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Petanjek Z, Banovac I, Sedmak D, Hladnik A. Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits. ADVANCES IN NEUROBIOLOGY 2023; 34:143-221. [PMID: 37962796 DOI: 10.1007/978-3-031-36159-3_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia.
| | - Ivan Banovac
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
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Wilson DF, Matschinsky FM. Cerebrovascular Blood Flow Design and Regulation; Vulnerability in Aging Brain. Front Physiol 2020; 11:584891. [PMID: 33178048 PMCID: PMC7596697 DOI: 10.3389/fphys.2020.584891] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 09/24/2020] [Indexed: 12/24/2022] Open
Abstract
Nutrient delivery to the brain presents a unique challenge because the tissue functions as a computer system with in the order of 200,000 neurons/mm3. Penetrating arterioles bud from surface arteries of the brain and penetrate downward through the cortex. Capillary networks spread from penetrating arterioles through the surrounding tissue. Each penetrating arteriole forms a vascular unit, with little sharing of flow among vascular units (collateral flow). Unlike cells in other tissues, neurons have to be operationally isolated, interacting with other neurons through specific electrical connections. Neuronal activation typically involves only a few of the cells within a vascular unit, but the local increase in nutrient consumption is substantial. The metabolic response to activation is transmitted to the feeding arteriole through the endothelium of neighboring capillaries and alters calcium permeability of smooth muscle in the wall resulting in modulation of flow through the entire vascular unit. Many age and trauma related brain pathologies can be traced to vascular malfunction. This includes: 1. Physical damage such as in traumatic injury with imposed shear stress as soft tissue moves relative to the skull. Lack of collateral flow among vascular units results in death of the cells in that vascular unit and loss of brain tissue. 2. Age dependent changes lead to progressive increase in vascular resistance and decrease in tissue levels of oxygen and glucose. Chronic hypoxia/hypoglycemia compromises tissue energy metabolism and related regulatory processes. This alters stem cell proliferation and differentiation, undermines vascular integrity, and suppresses critical repair mechanisms such as oligodendrocyte generation and maturation. Reduced structural integrity results in local regions of acute hypoxia and microbleeds, while failure of oligodendrocytes to fully mature leads to poor axonal myelination and defective neuronal function. Understanding and treating age related pathologies, particularly in brain, requires better knowledge of why and how vasculature changes with age. That knowledge will, hopefully, make possible drugs/methods for protecting vascular function, substantially alleviating the negative health and cognitive deficits associated with growing old.
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Affiliation(s)
- David F Wilson
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Franz M Matschinsky
- Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Gu QLL, Tian ZQK, Kovačič G, Zhou D, Cai D. The Dynamics of Balanced Spiking Neuronal Networks Under Poisson Drive Is Not Chaotic. Front Comput Neurosci 2018; 12:47. [PMID: 30013471 PMCID: PMC6036256 DOI: 10.3389/fncom.2018.00047] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2017] [Accepted: 05/30/2018] [Indexed: 11/30/2022] Open
Abstract
Some previous studies have shown that chaotic dynamics in the balanced state, i.e., one with balanced excitatory and inhibitory inputs into cortical neurons, is the underlying mechanism for the irregularity of neural activity. In this work, we focus on networks of current-based integrate-and-fire neurons with delta-pulse coupling. While we show that the balanced state robustly persists in this system within a broad range of parameters, we mathematically prove that the largest Lyapunov exponent of this type of neuronal networks is negative. Therefore, the irregular firing activity can exist in the system without the chaotic dynamics. That is the irregularity of balanced neuronal networks need not arise from chaos.
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Affiliation(s)
- Qing-Long L Gu
- School of Mathematical Sciences, MOE-LSC, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Zhong-Qi K Tian
- School of Mathematical Sciences, MOE-LSC, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - Gregor Kovačič
- Mathematical Sciences Department, Rensselaer Polytechnic Institute, Troy, NY, United States
| | - Douglas Zhou
- School of Mathematical Sciences, MOE-LSC, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China
| | - David Cai
- School of Mathematical Sciences, MOE-LSC, Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai, China.,Courant Institute of Mathematical Sciences, Center for Neural Science, New York University, New York, NY, United States.,NYUAD Institute, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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Abstract
Neurons sharing similar features are often selectively connected with a higher probability and should be located in close vicinity to save wiring. Selective connectivity has, therefore, been proposed to be the cause for spatial organization in cortical maps. Interestingly, orientation preference (OP) maps in the visual cortex are found in carnivores, ungulates, and primates but are not found in rodents, indicating fundamental differences in selective connectivity that seem unexpected for closely related species. Here, we investigate this finding by using multidimensional scaling to predict the locations of neurons based on minimizing wiring costs for any given connectivity. Our model shows a transition from an unstructured salt-and-pepper organization to a pinwheel arrangement when increasing the number of neurons, even without changing the selectivity of the connections. Increasing neuronal numbers also leads to the emergence of layers, retinotopy, or ocular dominance columns for the selective connectivity corresponding to each arrangement. We further show that neuron numbers impact overall interconnectivity as the primary reason for the appearance of neural maps, which we link to a known phase transition in an Ising-like model from statistical mechanics. Finally, we curated biological data from the literature to show that neural maps appear as the number of neurons in visual cortex increases over a wide range of mammalian species. Our results provide a simple explanation for the existence of salt-and-pepper arrangements in rodents and pinwheel arrangements in the visual cortex of primates, carnivores, and ungulates without assuming differences in the general visual cortex architecture and connectivity.
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Merker BH. Cortical Gamma Oscillations: Details of Their Genesis Preclude a Role in Cognition. Front Comput Neurosci 2016; 10:78. [PMID: 27512371 PMCID: PMC4961686 DOI: 10.3389/fncom.2016.00078] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 07/14/2016] [Indexed: 11/13/2022] Open
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Markram H, Muller E, Ramaswamy S, Reimann MW, Abdellah M, Sanchez CA, Ailamaki A, Alonso-Nanclares L, Antille N, Arsever S, Kahou GAA, Berger TK, Bilgili A, Buncic N, Chalimourda A, Chindemi G, Courcol JD, Delalondre F, Delattre V, Druckmann S, Dumusc R, Dynes J, Eilemann S, Gal E, Gevaert ME, Ghobril JP, Gidon A, Graham JW, Gupta A, Haenel V, Hay E, Heinis T, Hernando JB, Hines M, Kanari L, Keller D, Kenyon J, Khazen G, Kim Y, King JG, Kisvarday Z, Kumbhar P, Lasserre S, Le Bé JV, Magalhães BRC, Merchán-Pérez A, Meystre J, Morrice BR, Muller J, Muñoz-Céspedes A, Muralidhar S, Muthurasa K, Nachbaur D, Newton TH, Nolte M, Ovcharenko A, Palacios J, Pastor L, Perin R, Ranjan R, Riachi I, Rodríguez JR, Riquelme JL, Rössert C, Sfyrakis K, Shi Y, Shillcock JC, Silberberg G, Silva R, Tauheed F, Telefont M, Toledo-Rodriguez M, Tränkler T, Van Geit W, Díaz JV, Walker R, Wang Y, Zaninetta SM, DeFelipe J, Hill SL, Segev I, Schürmann F. Reconstruction and Simulation of Neocortical Microcircuitry. Cell 2015; 163:456-92. [PMID: 26451489 DOI: 10.1016/j.cell.2015.09.029] [Citation(s) in RCA: 775] [Impact Index Per Article: 86.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2014] [Revised: 05/04/2015] [Accepted: 09/11/2015] [Indexed: 02/03/2023]
Affiliation(s)
- Henry Markram
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland; Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland.
