
Distinct brain and behavioural states are associated with organized neural population dynamics that are thought to serve specific cognitive functions1-3. Memory replay events, for example, occur during synchronous population events called sharp-wave ripples in the hippocampus while mice are in an 'offline' behavioural state, enabling cognitive mechanisms such as memory consolidation and planning4-11. But how does the brain re-engage with the external world during this behavioural state and permit access to current sensory information or promote new memory formation? Here we found that the hippocampal dentate spike, an understudied population event that frequently occurs between sharp-wave ripples12, may underlie such a mechanism. We show that dentate spikes are associated with distinctly elevated brain-wide firing rates, primarily observed in higher order networks, and couple to brief periods of arousal. Hippocampal place coding during dentate spikes aligns to the mouse's current spatial location, unlike the memory replay accompanying sharp-wave ripples. Furthermore, inhibiting neural activity during dentate spikes disrupts associative memory formation. Thus, dentate spikes represent a distinct brain state and support memory during non-locomotor behaviour, extending the repertoire of cognitive processes beyond the classical offline functions.
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Affiliation(s)
- Jordan S Farrell
- Department of Neurosurgery, Stanford University, Stanford, CA, USA.
- F.M. Kirby Neurobiology Center and Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Ernie Hwaun
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Barna Dudok
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Departments of Neurology and Neuroscience, Baylor College of Medicine, Houston, TX, USA
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
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30
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Goralski TM, Meyerdirk L, Breton L, Brasseur L, Kurgat K, DeWeerd D, Turner L, Becker K, Adams M, Newhouse DJ, Henderson MX. Spatial transcriptomics reveals molecular dysfunction associated with cortical Lewy pathology. Nat Commun 2024; 15:2642. [PMID: 38531900 PMCID: PMC10966039 DOI: 10.1038/s41467-024-47027-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/18/2024] [Indexed: 03/28/2024] Open
Abstract
A key hallmark of Parkinson's disease (PD) is Lewy pathology. Composed of α-synuclein, Lewy pathology is found both in dopaminergic neurons that modulate motor function, and cortical regions that control cognitive function. Recent work has established the molecular identity of dopaminergic neurons susceptible to death, but little is known about cortical neurons susceptible to Lewy pathology or molecular changes induced by aggregates. In the current study, we use spatial transcriptomics to capture whole transcriptome signatures from cortical neurons with α-synuclein pathology compared to neurons without pathology. We find, both in PD and related PD dementia, dementia with Lewy bodies and in the pre-formed fibril α-synucleinopathy mouse model, that specific classes of excitatory neurons are vulnerable to developing Lewy pathology. Further, we identify conserved gene expression changes in aggregate-bearing neurons that we designate the Lewy-associated molecular dysfunction from aggregates (LAMDA) signature. Neurons with aggregates downregulate synaptic, mitochondrial, ubiquitin-proteasome, endo-lysosomal, and cytoskeletal genes and upregulate DNA repair and complement/cytokine genes. Our results identify neurons vulnerable to Lewy pathology in the PD cortex and describe a conserved signature of molecular dysfunction in both mice and humans.
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Affiliation(s)
- Thomas M Goralski
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lindsay Meyerdirk
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Libby Breton
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Laura Brasseur
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Kevin Kurgat
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Daniella DeWeerd
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lisa Turner
- Van Andel Institute Pathology Core, Grand Rapids, MI, 49503, USA
| | - Katelyn Becker
- Van Andel Institute Genomics Core, Grand Rapids, MI, 49503, USA
| | - Marie Adams
- Van Andel Institute Genomics Core, Grand Rapids, MI, 49503, USA
| | | | - Michael X Henderson
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, 49503, USA.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
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31
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Geertsma HM, Fisk ZA, Sauline L, Prigent A, Kurgat K, Callaghan SM, Henderson MX, Rousseaux MWC. A topographical atlas of α-synuclein dosage and cell type-specific expression in adult mouse brain and peripheral organs. NPJ Parkinsons Dis 2024; 10:65. [PMID: 38504090 PMCID: PMC10951202 DOI: 10.1038/s41531-024-00672-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 02/26/2024] [Indexed: 03/21/2024] Open
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neurodegeneration. Lewy pathology contains aggregated α-synuclein (αSyn), a protein encoded by the SNCA gene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in a diffuse reactivity pattern, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus (SncaNLS) and in situ hybridization of Snca in wild-type mice, we systematically mapped the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels and further identify cell types with low and high αSyn content. We also find high αSyn expression in neurons, particularly those involved in PD, and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage, which are relevant to multiple system atrophy pathogenesis. Surprisingly, we also found that αSyn is relatively absent from select neuron types, e.g., ChAT-positive motor neurons, whereas enteric neurons universally express some degree of αSyn. Together, this integrated atlas provides insight into the cellular topography of αSyn, and provides a quantitative map to test hypotheses about the role of αSyn in network vulnerability, and thus serves investigations into PD pathogenesis and other α-synucleinopathies.
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Affiliation(s)
- Haley M Geertsma
- University of Ottawa Brain and Mind Research Institute, Ottawa, ON, K1H8M5, Canada
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, K1H8M5, Canada
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Zoe A Fisk
- University of Ottawa Brain and Mind Research Institute, Ottawa, ON, K1H8M5, Canada
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, K1H8M5, Canada
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lillian Sauline
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Alice Prigent
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Kevin Kurgat
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Steve M Callaghan
- University of Ottawa Brain and Mind Research Institute, Ottawa, ON, K1H8M5, Canada
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, K1H8M5, Canada
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Michael X Henderson
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA.
| | - Maxime W C Rousseaux
- University of Ottawa Brain and Mind Research Institute, Ottawa, ON, K1H8M5, Canada.
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON, K1H8M5, Canada.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA.
