DOCSLIB.ORG

An Energy Budget for Signaling in the Grey Matter of the Brain

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
An Energy Budget for Signaling in the Grey Matter of the Brain Journal of Cerebral Blood Flow and Metabolism 21:1133–1145 © 2001 The International Society for Cerebral Blood Flow and Metabolism Published by Lippincott Williams & Wilkins, Inc., Philadelphia Review Article An Energy Budget for Signaling in the Grey Matter of the Brain David Attwell and *Simon B. Laughlin Department of Physiology, University College London, London, and *Department of Zoology, University of Cambridge, Cambridge, U.K. Summary: Anatomic and physiologic data are used to analyze signaling is a large fraction of the total energy used by the the energy expenditure on different components of excitatory brain; this favors the use of energy efficient neural codes and signaling in the grey matter of rodent brain. Action potentials wiring patterns. Our estimates of energy usage predict the use and postsynaptic effects of glutamate are predicted to consume of distributed codes, with Յ15% of neurons simultaneously much of the energy (47% and 34%, respectively), with the active, to reduce energy consumption and allow greater com- resting potential consuming a smaller amount (13%), and glu- puting power from a fixed number of neurons. Functional mag- tamate recycling using only 3%. Energy usage depends netic resonance imaging signals are likely to be dominated by strongly on action potential rate—an increase in activity of 1 changes in energy usage associated with synaptic currents and action potential/cortical neuron/s will raise oxygen consump- action potential propagation. Key Words: Action potential— tion by 145 mL/100 g grey matter/h. The energy expended on Energy—fMRI—Resting potential—Signaling—Synapse. The neural processing of information is metabolically of functional imaging techniques. These techniques de- expensive. Although the human brain is 2% of the body’s tect the mismatch between energy use and blood supply weight, it accounts for 20% of its resting metabolism in small volumes of brain, and an increase in signal is (Kety, 1957; Sokoloff, 1960; Rolfe and Brown, 1997). taken to indicate heightened neural activity. However, This requirement for metabolic energy has important im- with the exception of retina (Ames, 1992; Ames and Li, plications for the brain’s evolution and function. The 1992; Ames et al. 1992; Laughlin et al., 1998), little is availability of energy could limit brain size, particularly understood regarding the metabolic demands made by in primates (Aiello and Wheeler, 1995), and could de- neural activity and the distribution of energy usage termine a brain’s circuitry and activity patterns by favor- among identified neural mechanisms. ing metabolically efficient wiring patterns (Mitchison, The restoration of the ion movements generated by 1992; Koulakov and Chklovskii, 2001) and neural codes postsynaptic currents, action potentials, and neurotrans- (Levy and Baxter, 1996; Baddeley et al., 1997; Balasu- mitter uptake contributes to the brain’s energy needs bramanian et al., 2001). The brain’s energy requirements (Siesjö, 1978; Ames, 1992, 2000; Erecin´ska and Silver, make it susceptible to damage during anoxia or ischemia, 1989; Sokoloff et al., 1996). Excitatory synapses domi- and understanding the demands made by different neural nate the brain’s grey matter (Abeles, 1991; Braitenberg mechanisms may help the design of treatments (Ames et and Schüz, 1998), and the distribution of mitochondria al., 1995). Interest in the relation between neural activity points to these glutamatergic synapses being major users and energy use has been heightened by the development of metabolic energy (Wong-Riley, 1989; Wong-Riley et al., 1998). Magnetic resonance studies (Sibson et al., 1998) find that glucose utilization is equal to the rate at Received May 1, 2001; final