Waxholm Space Atlas of the Sprague Dawley Rat Brain
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Brainstem: Midbrainmidbrain
Brainstem:Brainstem: MidbrainMidbrain 1.1. MidbrainMidbrain –– grossgross externalexternal anatomyanatomy 2.2. InternalInternal structurestructure ofof thethe midbrain:midbrain: cerebral peduncles tegmentum tectum (guadrigeminal plate) Midbrain MidbrainMidbrain –– generalgeneral featuresfeatures location – between forebrain and hindbrain the smallest region of the brainstem – 6-7g the shortest brainstem segment ~ 2 cm long least differentiated brainstem division human midbrain is archipallian – shared general architecture with the most ancient of vertebrates embryonic origin – mesencephalon main functions:functions a sort of relay station for sound and visual information serves as a nerve pathway of the cerebral hemispheres controls the eye movement involved in control of body movement Prof. Dr. Nikolai Lazarov 2 Midbrain MidbrainMidbrain –– grossgross anatomyanatomy dorsal part – tectum (quadrigeminal plate): superior colliculi inferior colliculi cerebral aqueduct ventral part – cerebral peduncles:peduncles dorsal – tegmentum (central part) ventral – cerebral crus substantia nigra Prof. Dr. Nikolai Lazarov 3 Midbrain CerebralCerebral cruscrus –– internalinternal structurestructure CerebralCerebral peduncle:peduncle: crus cerebri tegmentum mesencephali substantia nigra two thick semilunar white matter bundles composition – somatotopically arranged motor tracts: corticospinal } pyramidal tracts – medial ⅔ corticobulbar corticopontine fibers: frontopontine tracts – medially temporopontine tracts – laterally -
The Brain Stem Medulla Oblongata
Chapter 14 The Brain Stem Medulla Oblongata Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. Central sulcus Parietal lobe • embryonic myelencephalon becomes Cingulate gyrus leaves medulla oblongata Corpus callosum Parieto–occipital sulcus Frontal lobe Occipital lobe • begins at foramen magnum of the skull Thalamus Habenula Anterior Epithalamus commissure Pineal gland • extends for about 3 cm rostrally and ends Hypothalamus Posterior commissure at a groove between the medulla and Optic chiasm Mammillary body pons Cerebral aqueduct Pituitary gland Fourth ventricle Temporal lobe • slightly wider than spinal cord Cerebellum Midbrain • pyramids – pair of external ridges on Pons Medulla anterior surface oblongata – resembles side-by-side baseball bats (a) • olive – a prominent bulge lateral to each pyramid • posteriorly, gracile and cuneate fasciculi of the spinal cord continue as two pair of ridges on the medulla • all nerve fibers connecting the brain to the spinal cord pass through the medulla • four pairs of cranial nerves begin or end in medulla - IX, X, XI, XII Medulla Oblongata Associated Functions • cardiac center – adjusts rate and force of heart • vasomotor center – adjusts blood vessel diameter • respiratory centers – control rate and depth of breathing • reflex centers – for coughing, sneezing, gagging, swallowing, vomiting, salivation, sweating, movements of tongue and head Medulla Oblongata Nucleus of hypoglossal nerve Fourth ventricle Gracile nucleus Nucleus of Cuneate nucleus vagus -
High-Yield Neuroanatomy
LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page i Aptara Inc. High-Yield TM Neuroanatomy FOURTH EDITION LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page ii Aptara Inc. LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page iii Aptara Inc. High-Yield TM Neuroanatomy FOURTH EDITION James D. Fix, PhD Professor Emeritus of Anatomy Marshall University School of Medicine Huntington, West Virginia With Contributions by Jennifer K. Brueckner, PhD Associate Professor Assistant Dean for Student Affairs Department of Anatomy and Neurobiology University of Kentucky College of Medicine Lexington, Kentucky LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page iv Aptara Inc. Acquisitions Editor: Crystal Taylor Managing Editor: Kelley Squazzo Marketing Manager: Emilie Moyer Designer: Terry Mallon Compositor: Aptara Fourth Edition Copyright © 2009, 2005, 2000, 1995 Lippincott Williams & Wilkins, a Wolters Kluwer business. 351 West Camden Street 530 Walnut Street Baltimore, MD 21201 Philadelphia, PA 19106 Printed in the United States of America. All rights reserved. This book is protected by copyright. No part of this book may be reproduced or transmitted in any form or by any means, including as photocopies or scanned-in or other electronic copies, or utilized by any information storage and retrieval system without written permission from the copyright owner, except for brief quotations embodied in critical articles and reviews. Materials appearing in this book prepared by individuals as part of their official duties as U.S. government employees are not covered by the above-mentioned copyright. To request permission, please contact Lippincott Williams & Wilkins at 530 Walnut Street, Philadelphia, PA 19106, via email at [email protected], or via website at http://www.lww.com (products and services). -