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32
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Lubben N, Brynildsen JK, Webb CM, Li HL, Leyns CEG, Changolkar L, Zhang B, Meymand ES, O'Reilly M, Madaj Z, DeWeerd D, Fell MJ, Lee VMY, Bassett DS, Henderson MX. LRRK2 kinase inhibition reverses G2019S mutation-dependent effects on tau pathology progression. Transl Neurodegener 2024; 13:13. [PMID: 38438877 PMCID: PMC10910783 DOI: 10.1186/s40035-024-00403-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 02/07/2024] [Indexed: 03/06/2024] Open
Abstract
BACKGROUND Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common cause of familial Parkinson's disease (PD). These mutations elevate the LRRK2 kinase activity, making LRRK2 kinase inhibitors an attractive therapeutic. LRRK2 kinase activity has been consistently linked to specific cell signaling pathways, mostly related to organelle trafficking and homeostasis, but its relationship to PD pathogenesis has been more difficult to define. LRRK2-PD patients consistently present with loss of dopaminergic neurons in the substantia nigra but show variable development of Lewy body or tau tangle pathology. Animal models carrying LRRK2 mutations do not develop robust PD-related phenotypes spontaneously, hampering the assessment of the efficacy of LRRK2 inhibitors against disease processes. We hypothesized that mutations in LRRK2 may not be directly related to a single disease pathway, but instead may elevate the susceptibility to multiple disease processes, depending on the disease trigger. To test this hypothesis, we have previously evaluated progression of α-synuclein and tau pathologies following injection of proteopathic seeds. We demonstrated that transgenic mice overexpressing mutant LRRK2 show alterations in the brain-wide progression of pathology, especially at older ages. METHODS Here, we assess tau pathology progression in relation to long-term LRRK2 kinase inhibition. Wild-type or LRRK2G2019S knock-in mice were injected with tau fibrils and treated with control diet or diet containing LRRK2 kinase inhibitor MLi-2 targeting the IC50 or IC90 of LRRK2 for 3-6 months. Mice were evaluated for tau pathology by brain-wide quantitative pathology in 844 brain regions and subsequent linear diffusion modeling of progression. RESULTS Consistent with our previous work, we found systemic alterations in the progression of tau pathology in LRRK2G2019S mice, which were most pronounced at 6 months. Importantly, LRRK2 kinase inhibition reversed these effects in LRRK2G2019S mice, but had minimal effect in wild-type mice, suggesting that LRRK2 kinase inhibition is likely to reverse specific disease processes in G2019S mutation carriers. Additional work may be necessary to determine the potential effect in non-carriers. CONCLUSIONS This work supports a protective role of LRRK2 kinase inhibition in G2019S carriers and provides a rational workflow for systematic evaluation of brain-wide phenotypes in therapeutic development.
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Affiliation(s)
- Noah Lubben
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
| | - Julia K Brynildsen
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Connor M Webb
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Institute On Aging and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Howard L Li
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Institute On Aging and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Cheryl E G Leyns
- Neuroscience Discovery, Merck & Co., Inc., Boston, MA, 02115, USA
| | - Lakshmi Changolkar
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Institute On Aging and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bin Zhang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Institute On Aging and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Emily S Meymand
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Institute On Aging and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mia O'Reilly
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zach Madaj
- Bioinformatics and Biostatistics Core, Van Andel Institute, 333 Bostwick Ave., NE, Grand Rapids, MI, 49503, USA
| | - Daniella DeWeerd
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
| | - Matthew J Fell
- Neuroscience Discovery, Merck & Co., Inc., Boston, MA, 02115, USA
| | - Virginia M Y Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Institute On Aging and Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Dani S Bassett
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Santa Fe Institute, Santa Fe, NM, 87501, USA
| | - Michael X Henderson
- Department of Neurodegenerative Science, Van Andel Institute, 333 Bostwick Ave NE, Grand Rapids, MI, 49503, USA.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA.
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Blixhavn CH, Reiten I, Kleven H, Øvsthus M, Yates SC, Schlegel U, Puchades MA, Schmid O, Bjaalie JG, Bjerke IE, Leergaard TB. The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases. Front Neuroinform 2024; 18:1284107. [PMID: 38421771 PMCID: PMC10884250 DOI: 10.3389/fninf.2024.1284107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
Neuroscientists employ a range of methods and generate increasing amounts of data describing brain structure and function. The anatomical locations from which observations or measurements originate represent a common context for data interpretation, and a starting point for identifying data of interest. However, the multimodality and abundance of brain data pose a challenge for efforts to organize, integrate, and analyze data based on anatomical locations. While structured metadata allow faceted data queries, different types of data are not easily represented in a standardized and machine-readable way that allow comparison, analysis, and queries related to anatomical relevance. To this end, three-dimensional (3D) digital brain atlases provide frameworks in which disparate multimodal and multilevel neuroscience data can be spatially represented. We propose to represent the locations of different neuroscience data as geometric objects in 3D brain atlases. Such geometric objects can be specified in a standardized file format and stored as location metadata for use with different computational tools. We here present the Locare workflow developed for defining the anatomical location of data elements from rodent brains as geometric objects. We demonstrate how the workflow can be used to define geometric objects representing multimodal and multilevel experimental neuroscience in rat or mouse brain atlases. We further propose a collection of JSON schemas (LocareJSON) for specifying geometric objects by atlas coordinates, suitable as a starting point for co-visualization of different data in an anatomical context and for enabling spatial data queries.
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Affiliation(s)
- Camilla H. Blixhavn
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ingrid Reiten
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Heidi Kleven
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Martin Øvsthus
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Sharon C. Yates
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ulrike Schlegel
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A. Puchades
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | | | - Jan G. Bjaalie
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ingvild E. Bjerke
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B. Leergaard
- Neural Systems Laboratory, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
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34
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Zhang A, Jin L, Yao S, Matsuyama M, van Velthoven CTJ, Sullivan HA, Sun N, Kellis M, Tasic B, Wickersham I, Chen X. Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing. eLife 2024; 12:RP87866. [PMID: 38319699 PMCID: PMC10942611 DOI: 10.7554/elife.87866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024] Open
Abstract
Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4130 retrogradely labeled cells and 2914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.