revision received July 17, 2001; ac- cepted July 18, 2001. which glutamate is converted to glutamine in the brain, Supported by the Wellcome Trust, the Rank Prize Fund, the BBSRC, which is a measure of synaptic glutamate release because and the Gatsby Foundation. the glia that take up glutamate convert some of it to Address correspondence and reprint requests to David Attwell, Dept. Physiology, University College London, Gower St., London, WC1E glutamine. If the activity evoked by glutamate release is 6BT, U.K. a major demand on brain energy supplies, then changes 1133 1134 D. ATTWELL AND S. B. LAUGHLIN in this glutamatergic activity may generate the imbalance centrations, involving extra energy consumption. Rewriting Eq. 1 in terms of changes (⌬) from the resting values, the change of between O2 supply and metabolism that is detected as “activation” in functional magnetic resonance imaging membrane potential is ⌬ =( ⌬ + ⌬ − ⌬ )ր( + )() experiments (Shulman and Rothman, 1998). However, V gNa VNa gK VK Ipump gNa gK 5 glutamate release stimulates a number of mechanisms The rates of change of [Na+] and [K+] in a cell of volume (for example, postsynaptic currents, action potentials, i i U are transmitter recycling) whose energy usage has not been systematically estimated. [ +] ր = (⌬ − ⌬ )− ⌬ ( ) UF d Na i dt gNa VNa V 3 Ipump 6 This article uses anatomic and physiologic data from [ +] ր = (⌬ − ⌬ )+ ⌬ ( ) rodents (primates are discussed at the end of the article) UF d K i dt gK VK V 2 Ipump 7 + ס + -to construct an energy budget for mammalian grey mat From Eq. 5 − Eq. 7, d[Na ]i/dt −d[K ]i/dt, and initially + ⌬ ס + ⌬ ter, specifying the metabolic cost of the mechanisms that [Na ]i − [K ]i (when the membrane potential has returned generate and transmit neural signals. Taking advantage essentially to its resting value, after an action potential or ex- of biophysical data gathered in recent years, we derive citatory input, when the Na+ entry has been balanced by K+ + ⌬ ס + ⌬ the first reasonable estimates of the amounts of energy exit). Thus, [Na ]i − [K ]i at all times. Equation 6 is solved by assuming that the pump rate varies linearly with consumed by the major processes underlying neuronal small changes of [Na+] around the resting value so that signaling. These values specify the distribution of energy i ⌬ = ␭⌬[ +] ( ) consumption between glia and neurons and between the Ipump Na i 8 neural mechanisms found in synapses, dendrites, and axons. The budget identifies major metabolic constraints and using (for small concentration changes) to cortical function and, by specifying the dependence of ⌬ =−( ր ) ([ +] ր[ +] ) VNa RT F ln Na i,new Na i,old energy usage on action potential frequency and synaptic ∼−( ր )(⌬[ +] ր ) RT F Na i Nai ; transmission, will help to define the ability of functional ⌬ ∼−( ր )(⌬[ +] ր ) VK RT F K i Ki imaging to detect changes in neural activity. where Nai and Ki are resting values. This gives (at time t) MATERIALS AND METHODS ⌬[ +] ( )=⌬[ +] ( = ) −tր␶ Na i t Na i t 0 e , Here, we present detailed calculations of energy expenditure where on different cellular mechanisms in the brain. Readers who are interested in the conclusions of the analysis, but do not wish to ր␶ =[{ ր( + )}{ ր }{( ր )+( ր )} + ␭( 1 gNagK gNa gK RT F 1 Nai 1 Ki 2gNa go through the calculations in detail, can read the Results sec- + 3g )ր(g + g )]րUF tion with no loss of continuity. Limitations on the accuracy of K Na K the calculations are considered in the Discussion. The extra ATP consumed is + Energy needed for Na extrusion ϱ + + + For a cell membrane with Na and K conductances (gNa and ⌬ ր = ␭␶ ⌬[ ] ( = )ր ∫ Ipump Fdt Na i t 0 F, gK, with reversal potentials VNa and VK), and a pump that extrudes 3 Na+ and imports 2 K+ per adenosine triphosphate O (ATP) consumed, on a time scale much slower than the mem- which is brane time constant, there is no net membrane current and ( ⌬[ +] ( = ))ր[{ ր( + )}{ ր }{( ր ) ( − )+ ( − )= ( ) U Na i t 0 gNagK gNa gK RT F 1 Nai gNa VNa V gK VK V Ipump 1 +( ր )}ր␭ +( + )ր( + )] ( ) 1 Ki 2gNa 3gK gNa gK 9 where V is membrane potential, and the pump current, Ipump,is + 1/3 of the Na+ extrusion rate. Adenosine triphosphate is con- If gNa<<gK, and the sensitivity of the pump to [Na ]i changes (␭) is large, this is ∼(Na+ load)/3, the approximation that is used sumed at a rate Ipump/F (F is the Faraday). At the resting po- in the rest of this article. In general, the ATP used differs from ס + ס + tential when d[Na ]i/dt d[K ]i/dt 0, ␭ this value by an amount that depends on gNa/gK and . For the ס + ס + I = g (V − V)ր3 (2) values of gNa/gK used below, [Na ]i 20 mmol/L, [K ]i pump Na Na + 140 mmol/L, and a pump rate that depends on [Na ]i according + From Eqs. 1 and 2, the current produced by Na influx at the to a Hill equation with a Hill coefficient of 3 and an EC50 of 20 resting potential, Vrp,is mmol/L, Eqs. 9, 8, and 2 show that for neurons and glia, re- spectively, the ATP used is 3% and 6% less than the value of ( − )= ( − )( − )ր{ ( + gNa VNa Vrp 3 VNa Vrp Vrp VK Rin Vrp 2VNa (Na+ load)/3. (The ATP usage can differ from (Na+ load)/3 − )} ( ) 3VK 3 because we are calculating the change in usage from its resting value, and the increase in [Na+] , decrease in [K+] , and altered where the input resistance, R , is 1/(g +g ) and the rate of i i in Na K potential change the passive Na+ influx, and hence the ATP ATP consumption is + needed to pump it out.) Other plausible [Na ]i dependencies for ( − )( − )ր{ ( + − )} ( ) the pump give similar small deviations from an ATP usage of VNa Vrp Vrp VK FRin Vrp 2VNa 3VK 4 (Na+ load/3)—for example, 9% and 11% less, for neurons and + When an action potential or synaptic current increases [Na ]i glia, for a Hill coefficient of 2, or for a pump rate proportional + + and decreases [K ]i, the sodium pump will restore these con- to [Na ]i.
Load more

Recommended publications
  • The Creation of Neuroscience
    The Creation of Neuroscience The Society for Neuroscience and the Quest for Disciplinary Unity 1969-1995 Introduction rom the molecular biology of a single neuron to the breathtakingly complex circuitry of the entire human nervous system, our understanding of the brain and how it works has undergone radical F changes over the past century. These advances have brought us tantalizingly closer to genu- inely mechanistic and scientifically rigorous explanations of how the brain’s roughly 100 billion neurons, interacting through trillions of synaptic connections, function both as single units and as larger ensem- bles. The professional field of neuroscience, in keeping pace with these important scientific develop- ments, has dramatically reshaped the organization of biological sciences across the globe over the last 50 years. Much like physics during its dominant era in the 1950s and 1960s, neuroscience has become the leading scientific discipline with regard to funding, numbers of scientists, and numbers of trainees. Furthermore, neuroscience as fact, explanation, and myth has just as dramatically redrawn our cultural landscape and redefined how Western popular culture understands who we are as individuals. In the 1950s, especially in the United States, Freud and his successors stood at the center of all cultural expla- nations for psychological suffering. In the new millennium, we perceive such suffering as erupting no longer from a repressed unconscious but, instead, from a pathophysiology rooted in and caused by brain abnormalities and dysfunctions. Indeed, the normal as well as the pathological have become thoroughly neurobiological in the last several decades. In the process, entirely new vistas have opened up in fields ranging from neuroeconomics and neurophilosophy to consumer products, as exemplified by an entire line of soft drinks advertised as offering “neuro” benefits.
