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Three systems of circuit formation: assembly, updating and tuning

Nature Reviews Neuroscience volume 26, pages 232–243 (2025)Cite this article

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Abstract

Understanding the relationship between genotype and neuronal circuit phenotype necessitates an integrated view of genetics, development, plasticity and learning. Challenging the prevailing notion that emphasizes learning and plasticity as primary drivers of circuit assembly, in this Perspective, we delineate a tripartite framework to clarify the respective roles that learning and plasticity might have in this process. In the first part of the framework, which we term System One, neural circuits are established purely through genetically driven algorithms, in which spike timing-dependent plasticity serves no instructive role. We propose that these circuits equip the animal with sufficient skill and knowledge to successfully engage the world. Next, System Two is governed by rare but critical ‘single-shot learning’ events, which occur in response to survival situations and prompt rapid synaptic reconfiguration. Such events serve as crucial updates to the existing hardwired knowledge base of an organism. Finally, System Three is characterized by a perpetual state of synaptic recalibration, involving continual plasticity for circuit stabilization and fine-tuning. By outlining the definitions and roles of these three core systems, our framework aims to resolve existing ambiguities related to and enrich our understanding of neural circuit formation.

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Fig. 1: The three systems.

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References

  1. Zador, A. M. A critique of pure learning and what artificial neural networks can learn from animal brains. Nat. Commun. 10, 3770 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  2. LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).

    Article  CAS  PubMed  Google Scholar 

  3. Martini, F. J., Guillamón-Vivancos, T., Moreno-Juan, V., Valdeolmillos, M. & López-Bendito, G. Spontaneous activity in developing thalamic and cortical sensory networks. Neuron 109, 2519–2534 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wu, M. W., Kourdougli, N. & Portera-Cailliau, C. Network state transitions during cortical development. Nat. Rev. Neurosci. 25, 535–552 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kuwahara, H. & Gao, X. Stochastic effects as a force to increase the complexity of signaling networks. Sci. Rep. 3, 2297 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Confavreux, B., Agnes, E. J., Zenke, F., Sprekeler, H. & Vogels, T. P. Balancing complexity, performance and plausibility to meta learn plasticity rules in recurrent spiking networks. Preprint at bioRxiv https://doi.org/10.1101/2024.06.17.599260 (2024).

  7. Váša, F. & Mišić, B. Null models in network neuroscience. Nat. Rev. Neurosci. 23, 493–504 (2022).

    Article  PubMed  Google Scholar 

  8. Lendvai, B., Stern, E. A., Chen, B. & Svoboda, K. Experience-dependent plasticity of dendritic spines in the developing rat barrel cortex in vivo. Nature 404, 876–881 (2000).

    Article  CAS  PubMed  Google Scholar 

  9. DeBello, W. M. Micro-rewiring as a substrate for learning. Trends Neurosci. 31, 577–584 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Power, J. D. & Schlaggar, B. L. Neural plasticity across the lifespan. WIREs Dev. Biol., 6, e216 (2017).

    Article  Google Scholar 

  11. Barabási, D. L., Schuhknecht, G. F. P. & Engert, F. Functional neuronal circuits emerge in the absence of developmental activity. Nat. Commun. 15, 364 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Warland, D. K., Huberman, A. D. & Chalupa, L. M. Dynamics of spontaneous activity in the fetal macaque retina during development of retinogeniculate pathways. J. Neurosci. 26, 5190–5197 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. 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 

  14. Langen, M. et al. The developmental rules of neural superposition in Drosophila. Cell 162, 120–133 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Hiesinger, P. R. et al. Activity-independent prespecification of synaptic partners in the visual map of Drosophila. Curr. Biol. 16, 1835–1843 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Corver, A., Wilkerson, N., Miller, J. & Gordus, A. Distinct movement patterns generate stages of spider web building. Curr. Biol. 31, 4983–4997.e5 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Moss, S. Planet Earth II: A New World Revealed (Penguin Random House, 2016).

  18. Honza, M., Vošlajerová, K. & Moskát, C. Eviction behaviour of the common cuckoo Cuculus canorus chicks. J. Avian Biol. 38, 385–389 (2007).