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Affiliation(s)
- Aixin Zhang
- Allen Institute for Brain ScienceSeattleUnited States
| | - Lei Jin
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Shenqin Yao
- Allen Institute for Brain ScienceSeattleUnited States
| | - Makoto Matsuyama
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | | | - Heather Anne Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Na Sun
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Broad Institute of MIT and HarvardCambridgeUnited States
- Broad Institute of MIT and HarvardCambridgeUnited States
| | - Manolis Kellis
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Broad Institute of MIT and HarvardCambridgeUnited States
- Broad Institute of MIT and HarvardCambridgeUnited States
| | | | - Ian Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Xiaoyin Chen
- Allen Institute for Brain ScienceSeattleUnited States
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35
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Catanese J, Murakami T, Kenny PJ, Ibanez-Tallon I. Precise 3D Localization of Intracerebral Implants with a simple Brain Clearing Method. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.22.573088. [PMID: 38187775 PMCID: PMC10769389 DOI: 10.1101/2023.12.22.573088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Determining the localization of intracerebral implants in rodent brain stands as a critical final step in most physiological and behaviroral studies, especially when targeting deep brain nuclei. Conventional histological approaches, reliant on manual estimation through sectioning and slice examination, are error-prone, potentially complicating data interpretation. Leveraging recent advances in tissue-clearing techniques and light-sheet fluorescence microscopy, we introduce a method enabling virtual brain slicing in any orientation, offering precise implant localization without the limitations of traditional tissue sectioning. To illustrate the method's utility, we present findings from the implantation of linear silicon probes into the midbrain interpeduncular nucleus (IPN) of anesthetized transgenic mice expressing chanelrhodopsin-2 and enhanced yellow fluorescent protein under the choline acetyltransferase (ChAT) promoter/enhancer regions (ChAT-Chr2-EYFP mice). Utilizing a fluorescent dye applied to the electrode surface, we visualized both the targeted area and the precise localization, enabling enhanced inter-subject comparisons. Three dimensional (3D) brain renderings, presented effortlessly in video format across various orientations, showcase the versatility of this approach.
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36
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Piluso S, Souedet N, Jan C, Hérard AS, Clouchoux C, Delzescaux T. giRAff: an automated atlas segmentation tool adapted to single histological slices. Front Neurosci 2024; 17:1230814. [PMID: 38274499 PMCID: PMC10808556 DOI: 10.3389/fnins.2023.1230814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 10/31/2023] [Indexed: 01/27/2024] Open
Abstract
Conventional histology of the brain remains the gold standard in the analysis of animal models. In most biological studies, standard protocols usually involve producing a limited number of histological slices to be analyzed. These slices are often selected into a specific anatomical region of interest or around a specific pathological lesion. Due to the lack of automated solutions to analyze such single slices, neurobiologists perform the segmentation of anatomical regions manually most of the time. Because the task is long, tedious, and operator-dependent, we propose an automated atlas segmentation method called giRAff, which combines rigid and affine registrations and is suitable for conventional histological protocols involving any number of single slices from a given mouse brain. In particular, the method has been tested on several routine experimental protocols involving different anatomical regions of different sizes and for several brains. For a given set of single slices, the method can automatically identify the corresponding slices in the mouse Allen atlas template with good accuracy and segmentations comparable to those of an expert. This versatile and generic method allows the segmentation of any single slice without additional anatomical context in about 1 min. Basically, our proposed giRAff method is an easy-to-use, rapid, and automated atlas segmentation tool compliant with a wide variety of standard histological protocols.
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Affiliation(s)
- Sébastien Piluso
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoire des Maladies Neurodégénératives, Fontenay-aux-Roses, France
- WITSEE, Paris, France
| | - Nicolas Souedet
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoire des Maladies Neurodégénératives, Fontenay-aux-Roses, France
| | - Caroline Jan
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoire des Maladies Neurodégénératives, Fontenay-aux-Roses, France
| | - Anne-Sophie Hérard
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoire des Maladies Neurodégénératives, Fontenay-aux-Roses, France
| | | | - Thierry Delzescaux
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoire des Maladies Neurodégénératives, Fontenay-aux-Roses, France
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37
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Seignette K, Jamann N, Papale P, Terra H, Porneso RO, de Kraker L, van der Togt C, van der Aa M, Neering P, Ruimschotel E, Roelfsema PR, Montijn JS, Self MW, Kole MHP, Levelt CN. Experience shapes chandelier cell function and structure in the visual cortex. eLife 2024; 12:RP91153. [PMID: 38192196 PMCID: PMC10963032 DOI: 10.7554/elife.91153] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024] Open
Abstract
Detailed characterization of interneuron types in primary visual cortex (V1) has greatly contributed to understanding visual perception, yet the role of chandelier cells (ChCs) in visual processing remains poorly characterized. Using viral tracing we found that V1 ChCs predominantly receive monosynaptic input from local layer 5 pyramidal cells and higher-order cortical regions. Two-photon calcium imaging and convolutional neural network modeling revealed that ChCs are visually responsive but weakly selective for stimulus content. In mice running in a virtual tunnel, ChCs respond strongly to events known to elicit arousal, including locomotion and visuomotor mismatch. Repeated exposure of the mice to the virtual tunnel was accompanied by reduced visual responses of ChCs and structural plasticity of ChC boutons and axon initial segment length. Finally, ChCs only weakly inhibited pyramidal cells. These findings suggest that ChCs provide an arousal-related signal to layer 2/3 pyramidal cells that may modulate their activity and/or gate plasticity of their axon initial segments during behaviorally relevant events.