    [Show full text]
  • Two Case Studies Detailing Bayesian Parameter Inference for Dynamic Energy Budget Models
    bioRxiv preprint doi: https://doi.org/10.1101/259705; this version posted July 30, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Two case studies detailing Bayesian parameter inference for dynamic energy budget models Philipp H. Boersch-SupanA,B,C,1 and Leah R. JohnsonD,2 July 30, 2018 ADepartment of Geography, University of Florida, Gainesville, FL 32611, USA BEmerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA CDepartment of Integrative Biology, University of South Florida, Tampa, FL 33610, USA DDepartment of Statistics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA [email protected] - ORCID ID 0000-0001-6723-6833 [email protected] - ORCID ID 0000-0002-9922-579X Abstract Mechanistic representations of individual life-history trajectories are powerful tools for the pre- diction of organismal growth, reproduction and survival under novel environmental conditions. Dynamic energy budget (DEB) theory provides compact models to describe the acquisition and allocation of energy by organisms over their full life cycle. However, estimating DEB model param- eters, and their associated uncertainties and covariances, is not trivial. Bayesian inference provides a coherent way to estimate parameter uncertainty, and propagate it through the model, while also making use of prior information to constrain the parameter space. We outline a Bayesian inference approach for energy budget models and provide two case studies – based on a simplified DEBkiss model, and the standard DEB model – detailing the implementation of such inference procedures using the open-source software package deBInfer.
    [Show full text]
  • Oligodendrocytes in Development, Myelin Generation and Beyond
    cells Review Oligodendrocytes in Development, Myelin Generation and Beyond Sarah Kuhn y, Laura Gritti y, Daniel Crooks and Yvonne Dombrowski * Wellcome-Wolfson Institute for Experimental Medicine, Queen’s University Belfast, Belfast BT9 7BL, UK; [email protected] (S.K.); [email protected] (L.G.); [email protected] (D.C.) * Correspondence: [email protected]; Tel.: +0044-28-9097-6127 These authors contributed equally. y Received: 15 October 2019; Accepted: 7 November 2019; Published: 12 November 2019 Abstract: Oligodendrocytes are the myelinating cells of the central nervous system (CNS) that are generated from oligodendrocyte progenitor cells (OPC). OPC are distributed throughout the CNS and represent a pool of migratory and proliferative adult progenitor cells that can differentiate into oligodendrocytes. The central function of oligodendrocytes is to generate myelin, which is an extended membrane from the cell that wraps tightly around axons. Due to this energy consuming process and the associated high metabolic turnover oligodendrocytes are vulnerable to cytotoxic and excitotoxic factors. Oligodendrocyte pathology is therefore evident in a range of disorders including multiple sclerosis, schizophrenia and Alzheimer’s disease. Deceased oligodendrocytes can be replenished from the adult OPC pool and lost myelin can be regenerated during remyelination, which can prevent axonal degeneration and can restore function. Cell population studies have recently identified novel immunomodulatory functions of oligodendrocytes, the implications of which, e.g., for diseases with primary oligodendrocyte pathology, are not yet clear. Here, we review the journey of oligodendrocytes from the embryonic stage to their role in homeostasis and their fate in disease. We will also discuss the most common models used to study oligodendrocytes and describe newly discovered functions of oligodendrocytes.