High-Yield Neuroanatomy, FOURTH EDITION
LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page i Aptara Inc. High-Yield TM Neuroanatomy FOURTH EDITION LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page ii Aptara Inc. LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page iii Aptara Inc. High-Yield TM Neuroanatomy FOURTH EDITION James D. Fix, PhD Professor Emeritus of Anatomy Marshall University School of Medicine Huntington, West Virginia With Contributions by Jennifer K. Brueckner, PhD Associate Professor Assistant Dean for Student Affairs Department of Anatomy and Neurobiology University of Kentucky College of Medicine Lexington, Kentucky LWBK110-3895G-FM[i-xviii].qxd 8/14/08 5:57 AM Page iv Aptara Inc. Acquisitions Editor: Crystal Taylor Managing Editor: Kelley Squazzo Marketing Manager: Emilie Moyer Designer: Terry Mallon Compositor: Aptara Fourth Edition Copyright © 2009, 2005, 2000, 1995 Lippincott Williams & Wilkins, a Wolters Kluwer business. 351 West Camden Street 530 Walnut Street Baltimore, MD 21201 Philadelphia, PA 19106 Printed in the United States of America. All rights reserved. This book is protected by copyright. No part of this book may be reproduced or transmitted in any form or by any means, including as photocopies or scanned-in or other electronic copies, or utilized by any information storage and retrieval system without written permission from the copyright owner, except for brief quotations embodied in critical articles and reviews. Materials appearing in this book prepared by individuals as part of their official duties as U.S. government employees are not covered by the above-mentioned copyright. To request permission, please contact Lippincott Williams & Wilkins at 530 Walnut Street, Philadelphia, PA 19106, via email at [email protected], or via website at http://www.lww.com (products and services). -
…Going One Step Further
…going one step further C20 (1017868) 2 Latin A Encephalon Mesencephalon B Telencephalon 31 Lamina tecti B1 Lobus frontalis 32 Tegmentum mesencephali B2 Lobus temporalis 33 Crus cerebri C Diencephalon 34 Aqueductus mesencephali D Mesencephalon E Metencephalon Metencephalon E1 Cerebellum 35 Cerebellum F Myelencephalon a Vermis G Circulus arteriosus cerebri (Willisii) b Tonsilla c Flocculus Telencephalon d Arbor vitae 1 Lobus frontalis e Ventriculus quartus 2 Lobus parietalis 36 Pons 3 Lobus occipitalis f Pedunculus cerebellaris superior 4 Lobus temporalis g Pedunculus cerebellaris medius 5 Sulcus centralis h Pedunculus cerebellaris inferior 6 Gyrus precentralis 7 Gyrus postcentralis Myelencephalon 8 Bulbus olfactorius 37 Medulla oblongata 9 Commissura anterior 38 Oliva 10 Corpus callosum 39 Pyramis a Genu 40 N. cervicalis I. (C1) b Truncus ® c Splenium Nervi craniales d Rostrum I N. olfactorius 11 Septum pellucidum II N. opticus 12 Fornix III N. oculomotorius 13 Commissura posterior IV N. trochlearis 14 Insula V N. trigeminus 15 Capsula interna VI N. abducens 16 Ventriculus lateralis VII N. facialis e Cornu frontale VIII N. vestibulocochlearis f Pars centralis IX N. glossopharyngeus g Cornu occipitale X N. vagus h Cornu temporale XI N. accessorius 17 V. thalamostriata XII N. hypoglossus 18 Hippocampus Circulus arteriosus cerebri (Willisii) Diencephalon 1 A. cerebri anterior 19 Thalamus 2 A. communicans anterior 20 Sulcus hypothalamicus 3 A. carotis interna 21 Hypothalamus 4 A. cerebri media 22 Adhesio interthalamica 5 A. communicans posterior 23 Glandula pinealis 6 A. cerebri posterior 24 Corpus mammillare sinistrum 7 A. superior cerebelli 25 Hypophysis 8 A. basilaris 26 Ventriculus tertius 9 Aa. pontis 10 A. -
Post-Mortem 1.5T MR Quantification of Regular Anatomical Brain Structures
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Bern Open Repository and Information System (BORIS) Int J Legal Med (2016) 130:1071–1080 DOI 10.1007/s00414-016-1318-3 ORIGINAL ARTICLE Post-mortem 1.5T MR quantification of regular anatomical brain structures Wolf-Dieter Zech1,3 & Anna-Lena Hottinger1 & Nicole Schwendener1 & Frederick Schuster1,2 & Anders Persson3 & Marcel J. Warntjes3 & Christian Jackowski1 Received: 17 November 2015 /Accepted: 13 January 2016 /Published online: 12 February 2016 # Springer-Verlag Berlin Heidelberg 2016 Abstract Recently, post-mortem MR quantification has been anatomical brain structures among each other in Group 1 introduced to the field of post-mortem magnetic resonance and Group 2 based on their quantitative values. Temperature imaging. By usage of a particular MR quantification se- dependence was observed mainly for T1 values, which were quence, T1 and T2 relaxation times and proton density (PD) slightly increasing with rising temperature in the investigated of tissues and organs can be quantified simultaneously. The brain structures in both groups. The results provide a base for aim of the present basic research study was to assess the quan- future computer-aided diagnosis of brain pathologies and le- titative T1, T2, and PD values of regular anatomical brain sions in post-mortem magnetic resonance imaging. structures for a 1.5T application and to correlate the assessed values with corpse temperatures. In a prospective study, 30 Keywords Brain .MRquantification .Post-mortemmagnetic forensic cases were MR-scanned with a quantification se- resonance imaging (PMMR) . Forensic . Neuroimaging quence prior to autopsy. -