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Affiliation(s)
- Koen Seignette
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Nora Jamann
- Department of Axonal Signaling, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Biology Cell Biology, Neurobiology and Biophysics, Faculty of Science, Utrecht UniversityUtrechtNetherlands
| | - Paolo Papale
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Huub Terra
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Ralph O Porneso
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Leander de Kraker
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Chris van der Togt
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Maaike van der Aa
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Paul Neering
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Emma Ruimschotel
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Pieter R Roelfsema
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la VisionParisFrance
- Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU UniversityAmsterdamNetherlands
- Department of Psychiatry, Academic Medical Center, University of AmsterdamAmsterdamNetherlands
| | - Jorrit S Montijn
- Department of Cortical Structure & Function, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Matthew W Self
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Maarten HP Kole
- Department of Axonal Signaling, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Biology Cell Biology, Neurobiology and Biophysics, Faculty of Science, Utrecht UniversityUtrechtNetherlands
| | - Christiaan N Levelt
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, VU University AmsterdamAmsterdamNetherlands
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38
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Timonidis N, Rubio-Teves M, Alonso-Martínez C, Bakker R, García-Amado M, Tiesinga P, Clascá F. Analyzing Thalamocortical Tract-Tracing Experiments in a Common Reference Space. Neuroinformatics 2024; 22:23-43. [PMID: 37864741 PMCID: PMC10917831 DOI: 10.1007/s12021-023-09644-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2023] [Indexed: 10/23/2023]
Abstract
Current mesoscale connectivity atlases provide limited information about the organization of thalamocortical projections in the mouse brain. Labeling the projections of spatially restricted neuron populations in thalamus can provide a functionally relevant level of connectomic analysis, but these need to be integrated within the same common reference space. Here, we present a pipeline for the segmentation, registration, integration and analysis of multiple tract-tracing experiments. The key difference with other workflows is that the data is transformed to fit the reference template. As a test-case, we investigated the axonal projections and intranuclear arrangement of seven neuronal populations of the ventral posteromedial nucleus of the thalamus (VPM), which we labeled with an anterograde tracer. Their soma positions corresponded, from dorsal to ventral, to cortical representations of the whiskers, nose and mouth. They strongly targeted layer 4, with the majority exclusively targeting one cortical area and the ones in ventrolateral VPM branching to multiple somatosensory areas. We found that our experiments were more topographically precise than similar experiments from the Allen Institute and projections to the primary somatosensory area were in agreement with single-neuron morphological reconstructions from publicly available databases. This pilot study sets the basis for a shared virtual connectivity atlas that could be enriched with additional data for studying the topographical organization of different thalamic nuclei. The pipeline is accessible with only minimal programming skills via a Jupyter Notebook, and offers multiple visualization tools such as cortical flatmaps, subcortical plots and 3D renderings and can be used with custom anatomical delineations.
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Affiliation(s)
- Nestor Timonidis
- Neuroinformatics Department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands.
| | - Mario Rubio-Teves
- Department of Anatomy and Neuroscience, School of Medicine, Autónoma de Madrid University, C. Arzobispo Morcillo 4, 28029, Madrid, Spain
| | - Carmen Alonso-Martínez
- Department of Anatomy and Neuroscience, School of Medicine, Autónoma de Madrid University, C. Arzobispo Morcillo 4, 28029, Madrid, Spain
| | - Rembrandt Bakker
- Neuroinformatics Department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
- Inst. of Neuroscience and Medicine (INM-6) and Inst. for Advanced Simulation (IAS-6) and JARA BRAIN Inst. I, Jülich Research Centre, Wilhelm-Johnen-Strasse, 52425, Jülich, Germany
| | - María García-Amado
- Department of Anatomy and Neuroscience, School of Medicine, Autónoma de Madrid University, C. Arzobispo Morcillo 4, 28029, Madrid, Spain
| | - Paul Tiesinga
- Neuroinformatics Department, Donders Centre for Neuroscience, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands
| | - Francisco Clascá
- Department of Anatomy and Neuroscience, School of Medicine, Autónoma de Madrid University, C. Arzobispo Morcillo 4, 28029, Madrid, Spain
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Surets M, Caban-Murillo A, Ramirez S. Prelimbic cortex ensembles promote appetitive learning-associated behavior. Learn Mem 2024; 31:a053892. [PMID: 38408863 PMCID: PMC10903945 DOI: 10.1101/lm.053892.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 01/30/2024] [Indexed: 02/28/2024]
Abstract
Memories of prior rewards bias our actions and future decisions. To determine the neural correlates of an appetitive associative learning task, we trained male mice to discriminate a reward-predicting cue over the course of 7 d. Encoding, recent recall, and remote recall were investigated to determine the areas of the brain recruited at each stage of learning. Using cFos as a proxy for neuronal activity, we found unique brain-wide patterns of activity across days that seem to correlate with distinct stages of learning. In particular, the prelimbic (PL) cortex was significantly recruited during the encoding of a novel association presentation, but its activity decreases as learning continues. To causally dissect the role of the PL in a reward memory across days, we chemogenetically inhibited first the PL entirely and then only tagged memory-bearing cells that were active during encoding in two stages of learning: early and late. Both nonspecific and specific PL inhibition experiments indicate that the PL drives behavior during late stages of learning to facilitate appropriate cue-driven behavior. Overall, our work underscores memory's role in discriminative reward seeking, and points to the PL as a target for modulating disorders in which impaired reward processing is a core component.
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Affiliation(s)
- Michelle Surets
- Psychological and Brain Sciences, Boston University, Boston, Massachusetts 02215, USA
- Boston University School of Medicine, Boston University, Boston, Massachusetts 02215, USA
| | - Albit Caban-Murillo
- Graduate Program for Neuroscience, Boston University, Boston, Massachusetts 02215, USA
| | - Steve Ramirez
- Psychological and Brain Sciences, Boston University, Boston, Massachusetts 02215, USA
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40
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Zhang A, Jin L, Yao S, Matsuyama M, van Velthoven C, Sullivan H, Sun N, Kellis M, Tasic B, Wickersham IR, Chen X. Rabies virus-based barcoded neuroanatomy resolved by single-cell RNA and in situ sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532873. [PMID: 36993334 PMCID: PMC10055146 DOI: 10.1101/2023.03.16.532873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Mapping the connectivity of diverse neuronal types provides the foundation for understanding the structure and function of neural circuits. High-throughput and low-cost neuroanatomical techniques based on RNA barcode sequencing have the potential to map circuits at cellular resolution and a brain-wide scale, but existing Sindbis virus-based techniques can only map long-range projections using anterograde tracing approaches. Rabies virus can complement anterograde tracing approaches by enabling either retrograde labeling of projection neurons or monosynaptic tracing of direct inputs to genetically targeted postsynaptic neurons. However, barcoded rabies virus has so far been only used to map non-neuronal cellular interactions in vivo and synaptic connectivity of cultured neurons. Here we combine barcoded rabies virus with single-cell and in situ sequencing to perform retrograde labeling and transsynaptic labeling in the mouse brain. We sequenced 96 retrogradely labeled cells and 295 transsynaptically labeled cells using single-cell RNA-seq, and 4,130 retrogradely labeled cells and 2,914 transsynaptically labeled cells in situ. We found that the transcriptomic identities of rabies virus-infected cells can be robustly identified using both single-cell RNA-seq and in situ sequencing. By associating gene expression with connectivity inferred from barcode sequencing, we distinguished long-range projecting cortical cell types from multiple cortical areas and identified cell types with converging or diverging synaptic connectivity. Combining in situ sequencing with barcoded rabies virus complements existing sequencing-based neuroanatomical techniques and provides a potential path for mapping synaptic connectivity of neuronal types at scale.
