The DOI matches its Crossref record; 103 of the 104 references it cites were found in a registry or an index.
The Energetics of CNS White Matter
Open accessAbstract
The energetics of CNS white matter are poorly understood. We derive a signaling energy budget for the white matter (based on data from the rodent optic nerve and corpus callosum) which can be compared with previous energy budgets for the gray matter regions of the brain, perform a cost-benefit analysis of the energetics of myelination, and assess mechanisms for energy production and glucose supply in myelinated axons. We show that white matter synapses consume ≤0.5% of the energy of gray matter synapses and that this, rather than more energy-efficient action potentials, is the main reason why CNS white matter uses less energy than gray matter. Surprisingly, while the energetic cost of building myelin could be repaid within months by the reduced ATP cost of neuronal action potentials, the energetic cost of maintaining the oligodendrocyte resting potential usually outweighs the saving on action potentials. Thus, although it dramatically speeds action potential propagation, myelination need not save energy. Finally, we show that mitochondria in optic nerve axons could sustain measured firing rates with a plausible density of glucose transporters in the nodal membrane, without the need for energy transfer from oligodendrocytes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“To perform all of their tasks, OL energy demand is enormous, reaching a maximum during early myelination and remaining at a high level throughout life [284].”
From Revisiting the Pathogenesis of X-Linked Adrenoleukodystrophy (2025) · cites this paper as [284]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The reconstructed blood vessels (~230 mm in length) did not show much evidence of layer-specific behavior but had a lower density in the white matter, presumably for energetic reasons (45) and in the regions surrounding large vessels (fig. 4B).”
From A petavoxel fragment of human cerebral cortex reconstructed at nanoscale resolution (2024) · cites this paper as [45]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Sokoloff, L., Reivich, M., Kennedy, C., Rosiers, M. H. D., Patlak, C. S., Pettigrew, K. D., Sakurada, O., & Shinohara, M. (1977) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1977.tb10649.x · Cited by 6,000
An Energy Budget for Signaling in the Grey Matter of the Brain
Attwell, D., & Laughlin, S. B. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200110000-00001 · Cited by 3,543
Self-citationSiesjö, B. K. (1978) · Medical Entomology and Zoology · Cited by 1,426
Basic Neurochemistry: Molecular, Cellular, and Medical Aspects
Siegel, G. J., & Agranoff, B. W. (1989) · Cited by 1,359
Cell death and control of cell survival in the oligodendrocyte lineage
Barres, B. A., Hart, I. K., Coles, H. S. R., Burne, J. F., Voyvodic, J. T., Richardson, W. D., & Raff, M. C. (1992) · Cell · doi:10.1016/0092-8674(92)90531-g · Cited by 1,345
Cortex: Statistics and Geometry of Neuronal Connectivity
Braitenberg, V., & Schüz, A. (1998) · doi:10.1007/978-3-662-03733-1 · Cited by 1,178 · cited 1×
“To calculate synapse density in the rat cerebral cortex (7.36 10 17 synapses/m 3), the number of synapses/neuron [8000: Braitenberg and Schuz (1998)] was multiplied by the density of neurons [9.2 10 13 neurons/m 3: Braitenberg and Schuz (1998)].”
MethodInfluentialThe cost of cortical computation.
Lennie, P. (2003) · Current Biology · doi:10.1016/s0960-9822(03)00135-0 · Cited by 1,134
Malonek, D., & Grinvald, A. (1996) · Science · doi:10.1126/science.272.5261.551 · Cited by 1,109
A theory of the effects of fibre size in medullated nerve
Rushton, W. A. H. (1951) · The Journal of Physiology · doi:10.1113/jphysiol.1951.sp004655 · Cited by 1,075
Energy limitation as a selective pressure on the evolution of sensory systems
Niven, J. E., & Laughlin, S. B. (2008) · Journal of Experimental Biology · doi:10.1242/jeb.017574 · Cited by 1,056
Research works printed but not linked: 1
- Royeck, 2010, Persistance of neuronal transmitter release onto oligodendrocyte precursor cells during progressive myelination in the mouse optic tract, Soc Neurosci Abstr, 36, 554
Cited by
Sorted by citations
The Pathobiology of Vascular Dementia
Iadecola, C. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.008 · Cited by 1,857
“Due to fewer synapses, white matter energy usage, and consequently blood flow, is 1/3 lower of that of the gray matter (Harris and Attwell, 2012).”