    [Show full text]
  • Dinosaur Energetics: Setting the Bounds on Feasible Physiologies and Ecologies
    Dinosaur energetics: setting the bounds on feasible physiologies and ecologies Andrew Clarke 1,2,* 1. British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 0ET, U.K. 2. School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, U.K. *Corresponding author; e-mail: [email protected] Article type: Synthesis Keywords: dinosaur, energetics, growth, metabolism, migration, size, temperature. Accepted for publication by American Naturalist on 29 March 2013 and published electronically on 19 July 2013. American Naturalist 182 (3): 283-297, 2013; doi: 10.1086/671259). See: http://www.jstor.org/stable/10.1086/670340. ___________________________________________________________________________ ABSTRACT: The metabolic status of dinosaurs has long been debated but remains unresolved as no consistent picture has yet emerged from a range of anatomical and isotopic evidence. Quantitative analysis of dinosaur energetics, based on general principles applicable to all vertebrates, shows that many features of dinosaur lifestyle are compatible with a physiology similar to that of extant lizards, scaled up to dinosaur body masses and temperatures. Sufficient metabolic scope would have been available to support observed dinosaur growth rates and allow considerable locomotor activity, perhaps even migration. Since at least one dinosaur lineage evolved true endothermy, this analysis emphasises that there was no single dinosaur physiology. Many small theropods were insulated with feathers and appear to have been partial or full endotherms. Uninsulated small taxa, and all juveniles, would presumably have been ectothermic, with consequent diurnal and seasonal variations in body temperature. In larger taxa inertial homeothermy would have resulted in warm and stable body temperatures, but with a basal metabolism significantly below that of living mammals or birds of the same size.
    [Show full text]
  • Nernst Potentials and Membrane Potential Changes
    UNDERSTANDING MEMBRANE POTENTIAL CHANGES IN TERMS OF NERNST POTENTIALS: For seeing how a change in conductance to ions affects the membrane potential, follow these steps: 1. Make a graph with membrane potential on the vertical axis (-100 to +55) and time on the horizontal axis. 2. Draw dashed lines indicating the standard Nernst potential (equilibrium potential) for each ion: Na+ = +55 mV, K+ = -90mV, Cl- = -65 mV. 3. Draw lines below the horizontal axis showing the increased conductance to individual ions. 4. Start plotting the membrane potential on the left. Most graphs will start at resting potential (-70 mV) 5. When current injection (Stim) is present, move the membrane potential upward to Firing threshold. 6. For the time during which membrane conductance to a particular ion increases, move the membrane potential toward the Nernst potential for that ion. 7. During the time when conductance to a particular ion decreases, move the membrane potential away from the Nernst potential of that ion, toward a position which averages the conductances of the other ions. 8. When conductances return to their original value, membrane potential will go to its starting value. +55mV ACTION POTENTIAL SYNAPTIC POTENTIALS 0mV Membrane potential Firing threshold Firing threshold -65mV -90mV Time Time Na+ K+ Conductances Stim CHANGES IN MEMBRANE POTENTIAL ALLOW NEURONS TO COMMUNICATE The membrane potential of a neuron can be measured with an intracellular electrode. This 1 provides a measurement of the voltage difference between the inside of the cell and the outside. When there is no external input, the membrane potential will usually remain at a value called the resting potential.