    Article  Google Scholar 

  19. Maggini, I. & Bairlein, F. Innate sex differences in the timing of spring migration in a songbird. PLoS ONE 7, e31271 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Berthold, P. & Helbig, A. J. The genetics of bird migration: stimulus, timing, and direction. IBIS 134, 35–40 (2008).

    Article  Google Scholar 

  21. Acworth, N. R. J. The healthy neonatal foal: routine examinations and preventative medicine. Equine Vet. Educ. 15, 207–211 (2003).

    Article  Google Scholar 

  22. Fishell, G. & Kepecs, A. Interneuron types as attractors and controllers. Annu. Rev. Neurosci. 43, 1–30 (2020).

    Article  CAS  PubMed  Google Scholar 

  23. Konstantinides, N. et al. A complete temporal transcription factor series in the fly visual system. Nature 604, 316–322 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Shabani, K. & Hassan, B. A. The brain on time: links between development and neurodegeneration. Development 150, dev200397 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kurmangaliyev, Y. Z., Yoo, J., Valdes-Aleman, J., Sanfilippo, P. & Zipursky, S. L. Transcriptional programs of circuit assembly in the Drosophila visual system. Neuron 108, 1045–1057.e6 (2020).

    Article  CAS  PubMed  Google Scholar 

  26. Kerstjens, S., Michel, G. & Douglas, R. J. Constructive connectomics: how neuronal axons get from here to there using gene-expression maps derived from their family trees. PLoS Comput. Biol. 18, e1010382 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Agi, E. et al. Axonal self-sorting without target guidance in visual map formation. Science 383, 1084–1092 (2024).

    Article  CAS  PubMed  Google Scholar 

  28. Sanes, J. R. & Zipursky, S. L. Synaptic specificity, recognition molecules, and assembly of neural circuits. Cell 181, 1434–1435 (2020).

    Article  CAS  PubMed  Google Scholar 

  29. Flaherty, E. & Maniatis, T. The role of clustered protocadherins in neurodevelopment and neuropsychiatric diseases. Curr. Opin. Genet. Dev. 65, 144–150 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Valdes-Aleman, J. et al. Comparative connectomics reveals how partner identity, location, and activity specify synaptic connectivity in Drosophila. Neuron 109, 105–122.e7 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Barabási, D. L. & Czégel, D. Constructing graphs from genetic encodings. Sci. Rep. 11, 13270 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Hiesinger, P. R. & Hassan, B. A. The evolution of variability and robustness in neural development. Trends Neurosci. 41, 577–586 (2018).

    Article  CAS  PubMed  Google Scholar 

  33. Hiesinger, P. R. The Self-Assembling Brain: How Neural Networks Grow Smarter (Princeton Univ. Press, 2021).

  34. Farhoodi, R. & Kording, K. P. Sampling neuron morphologies. Preprint at bioRxiv https://doi.org/10.1101/248385 (2018).

  35. Xu, C. et al. Molecular and cellular mechanisms of teneurin signaling in synaptic partner matching. Cell 187, 5081–5101.e19 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ferreira Castro, A. et al. Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction. eLife 9, e60920 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  37. McFarland, B. W. et al. Axon arrival times and physical occupancy establish visual projection neuron integration on developing dendrites in the Drosophila optic glomeruli. eLife 13, RP96223 (2024).

    Google Scholar 

  38. Barabási, D. L. & Barabási, A.-L. A genetic model of the connectome. Neuron 105, 435–445.e5 (2020).

    Article  PubMed  Google Scholar 

  39. Carrillo, R. A. et al. Control of synaptic connectivity by a network of Drosophila IgSF cell surface proteins. Cell 163, 1770–1782 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Munz, M. et al. Pyramidal neurons form active, transient, multilayered circuits perturbed by autism-associated mutations at the inception of neocortex. Cell 186, 1930–1949.e31 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Mòdol, L., Moissidis, M., Selten, M., Oozeer, F. & Marín, O. Somatostatin interneurons control the timing of developmental desynchronization in cortical networks. Neuron 112, 2015–2030.e5 (2024).