Synaptic Energy Use and Supply
Harris, J. J., Jolivet, R., & Attwell, D. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.019 · Cited by 1,747
Self-citationSugar for the brain: the role of glucose in physiological and pathological brain function
Mergenthaler, P., Lindauer, U., Dienel, G. A., & Meisel, A. (2013) · Trends in Neurosciences · doi:10.1016/j.tins.2013.07.001 · Cited by 1,612
The nature of feelings: evolutionary and neurobiological origins
Damasio, A., & Carvalho, G. B. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3403 · Cited by 1,280
Myelination of the Nervous System: Mechanisms and Functions
Nave, K.-A., & Werner, H. B. (2014) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100913-013101 · Cited by 983
Brain Glucose Metabolism: Integration of Energetics with Function
Dienel, G. A. (2018) · Physiological Reviews · doi:10.1152/physrev.00062.2017 · Cited by 911
Axonal transport: cargo-specific mechanisms of motility and regulation
Maday, S., Twelvetrees, A. E., Moughamian, A. J., & Holzbaur, E. L. F. (2014) · Neuron · doi:10.1016/j.neuron.2014.10.019 · Cited by 683
Sterling, P., & Laughlin, S. (2015) · doi:10.7551/mitpress/9780262028707.001.0001 · Cited by 482
Oligodendrocyte-Encoded HIF Function Couples Postnatal Myelination and White Matter Angiogenesis
Yuen, T. J., Silbereis, J. C., Griveau, A., Chang, S. M., Daneman, R., Fancy, S. P. J., Zahed, H., Maltepe, E., & Rowitch, D. H. (2014) · Cell · doi:10.1016/j.cell.2014.04.052 · Cited by 433
Myelin Fat Facts: An Overview of Lipids and Fatty Acid Metabolism
Poitelon, Y., Kopec, A. M., & Belin, S. (2020) · Cells · doi:10.3390/cells9040812 · Cited by 394
Cortical column and whole-brain imaging with molecular contrast and nanoscale resolution
Gao, R., Asano, S. M., Upadhyayula, S., Pisarev, I., Milkie, D. E., Liu, T., Singh, V. P., Graves, A. R., Huynh, G. H., Zhao, Y., et al. (2019) · Science · doi:10.1126/science.aau8302 · Cited by 376
Spatially Stable Mitochondrial Compartments Fuel Local Translation during Plasticity
Rangaraju, V., Lauterbach, M. A., & Schuman, E. M. (2019) · Cell · doi:10.1016/j.cell.2018.12.013 · Cited by 367
A petavoxel fragment of human cerebral cortex reconstructed at nanoscale resolution
Shapson-Coe, A., Januszewski, M., Berger, D. R., Pope, A., Wu, Y., Blakely, T., Schalek, R. L., Li, P. H., Wang, S., Maitin-Shepard, J., et al. (2024) · Science · doi:10.1126/science.adk4858 · Cited by 361
Oligodendroglia: metabolic supporters of neurons
Philips, T., & Rothstein, J. D. (2017) · Journal of Clinical Investigation · doi:10.1172/jci90610 · Cited by 379
Neuregulin and BDNF Induce a Switch to NMDA Receptor-Dependent Myelination by Oligodendrocytes
Lundgaard, I., Luzhynskaya, A., Stockley, J. H., Wang, Z., Evans, K. A., Swire, M., Volbracht, K., Gautier, H. O. B., Franklin, R. J. M., ffrench‐Constant, C., et al. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001743 · Cited by 351
Self-citationThe role of myelin and oligodendrocytes in axonal energy metabolism
Saab, A. S., Tzvetanova, I. D., & Nave, K.-A. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.09.008 · Cited by 324
Motor learning promotes remyelination via new and surviving oligodendrocytes