    [Show full text]
  • Rapid and Efficient Generation of Oligodendrocytes from Human
    Rapid and efficient generation of oligodendrocytes PNAS PLUS from human induced pluripotent stem cells using transcription factors Marc Ehrlicha,b, Sabah Mozafaric,d,e,f, Michael Glatzab, Laura Starosta,b, Sergiy Velychkob, Anna-Lena Hallmanna,b, Qiao-Ling Cuig, Axel Schambachh, Kee-Pyo Kimb, Corinne Bachelinc,d,e,f, Antoine Marteync,d,e,f, Gunnar Hargusa,b, Radia Marie Johnsoni, Jack Antelg, Jared Sterneckertj, Holm Zaehresb,k, Hans R. Schölerb,l, Anne Baron-Van Evercoorenc,d,e,f, and Tanja Kuhlmanna,1 aInstitute of Neuropathology, University Hospital Münster, 48149 Muenster, Germany; bDepartment of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, 48149 Muenster, Germany; cINSERM, U1127, F-75013 Paris, France; dCNRS, UMR 7225, F-75013 Paris, France; eSorbonne Universités, Université Pierre et Marie Curie Paris 06, UM-75, F-75005 Paris, France; fInstitut du Cerveau et de la Moelle epinière-Groupe Hospitalier Pitié-Salpêtrière, F-75013 Paris, France; gMontreal Neurological Institute, McGill University, Montreal, QC, Canada H3A 2B4; hInstitute of Experimental Hematology, Hannover Medical School, 30625 Hannover, Germany; iDepartment of Physiology, McGill University, Montreal, QC, Canada H3A 2B4; jDFG Research Center for Regenerative Therapies, Technische Universität Dresden, 01307 Dresden, Germany; kMedical Faculty, Department of Anatomy and Molecular Embryology, Ruhr-University Bochum, 44801 Bochum, Germany; and lMedicial Faculty, Westphalian Wilhelms-University of Muenster, 48149 Muenster, Germany Edited by Brigid L. M. Hogan, Duke University Medical Center, Durham, NC, and approved February 1, 2017 (received for review August 30, 2016) Rapid and efficient protocols to generate oligodendrocytes (OL) more, these protocols require long culture periods (70–150 d) to + from human induced pluripotent stem cells (iPSC) are currently obtain O4 OL and show limited efficiency (9–12).
    [Show full text]
  • Neurotransmitter Release Is Blocked Intracellularly by Botulinum
    Proc. Nati. Acad. Sci. USA Vol. 85, pp. 4090-4094, June 1988 Neurobiology Neurotransmitter release is blocked intracellularly by botulinum neurotoxin, and this requires uptake of both toxin polypeptides by a process mediated by the larger chain (cholinergic synapse/noncholinergic synapse/intraceliular in ection/quantal release/Aplysia cahifornica) B. POULAIN*, L. TAUC*, E. A. MAISEYt, J. D. F. WADSWORTHt, P. M. MOHANt, AND J. 0. DOLLYt *Laboratoire de Neurobiologie Cellulaire et Moldculaire, Centre National de la Recherche Scientifique, Gif-sur-Yvette, 91190 France; tDepartment of Biochemistry, Imperial College, London SW7 2AZ, United Kingdom; and tDepartment of Zoology, S.V. University, Tirupati, 515502, A.P. India Communicated by C. Ladd Prosser, February 17, 1988 ABSTRACT Botulinum neurotoxins (types A and B), lacking for a multistep process of intoxication (2, 9) and, in which are microbial proteins consisting of two disulfide-linked particular, for the inactivation by BoNT of an intracellular chains, inhibit specifically and with high potency the release of component that is involved in the release of AcCho and, acetylcholine from peripheral nerve terminals. As a prerequi- perhaps, all transmitters. Furthermore, the role of the HC site for a long-term development of effective treatments for and LC of BoNT in such a scheme for its neuroparalytic botulism, the internalization and inhibitory action of the toxin action remains to be established. Pertinent questions to be and its constituent chains were examined by electrophysiolog- answered include (i) whether the HC, by virtue of its ability ical methods at identified synapses inAplysia preparations that to recognize neural membrane receptors (8, 10), allows allow both intracellular and bath application of the neurotox- functional recognition ofcholinergic terminals and whether it ins.
