Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Long-range axon branching: contributions to brain network plasticity and repair

Nature Reviews Neuroscience volume 27, pages 243–259 (2026)Cite this article

Subjects

Abstract

Brain function requires exquisitely adapted plasticity at multiple scales, from synapses to whole-brain networks. Evidence for large-scale plasticity in functional brain networks comes from neuroimaging data across a variety of species, particularly during development and following injury. However, how large-scale network remodelling is achieved at the microscopic level is unknown as the growth of entirely new long-distance axons is unlikely to occur. Recent insights from electron microscopic connectome studies and single-cell projectomes of neurons in the brains of multiple model organisms have provided new evidence for the incredible structural complexity of axons and their branches that traverse the brain. This evidence shows highly arborized axonal projections, differentially myelinated branches of the same axon, and axonal regions devoid of synaptic contacts but with the potential to form synaptic connections in new or additional areas. Recent electron microscopic data suggest that these axonal features may be evolutionarily conserved. Here we consider whether these features could enable long-range and large-scale neuroplastic changes at a functional level, particularly following focal brain injury. These insights contribute to our emerging understanding of how the brain undergoes large-scale reorganization to adapt to changing circumstances.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Projectome mapping highlights diverse and variable long-range axonal projections across multiple brain regions.
Fig. 2: Examples of axonal complexity, connectivity and plasticity across species revealed by connectomic approaches.
Fig. 3: Long-range axons provide a substrate for functional brain network connectivity.
Fig. 4: Poststroke plasticity facilitated by short axonal branch extension.

Similar content being viewed by others

References

  1. Innocenti, G. M. Defining neuroplasticity. Handb. Clin. Neurol. 184, 3–18 (2022).

    Article  PubMed  Google Scholar 

  2. Merzenich, M. M., Van Vleet, T. M. & Nahum, M. Brain plasticity-based therapeutics. Front. Hum. Neurosci. 8, 385 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Carmichael, S. T. et al. Molecular, cellular and functional events in axonal sprouting after stroke. Exp. Neurol. 287, 384–394 (2017).

    Article  CAS  PubMed  Google Scholar 

  4. Blizzard, C. A. et al. Focal damage to the adult rat neocortex induces wound healing accompanied by axonal sprouting and dendritic structural plasticity. Cereb. Cortex 21, 281–291 (2010).

    Article  PubMed  Google Scholar 

  5. Sporns, O., Tononi, G. & Kötter, R. The human connectome: a structural description of the human brain. PLoS Comput. Biol. 1, e42 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Citri, A. & Malenka, R. C. Synaptic plasticity: multiple forms, functions, and mechanisms. Neuropsychopharmacology 33, 18–41 (2008).

    Article  PubMed  Google Scholar 

  7. Gouwens, N. W. et al. Classification of electrophysiological and morphological neuron types in the mouse visual cortex. Nat. Neurosci. 22, 1182–1195 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ascoli, G. A., Donohue, D. E. & Halavi, M. Neuromorpho.org: a central resource for neuronal morphologies. J. Neurosci. 27, 9247–9251 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Barzó, P. et al. Electrophysiology and morphology of human cortical supragranular pyramidal cells in a wide age range. Elife 13, RP100390 (2025).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Scala, F. et al. Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas. Nat. Commun. 10, 4174 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Rubio-Teves, M. et al. Benchmarking of tools for axon length measurement in individually-labeled projection neurons. PLoS Comput. Biol. 17, e1009051 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Köbbert, C. et al. Current concepts in neuroanatomical tracing. Prog. Neurobiol. 62, 327–351 (2000).

    Article  PubMed  Google Scholar 

  13. Wang, Q. & Burkhalter, A. Area map of mouse visual cortex. J. Comp. Neurol. 502, 339–357 (2007).

    Article  PubMed  Google Scholar 

  14. Luo, W. et al. Supernova: a versatile vector system for single-cell labeling and gene function studies in vivo. Sci. Rep. 6, 35747 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Peng, H. et al. Morphological diversity of single neurons in molecularly defined cell types. Nature 598, 174–181 (2021). This study systematically examines single-neuron morphologies of 1,741 individual neurons in the mouse brain reveals that the long-range axonal projections are incredibly diverse, even within the same molecularly defined cell type.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Liu, Y. et al. Neuronal diversity and stereotypy at multiple scales through whole brain morphometry. Nat. Commun. 15, 10269 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Jiang, S. et al. Petabyte-scale multi-morphometry of single neurons for whole brains. Neuroinformatics 20, 525–536 (2022).

    Article  PubMed  Google Scholar 

  18. Yuan, L. et al. Massive multiplexing of spatially resolved single neuron projections with axonal BARseq. Nat. Commun. 15, 8371 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Swanson, L. W. & Lichtman, J. W. From cajal to connectome and beyond. Annu. Rev. Neurosci. 39, 197–216 (2016).

    Article  CAS  PubMed  Google Scholar 

  20. Rozo, J. A., Martínez-Gallego, I. & Rodríguez-Moreno, A. Cajal, the neuronal theory and the idea of brain plasticity. Front. Neuroanat. 18, 1331666 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Lendvai, B. et al. Experience-dependent plasticity of dendritic spines in the developing rat barrel cortex in vivo. Nature 404, 876–881 (2000).

    Article  CAS  PubMed  Google Scholar 

  22. Lee, K. W. et al. Cocaine-induced dendritic spine formation in D1 and D2 dopamine receptor-containing medium spiny neurons in nucleus accumbens. Proc. Natl Acad. Sci. USA 103, 3399–3404 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Forrest, M. P., Parnell, E. & Penzes, P. Dendritic structural plasticity and neuropsychiatric disease. Nat. Rev. Neurosci. 19, 215–234 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Heilingoetter, C. L. & Jensen, M. B. Histological methods for ex vivo axon tracing: a systematic review. Neurol. Res. 38, 561–569 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Saper, C. B., Loewy, A. D. & Swanson, L. W. Commentary on: Saper C.B., Loewy A.D., Swanson L.W., Cowan W.M. (1976) Direct hypothalamo-autonomic connections. Brain Res. 117, 305–312. Brain Res. 1645, 12–14 (2016).

    Article  CAS  PubMed  Google Scholar 

  26. Lanciego, J. L. & Wouterlood, F. G. A half century of experimental neuroanatomical tracing. J. Chem. Neuroanat. 42, 157–183 (2011).

    Article  PubMed  Google Scholar 

  27. Zeng, H. Mesoscale connectomics. Curr. Opin. Neurobiol. 50, 154–162 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kawaguchi, Y., Wilson, C. J. & Emson, P. C. Projection subtypes of rat neostriatal matrix cells revealed by intracellular injection of biocytin. J. Neurosci. 10, 3421–3438 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wittner, L. et al. Three-dimensional reconstruction of the axon arbor of a CA3 pyramidal cell recorded and filled in vivo. Brain Struct. Funct. 212, 75–83 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kuramoto, E. et al. Two types of thalamocortical projections from the motor thalamic nuclei of the rat: a single neuron-tracing study using viral vectors. Cereb. Cortex 19, 2065–2077 (2009).

    Article  PubMed  Google Scholar 

  31. Ghosh, S. et al. Sensory maps in the olfactory cortex defined by long-range viral tracing of single neurons. Nature 472, 217–220 (2011).