| | - Eilif Muller
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Srikanth Ramaswamy
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Michael W Reimann
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Marwan Abdellah
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Carlos Aguado Sanchez
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Anastasia Ailamaki
- Data-Intensive Applications and Systems Lab, EPFL, 1015 Lausanne, Switzerland
| | - Lidia Alonso-Nanclares
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid, Spain; Instituto Cajal (CSIC) and CIBERNED, 28002 Madrid, Spain
| | - Nicolas Antille
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Selim Arsever
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Guy Antoine Atenekeng Kahou
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Thomas K Berger
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Ahmet Bilgili
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Nenad Buncic
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Athanassia Chalimourda
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Giuseppe Chindemi
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Jean-Denis Courcol
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Fabien Delalondre
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Vincent Delattre
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Shaul Druckmann
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel; Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Raphael Dumusc
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - James Dynes
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Stefan Eilemann
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Eyal Gal
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Michael Emiel Gevaert
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Jean-Pierre Ghobril
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Albert Gidon
- Department of Neurobiology, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Joe W Graham
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Anirudh Gupta
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Valentin Haenel
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Etay Hay
- Department of Neurobiology, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel; The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Thomas Heinis
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland; Data-Intensive Applications and Systems Lab, EPFL, 1015 Lausanne, Switzerland; Imperial College London, London SW7 2AZ, UK
| | - Juan B Hernando
- CeSViMa, Centro de Supercomputación y Visualización de Madrid, Universidad Politécnica de Madrid, 28223 Madrid, Spain
| | - Michael Hines
- Department of Neurobiology, Yale University, New Haven, CT 06510 USA
| | - Lida Kanari
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Daniel Keller
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - John Kenyon
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Georges Khazen
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Yihwa Kim
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - James G King
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Zoltan Kisvarday
- MTA-Debreceni Egyetem, Neuroscience Research Group, 4032 Debrecen, Hungary
| | - Pramod Kumbhar
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Sébastien Lasserre
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland; Laboratoire d'informatique et de visualisation, EPFL, 1015 Lausanne, Switzerland
| | - Jean-Vincent Le Bé
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Bruno R C Magalhães
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Angel Merchán-Pérez
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid, Spain; Instituto Cajal (CSIC) and CIBERNED, 28002 Madrid, Spain
| | - Julie Meystre
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Benjamin Roy Morrice
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Jeffrey Muller
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Alberto Muñoz-Céspedes
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid, Spain; Instituto Cajal (CSIC) and CIBERNED, 28002 Madrid, Spain
| | - Shruti Muralidhar
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Keerthan Muthurasa
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Daniel Nachbaur
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Taylor H Newton
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Max Nolte
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Aleksandr Ovcharenko
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Juan Palacios
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Luis Pastor
- Modeling and Virtual Reality Group, Universidad Rey Juan Carlos, 28933 Móstoles, Madrid, Spain
| | - Rodrigo Perin
- Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Rajnish Ranjan
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland; Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Imad Riachi
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - José-Rodrigo Rodríguez
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid, Spain; Instituto Cajal (CSIC) and CIBERNED, 28002 Madrid, Spain
| | - Juan Luis Riquelme
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Christian Rössert
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Konstantinos Sfyrakis
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Ying Shi
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland; Laboratory of Neural Microcircuitry, Brain Mind Institute, EPFL, 1015 Lausanne, Switzerland
| | - Julian C Shillcock
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Gilad Silberberg
- Department of Neuroscience, Karolinska Institutet, Stockholm 17177, Sweden
| | - Ricardo Silva
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Farhan Tauheed
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland; Data-Intensive Applications and Systems Lab, EPFL, 1015 Lausanne, Switzerland
| | - Martin Telefont
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | | | - Thomas Tränkler
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Jafet Villafranca Díaz
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Richard Walker
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Yun Wang
- Key Laboratory of Visual Science and National Ministry of Health, School of Optometry and Opthalmology, Wenzhou Medical College, Wenzhou 325003, China; Caritas St. Elizabeth's Medical Center, Genesys Research Institute, Tufts University, Boston, MA 02111, USA
| | - Stefano M Zaninetta
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Madrid, Spain; Instituto Cajal (CSIC) and CIBERNED, 28002 Madrid, Spain
| | - Sean L Hill
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
| | - Idan Segev
- Department of Neurobiology, Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel; The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Felix Schürmann
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL) Biotech Campus, 1202 Geneva, Switzerland
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Medalla M, Barbas H. Specialized prefrontal "auditory fields": organization of primate prefrontal-temporal pathways. Front Neurosci 2014; 8:77. [PMID: 24795553 PMCID: PMC3997038 DOI: 10.3389/fnins.2014.00077] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2014] [Accepted: 03/27/2014] [Indexed: 12/14/2022] Open
Abstract
No other modality is more frequently represented in the prefrontal cortex than the auditory, but the role of auditory information in prefrontal functions is not well understood. Pathways from auditory association cortices reach distinct sites in the lateral, orbital, and medial surfaces of the prefrontal cortex in rhesus monkeys. Among prefrontal areas, frontopolar area 10 has the densest interconnections with auditory association areas, spanning a large antero-posterior extent of the superior temporal gyrus from the temporal pole to auditory parabelt and belt regions. Moreover, auditory pathways make up the largest component of the extrinsic connections of area 10, suggesting a special relationship with the auditory modality. Here we review anatomic evidence showing that frontopolar area 10 is indeed the main frontal “auditory field” as the major recipient of auditory input in the frontal lobe and chief source of output to auditory cortices. Area 10 is thought to be the functional node for the most complex cognitive tasks of multitasking and keeping track of information for future decisions. These patterns suggest that the auditory association links of area 10 are critical for complex cognition. The first part of this review focuses on the organization of prefrontal-auditory pathways at the level of the system and the synapse, with a particular emphasis on area 10. Then we explore ideas on how the elusive role of area 10 in complex cognition may be related to the specialized relationship with auditory association cortices.
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Affiliation(s)
- Maria Medalla
- Department of Anatomy and Neurobiology, Boston University Boston, MA, USA ; Neural Systems Laboratory, Department of Health Sciences, Boston University Boston, MA, USA
| | - Helen Barbas
- Department of Anatomy and Neurobiology, Boston University Boston, MA, USA ; Neural Systems Laboratory, Department of Health Sciences, Boston University Boston, MA, USA ; Department of Health Sciences, Boston University Boston, MA, USA
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8
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Guerra L, McGarry LM, Robles V, Bielza C, Larrañaga P, Yuste R. Comparison between supervised and unsupervised classifications of neuronal cell types: a case study. Dev Neurobiol 2011; 71:71-82. [PMID: 21154911 PMCID: PMC3058840 DOI: 10.1002/dneu.20809] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical GABAergic interneurons, the problem to discern among different cell types is particularly difficult and better methods are needed to perform objective classifications. Here we explore the use of supervised classification algorithms to classify neurons based on their morphological features, using a database of 128 pyramidal cells and 199 interneurons from mouse neocortex. To evaluate the performance of different algorithms we used, as a “benchmark,” the test to automatically distinguish between pyramidal cells and interneurons, defining “ground truth” by the presence or absence of an apical dendrite. We compared hierarchical clustering with a battery of different supervised classification algorithms, finding that supervised classifications outperformed hierarchical clustering. In addition, the selection of subsets of distinguishing features enhanced the classification accuracy for both sets of algorithms. The analysis of selected variables indicates that dendritic features were most useful to distinguish pyramidal cells from interneurons when compared with somatic and axonal morphological variables. We conclude that supervised classification algorithms are better matched to the general problem of distinguishing neuronal cell types when some information on these cell groups, in our case being pyramidal or interneuron, is known a priori. As a spin-off of this methodological study, we provide several methods to automatically distinguish neocortical pyramidal cells from interneurons, based on their morphologies. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 71: 71–82, 2011
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Affiliation(s)
- Luis Guerra
- Departamento de Inteligencia Artificial, Facultad de Informatica, Universidad Politécnica de Madrid, Spain.
