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Homeostatic coordination and up-regulation of neural activity by activity-dependent myelination

Abstract

Activity-dependent myelination (ADM) is a fundamental dimension of brain plasticity through which myelin changes as a function of neural activity. Mediated by structural changes in glia, ADM notably regulates axonal conduction velocity. Yet, it remains unclear how neural activity impacts myelination to orchestrate the timing of neural signalling, and how ADM shapes neural activity. We developed a model of spiking neurons enhanced with neuron–oligodendrocyte feedback and examined the relationship between ADM and neural activity. We found that ADM implements a homeostatic gain control mechanism that enhances neural firing rates and correlations through the temporal coordination of action potentials as axon lengths increase. Stimuli engage ADM plasticity to trigger bidirectional and reversible changes in conduction delays, as may occur during learning. Furthermore, ADM was found to enhance information transmission under various types of time-varying stimuli. These results highlight the role of ADM in shaping neural activity and communication.

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Fig. 1: ADM plasticity model.
Fig. 2: Effect of ADM on neural activity.
Fig. 3: Up-regulation of neural activity through changes in network geometry.
Fig. 4: Bidirectional control of axonal CVs and delays by stimuli.
Fig. 5: Enhanced information transmission.

Data availability

Source data for Figs. 15 are available with this manuscript, via ref. 57 and publicly available on GitHub at https://github.com/Jeremie-Lefebvre/Talidou-et-al.-Nat-Comp-Sci-2022.

Code availability

Source codes for all results reported in this study are available with this manuscript via ref. 57 and publicly available on GitHub at https://github.com/Jeremie-Lefebvre/Talidou-et-al.-Nat-Comp-Sci-2022.

References

  1. Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O. & Kötter, R. Key role of coupling, delay, and noise in resting brain fluctuations. Proc. Natl Acad. Sci. USA 106, 10302–10307 (2009).

    Article  Google Scholar 

  2. Dhamala, M., Jirsa, V. K. & Ding, M. Enhancement of neural synchrony by time delay. Phys. Rev. Lett. 92, 074104 (2004).

    Article  Google Scholar 

  3. Cabral, J., Hugues, E., Sporns, O. & Deco, G. Role of local network oscillations in resting state functional connectivity. Neuroimage 57, 130–139 (2011).

    Article  Google Scholar 

  4. Cabral, J., Hugues, E., Kringelbach, M. L. & Deco, G. Modeling the outcome of structural disconnection on resting-state functional connectivity. Neuroimage 62, 1342–1353 (2012).

    Article  Google Scholar 

  5. Gibson, E. M. et al. Neuronal activity promotes oligodendrogenesis and adaptive myelination in the mammalian brain. Science 344, 1252304 (2014).

    Article  Google Scholar 

  6. Cullen, C. L. et al. Periaxonal and nodal plasticities modulate action potential conduction in the adult mouse brain. Cell Rep. 34, 108641 (2021).

    Article  Google Scholar 

  7. Xin, W. & Chan, J. R. Myelin plasticity: sculpting circuits in learning and memory. Nat. Rev. Neurosci. 21, 682–694 (2020).

    Article  Google Scholar 

  8. Steadman, P. E. et al. Disruption of oligodendrogenesis impairs memory consolidation in adult mice. Neuron 105, 150–164 (2020).

    Article  Google Scholar 

  9. 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).

    Article  Google Scholar 

  10. Stedehouder, J. et al. Local axonal morphology guides the topography of interneuron myelination in mouse and human neocortex. Elife 8, e48615 (2019).

    Article  Google Scholar 

  11. 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).

    Article  Google Scholar 

  12. Auer, F., Vagionitis, S. & Czopka, T. Evidence for myelin sheath remodeling in the CNS revealed by in vivo imaging. Curr. Biol. 28, 549–559 (2018).

    Article  Google Scholar 

  13. Young, K. M. et al. Oligodendrocyte dynamics in the healthy adult CNS: evidence for myelin remodeling. Neuron 77, 873–885 (2013).

    Article  Google Scholar 

  14. Bells, S. et al. Changes in white matter microstructure impact cognition by disrupting the ability of neural assemblies to synchronize. J. Neurosci. 37, 8227–8238 (2017).

    Article  Google Scholar 

  15. Scholz, J., Klein, M. C., Behrens, T. E. J. & Johansen-Berg, H. Training induces changes in white-matter architecture. Nat. Neurosci. 12, 1370–1371 (2009).