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Affiliation(s)
- Aixin Zhang
- Allen Institute for Brain Science, Seattle, WA
| | - Lei Jin
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
- Current address: Lingang Laboratory, Shanghai, China
| | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA
| | - Makoto Matsuyama
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
- Current address: Metcela Inc., Kawasaki, Kanagawa, Japan
| | | | - Heather Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
| | - Na Sun
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Manolis Kellis
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Ian R. Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
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Kleven H, Bjerke IE, Clascá F, Groenewegen HJ, Bjaalie JG, Leergaard TB. Waxholm Space atlas of the rat brain: a 3D atlas supporting data analysis and integration. Nat Methods 2023; 20:1822-1829. [PMID: 37783883 PMCID: PMC10630136 DOI: 10.1038/s41592-023-02034-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 09/01/2023] [Indexed: 10/04/2023]
Abstract
Volumetric brain atlases are increasingly used to integrate and analyze diverse experimental neuroscience data acquired from animal models, but until recently a publicly available digital atlas with complete coverage of the rat brain has been missing. Here we present an update of the Waxholm Space rat brain atlas, a comprehensive open-access volumetric atlas resource. This brain atlas features annotations of 222 structures, of which 112 are new and 57 revised compared to previous versions. It provides a detailed map of the cerebral cortex, hippocampal region, striatopallidal areas, midbrain dopaminergic system, thalamic cell groups, the auditory system and main fiber tracts. We document the criteria underlying the annotations and demonstrate how the atlas with related tools and workflows can be used to support interpretation, integration, analysis and dissemination of experimental rat brain data.
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Affiliation(s)
- Heidi Kleven
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Ingvild E Bjerke
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Francisco Clascá
- Department of Anatomy and Neuroscience, Autónoma de Madrid University, Madrid, Spain
| | - Henk J Groenewegen
- Department of Anatomy and Neurosciences, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve B Leergaard
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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42
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Reiten I, Olsen GM, Bjaalie JG, Witter MP, Leergaard TB. The efferent connections of the orbitofrontal, posterior parietal, and insular cortex of the rat brain. Sci Data 2023; 10:645. [PMID: 37735463 PMCID: PMC10514078 DOI: 10.1038/s41597-023-02527-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 08/31/2023] [Indexed: 09/23/2023] Open
Abstract
The orbitofrontal, posterior parietal, and insular cortices are sites of higher-order cognitive processing implicated in a wide range of behaviours, including working memory, attention guiding, decision making, and spatial navigation. To better understand how these regions contribute to such functions, we need detailed knowledge about the underlying structural connectivity. Several tract-tracing studies have investigated specific aspects of orbitofrontal, posterior parietal and insular connectivity, but a digital resource for studying the cortical and subcortical projections from these areas in detail is not available. We here present a comprehensive collection of brightfield and fluorescence microscopic images of serial coronal sections from 49 rat brain tract-tracing experiments, in which discrete injections of the anterograde tracers biotinylated dextran amine and/or Phaseolus vulgaris leucoagglutinin were placed in the orbitofrontal, parietal, or insular cortex. The images are spatially registered to the Waxholm Space Rat brain atlas. The image collection, with corresponding reference atlas maps, is suitable as a reference framework for investigating the brain-wide efferent connectivity of these cortical association areas.
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Affiliation(s)
- Ingrid Reiten
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Grethe M Olsen
- Kavli Institute for Systems Neuroscience, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Jan G Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Menno P Witter
- Kavli Institute for Systems Neuroscience, NTNU Norwegian University of Science and Technology, Trondheim, Norway
| | - Trygve B Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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43
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Carey H, Pegios M, Martin L, Saleeba C, Turner AJ, Everett NA, Bjerke IE, Puchades MA, Bjaalie JG, McMullan S. DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas. Nat Commun 2023; 14:5884. [PMID: 37735467 PMCID: PMC10514056 DOI: 10.1038/s41467-023-41645-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 09/12/2023] [Indexed: 09/23/2023] Open
Abstract
Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.
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Affiliation(s)
- Harry Carey
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Michael Pegios
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | | | - Chris Saleeba
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | - Anita J Turner
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia
| | | | - Ingvild E Bjerke
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maja A Puchades
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Simon McMullan
- Macquarie Medical School, Faculty of Medicine, Health & Human Sciences, Macquarie University, Marsfield, NSW, Australia.
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44
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Bjerke IE, Yates SC, Carey H, Bjaalie JG, Leergaard TB. Scaling up cell-counting efforts in neuroscience through semi-automated methods. iScience 2023; 26:107562. [PMID: 37636060 PMCID: PMC10457595 DOI: 10.1016/j.isci.2023.107562] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023] Open
Abstract
Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.