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Ramaswamy S, Hill SL, King JG, Schürmann F, Wang Y, Markram H. Intrinsic morphological diversity of thick-tufted layer 5 pyramidal neurons ensures robust and invariant properties of in silico synaptic connections. J Physiol 2011; 590:737-52. [PMID: 22083599 DOI: 10.1113/jphysiol.2011.219576] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The morphology of neocortical pyramidal neurons is not only highly characteristic but also displays an intrinsic diversity that renders each neuron morphologically unique. We investigated the significance of this intrinsic morphological diversity in in silico networks composed of thick-tufted layer 5 (TTL5) pyramidal neurons, by comparing the in silico and in vitro properties of TTL5 synaptic connections. The synaptic locations of in silico connections were determined by placing 3D reconstructed TTL5 neurons randomly in a volume equivalent to that of layer 5 in the juvenile rat somatosensory cortex and using a 'collision-detection' algorithm to identify the incidental loci of axo-dendritic overlap. The activation time of the modelled synapses and their biophysical properties were characterized based on experimental measurements. We found that the anatomical loci of synapses and the physiological properties of the somatically recorded EPSPs closely matched those recorded experimentally without the need for any fine-tuning. Furthermore, perturbations to both the physiological or anatomical parameters of the model did not alter the average physiological properties of the population of modelled synaptic connections. This microcircuit-level robust behaviour was due to the intrinsic diversity of the morphology of pyramidal neurons in the microcircuit. We conclude that synaptic transmission in a network of TTL5 neurons is highly invariant across microcircuits suggesting that intrinsic diversity is a mechanism to ensure the same average synaptic properties in different animals of the same species. Finally, we show that the average physiological properties of the TTL5 microcircuit are surprisingly robust to anatomical and physiological perturbations also partly due to the intrinsic diversity of pyramidal neuron morphology.
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Affiliation(s)
- Srikanth Ramaswamy
- Brain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015, Lausanne, Switzerland
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10
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Wickens J, Hyland B, Anson G. Cortical Cell Assemblies: A Possible Mechanism for Motor Programs. J Mot Behav 2010; 26:66-82. [PMID: 15753061 DOI: 10.1080/00222895.1994.9941663] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The concept of a motor program has been used to interpret a diverse range of empirical findings related to preparation and initiation of voluntary movement. In the absence of an underlying mechanism, its exploratory power has been limited to that of an analogy with running a stored computer program. We argue that the theory of cortical cell assemblies suggests a possible neural mechanism for motor programming. According to this view, a motor program may be conceptualized as a cell assembly, which is stored in the form of strengthened synaptic connections between cortical pyramidal neurons. These connections determine which combinations of corticospinal neurons are activated when the cell assembly is ignited. The dynamics of cell assembly ignition are considered in relation to the problem of serial order. These considerations lead to a plausible neural mechanism for the programming of movements and movement sequences that is compatible with the effects of precue information and sequence length on reaction times. Anatomical and physiological guidelines for future quantitative models of cortical cell assemblies are suggested. By taking into account the parallel re-entrant loops between the cerebral cortex and basal ganglia, the theory of cortical cell assemblies suggests a mechanism for motor plans that involve longer sequences. The suggested model is compared with other existing neural network models for motor programming.
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Affiliation(s)
- J Wickens
- Department of Anatomy and Structural Biology, School of Medicine and Neuroscience, Research Centre, University of Otago, New Zealand.
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11
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Abstract
There are more than forty million blind individuals in the world whose plight would be greatly ameliorated by creating a visual prosthesis. We begin by outlining the basic operational characteristics of the visual system, as this knowledge is essential for producing a prosthetic device based on electrical stimulation through arrays of implanted electrodes. We then list a series of tenets that we believe need to be followed in this effort. Central among these is our belief that the initial research in this area, which is in its infancy, should first be carried out on animals. We suggest that implantation of area V1 holds high promise as the area is of a large volume and can therefore accommodate extensive electrode arrays. We then proceed to consider coding operations that can effectively convert visual images viewed by a camera to stimulate electrode arrays to yield visual impressions that can provide shape, motion, and depth information. We advocate experimental work that mimics electrical stimulation effects non-invasively in sighted human subjects with a camera from which visual images are converted into displays on a monitor akin to those created by electrical stimulation.
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Affiliation(s)
- Peter H Schiller
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA.
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12
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Tehovnik EJ, Slocum WM, Schiller PH. Delaying visually guided saccades by microstimulation of macaque V1: spatial properties of delay fields. Eur J Neurosci 2005; 22:2635-43. [PMID: 16307605 DOI: 10.1111/j.1460-9568.2005.04454.x] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Electrical microstimulation of macaque primary visual cortex (area V1) is known to delay the execution of saccadic eye movements made to a punctate visual target placed into the receptive field of the stimulated neurons. We examined the spatial extent of this delay effect, which we call a delay field, by placing a 0.2 degrees visual target at various locations relative to the receptive field of the stimulated neurons and by stimulating different sites within the operculum of V1. A 100-ms train of stimulation consisting of current pulses at or less than 100 microA was delivered immediately before monkeys generated a saccadic eye movement to the visual target. The region of tissue activated was within 0.5 mm from the electrode tip. The depth of stimulation for a given site ranged from 0.9 to 2.0 mm below the cortical surface. The location of the receptive fields of the stimulated neurons ranged from 1.8 to 4.4 degrees of eccentricity from the center of gaze. Within this range, the size of the delay field increased from 0.1 to 0.55 degrees of visual angle. The shape of the field was roughly circular. The size of the delay field increased as the stimulation site was located further from the foveal representation of V1. These results are consistent with the finding that phosphenes evoked by electrical stimulation of human V1 are circular and increase in size as the stimulating electrode is placed more distant from the foveal representation of V1.
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Affiliation(s)
- Edward J Tehovnik
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, E25-634, Cambridge, MA 02139, USA
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13
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Tehovnik EJ, Slocum WM. Microstimulation of V1 affects the detection of visual targets: manipulation of target contrast. Exp Brain Res 2005; 165:305-14. [PMID: 15942738 DOI: 10.1007/s00221-005-2306-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2004] [Accepted: 02/04/2005] [Indexed: 11/30/2022]
Abstract
Electrical microstimulation of the striate cortex (area V1) in monkeys delays the execution of saccadic eye movements generated to a visual target located in the receptive field of the stimulated neurons. We have argued that this effect is because of disruption of the visual signal transmitted along the geniculostriate pathway. The delivery of electrical stimulation to V1 evokes a punctate light or dark phosphene in human subjects. If electrical stimulation of V1 in monkeys evokes a light or dark phosphene, then one might expect that the delay effect might vary according to whether monkeys are required to detect a light or a dark visual target. For instance, if the stimulation is activating V1 elements coding for a light visual stimulus but not a dark visual stimulus then stimulation may delay saccades generated to a light target but not to a dark target. We tested this idea by having monkeys generate saccadic eye movements to light or dark visual targets immediately after the stimulation was delivered to V1. We found that the delay effect induced by stimulation varied with target contrast, but remained invariant to whether a bright or dark visual target was presented in the receptive field of the stimulated neurons. The significance of these results is discussed with regard to using monkeys to develop a visual prosthesis for the blind.
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Affiliation(s)
- Edward J Tehovnik
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, E25-634, Cambridge, MA 02139, USA.