    Article  Google Scholar 

  16. Noori, R. et al. Activity-dependent myelination: a glial mechanism of oscillatory self-organization in large-scale brain networks. Proc. Natl Acad. Sci. USA 117, 13227–13237 (2020).

    Article  Google Scholar 

  17. Liu, J. et al. Impaired adult myelination in the prefrontal cortex of socially isolated mice. Nat. Neurosci. 15, 1621–1623 (2012).

    Article  Google Scholar 

  18. Makinodan, M., Rosen, K. M., Ito, S. & Corfas, G. A critical period for social experience-dependent oligodendrocyte maturation and myelination. Science 337, 1357–1360 (2012).

    Article  Google Scholar 

  19. Dutta, D. J. et al. Regulation of myelin structure and conduction velocity by perinodal astrocytes. Proc. Natl Acad. Sci. USA 115, 11832–11837 (2018).

    Article  Google Scholar 

  20. Kato, D., Wake, H. & Lee, P. R. et al. Motor learning requires myelination to reduce asynchrony and spontaneity in neural activity. Glia 68, 193–210 (2020).

    Article  Google Scholar 

  21. Cheng, S. M. & Carr, C. E. Functional delay of myelination of auditory delay lines in the nucleus laminaris of the barn owl. Dev. Neurobiol. 67, 1957–1974 (2007).

    Article  Google Scholar 

  22. 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).

    Article  Google Scholar 

  23. Tomassy, G. S. et al. Distinct profiles of myelin distribution along single axons of pyramidal neurons in the neocortex. Science 344, 319–324 (2014).

    Article  Google Scholar 

  24. Morrison, A., Diesmann, M. & Gerstner, W. Phenomenological models of synaptic plasticity based on spike timing. Biol. Cybern. 98, 459–478 (2008).

    Article  MathSciNet  MATH  Google Scholar 

  25. Seidl, A. H. Regulation of conduction time along axons. Neuroscience 276, 126–134 (2014).

    Article  Google Scholar 

  26. Aboitiz, F., Morales, D. & Montiel, J. The evolutionary origin of the mammalian isocortex: towards an integrated developmental and functional approach. Behav. Brain Sci. 26, 535–552 (2003).

    Article  Google Scholar 

  27. Ma, Z., Turrigiano, G. G., Wessel, R. & Hengen, K. B. Cortical circuit dynamics are homeostatically tuned to criticality in vivo. Neuron 104, 655–664 (2019).

    Article  Google Scholar 

  28. Atay, F. M. Distributed delays facilitate amplitude death of coupled oscillators. Phys. Rev. Lett. 91, 94101 (2003).

    Article  Google Scholar 

  29. McNamara, B. & Wiesenfeld, K. Theory of stochastic resonance. Phys. Rev. A 39, 4854–4869 (1989).

    Article  Google Scholar 

  30. Frank, T. D. Delay Fokker–Planck equations, perturbation theory, and data analysis for nonlinear stochastic systems with time delays. Phys. Rev. E 71, 031106 (2005).

    Article  Google Scholar 

  31. Frank, T. D. Kramers–Moyal expansion for stochastic differential equations with single and multiple delays: applications to financial physics and neurophysics. Phys. Lett. A 360, 552–562 (2007).

    Article  MATH  Google Scholar 

  32. Turrigiano, G. Homeostatic synaptic plasticity: local and global mechanisms for stabilizing neuronal function. Cold Spring Harb. Perspect. Biol. 4, a005736 (2012).

    Article  Google Scholar 

  33. Tien, N. W. & Kerschensteiner, D. Homeostatic plasticity in neural development. Neural Dev 13, 9 (2018).

    Article  Google Scholar 

  34. Zohary, E., Shadlen, M. N. & Newsome, W. T. Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370, 140–143 (1994).

    Article  Google Scholar 

  35. Vyazovskiy, V. V., Olcese, U. & Lazimy, Y. M. et al. Cortical firing and sleep homeostasis. Neuron 63, 865–878 (2009).

    Article  Google Scholar 

  36. Uhlhaas, P. J. & Wolf, S. Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52, 155–168 (2006).

    Article  Google Scholar 

  37. Knowles, J. K., Xu, H. & Soane, C. et al. Maladaptive myelination promotes generalized epilepsy progression. Nat. Neurosci. 25, 596–606 (2022).

    Article  Google Scholar 

  38. Tan, A. Y., Chen, Y., Scholl, B., Seidemann, E. & Priebe, N. J. Sensory stimulation shifts visual cortex from synchronous to asynchronous states. Nature 509, 226–229 (2014).