Is Composed from Spinal Cord and Brain
doc. MUDr. Adriana Boleková, PhD. MVDr. Natália Hvizdošová, PhD. CENTRAL NERVOUS SYSTEM – is composed from spinal cord and brain SPINAL CORD cranial border: foramen magnum, pyramidal decussation, exit of first pair of spinal nerves caudal border: level of L1 – L2 vertebrae medullary cone – filum terminale (S2) – cauda equina enlargements: cervical enlargement (C5 – Th1): origin of nerves for upper extremity – brachial plexus lumbosacral enlargement (L1 – S2): origin of nerves for lower extremity – lumbosacral plexus external features: anterior median fissure anterolateral sulcus – anterior roots of spinal nn. posterolateral sulcus – posterior roots of spinal nn. posterior median sulcus posterior intermediate sulcus internal features: White matter anterior funiculus (between anterior median fissure and anterolateral sulcus) lateral funiculus (between anterolateral and posterolateral sulci) posterior funiculus (between posterolateral sulcus and posterior median sulcus) fasciculus gracilis fasciculus cuneatus Gray matter anterior (ventral) horn – motor function: Rexed laminae I – VI lateral horn – serves to visceral function: Rexed lamina VII dorsal (posterior) horn – sensory information: Rexed laminae VIII – IX central grey matter – interneurons: around central canal Rexed lamina X Central canal cranially opens into IV. ventricle caudally expands into terminal ventricle vessels of spinal cord: Arteries: spinal brr. from surrounding arteries – anterior radicular aa., posterior radicular aa.: posterior spinal aa. (in posterolateral -
The Neuron Phenotype Ontology: a FAIR Approach to Proposing and Classifying Neuronal Types
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.01.278879; this version posted September 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. The Neuron Phenotype Ontology: A FAIR Approach to Proposing and Classifying Neuronal Types Thomas H. Gillespie 1 (https://orcid.org/0000-0002-7509-4801) Shreejoy Tripathy2,3 (https://orcid.org/0000-0002-1007-9061) Mohameth François Sy (https://orcid.org/0000-0002-4603-9838) Maryann E. Martone 1, (https://orcid.org/0000-0002-8406-3871) Sean L. Hill2,3,4 (https://orcid.org/0000-0001-8055-860X) 1Department of Neuroscience, University of California, San Diego 2Department of Psychiatry, University of Toronto 3Krembil Center for Neuroinformatics, Centre for Addiction and Mental Health: Toronto 4Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland Corresponding Author: Sean Hill, Ph.D., [email protected] Blue Brain Project Campus Biotech, EPFL chemin des Mines, 9 Geneva, Switzerland CH-1202 Acknowledgements: This work was supported by NIH Brain Initiative award 5U24MH114827-04, a Canadian Institute for Health Research post-doctoral fellowship and National Institutes of Health grant MH111099, the Krembil Foundation, and by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology . Meetings supporting this work were facilitated by the International Neuroinformatics Coordinating Facility (INCF) through the Neuroinformatics for cell types special interest group. -
Neuroinformatics.Pdf
1 23 Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be self- archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”. 1 23 Author's personal copy Neuroinform DOI 10.1007/s12021-013-9210-5 ORIGINAL ARTICLE Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics Michael A. Arbib & James J. Bonaiuto & Ina Bornkessel-Schlesewsky & David Kemmerer & Brian MacWhinney & Finn Årup Nielsen & Erhan Oztop # Springer Science+Business Media New York 2013 Abstract We assess the challenges of studying action and Databasing empirical data . Federation of databases . language mechanisms in the brain, both singly and in relation Collaboratory workspaces to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and Bridging the Gap Between Models and Experiments empirical data that serve systems and cognitive neuroscience. The present article offers a perspective on the neuroinformatics Keywords Linking models and experiments . Models, challenges of linking neuroscience data with models of the neurocomputational . -
Foundational Model of Structural Connectivity in the Nervous System