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Affiliation(s)
- Ingvild Elise Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Sharon Christine Yates
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Harry Carey
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Jan Gunnar Bjaalie
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Trygve Brauns Leergaard
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
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45
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Jovanovic P, Pool AH, Morones N, Wang Y, Novinbakht E, Keshishian N, Jang K, Oka Y, Riera CE. A sex-specific thermogenic neurocircuit induced by predator smell recruiting cholecystokinin neurons in the dorsomedial hypothalamus. Nat Commun 2023; 14:4937. [PMID: 37582805 PMCID: PMC10427624 DOI: 10.1038/s41467-023-40484-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 07/31/2023] [Indexed: 08/17/2023] Open
Abstract
Olfactory cues are vital for prey animals like rodents to perceive and evade predators. Stress-induced hyperthermia, via brown adipose tissue (BAT) thermogenesis, boosts physical performance and facilitates escape. However, many aspects of this response, including thermogenic control and sex-specific effects, remain enigmatic. Our study unveils that the predator odor trimethylthiazoline (TMT) elicits BAT thermogenesis, suppresses feeding, and drives glucocorticoid release in female mice. Chemogenetic stimulation of olfactory bulb (OB) mitral cells recapitulates the thermogenic output of this response and associated stress hormone corticosterone release in female mice. Neuronal projections from OB to medial amygdala (MeA) and dorsomedial hypothalamus (DMH) exhibit female-specific cFos activity toward odors. Cell sorting and single-cell RNA-sequencing of DMH identify cholecystokinin (CCK)-expressing neurons as recipients of predator odor cues. Chemogenetic manipulation and neuronal silencing of DMHCCK neurons further implicate these neurons in the propagation of predator odor-associated thermogenesis and food intake suppression, highlighting their role in female stress-induced hyperthermia.
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Affiliation(s)
- Predrag Jovanovic
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
| | - Allan-Hermann Pool
- Department of Neuroscience, Department of Anesthesiology and Pain Management, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Nancy Morones
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
| | - Yidan Wang
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
| | - Edward Novinbakht
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
| | - Nareg Keshishian
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
| | - Kaitlyn Jang
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA
| | - Yuki Oka
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Celine E Riera
- Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA.
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA.
- Department of Neurology, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Los Angeles, CA, 90048, USA.
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46
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Kleven H, Gillespie TH, Zehl L, Dickscheid T, Bjaalie JG, Martone ME, Leergaard TB. AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures. Sci Data 2023; 10:486. [PMID: 37495585 PMCID: PMC10372146 DOI: 10.1038/s41597-023-02389-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 07/14/2023] [Indexed: 07/28/2023] Open
Abstract
Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.
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Affiliation(s)
- Heidi Kleven
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | | | - Lyuba Zehl
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Timo Dickscheid
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute of Computer Science, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jan G Bjaalie
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Maryann E Martone
- Department of Neurosciences, University of California, San Diego, USA
| | - Trygve B Leergaard
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
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47
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Lupori L, Totaro V, Cornuti S, Ciampi L, Carrara F, Grilli E, Viglione A, Tozzi F, Putignano E, Mazziotti R, Amato G, Gennaro C, Tognini P, Pizzorusso T. A comprehensive atlas of perineuronal net distribution and colocalization with parvalbumin in the adult mouse brain. Cell Rep 2023; 42:112788. [PMID: 37436896 DOI: 10.1016/j.celrep.2023.112788] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 05/03/2023] [Accepted: 06/25/2023] [Indexed: 07/14/2023] Open
Abstract
Perineuronal nets (PNNs) surround specific neurons in the brain and are involved in various forms of plasticity and clinical conditions. However, our understanding of the PNN role in these phenomena is limited by the lack of highly quantitative maps of PNN distribution and association with specific cell types. Here, we present a comprehensive atlas of Wisteria floribunda agglutinin (WFA)-positive PNNs and colocalization with parvalbumin (PV) cells for over 600 regions of the adult mouse brain. Data analysis shows that PV expression is a good predictor of PNN aggregation. In the cortex, PNNs are dramatically enriched in layer 4 of all primary sensory areas in correlation with thalamocortical input density, and their distribution mirrors intracortical connectivity patterns. Gene expression analysis identifies many PNN-correlated genes. Strikingly, PNN-anticorrelated transcripts are enriched in synaptic plasticity genes, generalizing PNNs' role as circuit stability factors.
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Affiliation(s)
| | | | - Sara Cornuti
- BIO@SNS Lab, Scuola Normale Superiore, 56126 Pisa, Italy
| | - Luca Ciampi
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Fabio Carrara
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Edda Grilli
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
| | | | | | | | | | - Giuseppe Amato
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Claudio Gennaro
- Institute of Information Science and Technologies (ISTI-CNR), 56124 Pisa, Italy
| | - Paola Tognini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy
| | - Tommaso Pizzorusso
- BIO@SNS Lab, Scuola Normale Superiore, 56126 Pisa, Italy; Institute of Neuroscience (IN-CNR), 56124 Pisa, Italy.
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48
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Sadeghi M, Ramos-Prats A, Neto P, Castaldi F, Crowley D, Matulewicz P, Paradiso E, Freysinger W, Ferraguti F, Goebel G. Localization and Registration of 2D Histological Mouse Brain Images in 3D Atlas Space. Neuroinformatics 2023; 21:615-630. [PMID: 37357231 PMCID: PMC10406728 DOI: 10.1007/s12021-023-09632-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/12/2023] [Indexed: 06/27/2023]
Abstract
To accurately explore the anatomical organization of neural circuits in the brain, it is crucial to map the experimental brain data onto a standardized system of coordinates. Studying 2D histological mouse brain slices remains the standard procedure in many laboratories. Mapping these 2D brain slices is challenging; due to deformations, artifacts, and tilted angles introduced during the standard preparation and slicing process. In addition, analysis of experimental mouse brain slices can be highly dependent on the level of expertise of the human operator. Here we propose a computational tool for Accurate Mouse Brain Image Analysis (AMBIA), to map 2D mouse brain slices on the 3D brain model with minimal human intervention. AMBIA has a modular design that comprises a localization module and a registration module. The localization module is a deep learning-based pipeline that localizes a single 2D slice in the 3D Allen Brain Atlas and generates a corresponding atlas plane. The registration module is built upon the Ardent python package that performs deformable 2D registration between the brain slice to its corresponding atlas. By comparing AMBIA's performance in localization and registration to human ratings, we demonstrate that it performs at a human expert level. AMBIA provides an intuitive and highly efficient way for accurate registration of experimental 2D mouse brain images to 3D digital mouse brain atlas. Our tool provides a graphical user interface and it is designed to be used by researchers with minimal programming knowledge.