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14
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Tehovnik EJ, Slocum WM, Carvey CE, Schiller PH. Phosphene Induction and the Generation of Saccadic Eye Movements by Striate Cortex. J Neurophysiol 2005; 93:1-19. [PMID: 15371496 DOI: 10.1152/jn.00736.2004] [Citation(s) in RCA: 72] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The purpose of this review is to critically examine phosphene induction and saccadic eye movement generation by electrical microstimulation of striate cortex (area V1) in humans and monkeys. The following issues are addressed: 1) Properties of electrical stimulation as they pertain to the activation of V1 elements; 2) the induction of phosphenes in sighted and blind human subjects elicited by electrical stimulation using various stimulation parameters and electrode types; 3) the induction of phosphenes with electrical microstimulation of V1 in monkeys; 4) the generation of saccadic eye movements with electrical microstimulation of V1 in monkeys; and 5) the tasks involved for the development of a cortical visual prosthesis for the blind. In this review it is concluded that electrical microstimulation of area V1 in trained monkeys can be used to accelerate the development of an effective prosthetic device for the blind.
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Affiliation(s)
- E J Tehovnik
- Department of Brain and Cognitive Sciences, Massachusetts, Institute of Technology, Cambridge, MA, USA.
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15
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Yoshiyama K, Uka T, Tanaka H, Fujita I. Architecture of binocular disparity processing in monkey inferior temporal cortex. Neurosci Res 2004; 48:155-67. [PMID: 14741390 DOI: 10.1016/j.neures.2003.10.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Neurons in the inferior temporal (IT) cortex respond not only to the shape, color or texture of objects, but to the horizontal positional disparity of visual features in the right and left retinal images. IT neurons with similar shape selectivity cluster in columns. In this study, we examined how IT neurons are spatially arranged in the IT according to their selectivity for binocular disparity. With a single electrode, we simultaneously recorded extracellular action potentials from a single neuron and those from background multiple neurons at the same sites or recorded multineuronal responses at successive sites along electrode penetrations, while monkeys performed a fixation task. For neurons at each recording site, effective shapes were first determined from a set of 20 shapes presented at the zero-disparity plane. The most effective shape was then presented with varying amounts of disparity. Single neuron responses and background multiunit responses recorded at the same sites showed a similar ability of disparity discrimination and tended to share the preferred disparity, suggesting that neurons with similar disparity selectivity are clustered in the IT. We estimated from sequential recordings along electrode penetrations that the size of the neuronal clusters with similar disparity selectivity was smaller than the size of clusters with similar shape selectivity.
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Affiliation(s)
- Kenji Yoshiyama
- Department of Cognitive Neuroscience, Osaka University Medical School, Yamadaoka 2-2, Suita, Osaka 565-0871, Japan
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16
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Tehovnik EJ, Slocum WM, Carvey CE. Behavioural state affects saccadic eye movements evoked by microstimulation of striate cortex. Eur J Neurosci 2003; 18:969-79. [PMID: 12925023 DOI: 10.1046/j.1460-9568.2003.02798.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
We examine how behavioural conditions affect the manner in which electrical stimulation of striate cortex (V1) influences the generation of saccadic eye movements. Monkeys were trained (i) to acquire a fixation spot and remain fixated for juice reward and (ii) to acquire a fixation spot and generate a saccade to a visual target for reward. Electrical stimulation was delivered at various times during the execution of these tasks. For stimulation trials, pulses were delivered at 200 Hz using a 100- or 200-ms train duration. Currents as high as 1500 micro A were not sufficient to evoke saccades from V1 when monkeys were actively fixating a visual target, whereas current < 100 micro A was sufficient to evoke saccades when monkeys were not actively fixating. By interleaving trials in which a visual target was presented in the receptive field of stimulated neurons with nontarget stimulation trials, saccades could be evoked from V1 during the nontarget stimulation trials with currents as low as 2 micro A. The position of the visual target on the interleaved trials affected the probability of saccade evocation on the nontarget stimulation trials. Additional factors that affected the evoked saccades were time of reward delivery, ratio of stimulation to nonstimulation trials, and whether stimulation was delivered on the interleaved trials in which a target was positioned in the receptive field of the stimulated neurons. We argue that the behavioural state of an animal acts on the nigra-collicular pathway to lower the current threshold for the elicitation of saccades from V1.
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Affiliation(s)
- Edward J Tehovnik
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, E25-634, Cambridge, MA 02139, USA.
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17
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Xu L, Tanigawa H, Fujita I. Distribution of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate-type glutamate receptor subunits (GluR2/3) along the ventral visual pathway in the monkey. J Comp Neurol 2003; 456:396-407. [PMID: 12532411 DOI: 10.1002/cne.10538] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
By using immunohistochemical methods, we examined the distribution of cells expressing subunits of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate (AMPA)-selective glutamate receptors (GluR2/3) in the cortical areas of the occipitotemporal pathway in monkeys. GluR2/3-immunoreactive (-ir) cells were primarily pyramidal cells; this category, however, also included large stellate cells in layer IVB of the striate cortex (V1) and fusiform cells in layer VI of all the areas examined. GluR2/3 immunoreactivity differed among the areas in laminar distribution and intensity. In V1, GluR2/3-ir cells were identified mainly in layers II, III, IVB, and VI. The prestriate areas V2 and V4 and the inferior temporal areas TEO and TE contained GluR2/3-ir cells in layers II, III, and VI. In the TE, GluR2/3-ir cells were also abundant in layer V. In area 36 of the perirhinal cortex, neurons in layers II, III, V, and VI were labeled in a similar manner to the TE labeling, but with greater staining intensity and numbers, especially in layer V. Thus, GluR2/3 immunoreactivity increased rostrally along the pathway. Within V1 and V2, cells strongly stained for GluR2/3 formed clusters that colocalized with cytochrome oxidase (CO)-rich regions. These distinct laminar and regional distribution patterns of GluR2/3 expression may contribute to the specific physiological properties of neurons within various visual areas and compartments.
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Affiliation(s)
- Lihua Xu
- Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, Osaka 565-0871, Japan
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18
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Tehovnik EJ, Slocum WM, Schiller PH. Differential effects of laminar stimulation of V1 cortex on target selection by macaque monkeys. Eur J Neurosci 2002; 16:751-60. [PMID: 12270051 DOI: 10.1046/j.1460-9568.2002.02123.x] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
We explored the effects of microstimulation on target selection by delivering stimulation at different depths within V1 (striate cortex) of the rhesus monkey (Macaca mulatta). Stimulation evoked saccadic eye movements that terminated in the receptive-field location of the activated neurons. The current thresholds for saccade evocation were highest (> or = 30 micro A) in the superficial layers and lowest (< or = 10 micro A) in the deep layers. To study target selection, one visual target was presented in the receptive-field location of the stimulated neurons and a second visual target was presented outside this location. Microstimulation delivered in concert with the appearance of the two targets decreased the probability that a monkey would select the target placed in the receptive-field location when the upper layers of V1 were stimulated, and it increased this probability when the lower layers were stimulated. We suggest that microstimulation of the upper layers of V1 disrupts visual signals from retina en route to higher cortical areas, whereas microstimulation of the lower layers activates V1 efferents that innervate the oculomotor system.
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Affiliation(s)
- Edward J Tehovnik
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, E25-634, Cambridge, MA 02139, USA.