    [Show full text]
  • Leaf Radiative Properties and the Leaf Energy Budget
    University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Agronomy & Horticulture -- Faculty Publications Agronomy and Horticulture Department 2005 Leaf Radiative Properties and the Leaf Energy Budget Timothy J. Arkebauer University of Nebraska-Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/agronomyfacpub Arkebauer, Timothy J., "Leaf Radiative Properties and the Leaf Energy Budget" (2005). Agronomy & Horticulture -- Faculty Publications. 693. https://digitalcommons.unl.edu/agronomyfacpub/693 This Article is brought to you for free and open access by the Agronomy and Horticulture Department at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Agronomy & Horticulture -- Faculty Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. 5 Leaf Radiative Properties and the Leaf Energy Budget T.J. ARKEBAUER University of Nebraska Lincoln, Nebraska Leaf radiative properties are the physical properties of leaves that characterize radiant energy exchange with their surroundings. Radiant energy exchange is an important consideration in studies of plant function since, for example, absorp- tion of photosynthetically active radiation (PAR) leads to the transformation of this energy into chemical energy via photosynthesis. Thus, plant productivity, and hence, agricultural production, ultimately depend on leaf radiative properties. Leaf temperature is an additional, very important, parameter in intimate association with leaf radiant energy exchange. This association occurs since energy gained via radiation must be in balance with energy lost through various processes and energy loss from the leaf is predicated on leaf temperature. Leaf temperature is a critical factor determining leaf transpiration (hence, crop water use), reaction rates of biochemical processes (hence, photosynthetic rates, respi- ration rates, growth rates and productivity), and many other aspects of plant func- tion.
    [Show full text]
  • The Body's Energy Budget
    The Body’s Energy Budget energy is measured in units called kcals = Calories the more H’s a molecule contains the more ATP (energy) can be generated of the various energy pathways: fat provides the most energy for its weight note all the H’s more oxidation can occur eg: glucose has 12 H’s 38ATP’s a 16-C FA has 32 H’s 129ATP’s we take in energy continuously we use energy periodically optimal body conditions when energy input = energy output any excess energy intake is stored as fat average person takes in ~1 Million Calories and expends 99% of them maintains energy stability 1 lb of body fat stores 3500 Calories 454g: 87% fat 395g x 9 Cal/g = 3555 kcal would seem if you burn an extra 3500 Cal you would lose 1 lb; and if you eat an extra 3500 Cal you would gain 1 lb not always so: 1. when a person overeats much of the excess energy is stored; some is spent to maintain a heavier body 2. People seem to gain more body fat when they eat extra fat calories than when they eat extra carbohydrate calories 3. They seem to lose body fat most efficiently when they limit fat calories For overweight people a reasonable rate of wt loss is 1/2 – 1 lb/week can be achieved with Cal intake of ~ 10 Cal/lb of body wt. Human Anatomy & Physiology: Nutrition and Metabolism; Ziser, 2004 5 Quicker Weight Loss: 1. may lose lean tissue 2. may not get 100% of nutrients 3.
    [Show full text]
  • 9.01 Introduction to Neuroscience Fall 2007
    MIT OpenCourseWare http://ocw.mit.edu 9.01 Introduction to Neuroscience Fall 2007 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 9.01 Recitation (R02) RECITATION #2: Tuesday, September 18th Review of Lectures: 3, 4 Reading: Chapters 3, 4 or Neuroscience: Exploring the Brain (3rd edition) Outline of Recitation: I. Previous Recitation: a. Questions on practice exam questions from last recitation? II. Review of Material: a. Exploiting Axoplasmic Transport b. Types of Glia c. THE RESTING MEMBRANE POTENTIAL d. THE ACTION POTENTIAL III. Practice Exam Questions IV. Questions on Pset? Exploiting Axoplasmic Transport: Maps connections of the brain Rates of transport: - slow: - fast: Examples: Uses anterograde transport: - Uses retrograde transport: - - - Types of Glia: - Microglia: - Astrocytes: - Myelinating Glia: 1 THE RESTING MEMBRANE POTENTIAL: The Cast of Chemicals: The Movement of Ions: ­ Influences by two factors: (1) Diffusion: (2) Electricity: Ohm’s Law: I = gV Ionic Equilibrium Potentials (EION): + Example: ENs * diffusional and electrical forces are equal 2 Nernst Equation: EION = 2.303 RT/zF log [ion]0/[ion]i Calculates equilibrium potential for a SINGLE ion. Inside Outside EION (at 37°C) + [K ] + [Na ] 2+ [Ca ] ­ [Cl ] *Pumps maintain concentration gradients (ex. sodium­potassium pump; calcium pump) Resting Membrane Potential (VM at rest): Measured resting membrane potential: ­ 65 mV Goldman Equation: + + + + VM = 61.54 mV log (PK[K ]o + PNa[Na ]o)/ (PK[K ]I + PNa[Na ]i) + + Calculates membrane potential when permeable to both Na and K . Remember: at REST, gK >>> gNa therefore, VM is closer to EK THE ACTION POTENTIAL (Nerve Impulse): Phases of an Action Potential: Vm (mV) ENa 0 EK Time 3 Conductance of Ion Channels during AP: Remember: Changes in conductance, or permeability of the membrane to a specific ion, changes the membrane potential.