Bacmeister, C. M., Barr, H. J., McClain, C. R., Thornton, M. A., Nettles, D., Welle, C. G., & Hughes, E. G. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0637-3 · Cited by 322
Node of Ranvier length as a potential regulator of myelinated axon conduction speed
Arancibia‐Cárcamo, I. L., Ford, M. C., Cossell, L., Ishida, K., Tohyama, K., & Attwell, D. (2017) · eLife · doi:10.7554/elife.23329 · Cited by 325
Self-citationA large fraction of neocortical myelin ensheathes axons of local inhibitory neurons
Micheva, K. D., Wolman, D. N., Mensh, B. D., Pax, E., Buchanan, J., Smith, S. J., & Bock, D. D. (2016) · eLife · doi:10.7554/elife.15784 · Cited by 291
Gawryluk, J. R., Mazerolle, E. L., & D’Arcy, R. C. N. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00239 · Cited by 274
Ding, F., Yao, J., Rettberg, J. R., Chen, S., & Brinton, R. D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079977 · Cited by 262
Energy matters: presynaptic metabolism and the maintenance of synaptic transmission
Li, S., & Sheng, Z. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00535-8 · Cited by 285
Yu, D., Cringle, S. J., Balaratnasingam, C., Morgan, W. H., Yu, P. K., & Su, E. (2013) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2013.07.001 · Cited by 248
A connectomic study of a petascale fragment of human cerebral cortex
Shapson-Coe, A., Januszewski, M., Berger, D. R., Pope, A., Wu, Y., Blakely, T., Schalek, R. L., Li, P. H., Wang, S., Maitin-Shepard, J., et al. (2021) · doi:10.1101/2021.05.29.446289 · Cited by 243
Adaptive Capacity: An Evolutionary Neuroscience Model Linking Exercise, Cognition, and Brain Health
Raichlen, D. A., & Alexander, G. E. (2017) · Trends in Neurosciences · doi:10.1016/j.tins.2017.05.001 · Cited by 264
Myelin damage and repair in pathologic CNS: challenges and prospects
Alizadeh, A., Dyck, S. M., & Karimi‐Abdolrezaee, S. (2015) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2015.00035 · Cited by 246
Specificity and robustness of long-distance connections in weighted, interareal connectomes
Betzel, R. F., & Bassett, D. S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1720186115 · Cited by 223
Non‐signalling energy use in the brain
Engl, E., & Attwell, D. (2015) · The Journal of Physiology · doi:10.1113/jphysiol.2014.282517 · Cited by 243
Self-citationEvaluating the gray and white matter energy budgets of human brain function
Yu, Y., Herman, P., Rothman, D. L., Agarwal, D., & Hyder, F. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17708691 · Cited by 211
On Myelinated Axon Plasticity and Neuronal Circuit Formation and Function
Almeida, R. G., & Lyons, D. A. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3185-16.2017 · Cited by 221
Natrajan, M. S., de la Fuente, A. G., Crawford, A. H., Linehan, E., Núñez, V., Johnson, K. R., Wu, T., Fitzgerald, D. C., Ricote, M., Bielekova, B., et al. (2015) · Brain · doi:10.1093/brain/awv289 · Cited by 225
Gao, Y., Ma, Y., Zhang, Q., Winder, A. T., Liang, Z., Antinori, L., Drew, P. J., & Zhang, N. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.069 · Cited by 226
Information and efficiency in the nervous system-a synthesis.