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19
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Bueno-López JL, Reblet C, López-Medina A, Gómez-Urquijo SM, Grandes P, Gondra J, Hennequet L. Targets and Laminar Distribution of Projection Neurons with 'Inverted' Morphology in Rabbit Cortex. Eur J Neurosci 2002; 3:415-430. [PMID: 12106181 DOI: 10.1111/j.1460-9568.1991.tb00829.x] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This study examines the axonal projections of so-called inverted pyramids and other neurons with their major dendritic shaft oriented in the direction of the white matter ('inverted cells') in the adult rabbit cortex. Single injections of horseradish peroxidase wheat germ agglutinin were made into cortical or subcortical sites. The resulting retrograde labelling in the cortex was analysed and the distribution across areas and layers of inverted cells contributing to each of these projections was estimated. In addition, the radial distribution of inverted cells was independently determined from rapid Golgi-impregnated and Nissl-stained material. All three procedures revealed that inverted cells lay overwhelmingly in infragranular layers, but congregated at the border between layers 5 and 6. Inverted cells, identified by retrograde labelling, seldom furnished non-telencephalic centres; in contrast, these cells constituted a major source for the projections to the ipsi- or the contralateral cortex, the claustrum or the nucleus caudatus. In general, each set of inverted cells (when defined by its specific destination as a group) was located below the typically oriented cells whose axons were aimed at the same target. Thus, the inverted cells of the rabbit cortex are characterized not only by their unique morphology and their corticocortical, corticoclaustral and corticostriatal projections, but also by their distinctive radial locations. These findings suggest that inverted cells, even though possibly composed of different cell types, are a specific class of projection neurons.
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Affiliation(s)
- José L. Bueno-López
- Section of Anatomy, Department of Neurosciences, Faculty of Medicine and Dentistry, University of the Basque Country, E-48940 Lejona, Biscay, Spain
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20
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Zhang K, Sejnowski TJ. A universal scaling law between gray matter and white matter of cerebral cortex. Proc Natl Acad Sci U S A 2000; 97:5621-6. [PMID: 10792049 PMCID: PMC25878 DOI: 10.1073/pnas.090504197] [Citation(s) in RCA: 468] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/1999] [Indexed: 11/18/2022] Open
Abstract
Neocortex, a new and rapidly evolving brain structure in mammals, has a similar layered architecture in species over a wide range of brain sizes. Larger brains require longer fibers to communicate between distant cortical areas; the volume of the white matter that contains long axons increases disproportionally faster than the volume of the gray matter that contains cell bodies, dendrites, and axons for local information processing, according to a power law. The theoretical analysis presented here shows how this remarkable anatomical regularity might arise naturally as a consequence of the local uniformity of the cortex and the requirement for compact arrangement of long axonal fibers. The predicted power law with an exponent of 4/3 minus a small correction for the thickness of the cortex accurately accounts for empirical data spanning several orders of magnitude in brain sizes for various mammalian species, including human and nonhuman primates.
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Affiliation(s)
- K Zhang
- Howard Hughes Medical Institute, Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, California 92037, USA
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21
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Weller RE, White DM, Walton MM. Intrinsic connections in the caudal subdivision of the dorsolateral visual area (DLC) in squirrel monkeys. J Comp Neurol 2000. [DOI: 10.1002/(sici)1096-9861(20000424)420:1<52::aid-cne4>3.0.co;2-o] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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22
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Gur M, Beylin A, Snodderly DM. Physiological properties of macaque V1 neurons are correlated with extracellular spike amplitude, duration, and polarity. J Neurophysiol 1999; 82:1451-64. [PMID: 10482761 DOI: 10.1152/jn.1999.82.3.1451] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
In the lateral geniculate nucleus (LGN) the large neurons of the magnocellular layers are functionally distinct and anatomically segregated from the small neurons of the parvocellular layers. This segregation of large and small cells is not maintained in the primary visual cortex (V1); instead a heterogeneous mixture of cells occurs, particularly in the output layers. Nevertheless, our results indicate that for the middle and upper layers of V1, cell size remains a predictor of physiological properties. We recorded extracellularly from neurons in V1 of alert monkeys and analyzed the amplitude, duration, and polarity of the action potentials of 199 cells. Of 156 cells that could be assigned to specific cortical layers, 137 (88%) were localized to the middle and upper cortical layers, layer 4 and above. We summarize evidence that the large-amplitude spikes are discharged by large cells, whereas small-amplitude spikes are the action potentials of smaller cells. Large spikes were predominantly negative and of longer duration, whereas small spikes were predominantly positive and briefer. The putative large cells had lower ongoing activity, smaller receptive field activating regions and higher selectivity for stimulus geometry and stimulus motion than the small cells. The contrasting properties of the large and the small cells were illustrated dramatically in simultaneous recordings made from adjacent cells. Our results imply that there may be an anatomic pairing or clustering of small and large cells that could be integral to the functional organization of the cortex. We suggest that the small and the large cells of area V1 have different roles, such that the small cells may shape the properties of the large output cells. If some of the small cells are also output cells, then cell size should be a predictor of the type of information being sent to other brain regions. Because of their high activity and relative ease of stimulation, the small cells also may contribute disproportionately to in vivo images based on metabolic responses such as changes in blood flow.
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Affiliation(s)
- M Gur
- Department of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, 32000, Israel
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23
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Shao Z, Burkhalter A. Role of GABAB receptor-mediated inhibition in reciprocal interareal pathways of rat visual cortex. J Neurophysiol 1999; 81:1014-24. [PMID: 10085329 DOI: 10.1152/jn.1999.81.3.1014] [Citation(s) in RCA: 41] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
In neocortex, synaptic inhibition is mediated by gamma-aminobutyric acid-A (GABAA) and GABAB receptors. By using intracellular and patch-clamp recordings in slices of rat visual cortex we studied the balance of excitation and inhibition in different intracortical pathways. The study was focused on the strength of fast GABAA- and slow GABAB-mediated inhibition in interareal forward and feedback connections between area 17 and the secondary, latero-medial visual area (LM). Our results demonstrate that in most layer 2/3 neurons forward inputs elicited excitatory postsynaptic potentials (EPSPs) that were followed by fast GABAA- and slow GABAB-mediated hyperpolarizing inhibitory postsynaptic potentials (IPSPs). These responses resembled those elicited by horizontal connections within area 17 and those evoked by stimulation of the layer 6/white matter border. In contrast, in the feedback pathway hyperpolarizing fast and slow IPSPs were rare. However weak fast and slow IPSPs were unmasked by bath application of GABAB receptor antagonists. Because in the feedback pathway disynaptic fast and slow IPSPs were rare, polysynaptic EPSPs were more frequent than in forward, horizontal, and interlaminar circuits and were activated over a broader stimulus range. In addition, in the feedback pathway large-amplitude polysynaptic EPSPs were longer lasting and showed a late component whose onset coincided with that of slow IPSPs. In the forward pathway these late EPSPs were only seen with stimulus intensities that were below the activation threshold of slow IPSPs. Unlike strong forward inputs, feedback stimuli of a wide range of intensities increased the rate of ongoing neuronal firing. Thus, when forward and feedback inputs are simultaneously active, feedback inputs may provide late polysynaptic excitation that can offset slow IPSPs evoked by forward inputs and in turn may promote recurrent excitation through local intracolumnar circuits. This may provide a mechanism by which feedback inputs from higher cortical areas can amplify afferent signals in lower areas.
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Affiliation(s)
- Z Shao
- Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
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24
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Zhou FM, Hablitz JJ. Dopamine modulation of membrane and synaptic properties of interneurons in rat cerebral cortex. J Neurophysiol 1999; 81:967-76. [PMID: 10085325 DOI: 10.1152/jn.1999.81.3.967] [Citation(s) in RCA: 110] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Dopamine (DA) is an endogenous neuromodulator in the mammalian brain. However, it is still controversial how DA modulates excitability and input-output relations in cortical neurons. It was suggested that DA innervation of dendritic spines regulates glutamatergic inputs to pyramidal neurons, but no experiments were done to test this idea. By recording individual neurons under direct visualization we found that DA enhances inhibitory neuron excitability but decreases pyramidal cell excitability, through depolarization and hyperpolarization, respectively. Accordingly, DA also increased the frequency and amplitude of spontaneous inhibitory postsynaptic currents (sIPSCs). In the presence of TTX, DA did not affect the frequency, amplitude, or kinetics of miniature IPSCs and excitatory postsynaptic currents in inhibitory interneurons or pyramidal cells. Our results suggest that DA can directly excite cortical interneurons, but there is no detectable DA gate to regulate spontaneous GABA and glutamate release or the properties of postsynaptic GABA and glutamate receptors in neocortical neurons.