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Affiliation(s)
- Maryam Sadeghi
- Department of Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria.
| | - Arnau Ramos-Prats
- Department of Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Pedro Neto
- Faculty of Engineering, University of Porto, Porto, Portugal
| | - Federico Castaldi
- Department of Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Devin Crowley
- Biomedical Engineering, Johns Hopkins University, Baltimore, United States
| | - Pawel Matulewicz
- Department of Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Enrica Paradiso
- KNAW, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
| | | | - Francesco Ferraguti
- Department of Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Georg Goebel
- Department of Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, Austria
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49
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Dorman R, Bos JJ, Vinck MA, Marchesi P, Fiorilli J, Lorteije JAM, Reiten I, Bjaalie JG, Okun M, Pennartz CMA. Spike-based coupling between single neurons and populations across rat sensory cortices, perirhinal cortex, and hippocampus. Cereb Cortex 2023; 33:8247-8264. [PMID: 37118890 PMCID: PMC10425201 DOI: 10.1093/cercor/bhad111] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 04/30/2023] Open
Abstract
Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and somatosensory, visual, and perirhinal cortices. Within-area coupling was heterogeneous across structures, with area CA1 showing higher levels than neocortical regions. In contrast to known anatomical connectivity, between-area coupling showed strong firing coherence of sensory neocortices with CA1, but less with perirhinal cortex. Cells in sensory neocortices and CA1 showed positive correlations between within- and between-area coupling; these were weaker for perirhinal cortex. All four areas harbored broadcasting cells, connecting to multiple external areas, which was uncorrelated to within-area coupling strength. When examining correlations between SNPC and spatial coding, we found that, if such correlations were significant, they were negative. This result was consistent with an overall preservation of SNPC across different brain states, suggesting a strong dependence on intrinsic network connectivity. Overall, SNPC offers an important window on cell-to-population synchronization in multi-area networks. Instead of pointing to specific information-coding functions, our results indicate a primary function of SNPC in dynamically organizing communication in systems composed of multiple, interconnected areas.
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Affiliation(s)
- Reinder Dorman
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jeroen J Bos
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HC Nijmegen, The Netherlands
| | - Martin A Vinck
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Plank Society, 60528 Frankfurt, Germany
| | - Pietro Marchesi
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Julien Fiorilli
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Jeanette A M Lorteije
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
| | - Ingrid Reiten
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Jan G Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, NO-0316 Oslo, Norway
| | - Michael Okun
- Department of Psychology and Neuroscience Institute, University of Sheffield, Sheffield S10 2TN, UK
| | - Cyriel M A Pennartz
- Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
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50
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Hawrylycz M, Martone ME, Ascoli GA, Bjaalie JG, Dong HW, Ghosh SS, Gillis J, Hertzano R, Haynor DR, Hof PR, Kim Y, Lein E, Liu Y, Miller JA, Mitra PP, Mukamel E, Ng L, Osumi-Sutherland D, Peng H, Ray PL, Sanchez R, Regev A, Ropelewski A, Scheuermann RH, Tan SZK, Thompson CL, Tickle T, Tilgner H, Varghese M, Wester B, White O, Zeng H, Aevermann B, Allemang D, Ament S, Athey TL, Baker C, Baker KS, Baker PM, Bandrowski A, Banerjee S, Bishwakarma P, Carr A, Chen M, Choudhury R, Cool J, Creasy H, D’Orazi F, Degatano K, Dichter B, Ding SL, Dolbeare T, Ecker JR, Fang R, Fillion-Robin JC, Fliss TP, Gee J, Gillespie T, Gouwens N, Zhang GQ, Halchenko YO, Harris NL, Herb BR, Hintiryan H, Hood G, Horvath S, Huo B, Jarecka D, Jiang S, Khajouei F, Kiernan EA, Kir H, Kruse L, Lee C, Lelieveldt B, Li Y, Liu H, Liu L, Markuhar A, Mathews J, Mathews KL, Mezias C, Miller MI, Mollenkopf T, Mufti S, Mungall CJ, Orvis J, Puchades MA, Qu L, Receveur JP, Ren B, Sjoquist N, Staats B, Tward D, van Velthoven CTJ, Wang Q, Xie F, Xu H, Yao Z, Yun Z, et alHawrylycz M, Martone ME, Ascoli GA, Bjaalie JG, Dong HW, Ghosh SS, Gillis J, Hertzano R, Haynor DR, Hof PR, Kim Y, Lein E, Liu Y, Miller JA, Mitra PP, Mukamel E, Ng L, Osumi-Sutherland D, Peng H, Ray PL, Sanchez R, Regev A, Ropelewski A, Scheuermann RH, Tan SZK, Thompson CL, Tickle T, Tilgner H, Varghese M, Wester B, White O, Zeng H, Aevermann B, Allemang D, Ament S, Athey TL, Baker C, Baker KS, Baker PM, Bandrowski A, Banerjee S, Bishwakarma P, Carr A, Chen M, Choudhury R, Cool J, Creasy H, D’Orazi F, Degatano K, Dichter B, Ding SL, Dolbeare T, Ecker JR, Fang R, Fillion-Robin JC, Fliss TP, Gee J, Gillespie T, Gouwens N, Zhang GQ, Halchenko YO, Harris NL, Herb BR, Hintiryan H, Hood G, Horvath S, Huo B, Jarecka D, Jiang S, Khajouei F, Kiernan EA, Kir H, Kruse L, Lee C, Lelieveldt B, Li Y, Liu H, Liu L, Markuhar A, Mathews J, Mathews KL, Mezias C, Miller MI, Mollenkopf T, Mufti S, Mungall CJ, Orvis J, Puchades MA, Qu L, Receveur JP, Ren B, Sjoquist N, Staats B, Tward D, van Velthoven CTJ, Wang Q, Xie F, Xu H, Yao Z, Yun Z, Zhang YR, Zheng WJ, Zingg B. A guide to the BRAIN Initiative Cell Census Network data ecosystem. PLoS Biol 2023; 21:e3002133. [PMID: 37390046 PMCID: PMC10313015 DOI: 10.1371/journal.pbio.3002133] [Show More Authors] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2023] Open
Abstract
Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.