    Article  CAS  PubMed  Google Scholar 

  32. Kita, T. & Kita, H. The subthalamic nucleus is one of multiple innervation sites for long-range corticofugal axons: a single-axon tracing study in the rat. J. Neurosci. 32, 5990–5999 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Ohno, S. et al. A morphological analysis of thalamocortical axon fibers of rat posterior thalamic nuclei: a single neuron tracing study with viral vectors. Cereb. Cortex 22, 2840–2857 (2012).

    Article  PubMed  Google Scholar 

  34. Economo, M. N. et al. A platform for brain-wide imaging and reconstruction of individual neurons. eLife 5, e10566 (2016). This study demonstrates a breakthrough platform that images and reconstructs the complete three-dimensional structure of individual neurons across the entire mouse brain.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Gong, H. et al. High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level. Nat. Commun. 7, 12142 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Seiriki, K. et al. High-speed and scalable whole-brain imaging in rodents and primates. Neuron 94, 1085–1100.e6 (2017).

    Article  CAS  PubMed  Google Scholar 

  37. Li, A. et al. Micro-optical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330, 1404–1408 (2010).

    Article  CAS  PubMed  Google Scholar 

  38. Gao, L. et al. Single-neuron projectome of mouse prefrontal cortex. Nat. Neurosci. 25, 515–529 (2022).

    Article  CAS  PubMed  Google Scholar 

  39. Fei, Y. et al. Diverse and asymmetric patterns of single-neuron projectome in regulating interhemispheric connectivity. Nat. Commun. 15, 3403 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Yao, M. et al. Long-range connectome of pyramidal neurons in the sensorimotor cortex. iScience 26, 106316 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Qiu, S. et al. Whole-brain spatial organization of hippocampal single-neuron projectomes. Science 383, eadj9198 (2024). A massive single-cell atlas of over 10,000 long-range axons elucidates the key organizational principles of the brain-wide connectivity of mouse hippocampal neurons.

    Article  CAS  PubMed  Google Scholar 

  42. Liu, Y. et al. Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices. eLife 13, RP97602 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Swanson, L. W., Hahn, J. D. & Sporns, O. Neural network architecture of a mammalian brain. Proc. Natl Acad. Sci. USA 121, e2413422121 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Kasthuri, N. et al. Saturated reconstruction of a volume of neocortex. Cell 162, 648–661 (2015).

    Article  CAS  PubMed  Google Scholar 

  45. Schmidt, H. et al. Axonal synapse sorting in medial entorhinal cortex. Nature 549, 469–475 (2017).

    Article  PubMed  Google Scholar 

  46. Winding, M. et al. The connectome of an insect brain. Science 379, eadd9330 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Scheffer, L. K. et al. A connectome and analysis of the adult Drosophila central brain. eLife 9, e57443 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Shapson-Coe, A. et al. A petavoxel fragment of human cerebral cortex reconstructed at nanoscale resolution. Science 384, eadk4858 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Dorkenwald, S. et al. Neuronal wiring diagram of an adult brain. Nature 634, 124–138 (2024). This work provides a first complete, synaptic-resolution wiring diagram of an entire insect brain that enables a systematic analysis of how long-range axons support information flows from sensory input to motor output through both global and local circuits.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Lin, A. et al. Network statistics of the whole-brain connectome of Drosophila. Nature 634, 153–165 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Loomba, S. et al. Connectomic comparison of mouse and human cortex. Science 377, eabo0924 (2022).

    Article  CAS  PubMed  Google Scholar 

  52. Lynn, C. W., Holmes, C. M. & Palmer, S. E. Heavy-tailed neuronal connectivity arises from Hebbian self-organization. Nat. Phys. 20, 484–491 (2024).

    Article  CAS  Google Scholar 

  53. White, J. G. et al. The structure of the nervous system of the nematode Caenorhabditis elegans. Philos. Trans. R. Soc. Lond. B 314, 1–340 (1986).

    Article  CAS  Google Scholar 

  54. Varshney, L. R. et al. Structural properties of the Caenorhabditis elegans neuronal network. PLoS Comput. Biol. 7, e1001066 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Helmstaedter, M. et al. Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500, 168–174 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Braitenberg, V. & Schüz, A. Cortex: Statistics and Geometry of Neuronal Connectivity (Springer, 2013).

  57. Motta, A. et al. Dense connectomic reconstruction in layer 4 of the somatosensory cortex. Science 366, eaay3134 (2019).

    Article  CAS  PubMed  Google Scholar 

  58. Aransay, A. et al. Long-range projection neurons of the mouse ventral tegmental area: a single-cell axon tracing analysis. Front. Neuroanat. 9, 59 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Rodríguez-López, C., Clascá, F. & Prensa, L. The mesoaccumbens pathway: a retrograde labeling and single-cell axon tracing analysis in the mouse. Front. Neuroanat. 11, 25 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Wildenberg, G. et al. Partial connectomes of labeled dopaminergic circuits reveal non-synaptic communication and axonal remodeling after exposure to cocaine. eLife 10, e71981 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Holtmaat, A. & Svoboda, K. Experience-dependent structural synaptic plasticity in the mammalian brain. Nat. Rev. Neurosci. 10, 647–658 (2009).

    Article  CAS  PubMed  Google Scholar 

  62. Caroni, P., Donato, F. & Muller, D. Structural plasticity upon learning: regulation and functions. Nat. Rev. Neurosci. 13, 478–490 (2012).

    Article  CAS  PubMed  Google Scholar 

  63. Johnson, C. M. et al. Rule learning enhances structural plasticity of long-range axons in frontal cortex. Nat. Commun. 7, 10785 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Yang, Y. et al. Selective synaptic remodeling of amygdalocortical connections associated with fear memory. Nat. Neurosci. 19, 1348–1355 (2016).

    Article  CAS  PubMed  Google Scholar 

  65. Nishiyama, H. et al. Axonal motility and its modulation by activity are branch-type specific in the intact adult cerebellum. Neuron 56, 472–487 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Ofer, N., Cornejo, V. H. & Yuste, R. Spike transmission failures in axons from cortical neurons in vivo. iScience 27, 110884 (2024). This study is the first to provide in vivo evidence to challenge the long-held view of axons as perfectly reliable signal conductors and shows that high-frequency spikes can fail to reach the end of certain branches, suggesting that an axon’s branching structure actively filters and processes information.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Suminaite, D., Lyons, D. A. & Livesey, M. R. Myelinated axon physiology and regulation of neural circuit function. Glia 67, 2050–2062 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Sampaio-Baptista, C. & Johansen-Berg, H. White matter plasticity in the adult brain. Neuron 96, 1239–1251 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Tomassy, G. S. et al. Distinct profiles of myelin distribution along single axons of pyramidal neurons in the neocortex. Science 344, 319–324 (2014). This study provides electron microscopic reconstructions of single pyramidal axons in the mouse neocortex reveal complex patterns of myelinated and unmyelinated segments, overturning the long-held assumption of uniform myelin insulation.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Song, S., Miller, K. D. & Abbott, L. F. Competitive hebbian learning through spike-timing-dependent synaptic plasticity. Nat. Neurosci. 3, 919–926 (2000).

