Myelin plasticity occurs when newly formed and pre-existing oligodendrocytes remodel existing patterns of myelination. Myelin remodeling occurs in response to changes in neuronal activity and is required for learning and memory. However, the link between behavior-induced neuronal activity and circuit-specific changes in myelination remains unclear. Using longitudinal in vivo two-photon imaging and targeted labeling of learning-activated neurons in mice, we explore how the pattern of intermittent myelination is altered on individual cortical axons during learning of a dexterous reach task. We show that behavior-induced myelin plasticity is targeted to learning-activated axons and occurs in a staged response across cortical layers in the mouse primary motor cortex. During learning, myelin sheaths retract, which results in lengthening of nodes of Ranvier. Following motor learning, addition of newly formed myelin sheaths increases the number of continuous stretches of myelination. Computational modeling suggests that motor learning-induced myelin plasticity initially slows and subsequently increases axonal conduction speed. Finally, we show that both the magnitude and timing of nodal and myelin dynamics correlate with improvement of behavioral performance during motor learning. Thus, learning-induced and circuit-specific myelination changes may contribute to information encoding in neural circuits during motor learning.
This is a preview of subscription content, access via your institution
Subscribe to Nature+
Get immediate online access to Nature and 55 other Nature journal
Subscribe to Journal
Get full journal access for 1 year
only $6.58 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
All data that support the findings, tools and reagents will be shared on an unrestricted basis; requests should be directed to the corresponding author.
Code for analysis associated with the manuscript is available at https://github.com/EthanHughesLab/Bacmeisteretal2022.
Lillie, R. S. Factors affecting transmission and recovery in the passive iron nerve model. J. Gen. Physiol. 7, 473–507 (1925).
Tomassy, G. S. et al. Distinct profiles of myelin distribution along single axons of pyramidal neurons in the neocortex. Science 344, 319–324 (2014).
Yakovlev, P. & Lecours, A. The myelogenetic cycles of regional maturation of the brain. In Regional Development of the Brain in Early Life (ed. Minkowski, A.) 3–70 (Blackwell Scientific Publications, 1967).
Gibson, E. M. et al. Neuronal activity promotes oligodendrogenesis and adaptive myelination in the mammalian brain. Science 344, 1252304 (2014).
Hughes, E. G., Orthmann-Murphy, J. L., Langseth, A. J. & Bergles, D. E. Myelin remodeling through experience-dependent oligodendrogenesis in the adult somatosensory cortex. Nat. Neurosci. 21, 696–706 (2018).
McKenzie, I. A. et al. Motor skill learning requires active central myelination. Science 346, 318–322 (2014).
Pan, S., Mayoral, S. R., Choi, H. S., Chan, J. R. & Kheirbek, M. A. Preservation of a remote fear memory requires new myelin formation. Nat. Neurosci. 23, 487–499 (2020).
Steadman, P. E. et al. Disruption of oligodendrogenesis impairs memory consolidation in adult mice. Neuron 105, 150–164.e6 (2020).
Hines, J. H., Ravanelli, A. M., Schwindt, R., Scott, E. K. & Appel, B. Neuronal activity biases axon selection for myelination in vivo. Nat. Neurosci. 18, 683–689 (2015).
Mensch, S. et al. Synaptic vesicle release regulates myelin sheath number of individual oligodendrocytes in vivo. Nat. Neurosci. 18, 628–630 (2015).
Mitew, S. et al. Pharmacogenetic stimulation of neuronal activity increases myelination in an axon-specific manner. Nat. Commun. 9, 306 (2018).
Baraban, M., Koudelka, S. & Lyons, D. A. Ca2+ activity signatures of myelin sheath formation and growth in vivo. Nat. Neurosci. 21, 19–23 (2018).
Krasnow, A. M., Ford, M. C., Valdivia, L. E., Wilson, S. W. & Attwell, D. Regulation of developing myelin sheath elongation by oligodendrocyte calcium transients in vivo. Nat. Neurosci. 21, 24–28 (2018).
Seidl, A. H., Rubel, E. W. & Harris, D. M. Mechanisms for adjusting interaural time differences to achieve binaural coincidence detection. J. Neurosci. 30, 70–80 (2010).
Ford, M. C. et al. Tuning of Ranvier node and internode properties in myelinated axons to adjust action potential timing. Nat. Commun. 6, 8073 (2015).
Arancibia-Cárcamo, I. L. et al. Node of Ranvier length as a potential regulator of myelinated axon conduction speed. eLife 6, e23329 (2017).
Salami, M., Itami, C., Tsumoto, T. & Kimura, F. Change of conduction velocity by regional myelination yields constant latency irrespective of distance between thalamus and cortex. Proc. Natl Acad. Sci USA 100, 6174–6179 (2003).