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Affiliation(s)
- F M Zhou
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
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25
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Yoshimura Y, Kimura F, Tsumoto T. Estimation of single channel conductance underlying synaptic transmission between pyramidal cells in the visual cortex. Neuroscience 1999; 88:347-52. [PMID: 10197757 DOI: 10.1016/s0306-4522(98)00382-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Axon collaterals originating from pyramidal cells are one of the most abundant presynaptic elements in the neocortical circuits. To understand a quantitative aspect of synaptic transmission between pyramidal cells, we attempted to estimate single channel conductance by applying non-stationary noise analysis to unitary excitatory postsynaptic currents. Simultaneous recordings were carried out in two pyramidal cells of superficial layers in visual cortical slices. Unitary postsynaptic currents, which were evoked by action potentials of presynaptic cells impaled with conventional sharp electrodes, were recorded from postsynaptic cells with whole-cell patch clamp techniques. Estimated single channel conductance was 12.8 3.8(S.D.) pS for kittens and 10.4 +/- 1.5 pS for rats. Dividing these values by the conductance for unitary postsynaptic currents, we calculated the number of non-N-methyl-D-aspartate receptor channels activated during the postsynaptic currents. The obtained estimates were 52 (kittens) and 41 (rats). To further estimate the number of channels involved in each quantal event, we analysed amplitude histograms of miniature and spike-evoked excitatory postsynaptic currents. The derived number of estimates from these two kinds of histograms agreed quite well; about 20 channels were required for individual quantal events. Assuming open probability of non-N-methyl-D-aspartate receptor channels to be 0.7, our results suggest that the number of channels available for synaptic transmission between individual pyramidal cells would be 74 (kittens) and 59 (rats). We propose that at pyramidal-pyramidal synapses, the number of open channels is several times smaller than that previously reported for the synapses between geniculo-cortical afferent and layer IV spiny stellate cells.
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Affiliation(s)
- Y Yoshimura
- Department of Neurophysiology, Biomedical Research Center, Osaka University Medical School, Suita, Japan
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26
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Kornack DR, Rakic P. Changes in cell-cycle kinetics during the development and evolution of primate neocortex. Proc Natl Acad Sci U S A 1998; 95:1242-6. [PMID: 9448316 PMCID: PMC18732 DOI: 10.1073/pnas.95.3.1242] [Citation(s) in RCA: 217] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
The evolutionary expansion of neocortical size in mammals is particularly prominent in anthropoid primates (i.e., monkeys, apes, and humans) and reflects an increased number of cortical cells, yet the developmental basis for this increase remains undefined. Cortical cell production depends on the length of the cell-division cycle of progenitor cells during neurogenesis, which previously has been measured only in smaller-brained rodents. To investigate whether cortical expansion in primates reflects modification of cell-cycle kinetics, we determined cell-cycle length during neurogenesis in the proliferative cerebral ventricular zone of fetal rhesus monkeys, by using cumulative S-phase labeling with bromodeoxyuridine. Cell-cycle durations in monkeys were as much as 5 times longer than those reported in rodents. Nonetheless, substantially more total rounds of cell division elapsed during the prolonged neurogenetic period of the monkey cortex, providing a basis for increased cell production. Moreover, unlike the progressive slowing that occurs during cortical development in rodents, cell division accelerated during neurogenesis of the enlarged cortical layers in monkeys. These findings suggest that evolutionary modification of the duration and number of progenitor cell divisions contributed to both the expansion and laminar elaboration of the primate neocortex.
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Affiliation(s)
- D R Kornack
- Section of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA.
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Catania KC, Kaas JH. Somatosensory fovea in the star-nosed mole: Behavioral use of the star in relation to innervation patterns and cortical representation. J Comp Neurol 1997. [DOI: 10.1002/(sici)1096-9861(19971020)387:2<215::aid-cne4>3.0.co;2-3] [Citation(s) in RCA: 98] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Bourgeois JP. Synaptogenesis, heterochrony and epigenesis in the mammalian neocortex. ACTA PAEDIATRICA (OSLO, NORWAY : 1992). SUPPLEMENT 1997; 422:27-33. [PMID: 9298788 DOI: 10.1111/j.1651-2227.1997.tb18340.x] [Citation(s) in RCA: 111] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
In the neocortex of the macaque monkey we have identified and described quantitatively five different phases of synaptogenesis and related them to its functional maturation. In all the cortical areas observed so far, the most rapid phase of synaptogenesis occurs within a time-window of only 40 days, centred on birth. The modifiability of phase 3 has been tested by bilaterally equilibrated stimulation or deprivation, using experimentally obtained preterm or blind monkeys. Our developmental and experimental observations, as well as phylogenetic comparisons, strongly suggest that the timing and rate of production of synapses during phase 3 are determined by mechanisms that are both intrinsic and common to the whole cortical mantle but can be modified epigenetically later on.
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Affiliation(s)
- J P Bourgeois
- Département des Biotechnologies, Institut Pasteur, Paris, France
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Abstract
In addition to the horizontal bands of myelinated axons that produce the line of Gennari and the inner band of Baillarger, the macaque primary visual cortex contains prominent vertical bundles of myelinated axons. In tangential sections through layer IVC, these axon bundles are regularly arranged. They have a mean center-to-center spacing of about 23 microns, and each one contains an average of 34 (S.D. +/- 13) myelinated axons. These bundles seem to be largely composed of efferent fibers, because in material in which pyramidal cells have been labelled in layer II/III and in layers IVA and IVB the axons of these neurons descend towards the white matter in bundles. However, it is doubtful whether all of the descending myelinated axons from the superficial layers emerge from the cortex, since counts show that the bundles contain maximum numbers of myelinated axons at the level of layer IVC, and that in layers V and VI their number is reduced by about 30%. Perhaps some of the axons enter the line of Baillarger, in layer V. When the bundles of myelinated axons and the clusters of apical dendrites of the layer V pyramidal cells are visualized simultaneously within layer IVC in electron microscopic preparations, it is apparent that their center-to-center spacing is similar, namely, about 23 microns and that a bundle of axons has a cluster of apical dendrites lying adjacent to it. Because of this association, and because axons from layer III pyramidal cells have been shown to enter the bundles, it is suggested that the myelinated axon bundles contain the efferent axons from the projection neurons in the individual pyramidal cell modules. However, in addition to the myelinated axons, the bundles contain unmyelinated axons, so that they also probably serve as the conduits for axons forming connections between layers. It is proposed that the pyramidal cell modules are the basic, functional neuronal units of the visual cortex, and since the neurons within a particular module can be expected to have slightly different inputs and response properties from those in neighboring modules, the individual axon bundles that emerge from each module would be expected to carry a unique set of efferent information.
