Principles of Dendritic Integration
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Dendritic Spikes and Their Influence on Extracellular Calcium Signaling
Dendritic Spikes and Their Influence on Extracellular Calcium Signaling MICHAEL C. WIEST,1 DAVID M. EAGLEMAN,2 RICHARD D. KING,1 AND P. READ MONTAGUE1 1Division of Neuroscience, Center for Theoretical Neuroscience, Baylor College of Medicine, Houston, Texas 77030; and 2Sloan Center for Theoretical Neurobiology, The Salk Institute, La Jolla, California 92037 Wiest, Michael C., David M. Eagleman, Richard D. King, and P. trical or neurotransmitter stimulation (Benninger et al. 1980; Read Montague. Dendritic spikes and their influence on extracellular Heinemann et al. 1990; Lucke et al. 1995; Nicholson et al. calcium signaling. J. Neurophysiol. 83: 1329–1337, 2000. Extracel- 1978; Pumain and Heinemann 1985; Stanton and Heine- lular calcium is critical for many neural functions, including neuro- mann 1986) (see Fig. 1). Given that many important com- transmission, cell adhesion, and neural plasticity. Experiments have putational processes function on millisecond time scales and shown that normal neural activity is associated with changes in extracellular calcium, which has motivated recent computational work submicron spatial scales, we were led to ask how electrical that employs such fluctuations in an information-bearing role. This events at these smaller scales affect the external calcium possibility suggests that a new style of computing is taking place in level. the mammalian brain in addition to current ‘circuit’ models that use In the mammalian brain, action potentials can propagate into only neurons and connections. Previous computational models of the dendrites of cortical and hippocampal neurons (Stuart and rapid external calcium changes used only rough approximations of Sakmann 1994). These spikes cause large influxes of calcium calcium channel dynamics to compute the expected calcium decre- from the extracellular space (Helmchen et al. -
Crayfish Escape Behavior and Central Synapses
Crayfish Escape Behavior and Central Synapses. III. Electrical Junctions and Dendrite Spikes in Fast Flexor Motoneurons ROBERT S. ZUCKER Department of Biological Sciences and Program in the Neurological Sciences, Stanford University, Stanford, California 94305 THE LATERAL giant fiber is the decision fiber and fast flexor motoneurons are located in for a behavioral response in crayfish in- the dorsal neuropil of each abdominal gan- volving rapid tail flexion in response to glion. Dye injections and anatomical recon- abdominal tactile stimulation (27). Each structions of ‘identified motoneurons reveal lateral giant impulse is followed by a rapid that only those motoneurons which have tail flexion or tail flip, and when the giant dentritic branches in contact with a giant fiber does not fire in response to such stim- fiber are activated by that giant fiber (12, uli, the movement does not occur. 21). All of tl ie fast flexor motoneurons are The afferent limb of the reflex exciting excited by the ipsilateral giant; all but F4, the lateral giant has been described (28), F5 and F7 are also excited by the contra- and the habituation of the behavior has latkral giant (21 a). been explained in terms of the properties The excitation of these motoneurons, of this part of the neural circuit (29). seen as depolarizing potentials in their The properties of the neuromuscular somata, does not always reach threshold for junctions between the fast flexor motoneu- generating a spike which propagates out the rons and the phasic flexor muscles have also axon to the periphery (14). Indeed, only t,he been described (13). -
Long-Term Adult Human Brain Slice Cultures As a Model System to Study