    [Show full text]
  • 11 Introduction to the Nervous System and Nervous Tissue
    11 Introduction to the Nervous System and Nervous Tissue ou can’t turn on the television or radio, much less go online, without seeing some- 11.1 Overview of the Nervous thing to remind you of the nervous system. From advertisements for medications System 381 Yto treat depression and other psychiatric conditions to stories about celebrities and 11.2 Nervous Tissue 384 their battles with illegal drugs, information about the nervous system is everywhere in 11.3 Electrophysiology our popular culture. And there is good reason for this—the nervous system controls our of Neurons 393 perception and experience of the world. In addition, it directs voluntary movement, and 11.4 Neuronal Synapses 406 is the seat of our consciousness, personality, and learning and memory. Along with the 11.5 Neurotransmitters 413 endocrine system, the nervous system regulates many aspects of homeostasis, including 11.6 Functional Groups respiratory rate, blood pressure, body temperature, the sleep/wake cycle, and blood pH. of Neurons 417 In this chapter we introduce the multitasking nervous system and its basic functions and divisions. We then examine the structure and physiology of the main tissue of the nervous system: nervous tissue. As you read, notice that many of the same principles you discovered in the muscle tissue chapter (see Chapter 10) apply here as well. MODULE 11.1 Overview of the Nervous System Learning Outcomes 1. Describe the major functions of the nervous system. 2. Describe the structures and basic functions of each organ of the central and peripheral nervous systems. 3. Explain the major differences between the two functional divisions of the peripheral nervous system.
    [Show full text]
  • The Action Potential
    See discussions, stats, and author profiles for this publication at: http://www.researchgate.net/publication/6316219 The action potential ARTICLE in PRACTICAL NEUROLOGY · JULY 2007 Source: PubMed CITATIONS READS 16 64 2 AUTHORS, INCLUDING: Mark W Barnett The University of Edinburgh 21 PUBLICATIONS 661 CITATIONS SEE PROFILE Available from: Mark W Barnett Retrieved on: 24 October 2015 192 Practical Neurology HOW TO UNDERSTAND IT Pract Neurol 2007; 7: 192–197 The action potential Mark W Barnett, Philip M Larkman t is over 60 years since Hodgkin and called ion channels that form the permeation Huxley1 made the first direct recording of pathways across the neuronal membrane. the electrical changes across the neuro- Although the first electrophysiological nal membrane that mediate the action recordings from individual ion channels were I 2 potential. Using an electrode placed inside a not made until the mid 1970s, Hodgkin and squid giant axon they were able to measure a Huxley predicted many of the properties now transmembrane potential of around 260 mV known to be key components of their inside relative to outside, under resting function: ion selectivity, the electrical basis conditions (this is called the resting mem- of voltage-sensitivity and, importantly, a brane potential). The action potential is a mechanism for quickly closing down the transient (,1 millisecond) reversal in the permeability pathways to ensure that the polarity of this transmembrane potential action potential only moves along the axon in which then moves from its point
    [Show full text]