Sengupta, B., Stemmler, M. B., & Friston, K. J. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003157 · Cited by 212
The impact of cerebrovascular aging on vascular cognitive impairment and dementia
Yang, T., Sun, Y., Lu, Z., Leak, R. K., & Zhang, F. (2016) · Ageing Research Reviews · doi:10.1016/j.arr.2016.09.007 · Cited by 214
The energetic brain—A review from students to students
Bordone, M. P., Salman, M. M., Titus, H. E., Amini, E., Andersen, J. V., Chakraborti, B., Diuba, A. V., Dubouskaya, T. G., Ehrke, E., Espindola de Freitas, A., et al. (2019) · Journal of Neurochemistry · doi:10.1111/jnc.14829 · Cited by 205
The sense of should: A biologically-based framework for modeling social pressure
Theriault, J. E., Young, L., & Barrett, L. F. (2021) · Physics of Life Reviews · doi:10.1016/j.plrev.2020.01.004 · Cited by 201
Remyelination after spinal cord injury: Is it a target for repair?
Plemel, J. R., Keough, M. B., Duncan, G. J., Sparling, J. S., Yong, V. W., Stys, P. K., & Tetzlaff, W. (2014) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2014.02.006 · Cited by 206
Jha, M. K., & Morrison, B. M. (2018) · Experimental Neurology · doi:10.1016/j.expneurol.2018.07.009 · Cited by 203
A mechanistic model of connector hubs, modularity and cognition
Bertolero, M. A., Yeo, B. T. T., Bassett, D. S., & D’Esposito, M. (2018) · Nature Human Behaviour · doi:10.1038/s41562-018-0420-6 · Cited by 213
Chamberlain, K. A., Huang, N., Xie, Y., Licausi, F., Li, S., Li, Y., & Sheng, Z. (2021) · Neuron · doi:10.1016/j.neuron.2021.08.011 · Cited by 184
Fueling and Imaging Brain Activation
Dienel, G. A. (2012) · ASN NEURO · doi:10.1042/an20120021 · Cited by 175
The node of Ranvier in CNS pathology
Arancibia-Carcamo, I. L., & Attwell, D. (2014) · Acta Neuropathologica · doi:10.1007/s00401-014-1305-z · Cited by 177
Self-citationA mechanistic model of connector hubs, modularity and cognition
Bertolero, M. A., Yeo, B. T. T., Bassett, D. S., & D’Esposito, M. (2018) · RePEc: Research Papers in Economics · Cited by 181
Functional MRI and resting state connectivity in white matter - a mini-review
Gore, J. C., Li, M., Gao, Y., Wu, T., Schilling, K. G., Huang, Y., Mishra, A., Newton, A. T., Rogers, B. P., Chen, L. M., et al. (2019) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2019.07.017 · Cited by 172
Lake, N. J., Bird, M., Isohanni, P., & Paetau, A. E. (2015) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0000000000000195 · Cited by 173
Intervertebral Disk Degeneration in Dogs: Consequences, Diagnosis, Treatment, and Future Directions
Jeffery, N. D., Levine, J. M., Olby, N. J., & Stein, V. M. (2013) · Journal of Veterinary Internal Medicine · doi:10.1111/jvim.12183 · Cited by 165
Axo-myelinic neurotransmission: a novel mode of cell signalling in the central nervous system
Micu, I., Plemel, J. R., Caprariello, A. V., Nave, K., & Stys, P. K. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.128 · Cited by 166
State and location dependence of action potential metabolic cost in cortical pyramidal neurons
Hallermann, S., de Kock, C. P. J., Stuart, G. J., & Kole, M. H. P. (2012) · Nature Neuroscience · doi:10.1038/nn.3132 · Cited by 163
Haddad, D., & Nakamura, K. (2015) · FEBS Letters · doi:10.1016/j.febslet.2015.10.021 · Cited by 167
GluT4: A central player in hippocampal memory and brain insulin resistance
McNay, E. C., & Pearson-Leary, J. (2019) · Experimental Neurology · doi:10.1016/j.expneurol.2019.113076 · Cited by 159
Hypomyelinating leukodystrophies: Translational research progress and prospects