    Article  CAS  PubMed  Google Scholar 

  71. Tessier-Lavigne, M. & Goodman, C. S. The molecular biology of axon guidance. Science 274, 1123–1133 (1996).

    Article  CAS  PubMed  Google Scholar 

  72. Blockus, H. & Polleux, F. Developmental mechanisms underlying circuit wiring: novel insights and challenges ahead. Curr. Opin. Neurobiol. 66, 205–211 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Curran, B. M., Moese, E. R. & Ma, L.in Wiring the Nervous System: Mechanisms of Axonal and Dendritic Remodelling in Health and Disease (eds. Tran, T. S. & Yaron, A.) 3–43 (River Publishers, 2024).

  74. Kirkby, L. owryA. et al. A role for correlated spontaneous activity in the assembly of neural circuits. Neuron 80, 1129–1144 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Blankenship, A. G. & Feller, M. B. Mechanisms underlying spontaneous patterned activity in developing neural circuits. Nat. Rev. Neurosci. 11, 18–29 (2010).

    Article  CAS  PubMed  Google Scholar 

  76. Huberman, A. D., Feller, M. B. & Chapman, B. Mechanisms underlying development of visual maps and receptive fields. Annu. Rev. Neurosci. 31, 479–509 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Guillamón-Vivancos, T. et al. Input-dependent segregation of visual and somatosensory circuits in the mouse superior colliculus. Science 377, 845–850 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Ben-Ari, Y. et al. Giant synaptic potentials in immature rat CA3 hippocampal neurones. J. Physiol. 416, 303–325 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Matsumoto, N. et al. Hebbian instruction of axonal connectivity by endogenous correlated spontaneous activity. Science 385, eadh7814 (2024). This study is the first to provide direct in vivo evidence that spontaneous patterns of correlated neuronal activity instruct where individual axonal process are added or eliminated.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Babola, T. A. et al. Homeostatic control of spontaneous activity in the developing auditory system. Neuron 99, 511–524.e5 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Ackman, J. B., Burbridge, T. J. & Crair, M. C. Retinal waves coordinate patterned activity throughout the developing visual system. Nature 490, 219–225 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Marder, E. & Rehm, K. J. Development of central pattern generating circuits. Curr. Opin. Neurobiol. 15, 86–93 (2005).

    Article  CAS  PubMed  Google Scholar 

  83. Landmesser, L. T. & O’Donovan, M. J. Activation patterns of embryonic chick hind limb muscles recorded in ovo and in an isolated spinal cord preparation. J. Physiol. 347, 189–204 (1984).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Ruthazer, E. S., Li, J. & Cline, H. T. Stabilization of axon branch dynamics by synaptic maturation. J. Neurosci. 26, 3594–3603 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Munz, M. et al. Rapid Hebbian axonal remodeling mediated by visual stimulation. Science 344, 904–909 (2014).

    Article  CAS  PubMed  Google Scholar 

  86. O’Leary, D. D. & Terashima, T. Cortical axons branch to multiple subcortical targets by interstitial axon budding: implications for target recognition and ‘waiting periods’. Neuron 1, 901–910 (1988).

    Article  PubMed  Google Scholar 

  87. Kuang, R. Z. & Kalil, K. Development of specificity in corticospinal connections by axon collaterals branching selectively into appropriate spinal targets. J. Comp. Neurol. 344, 270–282 (1994).

    Article  CAS  PubMed  Google Scholar 

  88. De Leon Reyes, N. S. et al. Transient callosal projections of L4 neurons are eliminated for the acquisition of local connectivity. Nat. Commun. 10, 4549 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  89. Ge, X. et al. Retinal waves prime visual motion detection by simulating future optic flow. Science 373, eabd0830 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Yuste, R., Cossart, R. & Yaksi, E. Neuronal ensembles: building blocks of neural circuits. Neuron 112, 875–892 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Henschke, J. U. et al. Early sensory experience influences the development of multisensory thalamocortical and intracortical connections of primary sensory cortices. Brain Struct. Funct. 223, 1165–1190 (2018).

    PubMed  Google Scholar 

  92. Roe, A. W. et al. Experimentally induced visual projections to the auditory thalamus in ferrets: evidence for a W cell pathway. J. Comp. Neurol. 334, 263–280 (1993).

    Article  CAS  PubMed  Google Scholar 

  93. Frost, D. O. & Metin, C. Induction of functional retinal projections to the somatosensory system. Nature 317, 162–164 (1985).

    Article  CAS  PubMed  Google Scholar 

  94. Constantine-Paton, M. & Law, M. I. Eye-specific termination bands in tecta of three-eyed frogs. Science 202, 639–641 (1978).

    Article  CAS  PubMed  Google Scholar 

  95. Sharma, J., Angelucci, A. & Sur, M. Induction of visual orientation modules in auditory cortex. Nature 404, 841–847 (2000).

    Article  CAS  PubMed  Google Scholar 

  96. von Melchner, L., Pallas, S. L. & Sur, M. Visual behaviour mediated by retinal projections directed to the auditory pathway. Nature 404, 871–876 (2000).

    Article  Google Scholar 

  97. Gao, W. J. & Pallas, S. L. Cross-modal reorganization of horizontal connectivity in auditory cortex without altering thalamocortical projections. J. Neurosci. 19, 7940 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Pallas, S. L., Littman, T. & Moore, D. R. Cross-modal reorganization of callosal connectivity without altering thalamocortical projections. Proc. Natl Acad. Sci. USA 96, 8751–8756 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Pallas, S. L., Hahm, J. & Sur, M. Morphology of retinal axons induced to arborize in a novel target, the medial geniculate nucleus. I. Comparison with arbors in normal targets. J. Comp. Neurol. 349, 343–362 (1994).

    Article  CAS  PubMed  Google Scholar 

  100. Sur, M., Garraghty, P. E. & Roe, A. W. Experimentally induced visual projections into auditory thalamus and cortex. Science 242, 1437–1441 (1988). This study shows that surgically rerouting visual nerve fibers to the auditory thalamus in higher mammals causes the auditory cortex to develop visual-like functional and structural characteristics.

    Article  CAS  PubMed  Google Scholar 

  101. Paul, L. K. et al. Agenesis of the corpus callosum: genetic, developmental and functional aspects of connectivity. Nat. Rev. Neurosci. 8, 287–299 (2007).

    Article  CAS  PubMed  Google Scholar 

  102. Hearne, L. J. et al. Increased cognitive complexity reveals abnormal brain network activity in individuals with corpus callosum dysgenesis. Neuroimage Clin. 21, 101595 (2019).

    Article  PubMed  Google Scholar 

  103. Gobius, I. et al. Astroglial-mediated remodeling of the interhemispheric midline is required for the formation of the corpus callosum. Cell Rep. 17, 735–747 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Probst, M. Ueber den bau des vollständig balkenlosen gross-hirnes sowie über mikrogyrie und heterotopie der grauen substanz. Arch. für Psychiatr. und Nervenkrankheiten 34, 709–786 (1901).