    Article  PubMed  Google Scholar 

  42. Antón-Bolaños, N. et al. Prenatal activity from thalamic neurons governs the emergence of functional cortical maps in mice. Science 364, 987–990 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Andreae, L. C. & Burrone, J. The role of spontaneous neurotransmission in synapse and circuit development. J. Neurosci. Res. 96, 354–359 (2018).

    Article  CAS  PubMed  Google Scholar 

  44. Sutton, M. A., Wall, N. R., Aakalu, G. N. & Schuman, E. M. Regulation of dendritic protein synthesis by miniature synaptic events. Science 304, 1979–1983 (2004).

    Article  CAS  PubMed  Google Scholar 

  45. Barabási, D. L. et al. Neuroscience needs network science. J. Neurosci. 43, 5989–5995 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Kovács, I. A., Barabási, D. L. & Barabási, A.-L. Uncovering the genetic blueprint of the nervous system. Proc. Natl Acad. Sci. USA 117, 33570–33577 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Lior, G., Shalev, Y., Stanovsky, G. & Goldstein, A. Computation or weight adaptation? Rethinking the role of plasticity in learning. Preprint at bioRxiv https://doi.org/10.1101/2024.03.07.583890 (2024).

  48. Kuutti, S., Fallah, S., Bowden, R. & Barber, P. Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects (Morgan & Claypool, 2019).

  49. Hürkey, S. et al. Gap junctions desynchronize a neural circuit to stabilize insect flight. Nature 618, 118–125 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Wehner, R. Desert Navigator: The Journey of an Ant (Harvard Univ. Press, 2020).

  51. Ronacher, B. Path integration in a three-dimensional world: the case of desert ants. J. Comp. Physiol. A 206, 379–387 (2020).

    Article  Google Scholar 

  52. Freas, C. A. & Schultheiss, P. How to navigate in different environments and situations: lessons from ants. Front. Psychol. 9, 841 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  53. O’Shea, H. & Redmond, S. J. A review of the neurobiomechanical processes underlying secure gripping in object manipulation. Neurosci. Biobehav. Rev. 123, 286–300 (2021).

    Article  PubMed  Google Scholar 

  54. Ammari, R. et al. Hormone-mediated neural remodeling orchestrates parenting onset during pregnancy. Science 382, 76–81 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Wu, Z., Autry, A. E., Bergan, J. F., Watabe-Uchida, M. & Dulac, C. G. Galanin neurons in the medial preoptic area govern parental behaviour. Nature 509, 325–330 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Wu, M. V. & Tollkuhn, J. Estrogen receptor alpha is required in GABAergic, but not glutamatergic, neurons to masculinize behavior. Horm. Behav. 95, 3–12 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Lesar, A., Tahir, J., Wolk, J. & Gershow, M. Switch-like and persistent memory formation in individual. eLife 10, e70317 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Giurfa, M., Núñez, J., Chittka, L. & Menzel, R. Colour preferences of flower-naive honeybees. J. Comp. Physiol. A 177, 247–259 (1995).

    Article  Google Scholar 

  59. Galvin, L., Mirza Agha, B., Saleh, M., Mohajerani, M. H. & Whishaw, I. Q. Learning to cricket hunt by the laboratory mouse (Mus musculus): skilled movements of the hands and mouth in cricket capture and consumption. Behav. Brain Res. 412, 113404 (2021).

    Article  PubMed  Google Scholar 

  60. Matsuzawa, T. Sweet-potato washing revisited: 50th anniversary of the Primates article. Primates 56, 285–287 (2015).

    Article  PubMed  Google Scholar 

  61. Bowman, C. R. & Zeithamova, D. Abstract memory representations in the ventromedial prefrontal cortex and hippocampus support concept generalization. J. Neurosci. 38, 2605–2614 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Tang, W., Shin, J. D. & Jadhav, S. P. Geometric transformation of cognitive maps for generalization across hippocampal-prefrontal circuits. Cell Rep. 42, 112246 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Jones, M. W. & McHugh, T. J. Updating hippocampal representations: CA2 joins the circuit. Trends Neurosci. 34, 526–535 (2011).