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Affiliation(s)
- A Peters
- Department and Anatomy and Neurobiology, Boston University School of Medicine, Massachusetts 02118, USA
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Gabbott PL, Bacon SJ. Local circuit neurons in the medial prefrontal cortex (areas 24a,b,c, 25 and 32) in the monkey: II. Quantitative areal and laminar distributions. J Comp Neurol 1996; 364:609-36. [PMID: 8821450 DOI: 10.1002/(sici)1096-9861(19960122)364:4<609::aid-cne2>3.0.co;2-7] [Citation(s) in RCA: 155] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
The companion paper (Gabbott and Bacon [1996] J. Comp. Neurol.) describes the morphology of calretinin (CR)-, parvalbumin (PV)-, calbindin (CB)-, and GABA-immunoreactive neurons, and NADPH diaphorase-reactive cells, in the medial prefrontal cortex (mPFC; areas 24a, 24b, 24c, 25 and 32) of the adult monkey. Since these local circuit neurons play crucial functional roles, the aim of this study was to provide supportive quantitative data defining their areal and laminar distribution in mPFC. The numerical densities of neurons (Nv, number of cells per mm3) in each area and layer were calculated stereologically. The mean total neuronal NV estimates across mPFC was 55,727 +/- 3,319 per mm3 (mean +/- S.D.; n = 3); values ranged from 50,489 +/- 8,374 per mm3 (area 24a) to 59,938 +/- 7,214 per mm3 (area 24c). Interareal differences were not significant. Cortical depth measurements and neuronal NV estimates for each area allowed the absolute number of neurons in a column of cortex under 1 mm2 of surface to be calculated; values varied between 86,457 +/- 15,063 (area 24a) and 128,464 +/- 24,050 (area 24c). Using immunolabelled Nissl-stained sections of mPFC, CR+ neurons constituted 11.2%, PV+ neurons 5.9%, and CB+ neurons 5.0% of the total neuron population. GABA+ neurons represented an overall 24.9% (23.5-27.3%) of neurons in the mPFC. Differences between areas were not significant. The cortical depth distribution histograms of CR+, PV+, CB+, and GABA+ cell populations in each area were derived and the percentage of a given cell population in each layer subsequently calculated. Peaks in the cortical depth distributions of CR+ and CB+ neurons occurred in layer 2 and upper layer 3, respectively; the peak distribution of PV+ neurons occurred between lower layer 3 and upper layer 5. The depth distribution of GABA+ cells reflected the combined distributions of CR+, PV+ and CR+ neurons. In all areas, the majority (74.4-84.0%) of the GABA cell population was located in layers 2/3. The depth distributions for each cell type were similar between areas. Diaphorase-reactive neurons accounted for 0.25% (0.2-0.32%) of all cortical neurons in mPFC and were distributed in two horizontal strata, in midlayer 3 and in mid/upper layer 6. A large population of diaphorase-reactive cells was present in the white matter. The absolute numbers of CR+, PV+, CB+ and GABA+ neurons within individual layers in a column of cortex under 1 mm2 and 50 x 50 microns of cortical surface have been derived. The data presented provide the basis for a quantitative definition of cortical circuits in monkey mPFC.
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Affiliation(s)
- P L Gabbott
- University Department of Pharmacology, Oxford, England
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Costa E, Thompson DM, Auta J, Guidotti A. Imidazenil: A Potent Benzodiazepine Partial Positive Modulator of GABAergic Transmission Virtually Devoid of Tolerance Liability. CNS DRUG REVIEWS 1995. [DOI: 10.1111/j.1527-3458.1995.tb00282.x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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McMullen NT, Smelser CB, de Venecia RK. A quantitative analysis of parvalbumin neurons in rabbit auditory neocortex. J Comp Neurol 1994; 349:493-511. [PMID: 7860786 DOI: 10.1002/cne.903490402] [Citation(s) in RCA: 33] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Parvalbumin (PV) is a calcium-binding protein present in GABAergic cells in the cerebral cortex and in thalamic relay neurons. In the present study, parvalbumin immunocytochemistry (PVi) and stereological methods were used to obtain estimates of cortical volume, total neuron number, laminar density, and the percentage of PV-immunoreactive neurons in auditory neocortex. PVi clearly delineated the primary auditory cortex (AI), which was characterized by two PV+ bands: dense terminal-like labeling within lamina III/IV and PV+ somata in lamina VIa. Stereological analysis of Nissl-stained sections revealed that the total number of neurons in rabbit AI was 1.48 x 10(6) with a mean neuronal density of 55 x 10(3)/mm3. Based on a mean cortical thickness of 1.92 mm, there are approximately 106,000 neurons in a 1 mm2 column of auditory cortex. PVi yields an extraordinary Golgi-like staining of nonpyramidal cells in all cortical layers. PV+ nonpyramidal cells constitute approximately 7.0% of the neurons in AI. There were significant differences in the morphology and density of PV+ neurons across layers. Although only 5% of cells in lamina I were PV+, three nonpyramidal cell types were present. Lamina II had the highest numerical density within AI but the lowest percentage of PV+ neurons (3.3%). Lamina II, however, contained the greatest diversity of PV+ nonpyramidal cell types, which included small multipolar cells, bipolar cells, and, less frequently, large cells of the bitufted, bipolar, and stellate varieties. Lamina IV had one of the highest numerical densities (67.6 x 10(3) neurons/mm3) and contributed nearly 27% of the total neuron number in AI. The numerical density of PV+ nonpyramidal cells was also greatest within lamina IV (7.1 x 10(3)/mm3) where they formed 10.4% of the neuronal population. PV+ nonpyramidal cells in lamina IV and lamina III were predominantly large basket-type cells with bitufted dendritic domains and tangentially oriented local axonal plexuses. The terminal-like label within lamina III/IV derived in part from the basket-cell axons, which formed pericellular arrays around unstained somata. Cell-sparse lamina V contained the largest PV+ nonpyramidal cells in AI. These cells, which formed 11% of the neuron population in lamina V, were notable for their tangentially oriented dendritic fields and local axonal arbors. PVi partitioned lamina VI into VIa and VIb. Large multipolar nonpyramidal cells were distributed throughout lamina VI and made up approximately 6% of the total population. Lamina VIa contained a band of lightly labeled PV+ pyramidal neurons that formed 15% of the neuronal population.(ABSTRACT TRUNCATED AT 400 WORDS)
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Affiliation(s)
- N T McMullen
- Department of Anatomy, University of Arizona College of Medicine, Tucson 85724
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Beaulieu C, Campistron G, Crevier C. Quantitative aspects of the GABA circuitry in the primary visual cortex of the adult rat. J Comp Neurol 1994; 339:559-72. [PMID: 8144746 DOI: 10.1002/cne.903390407] [Citation(s) in RCA: 59] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The number and size of synaptic contacts made by GABA-immunoreactive axonal boutons were estimated in each layer of the primary visual cortex (area Oc1M) of adult rats by using the dissector method. Immunoreactivity for GABA was detected with the postembedding immunogold technique on ultrathin sections. Targets of GABA synaptic contacts were also identified to predict the sites of GABA influence in the rat visual cortex. For the total cortical depth, 82 million out of an overall population of 666 million synaptic contacts per mm3 of tissue (or 1 in 8 contacts, 12%) were GABA. Layer IV averaged 62% more GABA contacts per unit volume than did any other cortical layer. Consequently, these represented a larger proportion (1 in 6, 17%) of the overall population of layer IV synaptic contacts. This higher number of GABA contacts was not due to a greater density of GABA boutons, but to an increased number of contacts made by each layer IV GABA bouton (mean of 1.4 contacts per bouton compared to 1.1 in other cortical layers). The total area occupied by the contacts on an average GABA bouton was similar in all layers; the higher number of contacts per GABA bouton in layer IV being compensated for by their smaller size. This observed constancy in the area of synaptic contacts suggests the presence of one or more regulatory mechanisms maintaining optimal numbers of the different macromolecules forming the synaptic contacts. The increased density of GABA contacts in layer IV compared to other cortical layers was due to their greater number targeting distal regions of the dendritic tree. Since layer IV receives the vast majority of thalamocortical terminals and since these axons preferentially target dendritic spines, the specific arrangement of GABA synaptic contacts in this layer could be designed to exert a precise inhibition near the site of the thalamic input and thus serve as the structural basis for the strong GABA-related hyperpolarization that followed the excitatory response after physiological stimulations of the thalamocortical pathway.