Pouwels, P. J. W., Vanderver, A. L., Bernard, G., Wolf, N. I., Dreha‐Kulaczewski, S. F., Deoni, S., Bertini, E., Kohlschütter, A., Richardson, W. D., ffrench‐Constant, C., et al. (2014) · Annals of Neurology · doi:10.1002/ana.24194 · Cited by 153
Kougioumtzidou, E., Shimizu, T., Hamilton, N. B., Tohyama, K., Sprengel, R., Monyer, H., Attwell, D., & Richardson, W. D. (2017) · eLife · doi:10.7554/elife.28080 · Cited by 154
Self-citationSynapses: The Brain’s Energy-Demanding Sites
Faria‐Pereira, A., & Morais, V. A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23073627 · Cited by 152
Neuronal energy consumption: biophysics, efficiency and evolution
Niven, J. E. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.09.004 · Cited by 135
Rone, M. B., Cui, Q., Fang, J. Q., Wang, L., Zhang, J., Khan, D., Bedard, M., Almazán, G., Ludwin, S. K., Jones, R., et al. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.4077-15.2016 · Cited by 136
Joutel, A., & Chabriat, H. (2017) · Clinical Science · doi:10.1042/cs20160380 · Cited by 141
Retinal energy metabolism in health and glaucoma
Casson, R. J., Chidlow, G., Crowston, J. G., Williams, P. A., & Wood, J. P. M. (2020) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2020.100881 · Cited by 132
Dulamea, A. O. (2017) · Advances in Experimental Medicine and Biology · doi:10.1007/978-3-319-47861-6_7 · Cited by 128
Labadie, C., Lee, J. H., Rooney, W. D., Jarchow, S., Aubert-Frécon, M., SPRINGER, C. S. J., & Möller, H. E. (2013) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24670 · Cited by 126
Getting around the cell: physical transport in the intracellular world
Mogre, S. S., Brown, A. I., & Koslover, E. F. (2020) · Physical Biology · doi:10.1088/1478-3975/aba5e5 · Cited by 128
Neuron-Oligodendrocyte Interactions in the Structure and Integrity of Axons
Duncan, G. J., Simkins, T., & Emery, B. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.653101 · Cited by 131
Alterations of Oligodendrocyte and Myelin Energy Metabolism in Multiple Sclerosis
López-Muguruza, E., & Matute, C. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241612912 · Cited by 138
Associative learning and sensory neuroplasticity: how does it happen and what is it good for?Preprint
McGann, J. P. (2015) · Learning & Memory · doi:10.1101/lm.039636.115 · Cited by 119
Mitochondrial dysfunction in Autism Spectrum Disorder: clinical features and perspectives
Hollis, F., Kanellopoulos, A. K., & Bagni, C. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.05.018 · Cited by 120
Adaptive responses to neurodegenerative stress in glaucoma
Calkins, D. J. (2021) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2021.100953 · Cited by 118
Energy‐efficient neural information processing in individual neurons and neuronal networks
Yu, L., & Yu, Y. (2017) · Journal of Neuroscience Research · doi:10.1002/jnr.24131 · Cited by 125
Brain vulnerability and viability after ischaemia
Daniele, S. G., Trummer, G., Hossmann, K. A., Vrselja, Z., Benk, C., Gobeske, K. T., Damjanović, D., Andrijević, D., Pooth, J., Dellal, D., et al. (2021) · Nature reviews. Neuroscience · doi:10.1038/s41583-021-00488-y · Cited by 125
Neuronal autophagy and intercellular regulation of homeostasis in the brain
Kulkarni, A., Chen, J., & Maday, S. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.02.008 · Cited by 125
Oligodendrocyte Bioenergetics in Health and Disease
Rosko, L. M., Smith, V. N., Yamazaki, R., & Huang, J. K. (2018) · The Neuroscientist · doi:10.1177/1073858418793077 · Cited by 121
The fate and function of oligodendrocyte progenitor cells after traumatic spinal cord injury
Duncan, G. J., Manesh, S. B., Hilton, B. J., Assinck, P., Plemel, J. R., & Tetzlaff, W. (2019) · Glia · doi:10.1002/glia.23706 · Cited by 119