    Article  Google Scholar 

  105. Speeey, R. Plasticity of neural maturation. Developmental Biol. 2, 306–327 (1968).

    Google Scholar 

  106. Granovetter, M. C. et al. With childhood hemispherectomy, one hemisphere can support-but is suboptimal for-word and face recognition. Proc. Natl Acad. Sci. USA 119, e2212936119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Ayzenberg, V. et al. Differential functional reorganization of ventral and dorsal visual pathways following childhood hemispherectomy. Dev. Cogn. Neurosci. 64, 101323 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Burton, H., Snyder, A. Z. & Raichle, M. E. Resting state functional connectivity in early blind humans. Front. Syst. Neurosci. 8, 51 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  109. Stafford, J. M. et al. Large-scale topology and the default mode network in the mouse connectome. Proc. Natl Acad. Sci. USA 111, 18745–18750 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Grandjean, J. et al. Structural basis of large-scale functional connectivity in the mouse. J. Neurosci. 37, 8092–8101 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Bauer, A. Q. et al. Effective connectivity measured using optogenetically evoked hemodynamic signals exhibits topography distinct from resting state functional connectivity in the mouse. Cereb. Cortex 28, 370–386 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Mohajerani, M. H. et al. Spontaneous cortical activity alternates between motifs defined by regional axonal projections. Nat. Neurosci. 16, 1426–1435 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Ferezou, I., Bolea, S. & Petersen, C. C. Visualizing the cortical representation of whisker touch: voltage-sensitive dye imaging in freely moving mice. Neuron 50, 617–629 (2006).

    Article  CAS  PubMed  Google Scholar 

  114. Rosenthal, Z. P. et al. Local perturbations of cortical excitability propagate differentially through large-scale functional networks. Cereb. Cortex 30, 3352–3369 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  115. Mohan, H. et al. Cortical glutamatergic projection neuron types contribute to distinct functional subnetworks. Nat. Neurosci. 26, 481–494 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. van den Heuvel, M. P., Bullmore, E. T. & Sporns, O. Comparative connectomics. Trends Cogn. Sci. 20, 345–361 (2016).

    Article  PubMed  Google Scholar 

  117. Betzel, R. F. & Bassett, D. S. Specificity and robustness of long-distance connections in weighted, interareal connectomes. Proc. Natl Acad. Sci. USA 115, E4880–e4889 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Shehzad, Z. et al. The resting brain: unconstrained yet reliable. Cereb. cortex 19, 2209–2229 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  119. Eggebrecht, A. T. et al. Mapping distributed brain function and networks with diffuse optical tomography. Nat. Photonics 8, 448–454 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Power, J. D. et al. Functional network organization of the human brain. Neuron 72, 665–678 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Smith, S. M. et al. Correspondence of the brain’s functional architecture during activation and rest. Proc. Natl Acad. Sci. USA 106, 13040–13045 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Cohen, A. L. et al. Defining functional areas in individual human brains using resting functional connectivity MRI. NeuroImage 41, 45–57 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Laumann, T. O. et al. Functional system and areal organization of a highly sampled individual human brain. Neuron 87, 657–670 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Poldrack, R. A. et al. Long-term neural and physiological phenotyping of a single human. Nat. Commun. 6, 8885 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Mitra, A. et al. Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep. eLife 4, e10781 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  126. Damoiseaux, J. S. et al. Consistent resting-state networks across healthy subjects. Proc. Natl Acad. Sci. USA 103, 13848–13853 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Albert, N. B., Robertson, E. M. & Miall, R. C. The resting human brain and motor learning. Curr. Biol. 19, 1023–1027 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Hampson, M. et al. Brain connectivity related to working memory performance. J. Neurosci. 26, 13338–13343 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Kelly, A. M. C. et al. Competition between functional brain networks mediates behavioral variability. NeuroImage 39, 527–537 (2008).

    Article  PubMed  Google Scholar 

  130. Lewis, C. M. et al. Learning sculpts the spontaneous activity of the resting human brain. Proc. Natl Acad. Sci. USA 106, 17558–17563 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Raichle, M. E. The brain’s default mode network. Annu. Rev. Neurosci. 38, 433–447 (2015).

    Article  CAS  PubMed  Google Scholar 

  132. Baldassarre, A. et al. Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke. Brain 139, 2024–2038 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Buckner, R. L. et al. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to alzheimer’s disease. J. Neurosci. 29, 1860–1873 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Schüz, A. & Miller, R. Cortical Creas: Unity and Diversity (CRC Press, 2002).

  135. Scholtens, L. H. et al. Common microscale and macroscale principles of connectivity in the human brain. J. Neurosci. 42, 4147–4163 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. van den Heuvel, M. P. & Yeo, B. T. T. A spotlight on bridging microscale and macroscale human brain architecture. Neuron 93, 1248–1251 (2017).

    Article  PubMed  Google Scholar 

  137. Glasser, M. F. et al. A multi-modal parcellation of human cerebral cortex. Nature 536, 171–178 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Scholtens, L. H., Feldman Barrett, L. & van den Heuvel, M. P. Cross-species evidence of interplay between neural connectivity at the micro- and macroscale of connectome organization in human, mouse, and rat brain. Brain Connect. 8, 595–603 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Buzsáki, G. et al. Interneuron diversity series: circuit complexity and axon wiring economy of cortical interneurons. Trends Neurosci. 27, 186–193 (2004).

    Article  PubMed  Google Scholar 

  140. Chen, B. L., Hall, D. H. & Chklovskii, D. B. Wiring optimization can relate neuronal structure and function. Proc. Natl Acad. Sci. USA 103, 4723–4728 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Raichle, M. E. & Mintun, M. A. Brain work and brain imaging. Annu. Rev. Neurosci. 29, 449–476 (2006).

    Article  CAS  PubMed  Google Scholar 

  142. Bullmore, E. & Sporns, O. The economy of brain network organization. Nat. Rev. Neurosci. 13, 336–349 (2012).

    Article  CAS  PubMed  Google Scholar 

  143. Betzel, R. F. et al. The modular organization of human anatomical brain networks: accounting for the cost of wiring. Netw. Neurosci. 1, 42–68 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  144. Roberts, J. A. et al. The contribution of geometry to the human connectome. NeuroImage 124, 379–393 (2016).

    Article  PubMed  Google Scholar 

  145. Samu, D., Seth, A. K. & Nowotny, T. Influence of wiring cost on the large-scale architecture of human cortical connectivity. PLoS Comput. Biol. 10, e1003557 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  146. Hagmann, P. et al. Mapping the structural core of human cerebral cortex. PLoS Biol. 6, e159 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  147. Hermundstad, A. M. et al. Structural foundations of resting-state and task-based functional connectivity in the human brain. Proc. Natl Acad. Sci. USA 110, 6169–6174 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  148. Suárez, L. E. et al. Linking structure and function in macroscale brain networks. Trends Cogn. Sci. 24, 302–315 (2020).

    Article  PubMed  Google Scholar 

  149. Uddin, L. Q. et al. Residual functional connectivity in the split-brain revealed with resting-state functional MRI. Neuroreport 19, 703–709 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  150. Mišić, B. et al. The functional connectivity landscape of the human brain. PLoS ONE 9, e111007 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  151. Honey, C. J. et al. Predicting human resting-state functional connectivity from structural connectivity. Proc. Natl Acad. Sci. USA 106, 2035–2040 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Owen, J. P. et al. Resting-state networks and the functional connectome of the human brain in agenesis of the corpus callosum. Brain Connect. 3, 547–562 (2013). 