TOOLS AND RESOURCES Long-term adult human brain slice cultures as a model system to study human CNS circuitry and disease Niklas Schwarz1, Betu¨ l Uysal1, Marc Welzer2,3, Jacqueline C Bahr1, Nikolas Layer1, Heidi Lo¨ ffler1, Kornelijus Stanaitis1, Harshad PA1, Yvonne G Weber1,4, Ulrike BS Hedrich1, Ju¨ rgen B Honegger4, Angelos Skodras2,3, Albert J Becker5, Thomas V Wuttke1,4†*, Henner Koch1†* 1Department of Neurology and Epileptology, Hertie-Institute for Clinical Brain Research, University of Tu¨ bingen, Tu¨ bingen, Germany; 2Department of Cellular Neurology, Hertie-Institute for Clinical Brain Research, University of Tu¨ bingen, Tu¨ bingen, Germany; 3German Center for Neurodegenerative Diseases (DZNE), Tu¨ bingen, Germany; 4Department of Neurosurgery, University of Tu¨ bingen, Tu¨ bingen, Germany; 5Department of Neuropathology, Section for Translational Epilepsy Research, University Bonn Medical Center, Bonn, Germany Abstract Most of our knowledge on human CNS circuitry and related disorders originates from model organisms. How well such data translate to the human CNS remains largely to be determined. Human brain slice cultures derived from neurosurgical resections may offer novel avenues to approach this translational gap. We now demonstrate robust preservation of the complex neuronal cytoarchitecture and electrophysiological properties of human pyramidal neurons *For correspondence: in long-term brain slice cultures. Further experiments delineate the optimal conditions for efficient [email protected] viral transduction of cultures, enabling ‘high throughput’ fluorescence-mediated 3D reconstruction tuebingen.de (TVW); of genetically targeted neurons at comparable quality to state-of-the-art biocytin fillings, and [email protected] demonstrate feasibility of long term live cell imaging of human cells in vitro. -
Biophysically Realistic Neuron Models for Simulation of Cortical Stimulation
bioRxiv preprint doi: https://doi.org/10.1101/328534; this version posted August 20, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Biophysically Realistic Neuron Models for Simulation of Cortical Stimulation Authors: Aman S. Aberra1, Angel V. Peterchev1,2,3,4, Warren M. Grill1,3,4,5,* 1 Dept. of Biomedical Engineering, School of Engineering, Duke University, NC 2 Dept. of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, NC 3 Dept. of Electrical and Computer Engineering, School of Engineering, Duke University, NC 4 Dept. of Neurosurgery, School of Medicine, Duke University, NC 5 Dept. of Neurobiology, School of Medicine, Duke University, NC * Corresponding Author: Warren M. Grill Keywords: neuron model, cortex, myelination, simulation, electric field, stimulation, axon bioRxiv preprint doi: https://doi.org/10.1101/328534; this version posted August 20, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 2 1. Abstract Objective. We implemented computational models of human and rat cortical neurons for simulating the neural response to cortical stimulation with electromagnetic fields. Approach. We adapted model neurons from the library of Blue Brain models to reflect biophysical and geometric properties of both adult rat and human cortical neurons and coupled the model neurons to exogenous electric fields (E-fields). The models included 3D reconstructed axonal and dendritic arbors, experimentally-validated electrophysiological behaviors, and multiple, morphological variants within cell types. -
Contribution of Apical and Basal Dendrites of L2/3 Pyramidal Neurons to Orientation Encoding in Mouse V1 Jiyoung Park1,4*†, Athanasia Papoutsi3†, Ryan T
bioRxiv preprint doi: https://doi.org/10.1101/566588; this version posted March 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Contribution of Apical and Basal Dendrites of L2/3 Pyramidal Neurons to Orientation Encoding in Mouse V1 Jiyoung Park1,4*†, Athanasia Papoutsi3†, Ryan T. Ash2,4, Miguel A. Marin2, Panayiota Poirazi3* & Stelios M. Smirnakis4* 1Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas 2Department of Neuroscience, Baylor College of Medicine, Houston, Texas 3Institute of Molecular Biology and Biotechnology (IMBB), Foundation of Research and Technology Hellas (FORTH), Vassilika Vouton, Heraklion, Crete, Greece 4Brigham and Women’s Hospital and Jamaica Plain VA Hospital, Harvard Medical School, Boston, MA †Equal contribution. * Correspondence: [email protected], [email protected], [email protected] Abstract: Pyramidal neurons integrate synaptic inputs from basal and apical dendrites to generate stimulus-specific responses. It has been proposed that feed-forward inputs to basal dendrites drive a neuron’s stimulus preference, while feedback inputs to apical dendrites sharpen selectivity. However, how a neuron’s dendritic domains relate to its functional selectivity has not been demonstrated experimentally. We performed 2-photon dendritic micro-dissection on layer- 2/3 pyramidal neurons in mouse primary visual cortex. We found that removing the apical dendritic tuft did not alter orientation-tuning. Furthermore, orientation-tuning curves were remarkably robust to the removal of basal dendrites: ablation of 2-3 basal dendrites was needed to cause a small shift in orientation preference, without significantly altering tuning width. -