Myelinated axon physiology and regulation of neural circuit function
Šuminaite, D., Lyons, D. A., & Livesey, M. R. (2019) · Glia · doi:10.1002/glia.23665 · Cited by 123
Arshad, M., Stanley, J. A., & Raz, N. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.047 · Cited by 115
Optic neuropathies: the tip of the neurodegeneration iceberg
Carelli, V., Morgia, C. L., Ross‐Cisneros, F. N., & Sadun, A. A. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx273 · Cited by 116
Motor learning drives dynamic patterns of intermittent myelination on learning-activated axons
Bacmeister, C. M., Huang, R., Osso, L. A., Thornton, M. A., Conant, L., Chavez, A. R., Poleg-Polsky, A., & Hughes, E. G. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01169-4 · Cited by 123
Adapting brain metabolism to myelination and long‐range signal transduction
Hirrlinger, J., & Nave, K. (2014) · Glia · doi:10.1002/glia.22737 · Cited by 109
Mechanisms for the maintenance and regulation of axonal energy supply
Chamberlain, K. A., & Sheng, Z. (2019) · Journal of Neuroscience Research · doi:10.1002/jnr.24411 · Cited by 111
Fragility and volatility of structural hubs in the human connectome
Gollo, L. L., Roberts, J. A., Cropley, V., Biase, M. A. D., Pantelis, C., Zalesky, A., & Breakspear, M. J. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0188-z · Cited by 105
The Endolysosomal System and Proteostasis: From Development to Degeneration
Winckler, B., Faúndez, V., Maday, S., Cai, Q., Almeida, C. G., & Zhang, H. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1665-18.2018 · Cited by 111
Metabotropic Glutamate Receptors in Glial Cells: A New Potential Target for Neuroprotection?
Spampinato, S. F., Copani, A., Nicoletti, F., Sortino, M. A., & Caraci, F. (2018) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2018.00414 · Cited by 105
Mapping white-matter functional organization at rest and during naturalistic visual perception
Lynch, L. K., Lu, K., Wen, H., & Liu, Z. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.10.005 · Cited by 104
Sound-Evoked Activity Influences Myelination of Brainstem Axons in the Trapezoid Body
Sinclair, J. L., Fischl, M. J., Alexandrova, O., Heβ, M., Grothe, B., Leibold, C., & Kopp‐Scheinpflug, C. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3728-16.2017 · Cited by 100
Afridi, R., Kim, J., Rahman, M. H., & Suk, K. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.00020 · Cited by 102
Chavali, M., Ulloa-Navas, M. J., Pérez-Borredá, P., García‐Verdugo, J. M., McQuillen, P. S., Huang, E. J., & Rowitch, D. H. (2020) · Neuron · doi:10.1016/j.neuron.2020.09.033 · Cited by 101
Protecting White Matter From Stroke Injury
Matute, C., Domercq, M., Pérez‐Samartín, A., & Ransom, B. R. (2012) · Stroke · doi:10.1161/strokeaha.112.658328 · Cited by 98
A behavioral neuroenergetics theory of ADHD
Killeen, P. R., Russell, V. A., & Sergeant, J. A. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.02.011 · Cited by 97
Age-related changes in the visual pathways: blame it on the axon
Calkins, D. J. (2013) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.13-12784 · Cited by 96
Determinants of resting cerebral blood flow in sickle cell disease
Bush, A., Borzage, M., Choi, S., Václavů, L., Tamrazi, B., Nederveen, A. J., Coates, T. D., & Wood, J. C. (2016) · American Journal of Hematology · doi:10.1002/ajh.24441 · Cited by 96
Axonal energy metabolism, and the effects in aging and neurodegenerative diseases
Yang, S., Park, J. H., & Lu, H.-C. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00634-3 · Cited by 94
“Myelination greatly improves the energetic efficiency of AP propagation, costing less than 1% of white matter’s energy budget [2, 169].”