    Article  Google Scholar 

  39. Beggs, J., Timme, N., Being critical of criticality in the brain. Front. Physiol. 3: 163 (2012).

  40. van Vreeswijk, C. & Sompolinsky, H. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274, 1724–1726 (1996).

    Article  Google Scholar 

  41. Isaacson, J. S. & Scanziani, M. How inhibition shapes cortical activity. Neuron 72, 231–43 (2011).

    Article  Google Scholar 

  42. Bialek, W., de Ruyter van Steveninck, R.R., Rieke, F. & Warland, D. Spikes: Exploring the Neural Code (MIT Press, 1996).

  43. de Ruyter van Steveninck, R. R., Lewen, G. D., Strong, S. P., Koberle, R. & Bialek, W. Reproducibility and variability in neural spike trains. Science 275, 1805–1808 (1997).

    Article  Google Scholar 

  44. Mount, C. W. & Monje, M. Wrapped to adapt: experience-dependent myelination. Neuron 95, 743–756 (2017).

    Article  Google Scholar 

  45. Fields, R. D. A new mechanism of nervous system plasticity: activity-dependent myelination. Nat. Rev. Neurosci. 16, 756–767 (2015).

    Article  Google Scholar 

  46. Watt, A. J. & Desai, N. S. Homeostatic plasticity and STDP: keeping a neuronas cool in a fluctuating world. Front. Synaptic Neurosci. 2, 5 (2010).

    Article  Google Scholar 

  47. Almeida, R. G. & Lyons, D. A. On myelinated axon plasticity and neuronal circuit formation and function. J. Neurosci. 37, 10023–10034 (2017).

    Article  Google Scholar 

  48. Klingseisen, A. & Lyons, D. A. Axonal regulation of central nervous system myelination: structure and function. Neuroscientist 24, 7–21 (2018).

    Article  Google Scholar 

  49. Shadlen, M. N. & Newsome, W. T. The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J. Neurosci. 18, 3870–3896 (1998).

    Article  Google Scholar 

  50. Hebb D. O. The Organization of Behavior (Wiley, 1949).

  51. Lefebvre, J., Hutt, A., Knebel, J. F., Whittingstall, K. & Murray, M. M. Stimulus statistics shape oscillations in nonlinear recurrent neural networks. J. Neurosci. 35, 2895–2903 (2015).

    Article  Google Scholar 

  52. Hutt, A., Mierau, A. & Lefebvre, J. Dynamic control of synchronous activity in networks of spiking neurons. PLoS ONE 11, e0161488 (2016).

    Article  Google Scholar 

  53. Horsthemke, W., & Lefever, R., Noise-Induced Transitions: Theory and Applications in Physics, Chemistry, and Biology (Springer, 1984).

  54. Tchumatchenko, T., Malyshev, A., Geisel, T., Volgushev, M. & Wolf, F. Correlations and synchrony in threshold neuron models. Phys. Rev. Lett. 104, 058102 (2010).

    Article  Google Scholar 

  55. T. Tchumatchenko, T. Geisel, M. Volgushev, and F. Wolf, Spike correlations – what can they tell about synchrony? Front. Neurosci. 5: 68 (2011).

  56. C., Laing, & G. J. Lord, Stochastic Methods in Neuroscience (Oxford, 2009).

  57. Talidou, A., Frankland, P.W., Mabbott, D., & Lefebvre, J. Homeostatic coordination and up-regulation of neural activity by activity-dependent myelination. Zenodo https://doi.org/10.5281/zenodo.6943969 (2022)

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Acknowledgements

We thank the National Research Council of Canada (NSERC grant RGPIN-2017-06662, J.L.) as well as the Canadian Institute of Health Research (CIHR grant NO PJT-156164, P.W.F., D.M. and J.L.) for funding.

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J.L. designed the study. J.L. and A.T. performed the mathematical derivations and simulations. J.L., A.T., P.W.F. and D.M. wrote the manuscript.

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Correspondence to Afroditi Talidou.

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Nature Computational Science thanks Maurice Chacron, Thomas R. Knösche and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Handling editor: Ananya Rastogi, in collaboration with the Nature Computational Science team.

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Talidou, A., Frankland, P.W., Mabbott, D. et al. Homeostatic coordination and up-regulation of neural activity by activity-dependent myelination. Nat Comput Sci 2, 665–676 (2022). https://doi.org/10.1038/s43588-022-00315-z

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