    Article  CAS  PubMed  Google Scholar 

  64. Flanagin, V. L. et al. Human exploration of enclosed spaces through echolocation. J. Neurosci. 37, 1614–1627 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Porter, J. et al. Mechanisms of scent-tracking in humans. Nat. Neurosci. 10, 27–29 (2007).

    Article  CAS  PubMed  Google Scholar 

  66. Bittner, K. C., Milstein, A. D., Grienberger, C., Romani, S. & Magee, J. C. Behavioral time scale synaptic plasticity underlies CA1 place fields. Science 357, 1033–1036 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Ahrens, M. B. et al. Brain-wide neuronal dynamics during motor adaptation in zebrafish. Nature 485, 471–477 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Bahl, A. & Engert, F. Neural circuits for evidence accumulation and decision making in larval zebrafish. Nat. Neurosci. 23, 94–102 (2020).

    Article  CAS  PubMed  Google Scholar 

  69. Arcaro, M., Schade, P. & Livingstone, M. Preserved cortical organization in the absence of early visual input. J. Vis. 18, 27–27 (2018).

    Article  Google Scholar 

  70. Hubel, D. H. & Wiesel, T. N. The period of susceptibility to the physiological effects of unilateral eye closure in kittens. J. Physiol. 206, 419–436 (1970).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Sansom, S. N. & Livesey, F. J. Gradients in the brain: the control of the development of form and function in the cerebral cortex. Cold Spring Harb. Perspect. Biol. 1, a002519 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Ahmed, M. et al. Input density tunes Kenyon cell sensory responses in the Drosophila mushroom body. Curr. Biol. 33, 2742–2760.e12 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Sterling, P. & Laughlin, S. Principles of Neural Design (MIT Press, 2017).

  74. Dean, P. et al. The cerebellar microcircuit as an adaptive filter: experimental and computational evidence. Nat. Rev. Neurosci. 11, 30–43 (2010).

    Article  CAS  PubMed  Google Scholar 

  75. Keller, G. B., Bonhoeffer, T. & Hübener, M. Sensorimotor mismatch signals in primary visual cortex of the behaving mouse. Neuron 74, 809–815 (2012).

    Article  CAS  PubMed  Google Scholar 

  76. Keller, G. B. & Hahnloser, R. H. Neural processing of auditory feedback during vocal practice in a songbird. Nature 457, 187–190 (2009).

    Article  CAS  PubMed  Google Scholar 

  77. Heindorf, M., Arber, S. & Keller, G. B. Mouse motor cortex coordinates the behavioral response to unpredicted sensory feedback. Neuron 99, 1040–1054.e5 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Moreno-Juan, V. et al. Prenatal thalamic waves regulate cortical area size prior to sensory processing. Nat. Commun. 8, 14172 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. 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 

  80. Kirkby, L. A., Sack, G. S., Firl, A. & Feller, M. B. A role for correlated spontaneous activity in the assembly of neural circuits. Neuron 80, 1129–1144 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Matsumoto, N., Barson, D., Liang, L. & Crair, M. C. Hebbian instruction of axonal connectivity by endogenous correlated spontaneous activity. Science 385, eadh7814 (2024).

    Article  CAS  PubMed  Google Scholar 

  82. Wiesel, T. N. & Hubel, D. H. Single-cell responses in striate cortex of kittens deprived of vision in one eye. J. Neurophysiol. 26, 1003–1017 (1963).

    Article  CAS  PubMed  Google Scholar 

  83. Wiesel, T. N. & Hubel, D. H. Comparison of the effects of unilateral and bilateral eye closure on cortical unit responses in kittens. J. Neurophysiol. 28, 1029–1040 (1965).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  85. 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 

  86. Yu, C. R. et al. Spontaneous neural activity is required for the establishment and maintenance of the olfactory sensory map. Neuron 42, 553–566 (2004).

    Article  CAS  PubMed  Google Scholar 

  87. Shatz, C. J. & Stryker, M. P. Prenatal tetrodotoxin infusion blocks segregation of retinogeniculate afferents. Science 242, 87–89 (1988).