BackgroundInfluentialGlaucoma: from pathogenic mechanisms to retinal glial cell response to damage
Fernández‐Albarral, J. A., Ramirez, A. I., de Hoz, R., Matamoros, J. A., Salobrar‐García, E., Elvira‐Hurtado, L., López‐Cuenca, I., Sánchez-Puebla, L., Salazar, J. J., & Ramirez, J. M. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1354569 · Cited by 105
Glucose metabolism in mammalian photoreceptor inner and outer segments
Narayan, D. S., Chidlow, G., Wood, J. P. M., & Casson, R. J. (2017) · Clinical and Experimental Ophthalmology · doi:10.1111/ceo.12952 · Cited by 91
Pukos, N., Goodus, M. T., Sahinkaya, F. R., & McTigue, D. M. (2019) · Glia · doi:10.1002/glia.23702 · Cited by 95
Expanding the function of oligodendrocytes to brain energy metabolism
Nave, K., Asadollahi, E., & Sasmita, A. O. (2023) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2023.102782 · Cited by 97
Metabolic Vulnerability in the Neurodegenerative Disease Glaucoma
Inman, D. M., & Harun-Or-Rashid, M. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00146 · Cited by 88
Myelin modifications after chronic sleep loss in adolescent mice
Bellesi, M., Haswell, J. D., de Vivo, L., Marshall, W., Roseboom, P. H., Tononi, G., & Cirelli, C. (2018) · SLEEP · doi:10.1093/sleep/zsy034 · Cited by 92
Boccuni, I., & Fairless, R. (2022) · Life · doi:10.3390/life12050638 · Cited by 85
Wang, P., Wang, J., Michael, A., Wang, Z., Klugah‐Brown, B., Meng, C., & Biswal, B. B. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab181 · Cited by 81
Pease-Raissi, S. E., & Chan, J. R. (2021) · Neuron · doi:10.1016/j.neuron.2021.02.003 · Cited by 85
Lactate Transporters Mediate Glia-Neuron Metabolic Crosstalk in Homeostasis and Disease
Jha, M. K., & Morrison, B. M. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.589582 · Cited by 81
Central Nervous System Remyelination: Roles of Glia and Innate Immune Cells
Baaklini, C. S., Rawji, K. S., Duncan, G. J., Ho, M. F. S., & Plemel, J. R. (2019) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2019.00225 · Cited by 88
A Metabolic Landscape for Maintaining Retina Integrity and Function
Viegas, F., & Neuhauss, S. C. F. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.656000 · Cited by 81
Metadata
- Authors
- Harris, J. J., & Attwell, D.
- Affiliations
- University College London (GB)
- Corresponding author
- Attwell, David
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2012-01-04
- Volume
- 32
- Issue
- 1
- Pages
- 356-371
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC3272449
- OpenAlex
- W1973747802
- Cited by
- 505
- References
- 104
- Citations by year
- 2026: 40 · 2025: 40 · 2024: 41 · 2023: 50 · 2022: 42 · 2021: 55 · 2020: 31 · 2019: 32 · 2018: 33 · 2017: 36 · 2016: 34 · 2015: 19 · 2014: 18 · 2013: 26 · 2012: 8
- FWCI
- 9.36
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust (075232)
- Fondation Leducq
- Medical Research Council
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Mitochondrial Function and Pathology
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- myelination, optic nerve, corpus callosum, action potential propagation, mitochondrial energy production, glucose transporters, nodal membrane
- MeSH terms
- Action Potentials, Animals, Cell Membrane, Central Nervous System, Energy Metabolism, Glucose, Mitochondria, Models, Neurological, Myelin Sheath, Nerve Fibers, Myelinated, Neural Conduction, Oligodendroglia, Optic Nerve, Synapses, Glucose Transport Proteins, Facilitative, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review