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Affiliation(s)
- C Beaulieu
- Département de Pathologie, Université de Montréal, Canada
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DeFelipe J, Fariñas I. The pyramidal neuron of the cerebral cortex: morphological and chemical characteristics of the synaptic inputs. Prog Neurobiol 1992; 39:563-607. [PMID: 1410442 DOI: 10.1016/0301-0082(92)90015-7] [Citation(s) in RCA: 579] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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Larkman AU. Dendritic morphology of pyramidal neurones of the visual cortex of the rat: III. Spine distributions. J Comp Neurol 1991; 306:332-43. [PMID: 1711059 DOI: 10.1002/cne.903060209] [Citation(s) in RCA: 190] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The vast majority of excitatory synaptic inputs to neocortical pyramidal cells terminate on dendritic spines, which can thus serve as markers, visible by light microscopy, for the locations of these synapses. The aim of this study was to provide estimates of the total numbers and distributions of spines on the dendrites of individual pyramidal neurones from layers 2/3 and 5 of the visual cortex of the rat. High magnification camera lucida drawings were made of dendritic segments lying close to the plane of section and the number of spines per unit length of dendrite calculated for each. These spine densities were used to estimate the numbers of spines on the other dendritic segments and the results were entered to a computer program that calculated various statistics. Mean total numbers of spines per cell were 7,965 +/- 2,723 (S.D.) for layer 2/3 cells, 8,647 +/- 3,097 for slender layer 5 cells, and 14,932 +/- 3,371 for thick layer 5 cells; these figures are in good agreement with previous stereological estimates. For all cell classes, 70% or more of spines were located on the basal and apical oblique dendrites. The distribution of spines with respect to cortical layers was also explored. Most cells had most of their spines in the layer containing the soma, but there were differences within and between cell classes. Layer 2/3 cells showed a progressive reduction in the proportion of their spines in layers 1 and 2 with increasing depth of their soma in the cortex. Thick layer 5 cells had substantial contributions from layers 4, 3, 2, and especially layer 1. Slender layer 5 cells had small contributions from layers 6 and 4, but relatively few spines in layers 3 and 2. The distribution of spines with path distance from the soma was explored by estimating the numbers of spines contained within a series of concentric shells centred on the soma. All cells showed a rapid increase in the number of spines per shell for the proximal 100 micrograms or so, followed by a sharp decline to approximately 250 micrograms, beyond which the number remained relatively constant until the end of the terminal arbor. In each case, the majority of spines were located within a path length of 150 micrograms from the soma.
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Affiliation(s)
- A U Larkman
- University Laboratory of Physiology, Oxford University, United Kingdom
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Abstract
In sections of area 17 of monkey visual cortex treated with an antibody to MAP2 the disposition of the cell bodies and dendrites of the neurons is readily visible. In such preparations it is evident that the apical dendrites of the pyramidal cells of layer VI form fascicles that pass into layer IV, where most of them gradually taper and form their terminal tufts. In contrast, the apical dendrites of the smaller layer V pyramidal cells come together in a more regular fashion. They form clusters that pass through layer IV and into layer II/III where the apical dendrites of many of the pyramidal cells in that layer add to the clusters. In horizontal sections taken through the middle of layer IV, these clusters of apical dendrites are found to have an average center-to-center spacing of about 30 microns, and it is proposed that each cluster of apical dendrites represents the axis of a module of pyramidal cells that has a diameter of about 30 microns and contains about 142 neurons. The MAP2 antibody reaction also reveals that some pyramidal cells in layers IVA and IVB have their cell bodies arranged into cones. There are about 118 such cones beneath 1 mm2 of cortical surface and the apical dendrites of the pyramidal cells within them bundle together at the apex of each cone to pass into layer III. Surrounding the cones of neurons there are horizontally aligned, thin dendrites. The location of these dendrites coincides with the dark walls of the honeycomb pattern seen in layer IVA after cytochrome oxidase reactions, or after the parvocellular input from the lateral geniculate nucleus has been labeled. Thus the cones of pyramidal cells within upper layer IV fit into the pockets of the honeycomb pattern. Below the cones of pyramidal cells are the outer Meynert cells within layer IVB, and the cell bodies of these large neurons are disposed so that they preferentially lie beneath the neuropil between the cones of pyramids. It is suggested that pyramidal cell modules are a basic feature of the cerebral cortex, and that these are combined together by afferent inputs to the cortex to generate the systems of functional columns.
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Affiliation(s)
- A Peters
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Massachusetts 02118
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Abstract
Quantitative anatomical investigations provide the basis for functional models. In this study the density of neurons and synapses was measured in three different areas (8, 6, and 17) of the neocortex of the mouse. Both kinds of measurements were made on the same material, embedded in Epon/Araldit. In order to determine the synaptic density per mm3, the proportion of synaptic neuropil was also measured; it was found to be 84%. The cortical volume occupied by cell bodies of neurons and glia cells amounted to 12%, that by blood vessels to 4%. The total average was 9.2 x 10(4) neurons/mm3 and 7.2 x 10(8) synapses/mm3. About 11% of the synapses were of type II. The density of neurons increased with decreasing cortical thickness; thus the number of neurons under a given surface area was about constant. The synaptic density, on the other hand, was almost constant in the three areas, the number of synapses under a given cortical surface area tended, therefore, to increase with cortical thickness. The average number of synapses per neuron was 8,200, with a tendency to increase with increasing cortical thickness. Shrinkage of the tissue was also measured for various staining techniques. No shrinkage occurred during perfusion with 3.7% formaldehyde or with a solution of buffered paraformaldehyde and glutaraldehyde and during fixation in situ. Electron microscopical material showed almost no shrinkage, whereas Nissl-preparations on paraffin-embedded material had only 43% of their original volume. After Nissl stain on frozen sections the volume had shrunken to 68% and after Golgi impregnation and embedding in celloidin to 70%. The total volume of the neocortex was 112 mm3 (both hemispheres together). The total number of neurons was thus 1.0 x 10(7) and the total number of synapses 8.1 x 10(10).
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Affiliation(s)
- A Schüz
- Max-Planck-Institut für biologische Kybernetik, Tübingen, Federal Republic of Germany
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Williams RW, Rakic P. Three-dimensional counting: an accurate and direct method to estimate numbers of cells in sectioned material. J Comp Neurol 1988; 278:344-52. [PMID: 3216047 DOI: 10.1002/cne.902780305] [Citation(s) in RCA: 344] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
We introduce a way to count and measure cells in an optically defined volume of tissue called a counting box. This method--direct three-dimensional counting (3DC)--eliminates the need for correction factors, such as that introduced by Abercrombie (Anat. Rec. 94:239-247,'46), to determine the number of cells per unit volume (NV). Problems caused by irregular cell shape and cell size, nonrandom orientation, and splitting of cells by the knife during sectioning are overcome. Furthermore, 3DC is insensitive to large variations in section thickness. The innovative feature of 3DC is the definition of a counting box with top and bottom sides located inside the section a precise distance away from the cut surfaces of the tissue. The positions of the top and bottom sides of the counting box are delimited by using a digital length gauge and a Z-axis control unit. Sections of tissue between 8 and 100 micron thick are examined with a high numerical aperture objective in combination with video-enhanced differential interference contrast optics (DIC). Cells are marked on a television screen while the microscopist scans systematically from the top to the bottom of the counting box. Cells that are located completely inside the box and cells that only cross through its top, right, or back sides are counted. All cells that cross the planes that define the bottom, left, and front sides of the counting box are not counted. Direct 3DC provides an accurate, simple, and reliable way to count cells, nuclei, nucleoli, or other objects in sectioned material.(ABSTRACT TRUNCATED AT 250 WORDS)
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Affiliation(s)
- R W Williams
- Section of Neuroanatomy, Yale University School of Medicine, New Haven, Connecticut 06511
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