    Article  CAS  PubMed  Google Scholar 

  88. Chapman, B. & Stryker, M. P. Development of orientation selectivity in ferret visual cortex and effects of deprivation. J. Neurosci. 13, 5251–5262 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Roy, A. et al. Does experience provide a permissive or instructive influence on the development of direction selectivity in visual cortex? Neural Dev. 13, 16 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Zelazo, P. R., Zelazo, N. A. & Kolb, S. ‘Walking’ in the newborn. Science 176, 314–315 (1972).

    Article  CAS  PubMed  Google Scholar 

  91. Verhage, M. et al. Synaptic assembly of the brain in the absence of neurotransmitter secretion. Science 287, 864–869 (2000).

    Article  CAS  PubMed  Google Scholar 

  92. Silver, D. et al. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science 362, 1140–1144 (2018).

    Article  CAS  PubMed  Google Scholar 

  93. Moravec, H. Mind Children: The Future of Robot and Human Intelligence (Harvard Univ. Press, 1988).

  94. Richards, B. A. et al. A deep learning framework for neuroscience. Nat. Neurosci. 22, 1761–1770 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. The new NeuroAI. Nat. Mach. Intell. 6, 245 (2024).

  96. Silva, C. G., Peyre, E. & Nguyen, L. Cell migration promotes dynamic cellular interactions to control cerebral cortex morphogenesis. Nat. Rev. Neurosci. 20, 318–329 (2019).

    Article  CAS  PubMed  Google Scholar 

  97. Knudsen, E. I. & Konishi, M. Mechanisms of sound localization in the barn owl (Tyto alba). J. Comp. Physiol. 133, 13–21 (1979).

    Article  Google Scholar 

  98. Ito, M. The molecular organization of cerebellar long-term depression. Nat. Rev. Neurosci. 3, 896–902 (2002).

    Article  CAS  PubMed  Google Scholar 

  99. Knudsen, E. I. & Knudsen, P. F. Vision calibrates sound localization in developing barn owls. J. Neurosci. 9, 3306–3313 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Lackner, J. R. Influence of abnormal postural and sensory conditions on human sensorimotor localization. Environ. Biol. Med. 2, 137–177 (1976).

    CAS  PubMed  Google Scholar 

  101. Hyde, P. S. & Knudsen, E. I. The optic tectum controls visually guided adaptive plasticity in the owl’s auditory space map. Nature 415, 73–76 (2002).

    Article  CAS  PubMed  Google Scholar 

  102. Linkenhoker, B. A. & Knudsen, E. I. Incremental training increases the plasticity of the auditory space map in adult barn owls. Nature 419, 293–296 (2002).

    Article  CAS  PubMed  Google Scholar 

  103. Gutfreund, Y., Zheng, W. & Knudsen, E. I. Gated visual input to the central auditory system. Science 297, 1556–1559 (2002).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors thank K. Miller and H. Baier for the fruitful discussions. This work was supported by New Science Microgrant to D.L.B. and by the National Institutes of Health (NIH) Grant U19NS104653, NIH Grant 1R01NS124017, National Science Foundation Grant IIS-1912293, and Simons Foundation SCGB 542973 to F.E.

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Author notes

  1. Dániel L. Barabási

    Present address: Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA

  2. André Ferreira Castro

    Present address: School of Life Sciences, Technical University of Munich, Freising, Germany

Authors and Affiliations

  1. Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK

    André Ferreira Castro

  2. Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK

    André Ferreira Castro

  3. Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA

    Florian Engert

  4. Center for Brain Science, Harvard University, Cambridge, MA, USA

    Florian Engert

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  1. Dániel L. Barabási
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D.L.B. and F.E. contributed to all aspects of the preparation of the manuscript. A.F.C. made a substantial contribution to the discussion of the content of the article and to the review and editing of the manuscript before submission.

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Correspondence to Dániel L. Barabási or Florian Engert.

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Barabási, D.L., Ferreira Castro, A. & Engert, F. Three systems of circuit formation: assembly, updating and tuning. Nat. Rev. Neurosci. 26, 232–243 (2025). https://doi.org/10.1038/s41583-025-00910-9

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