    Article  PubMed  PubMed Central  Google Scholar 

  153. O’Reilly, J. X. et al. Causal effect of disconnection lesions on interhemispheric functional connectivity in rhesus monkeys. Proc. Natl Acad. Sci. USA 110, 13982–13987 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  154. Roland, J. L. et al. On the role of the corpus callosum in interhemispheric functional connectivity in humans. Proc. Natl Acad. Sci. USA 114, 13278–13283 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Tyszka, J. M. et al. Intact bilateral resting-state networks in the absence of the corpus callosum. J. Neurosci. 31, 15154–15162 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Sporns, O. & Zwi, J. D. The small world of the cerebral cortex. Neuroinformatics 2, 145–162 (2004).

    Article  PubMed  Google Scholar 

  157. Kaiser, M. & Hilgetag, C. C. Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems. PLoS Comput. Biol. 2, e95 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  158. Sporns, O., Tononi, G. & Edelman, G. M. Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. Cereb. Cortex 10, 127–141 (2000).

    Article  CAS  PubMed  Google Scholar 

  159. Passingham, R. E., Stephan, K. E. & Kötter, R. The anatomical basis of functional localization in the cortex. Nat. Rev. Neurosci. 3, 606–616 (2002).

    Article  CAS  PubMed  Google Scholar 

  160. Zeki, S. & Shipp, S. The functional logic of cortical connections. Nature 335, 311–317 (1988).

    Article  CAS  PubMed  Google Scholar 

  161. Betzel, R. F., Medaglia, J. D. & Bassett, D. S. Diversity of meso-scale architecture in human and non-human connectomes. Nat. Commun. 9, 346 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  162. Chiang, A. S. et al. Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolution. Curr. Biol. 21, 1–11 (2011).

    Article  CAS  PubMed  Google Scholar 

  163. Oh, S. W. et al. A mesoscale connectome of the mouse brain. Nature 508, 207–214 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Markov, N. T. et al. A weighted and directed interareal connectivity matrix for macaque. Cereb. Cortex. Cereb. Cortex 24, 17–36 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  165. Antonini, A. & Stryker, M. P. Plasticity of geniculocortical afferents following brief or prolonged monocular occlusion in the cat. J. Comp. Neurol. 369, 64–82 (1996).

    Article  CAS  PubMed  Google Scholar 

  166. Zhou, Y., Lai, B. & Gan, W.-B. Monocular deprivation induces dendritic spine elimination in the developing mouse visual cortex. Sci. Rep. 7, 4977 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  167. Faust, T. E., Gunner, G. & Schafer, D. P. Mechanisms governing activity-dependent synaptic pruning in the developing mammalian CNS. Nat. Rev. Neurosci. 22, 657–673 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Kraft, A. W., Bauer, A. Q., Culver, J. P. & Lee, J. M. Sensory deprivation after focal ischemia in mice accelerates brain remapping and improves functional recovery through Arc-dependent synaptic plasticity. Sci. Transl. Med. 10, eaag1328 (2018).

    Article  PubMed  Google Scholar 

  169. Bassett, D. S. et al. Dynamic reconfiguration of human brain networks during learning. Proc. Natl Acad. Sci. USA 108, 7641–7646 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Finc, K. et al. Dynamic reconfiguration of functional brain networks during working memory training. Nat. Commun. 11, 2435 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Newbold, D. J. et al. Plasticity and spontaneous activity pulses in disused human brain circuits. Neuron 107, 580–589.e6 (2020). This study shows that induction of large-scale brain plasticity in humans through arm immobilization demonstrates rapid (<48 h) functional dampening of brain circuits that usually process information from the immobilized arm from the larger motor system and a return to the prior state following cast removal.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Laumann, T. O. & Snyder, A. Z. Brain activity is not only for thinking. Curr. Opin. Behav. Sci. 40, 130–136 (2021).

    Article  Google Scholar 

  173. Dimakou, A. et al. The predictive nature of spontaneous brain activity across scales and species. Neuron 113, 1310–1332 (2025).

    Article  CAS  PubMed  Google Scholar 

  174. Vancura, B. et al. Inhibitory control of sharp-wave ripple duration during learning in hippocampal recurrent networks. Nat. Neurosci. 26, 788–797 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Deco, G., Jirsa, V. K. & McIntosh, A. R. Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat. Rev. Neurosci. 12, 43–56 (2011).

    Article  CAS  PubMed  Google Scholar 

  176. Strogatz, S. H. Exploring complex networks. Nature 410, 268–276 (2001).

    Article  CAS  PubMed  Google Scholar 

  177. Sporns, O., Tononi, G. & Edelman, G. M. Theoretical neuroanatomy and the connectivity of the cerebral cortex. Behav. Brain Res. 135, 69–74 (2002).

    Article  CAS  PubMed  Google Scholar 

  178. Honey, C. J. et al. Network structure of cerebral cortex shapes functional connectivity on multiple time scales. Proc. Natl Acad. Sci. USA 104, 10240–10245 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Laughlin, S. B. & Sejnowski, T. J. Communication in neuronal networks. Science 301, 1870–1874 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  180. Kannan, M. et al. Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types. Science 378, eabm8797 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  181. Musall, S. et al. Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making. Nat. Neurosci. 26, 495–505 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  182. Qi, Y. & Ge, H. Modularity and dynamics of cellular networks. PLOS Comput. Biol. 2, e174 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  183. Faskowitz, J. et al. Connectome topology of mammalian brains and its relationship to taxonomy and phylogeny. Front. Neurosci. 16, 1044372 (2022).

    Article  PubMed  Google Scholar 

  184. Gutierrez-Barragan, D. et al. Evolutionarily conserved fMRI network dynamics in the mouse, macaque, and human brain. Nat. Commun. 15, 8518 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Ragone, E. et al. Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains. Commun. Biol. 7, 126 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  186. Merabet, L. B. & Pascual-Leone, A. Neural reorganization following sensory loss: the opportunity of change. Nat. Rev. Neurosci. 11, 44–52 (2010).

    Article  CAS  PubMed  Google Scholar 

  187. Wang, D. et al. Altered resting-state network connectivity in congenital blind. Hum. Brain Mapp. 35, 2573–2581 (2014).

    Article  PubMed  Google Scholar 

  188. Rauschecker, J. P. et al. Crossmodal changes in the somatosensory vibrissa/barrel system of visually deprived animals. Proc. Natl Acad. Sci. USA 89, 5063–5067 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Rabinowitch, I. & Bai, J. The foundations of cross-modal plasticity. Commun. Integr. Biol. 9, e1158378 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  190. Laumann, T. O. et al. Brain network reorganisation in an adolescent after bilateral perinatal strokes. Lancet Neurol. 20, 255–256 (2021). This study demonstrates the brain’s incredible capacity for plasticity in a child who sustained large, bilateral perinatal strokes 3 weeks postnatally, but otherwise experienced typical neurodevelopment, with injuries going unnoticed until 13 years of age.