Neuronal Organization of Olfactory Bulb Circuits
REVIEW ARTICLE published: 03 September 2014 doi: 10.3389/fncir.2014.00098 Neuronal organization of olfactory bulb circuits Shin Nagayama 1*, Ryota Homma1 and Fumiaki Imamura 2 1 Department of Neurobiology and Anatomy, The University of Texas Medical School at Houston, Houston, TX, USA 2 Department of Pharmacology, Pennsylvania State University College of Medicine, Hershey, PA, USA Edited by: Olfactory sensory neurons extend their axons solely to the olfactory bulb, which is Benjamin R. Arenkiel, Baylor College dedicated to odor information processing.The olfactory bulb is divided into multiple layers, of Medicine, USA with different types of neurons found in each of the layers. Therefore, neurons in the Reviewed by: olfactory bulb have conventionally been categorized based on the layers in which their cell Kazushige Touhara, University of Tokyo, Japan bodies are found; namely, juxtaglomerular cells in the glomerular layer, tufted cells in the Veronica Egger, external plexiform layer, mitral cells in the mitral cell layer, and granule cells in the granule Ludwig-Maximilians-Universität, cell layer. More recently, numerous studies have revealed the heterogeneous nature of each Germany Kathleen Quast, Baylor College of of these cell types, allowing them to be further divided into subclasses based on differences Medicine, USA in morphological, molecular, and electrophysiological properties. In addition, technical *Correspondence: developments and advances have resulted in an increasing number of studies regarding Shin Nagayama, Department of cell types other than the conventionally categorized ones described above, including short- Neurobiology and Anatomy, The axon cells and adult-generated interneurons. Thus, the expanding diversity of cells in the University of Texas Medical School at Houston, 6431 Fannin Street, olfactory bulb is now being acknowledged. -
The Narrowing of Dendrite Branches Across Nodes Follows a Well-Defined Scaling Law
The narrowing of dendrite branches across nodes follows a well-defined scaling law Maijia Liaoa, Xin Liangb, and Jonathon Howarda,1 aDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520; and bTsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, 100084 Beijing, China Edited by Yuh Nung Jan, Howard Hughes Medical Institute, University of California San Francisco, San Francisco, CA, and approved May 17, 2021 (received for review October 28, 2020) The systematic variation of diameters in branched networks has minimized. Da Vinci’s law has been reformulated as the “pipe tantalized biologists since the discovery of da Vinci’s rule for trees. model” for plants, in which a fixed cross-section of stems and Da Vinci’s rule can be formulated as a power law with exponent branches is required to support each unit amount of leaves (13). two: The square of the mother branch’s diameter is equal to the Experimental support for scaling laws, however, is scarce because sum of the squares of those of the daughters. Power laws, with of the difficulties of imaging entire branched networks and because different exponents, have been proposed for branching in circula- intrinsic anatomical variability may obscure precise laws (14). Thus, tory systems (Murray’s law with exponent 3) and in neurons (Rall’s it is an open question whether scaling laws such as Eq. 1 apply in law with exponent 3/2). The laws have been derived theoretically, biological systems. based on optimality arguments, but, for the most part, have not To quantitatively test diameter-scaling laws in neurons, it is been tested rigorously. -
Action Potentials in Basal and Oblique Dendrites of Rat Neocortical Pyramidal Neurons Srdjan D