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Affiliation(s)
- Michael Hawrylycz
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Maryann E. Martone
- Department of Neuroscience, University of California San Diego, San Diego, California, United States of America
- San Francisco Veterans Affairs Medical Center, San Francisco, California, United States of America
| | - Giorgio A. Ascoli
- Bioengineering Department and Center for Neural Informatics, Structures, & Plasticity, Volgenau School of Engineering, George Mason University, Fairfax, Virginia, United States of America
| | - Jan G. Bjaalie
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Hong-Wei Dong
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, California, United States of America
| | - Satrajit S. Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Jesse Gillis
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Ronna Hertzano
- Department of Otorhinolaryngology Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Department of Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - David R. Haynor
- Department of Radiology, University of Washington, Seattle, Washington, United States of America
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Yongsoo Kim
- Department of Neural and Behavioral Sciences, College of Medicine, The Pennsylvania State University, Hershey, Pennsylvania, United States of America
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Yufeng Liu
- SEU-Allen Institute Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu Province, China
| | - Jeremy A. Miller
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Partha P. Mitra
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Eran Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, California, United States of America
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - David Osumi-Sutherland
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Hanchuan Peng
- SEU-Allen Institute Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu Province, China
| | - Patrick L. Ray
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Raymond Sanchez
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Aviv Regev
- Genentech, South San Francisco, California, United States of America
| | - Alex Ropelewski
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | | | - Shawn Zheng Kai Tan
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Carol L. Thompson
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Timothy Tickle
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Hagen Tilgner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, New York, United States of America
| | - Merina Varghese
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Brock Wester
- Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, United States of America
| | - Owen White
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Brian Aevermann
- Chan Zuckerberg Initiative, Redwood City, California, United States of America
| | - David Allemang
- Kitware Inc., Albany, New York, United States of America
| | - Seth Ament
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Thomas L. Athey
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Cody Baker
- CatalystNeuro, Benicia, California, United States of America
| | - Katherine S. Baker
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Pamela M. Baker
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Anita Bandrowski
- Department of Neuroscience, University of California San Diego, San Diego, California, United States of America
| | - Samik Banerjee
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Prajal Bishwakarma
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Ambrose Carr
- Chan Zuckerberg Initiative, Redwood City, California, United States of America
| | - Min Chen
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Roni Choudhury
- Kitware Inc., Albany, New York, United States of America
| | - Jonah Cool
- Chan Zuckerberg Initiative, Redwood City, California, United States of America
| | - Heather Creasy
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Florence D’Orazi
- Chan Zuckerberg Initiative, Redwood City, California, United States of America
| | - Kylee Degatano
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | | | - Song-Lin Ding
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Tim Dolbeare
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, Howard Hughes Medical Institute, The Salk Institute for Biological Studies La Jolla, California, United States of America
| | - Rongxin Fang
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, United States of America
| | | | - Timothy P. Fliss
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - James Gee
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Tom Gillespie
- Department of Neuroscience, University of California San Diego, San Diego, California, United States of America
| | - Nathan Gouwens
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Guo-Qiang Zhang
- Texas Institute for Restorative Neurotechnologies, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Yaroslav O. Halchenko
- Department of Psychological and Brain Sciences, Dartmouth College, Hannover, New Hampshire, United States of America
| | - Nomi L. Harris
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Brian R. Herb
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Houri Hintiryan
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, California, United States of America
| | - Gregory Hood
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Sam Horvath
- Kitware Inc., Albany, New York, United States of America
| | - Bingxing Huo
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Dorota Jarecka
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Shengdian Jiang
- SEU-Allen Institute Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu Province, China
| | - Farzaneh Khajouei
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Elizabeth A. Kiernan
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Huseyin Kir
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Lauren Kruse
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Changkyu Lee
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Boudewijn Lelieveldt
- Department of Intelligent Systems, Delft University of Technology, Delft, the Netherlands
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Yang Li
- Center for Epigenomics, Department of Cellular and Molecular Medicine, UC San Diego School of Medicine, La Jolla, California, United States of America
| | - Hanqing Liu
- Genomic Analysis Laboratory, Howard Hughes Medical Institute, The Salk Institute for Biological Studies La Jolla, California, United States of America
| | - Lijuan Liu
- SEU-Allen Institute Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu Province, China
| | - Anup Markuhar
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - James Mathews
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Kaylee L. Mathews
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Chris Mezias
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Michael I. Miller
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Tyler Mollenkopf
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Shoaib Mufti
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Christopher J. Mungall
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Joshua Orvis
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Maja A. Puchades
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Lei Qu
- SEU-Allen Institute Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu Province, China
| | - Joseph P. Receveur
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Bing Ren
- Center for Epigenomics, Department of Cellular and Molecular Medicine, UC San Diego School of Medicine, La Jolla, California, United States of America
- Ludwig Institute for Cancer Research, La Jolla, California, United States of America
| | - Nathan Sjoquist
- Microsoft Corporation, Seattle, Washington, United States of America
| | - Brian Staats
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Daniel Tward
- UCLA Brain Mapping Center, University of California, Los Angeles, California, United States of America
| | | | - Quanxin Wang
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Fangming Xie
- Department of Chemistry and Biochemistry, University of California Los Angeles, California, United States of America
| | - Hua Xu
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Zhixi Yun
- SEU-Allen Institute Joint Center, Institute for Brain and Intelligence, Southeast University, Nanjing, Jiangsu Province, China
| | - Yun Renee Zhang
- J. Craig Venter Institute, La Jolla, California, United States of America
| | - W. Jim Zheng
- School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Brian Zingg
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, California, United States of America
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