    Article  PubMed  Google Scholar 

  191. De León Reyes, N. S. et al. Transient callosal projections of L4 neurons are eliminated for the acquisition of local connectivity. Nat. Commun. 10, 4549 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  192. Griffis, J. C. et al. Structural disconnections explain brain network dysfunction after stroke. Cell Rep. 28, 2527–2540.e9 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  193. Marebwa, B. K. et al. Chronic post-stroke aphasia severity is determined by fragmentation of residual white matter networks. Sci. Rep. 7, 8188 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  194. Carrera, E. & Tononi, G. Diaschisis: past, present, future. Brain 137, 2408–2422 (2014).

    Article  PubMed  Google Scholar 

  195. Silasi, G. & Murphy, T. H. Stroke and the connectome: how connectivity guides therapeutic intervention. Neuron 83, 1354–1368 (2014).

    Article  CAS  PubMed  Google Scholar 

  196. Feeney, D. M. & Baron, J. C. Diaschisis. Stroke 17, 817–830 (1986).

    Article  CAS  PubMed  Google Scholar 

  197. Brown, C. E. et al. In vivo voltage-sensitive dye imaging in adult mice reveals that somatosensory maps lost to stroke are replaced over weeks by new structural and functional circuits with prolonged modes of activation within both the peri-infarct zone and distant sites. J. Neurosci. 29, 1719–1734 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Kraft, A. W. et al. Sensory deprivation after focal ischemia in mice accelerates brain remapping and improves functional recovery through arc-dependent synaptic plasticity. Sci. Transl. Med. 10, eaag1328 (2018).

    Article  PubMed  Google Scholar 

  199. Cramer, S. C. & Riley, J. D. Neuroplasticity and brain repair after stroke. Curr. Opin. Neurol. 21, 76–82 (2008).

    Article  PubMed  Google Scholar 

  200. Jaillard, A. et al. Vicarious function within the human primary motor cortex? A longitudinal fMRI stroke study. Brain 128, 1122–1138 (2005).

    Article  PubMed  Google Scholar 

  201. Dijkhuizen, R. M. et al. Functional magnetic resonance imaging of reorganization in rat brain after stroke. Proc. Natl Acad. Sci. USA 98, 12766–12771 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  202. Gonzalez, C. L. & Kolb, B. A comparison of different models of stroke on behaviour and brain morphology. Eur. J. Neurosci. 18, 1950–1962 (2003).

    Article  CAS  PubMed  Google Scholar 

  203. Harrison, T. C. et al. Displacement of sensory maps and disorganization of motor cortex after targeted stroke in mice. Stroke 44, 2300–2306 (2013).

    Article  PubMed  Google Scholar 

  204. Castro-Alamancos, M. A. & Borrel, J. Functional recovery of forelimb response capacity after forelimb primary motor cortex damage in the rat is due to the reorganization of adjacent areas of cortex. Neuroscience 68, 793–805 (1995).

    Article  CAS  PubMed  Google Scholar 

  205. Bice, A. R. et al. Homotopic contralesional excitation suppresses spontaneous circuit repair and global network reconnections following ischemic stroke. eLife 11, e68852 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  206. Calautti, C. et al. Sequential activation brain mapping after subcortical stroke: changes in hemispheric balance and recovery. Neuroreport 12, 3883–3886 (2001).

    Article  CAS  PubMed  Google Scholar 

  207. Traversa, R. et al. Mapping of motor cortical reorganization after stroke. A brain stimulation study with focal magnetic pulses. Stroke 28, 110–117 (1997).

    Article  CAS  PubMed  Google Scholar 

  208. Ward, N. S. et al. Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain 126, 2476–2496 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  209. Bowen, R. et al. Early changes in spatiotemporal dynamics of remapped circuits and global networks predict functional recovery after stroke in mice. Neurophotonics 12, S14604 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  210. Nudo, R. J. et al. Neural substrates for the effects of rehabilitative training on motor recovery after ischemic infarct. Science 272, 1791–1794 (1996).

    Article  CAS  PubMed  Google Scholar 

  211. Wei, L. et al. Collateral growth and angiogenesis around cortical stroke. Stroke 32, 2179–2184 (2001).

    Article  CAS  PubMed  Google Scholar 

  212. Johansson, B. B. & Belichenko, P. V. Neuronal plasticity and dendritic spines: effect of environmental enrichment on intact and postischemic rat brain. J. Cereb. Blood Flow. Metab. 22, 89–96 (2002).

    Article  PubMed  Google Scholar 

  213. Zhang, S. et al. Rapid reversible changes in dendritic spine structure in vivo gated by the degree of ischemia. J. Neurosci. 25, 5333–5338 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  214. Brown, C. E., Wong, C. & Murphy, T. H. Rapid morphologic plasticity of peri-infarct dendritic spines after focal ischemic stroke. Stroke 39, 1286–1291 (2008).

    Article  PubMed  Google Scholar 

  215. Brown, C. E. et al. Extensive turnover of dendritic spines and vascular remodeling in cortical tissues recovering from stroke. J. Neurosci. 27, 4101–4109 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  216. Li, S. et al. An age-related sprouting transcriptome provides molecular control of axonal sprouting after stroke. Nat. Neurosci. 13, 1496–1504 (2010). In this study, by comparing isolated cortical neurons that sprout new connections after stroke with adjacent non-sprouting neurons, the authors define a ‘sprouting transcriptome’ that identified distinct pathways involving growth factors, cell adhesion, and axonal guidance molecules.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  217. Wu, F. et al. Urokinase-type plasminogen activator promotes dendritic spine recovery and improves neurological outcome following ischemic stroke. J. Neurosci. 34, 14219–14232 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  218. Winship, I. R. & Murphy, T. H. In vivo calcium imaging reveals functional rewiring of single somatosensory neurons after stroke. J. Neurosci. 28, 6592–6606 (2008). Calcium imaging in mice reveals that individual somatosensory neurons undergo dynamic functional rewiring after stroke, demonstrating that surviving neurons can shift their sensory responses from hindpaw to forepaw, highlighting cortical plasticity as a mechanism of post-stroke repair and recovery.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  219. Murata, Y. et al. Increased expression of the growth-associated protein-43 gene after primary motor cortex lesion in macaque monkeys. Neurosci. Res. 98, 64–69 (2015).

    Article  CAS  PubMed  Google Scholar 

  220. Stroemer, R. P., Kent, T. A. & Hulsebosch, C. E. Neocortical neural sprouting, synaptogenesis, and behavioral recovery after neocortical infarction in rats. Stroke 26, 2135–2144 (1995).

    Article  CAS  PubMed  Google Scholar 

  221. Dijk, F., Bergen, A. A. & Kamphuis, W. GAP-43 expression is upregulated in retinal ganglion cells after ischemia/reperfusion-induced damage. Exp. Eye Res. 84, 858–867 (2007).

    Article  CAS  PubMed  Google Scholar 

  222. Gallo, G. & Letourneau, P. C. Regulation of growth cone actin filaments by guidance cues. J. Neurobiol. 58, 92–102 (2004).

    Article  CAS  PubMed  Google Scholar 

  223. Denny, J. B. Molecular mechanisms, biological actions, and neuropharmacology of the growth-associated protein GAP-43. Curr. Neuropharmacol. 4, 293–304 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  224. de Graan, P. N. et al. Phosphoprotein B-50 in nerve growth cones from fetal rat brain. Neurosci. Lett. 61, 235–241 (1985).