Auer, F., Vagionitis, S. & Czopka, T. Evidence for myelin sheath remodeling in the CNS revealed by in vivo imaging. Curr. Biol. 28, 549–559.e3 (2018).
Bacmeister, C. M. et al. Motor learning promotes remyelination via new and surviving oligodendrocytes. Nat. Neurosci. 23, 819–831 (2020).
Cullen, C. L. et al. Periaxonal and nodal plasticities modulate action potential conduction in the adult mouse brain. Cell Rep. 34, 108641 (2021).
Yang, S. M., Michel, K., Jokhi, V., Nedivi, E. & Arlotta, P. Neuron class–specific responses govern adaptive myelin remodeling in the neocortex. Science 370, eabd2109 (2020).
Bishop, D. et al. Near-infrared branding efficiently correlates light and electron microscopy. Nat. Methods 8, 568–570 (2011).
Bostock, H. & Sears, T. A. The internodal axon membrane: electrical excitability and continuous conduction in segmental demyelination. J. Physiol. 280, 273–301 (1978).
Foster, R. E., Whalen, C. C. & Waxman, S. G. Reorganization of the axon membrane in demyelinated peripheral nerve fibers: morphological evidence. Science 210, 661–663 (1980).
Rasminsky, M. & Sears, T. A. Internodal conduction in undissected demyelinated nerve fibres. J. Physiol. 227, 323–350 (1972).
Coggan, J. S., Prescott, S. A., Bartol, T. M. & Sejnowski, T. J. Imbalance of ionic conductances contributes to diverse symptoms of demyelination. Proc. Natl Acad. Sci. USA 107, 20602–20609 (2010).
Ye, L. et al. Wiring and molecular features of prefrontal ensembles representing distinct experiences. Cell 165, 1776–1788 (2016).
Papale, A. E. & Hooks, B. M. Circuit changes in motor cortex during motor skill learning. Neuroscience 368, 283–297 (2018).
Young, K. M. et al. Oligodendrocyte dynamics in the healthy adult CNS: evidence for myelin remodeling. Neuron 77, 873–885 (2013).
Hill, R. A., Li, A. M. & Grutzendler, J. Lifelong cortical myelin plasticity and age-related degeneration in the live mammalian brain. Nat. Neurosci. 21, 683–695 (2018).
Koudelka, S. et al. Individual neuronal subtypes exhibit diversity in CNS myelination mediated by synaptic vesicle release. Curr. Biol. 26, 1447–1455 (2016).
Bechler, M. E., Byrne, L. & ffrench-Constant, C. CNS myelin sheath lengths are an intrinsic property of oligodendrocytes. Curr. Biol. 25, 2411–2416 (2015).
Swire, M. et al. Oligodendrocyte HCN2 channels regulate myelin sheath length. J. Neurosci. 41, 7954–7964 (2021).
Chong, S. Y. C. et al. Neurite outgrowth inhibitor Nogo-A establishes spatial segregation and extent of oligodendrocyte myelination. Proc. Natl Acad. Sci. USA 109, 1299–1304 (2012).
Dhawale, A. K., Smith, M. A. & Ölveczky, B. P. The role of variability in motor learning. Annu. Rev. Neurosci. 40, 479–498 (2017).
Feldman, D. E. The spike-timing dependence of plasticity. Neuron 75, 556–571 (2012).
Fields, R. D. A new mechanism of nervous system plasticity: activity-dependent myelination. Nat. Rev. Neurosci. 16, 756–767 (2015).
Egger, R. et al. Local axonal conduction shapes the spatiotemporal properties of neural sequences. Cell 183, 537–548.e12 (2020).
de Waegh, S. M., Lee, V. M.-Y. & Brady, S. T. Local modulation of neurofilament phosphorylation, axonal caliber, and slow axonal transport by myelinating Schwann cells. Cell 68, 451–463 (1992).
Fünfschilling, U. et al. Glycolytic oligodendrocytes maintain myelin and long-term axonal integrity. Nature 485, 517–521 (2012).
Moore, S. et al. A role of oligodendrocytes in information processing. Nat. Commun. 11, 5497 (2020).
Harris, J. J. & Attwell, D. The energetics of CNS white matter. J. Neurosci. 32, 356–371 (2012).
Lee, Y. et al. Oligodendroglia metabolically support axons and contribute to neurodegeneration. Nature 487, 443–448 (2012).
Brown, A. M., Tekkök, S. B. & Ransom, B. R. Glycogen regulation and functional role in mouse white matter. J. Physiol. 549, 501–512 (2003).