Physiology in Press; published online on May 9, 2003 as 10.1113/jphysiol.2002.033746 J Physiol (2003), xxx.x, pp. 000–000 DOI: 10.1113/jphysiol.2002.033746 © The Physiological Society 2003 www.jphysiol.org Action potentials in basal and oblique dendrites of rat neocortical pyramidal neurons Srdjan D. Antic Department of Cellular and Molecular Physiology, and Department of Neurobiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520, USA Basal and oblique dendrites comprise ~2/3 of the total excitable membrane in the mammalian cerebral cortex, yet they have never been probed with glass electrodes, and therefore their electrical properties and overall impact on synaptic processing are unknown. In the present study, fast multi- site voltage-sensitive dye imaging combined with somatic recording was used to provide a detailed description of the membrane potential transients in basal and oblique dendrites of pyramidal neurons during single and trains of action potentials (APs). The optical method allowed simultaneous measurements from several dendrites in the visual field up to 200 mm from the soma, thus providing a unique report on how an AP invades the entire dendritic tree. In contrast to apical dendrites, basal and oblique branches: (1) impose very little amplitude and time course modulation on backpropagating APs; (2) are strongly invaded by the somatic spike even when somatic firing rates reach 40 Hz (activity-independent backpropagation); and (3) do not exhibit signs of a ‘calcium shoulder’ on the falling phase of the AP. A compartmental model incorporating AP peak latencies and half-widths obtained from the apical, oblique and basal dendrites indicates that the specific intracellular resistance (Ri) is less than 100 V cm. -
Bi 360 Week 4 Discussion Questions: Electrical and Chemical Synapses
Bi 360 Week 4 Discussion Questions: Electrical and Chemical Synapses 1a) What is the difference between a non-rectifying electrical synapse and a rectifying electrical synapse? A non-rectifying electrical synapse allows information to flow between two cells in either direction (presynaptic cell postsynaptic cell and postsynaptic cell presynaptic cell). A rectifying electrical synapse allows information to flow in only one direction; positive current will flow in one direction which is equivalent to negative current flowing in the opposite direction. 1b) You are conducting a voltage clamp experiment to determine the properties of a synapse within the central nervous system. You conduct the experiment as follows: 1) You depolarize the presynaptic cell and record the voltage in both the pre- and the postsynaptic cell. 2) You hyperpolarize the presynaptic cell and record from the pre- and postsynaptic cell. 3) You depolarize the postsynaptic cell and record from the pre- and postsynaptic cell. 4) You hyperpolarize the postsynaptic cell and record from the pre- and postsynaptic cell. Analyze each piece of data shown below and determine what kind of synapse this is. How did you draw your conclusion? This is a rectifying electrical synapse. When you depolarize the presynaptic cell, there is a response in both the pre and post synaptic cell. When the postsynaptic cell is depolarized, however, there is a depolarization in the postsynaptic cell but no response in the presynaptic cell. A similar trend can be seen in the hyperpolarizing data but in the opposite direction. This means there must be a voltage dependent gate allowing positive current to flow in one direction while preventing it from flowing in the other. -
NEURAL CONNECTIONS: Some You Use, Some You Lose
NEURAL CONNECTIONS: Some You Use, Some You Lose by JOHN T. BRUER SOURCE: Phi Delta Kappan 81 no4 264-77 D 1999 . The magazine publisher is the copyright holder of this article and it is reproduced with permission. Further reproduction of this article in violation of the copyright is prohibited JOHN T. BRUER is president of the James S. McDonnell Foundation, St. Louis. This article is adapted from his new book, The Myth of the First Three Years (Free Press, 1999), and is reprinted by arrangement with The Free Press, a division of Simon Schuster Inc. ©1999, John T. Bruer . OVER 20 YEARS AGO, neuroscientists discovered that humans and other animals experience a rapid increase in brain connectivity -- an exuberant burst of synapse formation -- early in development. They have studied this process most carefully in the brain's outer layer, or cortex, which is essentially our gray matter. In these studies, neuroscientists have documented that over our life spans the number of synapses per unit area or unit volume of cortical tissue changes, as does the number of synapses per neuron. Neuroscientists refer to the number of synapses per unit of cortical tissue as the brain's synaptic density. Over our lifetimes, our brain's synaptic density changes in an interesting, patterned way. This pattern of synaptic change and what it might mean is the first neurobiological strand of the Myth of the First Three Years. (The second strand of the Myth deals with the notion of critical periods, and the third takes up the matter of enriched, or complex, environments.) Popular discussions of the new brain science trade heavily on what happens to synapses during infancy and childhood. -
Transient Hypoxemia Chronically Disrupts Maturation of Preterm Fetal Ovine Subplate Neuron Arborization and Activity
11912 • The Journal of Neuroscience, December 6, 2017 • 37(49):11912–11929 Development/Plasticity/Repair Transient Hypoxemia Chronically Disrupts Maturation of Preterm Fetal Ovine Subplate Neuron Arborization and Activity XEvelyn McClendon,1 Daniel C. Shaver,1 Kiera Degener-O’Brien,1 Xi Gong,1 Thuan Nguyen,2 Anna Hoerder-Suabedissen,3 Zolta´n Molna´r,3 Claudia Mohr,4 XBen D. Richardson,4 David J. Rossi,4 and Stephen A. Back1,5 1Department of Pediatrics and 2Public Health and Preventive Medicine, Oregon Health & Science University, Portland, Oregon 97239, 3Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom OX1 3QX, 4Department of Integrative Physiology and Neuroscience, College of Veterinary Medicine, Washington State University, Pullman, Washington 99164, and 5Department of Neurology, Oregon Health & Science University, Portland, Oregon 97239 Preterm infants are at risk for a broad spectrum of neurobehavioral disabilities associated with diffuse disturbances in cortical growth and development. During brain development, subplate neurons (SPNs) are a largely transient population that serves a critical role to establish functional cortical circuits. By dynamically integrating into developing cortical circuits, they assist in consolidation of intra- cortical and extracortical circuits. Although SPNs reside in close proximity to cerebral white matter, which is particularly vulnerable to oxidative stress, the susceptibility of SPNs remains controversial. We determined SPN responses to two common insults to the preterm brain: hypoxia-ischemia and hypoxia. We used a preterm fetal sheep model using both sexes that reproduces the spectrum of human cerebral injury and abnormal cortical growth. Unlike oligodendrocyte progenitors, SPNs displayed pronounced resistance to early or delayed cell death from hypoxia or hypoxia-ischemia. -
How Do Dendrites Take Their Shape?
© 2001 Nature Publishing Group http://neurosci.nature.com review How do dendrites take their shape? Ethan K. Scott1 and Liqun Luo1,2 1 Department of Biological Sciences, Stanford University, Stanford, California 94305, USA 2 Neurosciences Program, Stanford University, Stanford, California 94305, USA Correspondence should be addressed to L.L. ([email protected]) Recent technical advances have made possible the visualization and genetic manipulation of individual dendritic trees. These studies have led to the identification and characterization of molecules that are important for different aspects of dendritic development. Although much remains to be learned, the existing knowledge has allowed us to take initial steps toward a comprehensive understanding of how complex dendritic trees are built. In this review, we describe recent advances in our understanding of the molecular mechanisms underlying dendritic morphogenesis, and discuss their cell-biological implications. With their great complexity and variety, dendrites (Fig. 1) are won- added advantage, can be used to study loss-of-function muta- ders of nature’s design. Built to receive and integrate inputs to neu- tions. Much of the progress reviewed in this article would not rons, dendrites occupy much of the brain’s volume and have been have been possible without these technological advances. the subject of studies since the days of Golgi and Cajal1. Over the course of much of the twentieth century, the prevailing belief that Breaking down complex dendritic trees axons take the more active role in wiring the brain and in estab- Although the processes used to build dendritic trees are complex lishing synaptic specificity led researchers to focus on the develop- and diverse (Fig.