    Article  PubMed  Google Scholar 

  225. Skene, J. H. & Virag, I. Posttranslational membrane attachment and dynamic fatty acylation of a neuronal growth cone protein, GAP-43. J. Cell Biol. 108, 613–624 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  226. Steketee, M. B. & Tosney, K. W. Three functionally distinct adhesions in filopodia: shaft adhesions control lamellar extension. J. Neurosci. 22, 8071–8083 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  227. Kawamata, T. et al. Intracisternal antisense oligonucleotide to growth associated protein-43 blocks the recovery-promoting effects of basic fibroblast growth factor after focal stroke. Exp. Neurol. 158, 89–96 (1999).

    Article  CAS  PubMed  Google Scholar 

  228. Clarkson, A. N. et al. Multimodal examination of structural and functional remapping in the mouse photothrombotic stroke model. J. Cereb. Blood Flow. Metab. 33, 716–723 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  229. Wahl, A. S. et al. Neuronal repair. Asynchronous therapy restores motor control by rewiring of the rat corticospinal tract after stroke. Science 344, 1250–1255 (2014).

    Article  CAS  PubMed  Google Scholar 

  230. Joy, M. T. et al. CCR5 Is a therapeutic target for recovery after stroke and traumatic brain injury. Cell 176, 1143–1157.e13 (2019). In this study, the authors identified the chemokine receptor CCR5 as a key regulator of recovery after stroke and traumatic brain injury, and show evidence that suggest it is a promising therapeutic target for brain repair and recovery.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  231. Overman, J. J. et al. A role for ephrin-A5 in axonal sprouting, recovery, and activity-dependent plasticity after stroke. Proc. Natl Acad. Sci. USA 109, E2230–E2239 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  232. Kugler, C. et al. Epothilones improve axonal growth and motor outcomes after stroke in the adult mammalian CNS. Cell Rep. Med. 1, 100159 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  233. Uryu, K., MacKenzie, L. & Chesselet, M. F. Ultrastructural evidence for differential axonal sprouting in the striatum after thermocoagulatory and aspiration lesions of the cerebral cortex in adult rats. Neuroscience 105, 307–316 (2001).

    Article  CAS  PubMed  Google Scholar 

  234. Makin, T. R. & Krakauer, J. W. Against cortical reorganisation. Elife 12, e84716 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  235. Posner, M. I. et al. Localization of cognitive operations in the human brain. Science 240, 1627–1631 (1988). This commentary presents arguments that the mechanism underlying remapping following stroke does not involve ‘rewiring’, but rather involves the potentiation of pre-existing circuits.

    Article  CAS  PubMed  Google Scholar 

  236. Felleman, D. J. & Essen, D. C. V. an Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 (1991).

    Article  CAS  PubMed  Google Scholar 

  237. Carter, A. R. et al. Upstream dysfunction of somatomotor functional connectivity after corticospinal damage in stroke. Neurorehabil. Neural Repair. 26, 7–19 (2012).

    Article  PubMed  Google Scholar 

  238. He, B. J. et al. Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect. Neuron 53, 905–918 (2007).

    Article  CAS  PubMed  Google Scholar 

  239. Bauer, A. Q. et al. Optical imaging of disrupted functional connectivity following ischemic stroke in mice. Neuroimage 99, 388–401 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  240. van Meer, M. P. A. et al. Recovery of sensorimotor function after experimental stroke correlates with restoration of resting-state interhemispheric functional connectivity. J. Neurosci. 30, 3964–3972 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  241. Hakon, J. et al. Multisensory stimulation improves functional recovery and resting-state functional connectivity in the mouse brain after stroke. Neuroimage Clin. 17, 717–730 (2018).

    Article  PubMed  Google Scholar 

  242. Sunil, S. et al. Neurovascular coupling is preserved in chronic stroke recovery after targeted photothrombosis. NeuroImage: Clin. 38, 103377 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  243. Lim, D. H. et al. Optogenetic mapping after stroke reveals network-wide scaling of functional connections and heterogeneous recovery of the peri-infarct. J. Neurosci. 34, 16455 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  244. Nudo, R. J. Postinfarct cortical plasticity and behavioral recovery. Stroke 38, 840–845 (2007).

    Article  PubMed  Google Scholar 

  245. Murase, N. et al. Influence of interhemispheric interactions on motor function in chronic stroke. Ann. Neurol. 55, 400–409 (2004).

    Article  PubMed  Google Scholar 

  246. Ramsey, L. E. et al. Normalization of network connectivity in hemispatial neglect recovery. Ann. Neurol. 80, 127–141 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  247. Mohajerani, M. H., Aminoltejari, K. & Murphy, T. H. Targeted mini-strokes produce changes in interhemispheric sensory signal processing that are indicative of disinhibition within minutes. Proc. Natl Acad. Sci. USA 108, E183–E191 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  248. Caracciolo, L. et al. CREB controls cortical circuit plasticity and functional recovery after stroke. Nat. Commun. 9, 2250 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  249. Li, S. et al. GDF10 is a signal for axonal sprouting and functional recovery after stroke. Nat. Neurosci. 18, 1737–1745 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  250. Nicoletti, F. et al. Metabotropic glutamate receptors: from the workbench to the bedside. Neuropharmacology 60, 1017–1041 (2011).

    Article  CAS  PubMed  Google Scholar 

  251. Hakon, J. et al. Inhibiting metabotropic glutamate receptor 5 after stroke restores brain function and connectivity. Brain 147, 186–200 (2023).

    Article  Google Scholar 

  252. Lim, T. K. Y. & Ruthazer, E. S. Microglial trogocytosis and the complement system regulate axonal pruning in vivo. eLife 10, e62167 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  253. Bae, J. A. et al. Functional connectomics spanning multiple areas of mouse visual cortex. Nature 640, 435–447 (2025).

    Article  Google Scholar 

  254. Schlegel, P. et al. Whole-brain annotation and multi-connectome cell typing of Drosophila. Nature 634, 139–152 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  255. Stürner, T. et al. Comparative connectomics of Drosophila descending and ascending neurons. Nature 643, 158–172 (2025).

    Article  PubMed  PubMed Central  Google Scholar 

  256. Tavakoli, M. R. et al. Light-microscopy-based connectomic reconstruction of mammalian brain tissue. Nature 642, 398–410 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  257. Shen, F. Y. et al. Light microscopy based approach for mapping connectivity with molecular specificity. Nat. Commun. 11, 4632 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  258. Stirman, J. N. et al. Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain. Nat. Biotechnol. 34, 857–862 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  259. Bumstead, J. R. et al. Designing a large field-of-view two-photon microscope using optical invariant analysis. Neurophotonics 5, 025001 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  260. Kim, T. H. et al. Long-term optical access to an estimated one million neurons in the live mouse cortex. Cell Rep. 17, 3385–3394 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  261. Fornito, A., Arnatkevičiūtė, A. & Fulcher, B. D. Bridging the gap between connectome and transcriptome. Trends Cogn. Sci. 23, 34–50 (2019).