Foundational model of structural connectivity in the INAUGURAL ARTICLE nervous system with a schema for wiring diagrams, connectome, and basic plan architecture Larry W. Swanson1 and Mihail Bota Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089 This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2010. Contributed by Larry W. Swanson, October 8, 2010 (sent for review September 13, 2010) The nervous system is a biological computer integrating the body’s ular, cellular, systems, and behavioral organization levels. A reflex and voluntary environmental interactions (behavior) with Human Connectome Project goal might be framed as providing a relatively constant internal state (homeostasis)—promoting sur- the detailed structural data needed to create a foundational vival of the individual and species. The wiring diagram of the nervous system structural model analogous to the DNA double- nervous system’s structural connectivity provides an obligatory helix structural model. foundational model for understanding functional localization at Neuroinformatics offers powerful new tools to store, share, molecular, cellular, systems, and behavioral organization levels. mine, analyze, and model data about neural connectivity in- This paper provides a high-level, downwardly extendible, concep- cluding the human brain—by far the most complex system tual framework—like a compass and map—for describing and known. Databases and inference engines for automatic reasoning exploring in neuroinformatics systems (such as our Brain Architec- in neuroinformatics workbenches require an integrated concep- ture Knowledge Management System) the structural architecture tual framework: (i)adefined universe of discourse (concept of the nervous system’s basic wiring diagram. -
Neuroanatomical Domain of the Foundational Model of Anatomy
Nichols et al. Journal of Biomedical Semantics 2014, 5:1 http://www.jbiomedsem.com/content/5/1/1 JOURNAL OF BIOMEDICAL SEMANTICS DATABASE Open Access Neuroanatomical domain of the foundational model of anatomy ontology B Nolan Nichols1*, Jose LV Mejino1, Landon T Detwiler1, Trond T Nilsen1, Maryann E Martone2, Jessica A Turner3, Daniel L Rubin4 and James F Brinkley1 Abstract Background: The diverse set of human brain structure and function analysis methods represents a difficult challenge for reconciling multiple views of neuroanatomical organization. While different views of organization are expected and valid, no widely adopted approach exists to harmonize different brain labeling protocols and terminologies. Our approach uses the natural organizing framework provided by anatomical structure to correlate terminologies commonly used in neuroimaging. Description: The Foundational Model of Anatomy (FMA) Ontology provides a semantic framework for representing the anatomical entities and relationships that constitute the phenotypic organization of the human body. In this paper we describe recent enhancements to the neuroanatomical content of the FMA that models cytoarchitectural and morphological regions of the cerebral cortex, as well as white matter structure and connectivity. This modeling effort is driven by the need to correlate and reconcile the terms used in neuroanatomical labeling protocols. By providing an ontological framework that harmonizes multiple views of neuroanatomical organization, the FMA provides developers with reusable and computable knowledge for a range of biomedical applications. Conclusions: A requirement for facilitating the integration of basic and clinical neuroscience data from diverse sources is a well-structured ontology that can incorporate, organize, and associate neuroanatomical data. We applied the ontological framework of the FMA to align the vocabularies used by several human brain atlases, and to encode emerging knowledge about structural connectivity in the brain. -
A Community-Based Transcriptomics Classification and Nomenclature Of
COMMENT | FOCUS comment | FOCUS A community-based transcriptomics classifcation and nomenclature of neocortical cell types To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unifed taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the frst time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defned by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classifcation should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic defnition of a cell type and incorporate data from diferent approaches, developmental stages and species. A community-based classifcation and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classifcation, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body. Rafael Yuste, Michael Hawrylycz, Nadia Aalling, Argel Aguilar-Valles, Detlev Arendt, Ruben Armananzas Arnedillo, Giorgio A. Ascoli, Concha Bielza, Vahid Bokharaie, Tobias Borgtoft Bergmann, Irina Bystron, Marco Capogna, Yoonjeung Chang, Ann Clemens, Christiaan P. J. de Kock, Javier DeFelipe, Sandra Esmeralda Dos Santos, Keagan Dunville, Dirk Feldmeyer, Richárd Fiáth, Gordon James Fishell, Angelica Foggetti, Xuefan Gao, Parviz Ghaderi, Natalia A.