Trevisiol, A. et al. Structural myelin defects are associated with low axonal ATP levels but rapid recovery from energy deprivation in a mouse model of spastic paraplegia. PLoS Biol. 18, e3000943 (2020).
Stedehouder, J. et al. Fast-spiking parvalbumin interneurons are frequently myelinated in the cerebral cortex of mice and humans. Cereb. Cortex 27, 5001–5013 (2017).
Sasaki, T., Matsuki, N. & Ikegaya, Y. Action-potential modulation during axonal conduction. Science 331, 599–601 (2011).
Kalish, B. T. et al. Single-nucleus RNA sequencing of mouse auditory cortex reveals critical period triggers and brakes. Proc. Natl Acad. Sci. USA 117, 11744–11752 (2020).
Cichon, J. & Gan, W.-B. Branch-specific dendritic Ca2+ spikes cause persistent synaptic plasticity. Nature 520, 180–185 (2015).
Fu, M., Yu, X., Lu, J. & Zuo, Y. Repetitive motor learning induces coordinated formation of clustered dendritic spines in vivo. Nature 483, 92–95 (2012).
Stedehouder, J., Brizee, D., Shpak, G. & Kushner, S. A. Activity-dependent myelination of parvalbumin interneurons mediated by axonal morphological plasticity. J. Neurosci. 38, 3631–3642 (2018).
Bramow, S. et al. Demyelination versus remyelination in progressive multiple sclerosis. Brain 133, 2983–2998 (2010).
Patrikios, P. et al. Remyelination is extensive in a subset of multiple sclerosis patients. Brain 129, 3165–3172 (2006).
Goldschmidt, T., Antel, J., König, F. B., Brück, W. & Kuhlmann, T. Remyelination capacity of the MS brain decreases with disease chronicity. Neurology 72, 1914–1921 (2009).
Snaidero, N. et al. Myelin replacement triggered by single-cell demyelination in mouse cortex. Nat. Commun. 11, 4901 (2020).
Orthmann-Murphy, J. et al. Remyelination alters the pattern of myelin in the cerebral cortex. eLife 9, e56621 (2020).
Hughes, E. G., Kang, S. H., Fukaya, M. & Bergles, D. E. Oligodendrocyte progenitors balance growth with self-repulsion to achieve homeostasis in the adult brain. Nat. Neurosci. 16, 668–676 (2013).
Xu, T. et al. Rapid formation and selective stabilization of synapses for enduring motor memories. Nature 462, 915–919 (2009).
Hines, M. L. & Carnevale, N. T. The NEURON Simulation Environment. Neural Comput. 9, 1179–1209 (1997).
Cohen, C. C. H. et al. Saltatory conduction along myelinated axons involves a periaxonal nanocircuit. Cell 180, 311–322.e15 (2020).
Hu, W. et al. Distinct contributions of Nav1.6 and Nav1.2 in action potential initiation and backpropagation. Nat. Neurosci. 12, 996–1002 (2009).
Mainen, Z. F., Joerges, J., Huguenard, J. R. & Sejnowski, T. J. A model of spike initiation in neocortical pyramidal neurons. Neuron 15, 1427–1439 (1995).
Hodgkin, A. L. & Huxley, A. F. A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 117, 500–544 (1952).
Huguenard, J. R., Hamill, O. P. & Prince, D. A. Developmental changes in Na+ conductances in rat neocortical neurons: appearance of a slowly inactivating component. J. Neurophysiol. 59, 778–795 (1988).
Hamill, O. P., Huguenard, J. R. & Prince, D. A. Patch-clamp studies of voltage-gated currents in identified neurons of the rat cerebral cortex. Cereb. Cortex 1, 48–61 (1991).
We thank M. Hall for machining expertise, H. Barr for the conversation that reinitiated interest in labeling activated axons, and past and current members of the Hughes and Welle labs and the CU Anschutz Myelin Group for discussions. M.A.T. is supported by the National Institutes of Health Institutional Neuroscience Graduate Training Grant (5T32NS099042-17). Funding was provided by the Boettcher Foundation Webb-Waring Biomedical Research Award, the Whitehall Foundation and the National Multiple Sclerosis Society (RG-1701–26733) and NINDS (NS115975, NS125230) to E.G.H.
The authors declare no competing interests.
Peer review information
Nature Neuroscience thanks Michelle Monje and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Near-infrared branding identifies the same oligodendrocytes and myelin sheaths in longitudinally, in vivo imaged areas and posthoc stained tissue.
a, The same field of view imaged in vivo (‘Live Tissue’, left) and in fixed, sectioned, and stained tissue (‘Fixed Tissue’, right). Patterns of cell bodies (examples outlined in white dotted lines) were maintained across live and processed tissue. Note the new oligodendrocyte generated at 60d and delineated with a white arrowhead. b, A newly generated oligodendrocyte in vivo (‘Live Tissue’, left) and fixed, sectioned tissue (‘Fixed Tissue’, right) stained for oligodendrocytes and myelin (GFP, green) and axons (NFH, magenta). Note the same T-junction across live and fixed samples is marked with the white arrowhead.
a, Illustration of forelimb reach training box environment. Mice learn to reach by extending their left hand through a slit in a plexiglass box to grab a pellet and return it to their mouth. b, Imaging and training timelines for untrained (top) and learning (bottom) mice. c, The majority of mice learn to perform the forelimb reach task (learners, green). Learners improve their success rate gradually over the course of seven days of training. In contrast, non-learners maintain a low success rate across time and do not attain higher than a 15% success rate at the end of the training regimen (purple). d, Successful learners of the task perform significantly better on the last day of training (Paired Student’s t-test, t(15)=11.72, p < 0.0001) and achieve higher than 15% success rate, in contrast to non-learners which do not improve significantly and do not attain above 15% success on the last day of training. Mice were excluded from data analysis if they did not succeed in at least 10% of reaches across the seven days of training (n = 2 mice). e, f, Breakdown of all mice included in each of the figures, where each dot is a unique color that represents a single mouse and is consistent across graphs. Neither success rate (e) nor change in success rate (f) differ across figures (REML with post hoc Tukey’s HSD). Bars and error bars represent mean ± s.e.m unless otherwise noted. For detailed statistics, see Supplementary Table 3.
a, The same node in live imaged (‘Live Tissue’, left) and fixed, sectioned tissue (‘Fixed Tissue’, right) stained for oligodendrocytes and myelin (GFP, green), sodium channels (NaV, magenta), and axons (NFH, yellow). White arrow points to node across time and in fixed tissue. b,c, 90.90 ± 3.73% of nodes visualized in vivo possess NaV staining characteristic of nodes of Ranvier (b, c), comparable to values of nodes identified fixed tissue of age-matched controls (c; random sample, nmice = 6; longitudinally imaged, nmice = 3). d, No difference in the proportion of gaps in myelination (larger than 3 microns) with and without appreciable sodium channel distributions in fixed tissue of age-matched controls (nmice = 8; Paired Student’s t-test). e, Representative in vivo imaging and post hoc immunostaining of a lengthening node with sodium channels (left) and without appreciable sodium channels (right). f, The same node confirmed with NaV staining in (a) is identified in live imaging by a marked decrease in autofluorescence between two GFP-labeled myelin paranodes. g, Axon morphology is accurately identified in vivo as confirmed by post hoc immunostaining of the same tissue. A lengthening node in vivo (‘Live Tissue’, left) and fixed, sectioned tissue (‘Fixed Tissue’, middle). Axon trajectory is identified using the shape of the myelin sheath prior to node lengthening (‘Live axon morphology’, magenta) and confirmed using post hoc immunostaining of the same sheaths for axons (NFH, magenta) and myelin (GFP, green) and reconstructions of the axons (‘Fixed axon morphology’, magenta). In vivo node morphology (‘In vivo nodal morphology’, top right) is reconstructed and confirmed using post hoc immunostaining and morphological reconstruction (‘Fixed nodal morphology’, bottom right). h, Sheath length and change in sheath length is determined by aligning fields of view using fiduciary marks (for example cell soma) which extend across the entire duration of the study, including pre-existing oligodendrocytes, which maintain their position throughout the course of imaging (left). Change in sheath length is mirrored by a change in paranode position (right). To determine the change in sheath length, the distance between the initial and final paranodal position is traced using Simple Neurite Tracer and overlayed stacks. Bars and error bars represent mean ± s.e.m unless otherwise noted. For detailed statistics, see Supplementary Table 3.
a, Sheath length is similar across sheaths with 2, 1, or 0 neighbors. b, Sheaths of many ages initiate sheath dynamics in young adult mice. c, Proportion of dynamic sheaths engaging in growth three weeks before learning, during learning (one week), and in the two weeks after learning. d, Proportion of dynamic sheaths engaging in retraction before, during and after learning. Learning modulates sheath retraction (F2,14 = 6.76, p = 0.0088). During learning, more sheaths retract relative to untrained mice (p = 0.0095; Tukey’s HSD) and relative to prelearning values in trained mice (p = 0.016; Tukey’s HSD). Two weeks after learning, more sheaths retract relative to prelearning values in trained mice (p = 0.0358; Tukey’s HSD). e, In learning mice, there are fewer stable sheaths with 2 (p = 0.013, t(5.91)=3.49), 1 (p = 0.0089, t(2.47)=7.62), and 0 neighbors (p = 0.043, t(2.04)=4.55). f, In learning mice, there are more growing sheaths with 1 neighbor (p = 0.0071, t(6.00)=−4.00). g, In learning mice, there are more retracting sheaths with 2 (p = 0.024, t(4.00)=−3.62) and 1 neighbors (p = 0.0050, t(6.00)=−4.31). h, Nodes and gaps in myelin that shorten are not modulated by learning (REML with post hoc Tukey’s HSD). Bars and error bars represent mean ± s.e.m unless otherwise noted. For detailed statistics, see Supplementary Table 3.
a, Maximum projection of a cFos+ neuron (AAv8-cFos-ER, red) and surrounding oligodendrocytes and myelin (in vivo, green) (top). Single slice at 159 microns below the pial surface, with white arrow identifying unmyelinated region of a cFos+ axon (middle). Single slice at 185 microns below the pial surface, with pink arrow identifying a myelinated region of a cFos+ axon (bottom). b, 3D projection of the cFos+ neuron and associated myelin sheaths from (a), with dashed lines corresponding to the single slices in (a). c, The same neuron as in (a), reconstructed using Simple Neurite Tracer. d, 3D projection of a longitudinally imaged axon with node lengthening and sheath retraction at the outset of the imaging experiment (0d) and at the final imaging timepoint (88d).
a, Average pre-existing myelin sheath length per mouse (nmice = 4). b, Mean node length of lengthening nodes per mouse, measured across time in prelearning, learning, and postlearning stages (nmice = 3). c, Distribution of the number of consecutive lengthening nodes along a single axon. d-g, Modeled change in conduction speed as a function of the number of consecutively remodeled nodes at different sodium:leak conductance ratios (node with = 35 microns, pink exponential fit; Chi-square goodness of fit test). Conductance ratios were generated using either 0.4 S/cm2 (low) or 3.4 S/cm2 (high) for sodium conductance (gNa) and either 0.01 S/cm2 (low) or 0.08 S/cm2 (high) for leak conductance (gL). h, Length of unmyelinated axon segment that received new sheath addition following learning, measured from one sheath to the nearest neighboring sheath (nmice = 6; box plot, white bar = median, bounds of rectangle are Q1 and Q3; whiskers reflect minima and maxima). i, Proportion of gaps filled by 1, 2, or 3 sheaths following learning. j, Modeled change in conduction speed as a function of proportion of a 184 micron gap filled in by new myelin (pink exponential fit; Chi-square goodness of fit test). Conductance ratios as in d-g. Bars and error bars represent mean ± s.e.m unless otherwise noted.
a, Maximum projection of motor cortex injected with the cFos virus 1 day before learning (−1d), one week after learning (7d), three weeks after learning (22d), and 5 weeks after learning (42d). 4-OHT was injected 3 hours after the final day of learning (7d). b, Fit curve for modeled change in cFos+ cell gain (calculated as % of tamoxifen-independent cFos+ neurons, that is the number of neurons labeled at 60 days) in mice that learn and receive tamoxifen (pink), untrained mice (gray), and mice that learn and are injected with sunflower oil (red). Each dot represents proportion of labeled neurons per mouse at a given timepoint. Shading represents 95% confidence interval. c, Rate of cFos+ cell gain in mice that learn and receive tamoxifen (pink), untrained mice (grey), and mice that learn and are injected with sunflower oil (red). Mice that learn have a heightened rate of cFos+ cell gain in the two weeks following learning, while the percentage of cFos+ neurons did not change in untrained mice and oil injected mice over the course of the experiment. Lines and shading represent mean ± s.e.m. Light pink lines in background represent individual learning mice. d, Significantly more cFos+ cells appear in L2/3 relative to L1 following learning and injection of tamoxifen. e, The majority of learning-activated cells are putative L2/3 pyramidal neurons (determined by morphology). f, Distribution of traced axon lengths for cFos+ neurons (nmice = 5; box plot, white bar = median, bounds of rectangle are Q1 and Q3; whiskers reflect minima and maxima). Bars and error bars represent mean ± s.e.m unless otherwise noted. For detailed statistics, see Supplementary Table 3.
About this article
Cite this article
Bacmeister, C.M., Huang, R., Osso, L.A. et al. Motor learning drives dynamic patterns of intermittent myelination on learning-activated axons. Nat Neurosci 25, 1300–1313 (2022). https://doi.org/10.1038/s41593-022-01169-4