    Article  PubMed  Google Scholar 

  262. Fulcher, B. D. & Fornito, A. A transcriptional signature of hub connectivity in the mouse connectome. Proc. Natl Acad. Sci. USA 113, 1435–1440 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  263. Ng, B. et al. Integration across biophysical scales identifies molecular and cellular correlates of person-to-person variability in human brain connectivity. Nat. Neurosci. 27, 2240–2252 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  264. De Paola, V. et al. Cell type-specific structural plasticity of axonal branches and boutons in the adult neocortex. Neuron 49, 861–875 (2006).

    Article  PubMed  Google Scholar 

  265. Li, F. et al. The connectome of the adult Drosophila mushroom body provides insights into function. eLife 9, e62576 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  266. Snyder, A. Z. & Bauer, A. Q. Mapping structure-function relationships in the brain. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 4, 510–521 (2019).

    PubMed  Google Scholar 

  267. Sporns, O., Honey, C. J. & Kötter, R. Identification and classification of hubs in brain networks. PLoS ONE 2, e1049 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  268. Griffa, A. & Van den Heuvel, M. P. Rich-club neurocircuitry: function, evolution, and vulnerability. Dialogues Clin. Neurosci. 20, 121–132 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  269. Schirmer, M. D. et al. Rich-club organization: an important determinant of functional outcome after acute ischemic stroke. Front. Neurol. 10, 956 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  270. Warren, D. E. et al. Network measures predict neuropsychological outcome after brain injury. Proc. Natl Acad. Sci. USA 111, 14247–14252 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  271. Shepherd, G. M. The Synaptic Organization of the Brain (Oxford Univ. Press, 2004).

  272. Chklovskii, D. B. Synaptic connectivity and neuronal morphology: two sides of the same coin. Neuron 43, 609–617 (2004).

    CAS  PubMed  Google Scholar 

  273. Pissadaki, E. K. & Bolam, J. P. The energy cost of action potential propagation in dopamine neurons: clues to susceptibility in Parkinson’s disease. Front. Comput. Neurosci. 7, 13 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  274. Rind, F. C. A chemical synapse between two motion detecting neurones in the locust brain. J. Exp. Biol. 110, 143–167 (1984).

    Article  CAS  PubMed  Google Scholar 

  275. Abbott, L. F. & Regehr, W. G. Synaptic computation. Nature 431, 796–803 (2004).

    Article  CAS  PubMed  Google Scholar 

  276. Wang, X.-J. Neurophysiological and computational principles of cortical rhythms in cognition. Physiol. Rev. 90, 1195–1268 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  277. Zhang, K. & Sejnowski, T. J. A universal scaling law between gray matter and white matter of cerebral cortex. Proc. Natl Acad. Sci. 97, 5621–5626 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  278. Misgeld, T. & Schwarz, T. L. Mitostasis in neurons: maintaining mitochondria in an extended cellular architecture. Neuron 96, 651–666 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  279. Marner, L. et al. Marked loss of myelinated nerve fibers in the human brain with age. J. Comp. Neurol. 462, 144–152 (2003).

    Article  PubMed  Google Scholar 

  280. Neumann, P. et al. Is microglial dystrophy a form of cellular senescence? An analysis of senescence markers in the aged human brain. Glia 71, 377–390 (2023).

    Article  CAS  PubMed  Google Scholar 

  281. Wang, X. & Michaelis, E. K. Selective neuronal vulnerability to oxidative stress in the brain. Front. Aging Neurosci. 2, 12 (2010).

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank N. Hiratani for discussion on ideas. L.J.R. is supported by DP1 OD031273 from the National Institutes of Health (NIH) National Institute for Neurological Disorders and Stroke (NINDS). A.Q.B. is supported by NIH grants R01NS126326 (NINDS), R01NS102870 (NINDS) and RF1AG07950301 (NIA), and J.-M.L. is supported by RF1NS139970, UF1NS125512, R01NS120481, R37NS110699 and R01AG079503.

Author information

Authors and Affiliations

  1. Department of Neuroscience, Washington University in St. Louis Medical School, St. Louis, MO, USA

    Linda J. Richards & Cheng Huang

  2. Department of Radiology, Washington University in St. Louis Medical School, St. Louis, MO, USA

    Adam Q. Bauer

  3. Department of Biomedical Engineering, Washington University in St. Louis Medical School, St. Louis, MO, USA

    Adam Q. Bauer

  4. Department of Neurology, Washington University in St. Louis Medical School, St. Louis, MO, USA

    Jin-Moo Lee

Authors
  1. Linda J. Richards
    View author publications

    Search author on:PubMed Google Scholar

  2. Cheng Huang
    View author publications

    Search author on:PubMed Google Scholar

  3. Adam Q. Bauer
    View author publications

    Search author on:PubMed Google Scholar

  4. Jin-Moo Lee
    View author publications

    Search author on:PubMed Google Scholar

Contributions

All authors contributed equally to the manuscript.

Corresponding author

Correspondence to Linda J. Richards.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Neuroscience thanks Bo Hu, who co-reviewed with Chun Xu; Martijn van den Heuvel; and the other, anonymous, reviewer(s) for their contribution to the peer review of this manuscript.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

MouseLight: https://ml-neuronbrowser.janelia.org/

NeuroMorpho.org: https://neuromorpho.org/

Glossary

Axonal plasticity

Any change to an axon; including an increase or decrease in activity, activation or loss/pruning of a specific branch, growth of a new branch (probably over a few micrometres) or synapse, a significant change in axonal trajectory from neurotypical (usually during development).

Connectome

A comprehensive, ultradetailed wiring diagram of each neuron and its individual synapses within a circuit or an entire nervous system, typically reconstructed from electron microscopy data. Although the concept of ‘connectome’ extends to macroscale structural and functional connectivity (for example, the human connectome), it specifically refers to the nanoscale diagrams in this review.

Global networks

Global networks comprising multiple interconnected local circuits, often across distant regions of the brain working together to perform more complex cognitive functions and behaviours.

Local circuits

Local circuits are populations of interconnected colocalized neurons that carry out specific, localized functions.

Long-range axon

Axons that project out of a given cortical functional domain (for example, a primary sensory area) or nuclei to another area in the same or opposite hemisphere or in a descending/ascending manner.

Peri-infarct region

The area of tissue surrounding a completed stroke (after the phase of active ischaemia) where the region of damage has a stabilized and is no longer expanding.

Projectome

A detailed map with single-neuron resolution of the axonal projections linking distinct brain regions, which reveals the target patterns of different neuron types and the large-scale architecture of the brain’s network.

Remapping

The brain’s ability to reorganize or reprioritize its neural connections and function in response to injury. Remapping describes a phenomenon but not necessarily a mechanism.

Silent or dormant long-range axonal branches

Axonal branches or regions of the axon shaft lacking, or with low density of, synaptic connections at a given time. These regions of the axon may or may not have previously had synaptic boutons. Previously active regions of the axon may be better primed for neuroplasticity.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Richards, L.J., Huang, C., Bauer, A.Q. et al. Long-range axon branching: contributions to brain network plasticity and repair. Nat. Rev. Neurosci. 27, 243–259 (2026). https://doi.org/10.1038/s41583-025-01008-y

Download citation

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41583-025-01008-y

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing