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  • Perspective
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Post-injury pain and behaviour: a control theory perspective

Abstract

Injuries of various types occur commonly in the lives of humans and other animals and lead to a pattern of persistent pain and recuperative behaviour that allows safe and effective recovery. In this Perspective, we propose a control-theoretic framework to explain the adaptive processes in the brain that drive physiological post-injury behaviour. We set out an evolutionary and ethological view on how animals respond to injury, illustrating how the behavioural state associated with persistent pain and recuperation may be just as important as phasic pain in ensuring survival. Adopting a normative approach, we suggest that the brain implements a continuous optimal inference of the current state of injury from diverse sensory and physiological signals. This drives the various effector control mechanisms of behavioural homeostasis, which span the modulation of ongoing motivation and perception to drive rest and hyper-protective behaviours. However, an inherent problem with this is that these protective behaviours may partially obscure information about whether injury has resolved. Such information restriction may seed a tendency to aberrantly or persistently infer injury, and may thus promote the transition to pathological chronic pain states.

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Fig. 1: A control perspective for injury and pain.
Fig. 2: Neural implementation and representations of injury and persistent pain.
Fig. 3: Brain oscillations that encode post-injury or pain states.
Fig. 4: Information restriction model of chronic pain.

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References

  1. Bateson, P. Assessment of pain in animals. Anim. Behav. 42, 827–839 (1991).

    Article  Google Scholar 

  2. Seymour, B. Pain: a precision signal for reinforcement learning and control. Neuron 101, 1029–1041 (2019).

    Article  CAS  PubMed  Google Scholar 

  3. Woolf, C. J. Central sensitization: implications for the diagnosis and treatment of pain. Pain 152, S2–S15 (2011).

    Article  PubMed  Google Scholar 

  4. Melzack, R. Pain — an overview. Acta Anaesthesiol. Scand. 43, 880–884 (1999).

    Article  CAS  PubMed  Google Scholar 

  5. Broom, D. M. The Evolution of Pain (Cambridge Univ. Press, 2001).

  6. Sneddon, L. U. Evolution of nociception and pain: evidence from fish models. Philos. Trans. R. Soc. B 374, 20190290 (2019).

    Article  CAS  Google Scholar 

  7. Bonavita, V. & De Simone, R. Pain as an evolutionary necessity. Neurol. Sci. 32, 61–66 (2011).

    Article  Google Scholar 

  8. Wu, Y. C., Franzenburg, S., Ribes, M. & Pita, L. Wounding response in Porifera (sponges) activates ancestral signaling cascades involved in animal healing, regeneration, and cancer. Sci. Rep. 12, 1307 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Peng, G., Shi, X. & Kadowaki, T. Evolution of TRP channels inferred by their classification in diverse animal species. Mol. Phylogene. Evol. 84, 145–157 (2015).

    Article  CAS  Google Scholar 

  10. Himmel, N. J. & Cox, D. N. Transient receptor potential channels: current perspectives on evolution, structure, function and nomenclature. Proc. R. Soc. B 287, 20201309 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Kang, K. et al. Analysis of Drosophila TRPA1 reveals an ancient origin for human chemical nociception. Nature 464, 597–600 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Anishkin, A. & Kung, C. Microbial mechanosensation. Curr. Opin. Neurobiol. 15, 397–405 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Jiang, Y., Idikuda, V., Chowdhury, S. & Chanda, B. Activation of the archaeal ion channel MthK is exquisitely regulated by temperature. eLife 9, e59055 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Capasso, L., Ganot, P., Planas-Bielsa, V., Tambutté, S. & Zoccola, D. Intracellular pH regulation: characterization and functional investigation of H+ transporters in Stylophora pistillata. BMC Mol. Cell Biol. 22, 18 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Arias-Darraz, L. et al. A transient receptor potential ion channel in Chlamydomonas shares key features with sensory transduction-associated TRP channels in mammals. Plant Cell 27, 177–188 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Meyer, J. J. & Byers, J. As good as dead? Sublethal predation facilitates lethal predation on an intertidal clam. Ecol. Lett. 8, 160–166 (2005).

    Article  Google Scholar 

  17. Wilbur, H. M. & Semlitsch, R. D. Ecological consequences of tail injury in Rana tadpoles. Copeia 1990, 18–24 (1990).

    Article  Google Scholar 

  18. Bertilsson-Friedman, P. Distribution and frequencies of shark-inflicted injuries to the endangered Hawaiian monk seal (Monachus schauinslandi). J. Zool. 268, 361–368 (2006).

    Article  Google Scholar 

  19. Mukherjee, S. & Heithaus, M. R. Dangerous prey and daring predators: a review. Biol. Rev. Camb. Philos. Soc. 88, 550–563 (2013).

    Article  PubMed  Google Scholar 

  20. Walters, E. T. & Moroz, L. L. Molluscan memory of injury: evolutionary insights into chronic pain and neurological disorders. Brain Behav. Evol. 74, 206–218 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Walters, E. T. Chronic pain, memory, and injury: evolutionary clues from snail and rat nociceptors. Int. J. Comp. Psychol. 22, 127–140 (2009).

    Article  Google Scholar 

  22. Wittenberg, N. & Baumeister, R. Thermal avoidance in Caenorhabditis elegans: an approach to the study of nociception. Proc. Natl Acad. Sci. USA 96, 10477–10482 (1999).

    Article  Google Scholar 

  23. Mackintosh, N. J. Animal Learning and Cognition (Academic Press, 2013).

  24. Kim, H., Kim, K. & Yim, J. Biosynthesis of drosopterins, the red eye pigments of Drosophila melanogaster. IURMB Life 65, 334–340 (2013).

    Article  CAS  PubMed  Google Scholar 

  25. Bolles, R. C. Species-specific defense reactions and avoidance learning. Psychol. Rev. 77, 32 (1970).

    Article  Google Scholar 

  26. Gillan, C. M., Urcelay, G. P., & Robbins, T. W. In The Wiley Handbook on the Cognitive Neuroscience of Learning (eds Murphy, R. A. & Honey, R. C.) 442–467 (Wiley-Blackwell, 2016).

  27. Walters, E. T. & Williams, A. C. D. C. Evolution of mechanisms and behaviour important for pain. Philos. Trans. R. Soc. B 374, 20190275 (2019).

    Article  CAS  Google Scholar 

  28. Lister, K. C. et al. Chronic pain produces hypervigilance to predator odor in mice. Curr. Biol. 30, R866–R867 (2020).

    Article  CAS  PubMed  Google Scholar 

  29. Morgan, M. M. & Ataras, K. Morphine restores and naloxone-precipitated withdrawal depresses wheel running in rats with hindpaw inflammation. Pharmacol. Biochem. Behav. 209, 173251 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Chen, G. et al. PD-L1 inhibits acute and chronic pain by suppressing nociceptive neuron activity via PD-1. Nat. Neurosci. 20, 917–926 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Walters, E. T. Nociceptors as chronic drivers of pain and hyperreflexia after spinal cord injury: an adaptive-maladaptive hyperfunctional state hypothesis. Front. Physiol. 3, 309 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Elwood, R. W. Discrimination between nociceptive reflexes and more complex responses consistent with pain in crustaceans. Philos. Trans. R. Soc. B 374, 20190368 (2019).

    Article  Google Scholar 

  33. Alupay, J. S., Hadjisolomou, S. P. & Crook, R. J. Arm injury produces long-term behavioral and neural hypersensitivity in octopus. Neurosci. Lett. 558, 137–142 (2014).

    Article  CAS  PubMed  Google Scholar 

  34. Crook, R. J. Behavioral and neurophysiological evidence suggests affective pain experience in octopus. iScience 24, 102229 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Birch, J., Burn, C., Schnell, A., Browning, H. & Crump, A. Review of the Evidence of Sentience in Cephalopod Molluscs and Decapod Crustaceans https://www.lse.ac.uk/business/consulting/reports/review-of-the-evidence-of-sentiences-in-cephalopod-molluscs-and-decapod-crustaceans (2021).

  36. McNamara, J. M. & Buchanan, K. L. Stress, resource allocation, and mortality. Behav. Ecol. 16, 1008–1018 (2005).

    Article  Google Scholar 

  37. Kappesser, J. The facial expression of pain in humans considered from a social perspective. Philos. Trans. R. Soc. B 374, 20190284 (2019).

    Article  Google Scholar 

  38. Ristau, C. A. In Cognitive Ethology pp. 111-146 (Psychology Press, 2013).

  39. Santiago, V. I. Painful truth: the need to re-center chronic pain on the functional role of pain. J. Pain Res. 15, 497–512 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wall, P. D. On the relation of injury to pain. Pain 6, 253–264 (1979).

    Article  PubMed  Google Scholar 

  41. Bolles, R. C. & Fanselow, M. S. A perceptual-defensive-recuperative model of fear and pain. Behav. Brain Sci. 3, 291–323 (1980).

    Article  Google Scholar 

  42. Walters, E. T. Injury-related behavior and neuronal plasticity: an evolutionary perspective on sensitization, hyperalgesia, and analgesia. Int. Rev. Neurobiol. 36, 325–427 (1994).

    Article  CAS  PubMed  Google Scholar 

  43. Młynarski, W., Hledík, M., Sokolowski, T. R. & Tkačik, G. Statistical analysis and optimality of neural systems. Neuron 109, 1227–1241 (2021).

    Article  PubMed  Google Scholar 

  44. Parker, G. A. & Smith, J. M. Optimality theory in evolutionary biology. Nature 348, 27–33 (1990).

    Article  Google Scholar 

  45. Marr, D. Vision (MIT Press, 1982).

  46. Elfwing, S., Uchibe, E., Doya, K. & Christensen, H. I. Co-evolution of shaping rewards and meta-parameters in reinforcement learning. Adapt. Behav. 16, 400–412 (2008).

    Article  Google Scholar 

  47. Singh, S., Lewis, R. L., Barto, A. G. & Sorg, J. Intrinsically motivated reinforcement learning: an evolutionary perspective. IEEE Trans. Auton. Ment. Dev. 2, 70–82 (2010).

    Article  CAS  Google Scholar 

  48. Michel, M. & Lau, H. On the dangers of conflating strong and weak versions of a theory of consciousness. Philos. Mind Sci. 1, 10.33735/phimisci.2020.II.54 (2020).

  49. Jepma, M. et al. Behavioural and neural evidence for self-reinforcing expectancy effects on pain. Nat. Hum. Behav. 2, 838–855 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Smith, R., Friston, K. J. & Whyte, C. J. A step-by-step tutorial on active inference and its application to empirical data. J. Math. Psychol. 107, 102632 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Tuttle, A. H. et al. A deep neural network to assess spontaneous pain from mouse facial expressions. Mol. Pain 14, 1744806918763658 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Jones, J. M. et al. A machine-vision approach for automated pain measurement at millisecond timescales. eLife 9, e57258 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Frank, M. G., Fonken, L. K., Watkins, L. R., & Maier, S. F. In Seminars in Cell & Developmental Biology Vol. 94, 176-185 (Academic Press, 2019).

  54. Grace, P. M., Hutchinson, M. R., Maier, S. F. & Watkins, L. R. Pathological pain and the neuroimmune interface. Nat. Rev. Immunol. 14, 217–231 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Senkowski, D., Höfle, M. & Engel, A. K. Crossmodal shaping of pain: a multisensory approach to nociception. Trends Cogn. Sci. 18, 319–327 (2014).

    Article  PubMed  Google Scholar 

  56. Vastano, R., Costantini, M. & Widerstrom-Noga, E. Maladaptive reorganization following SCI: the role of body representation and multisensory integration. Prog. Neurobiol. 208, 102179 (2022).

    Article  PubMed  Google Scholar 

  57. Grossman, C. D. & Cohen, J. Y. Neuromodulation and neurophysiology on the timescale of learning and decision-making. Annu. Rev. Neurosci. 45, 317–337 (2022).

    Article  PubMed  Google Scholar 

  58. Keramati, M. & Gutkin, B. Homeostatic reinforcement learning for integrating reward collection and physiological stability. eLife 3, e04811 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Navratilova, E. & Porreca, F. Reward and motivation in pain and pain relief. Nat. Neurosci. 17, 1304–1312 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Dantzer, R., Heijnen, C. J., Kavelaars, A., Laye, S. & Capuron, L. The neuroimmune basis of fatigue. Trends Neurosci. 37, 39–46 (2014).

    Article  CAS  PubMed  Google Scholar 

  61. Khandaker, G., Harrison, N., Bullmore, E., & Dantzer, R. Textbook of Immunopsychiatry (Cambridge Univ. Press, 2021).

  62. Lopes, P. C., French, S. S., Woodhams, D. C. & Binning, S. A. Sickness behaviors across vertebrate taxa: proximate and ultimate mechanisms. J. Exp. Biol. 224, jeb225847 (2021).

    Article  PubMed  Google Scholar 

  63. Butler, R. K. & Finn, D. P. Stress-induced analgesia. Prog. Neurobiol. 88, 184–202 (2009).

    Article  CAS  PubMed  Google Scholar 

  64. Vachon-Presseau, E. Effects of stress on the corticolimbic system: implications for chronic pain. Prog. Neuropsychopharmacol. Biol. Psychiatry 87, 216–223 (2018).

    Article  CAS  PubMed  Google Scholar 

  65. Kavaliers, M. Evidence for opioid and non-opioid forms of stress-induced analgesia in the snail, Cepaea nemoralis. Brain Res. 410, 111–115 (1987).

    Article  CAS  PubMed  Google Scholar 

  66. Rodgers, R. J. & Randall, J. I. Defensive analgesia in rats and mice. Psychol. Rec. 37, 335–347 (1987).

    Google Scholar 

  67. Marek, P. & Szacki, J. Environmentally induced analgesia in wild mice: comparison with laboratory mice. Physiol. Zool. 61, 330–332 (1988).

    Article  Google Scholar 

  68. Saksida, L. M., Galea, L. A. M. & Kavaliers, M. Predator-induced opioid and non-opioid mediated analgesia in young meadow voles: sex differences and developmental changes. Brain Res 617, 214–219 (1993).

    Article  CAS  PubMed  Google Scholar 

  69. Kuner, R. & Flor, H. Structural plasticity and reorganisation in chronic pain. Nat. Rev. Neurosci. 18, 20–30 (2017).

    Article  CAS  Google Scholar 

  70. Sandkuhler, J. Models and mechanisms of hyperalgesia and allodynia. Physiol. Rev. 89, 707–758 (2009).

    Article  PubMed  Google Scholar 

  71. Takeuchi, Y., Osaki, H., Yagasaki, Y., Katayama, Y. & Miyata, M. Afferent fiber remodeling in the somatosensory thalamus of mice as a neural basis of somatotopic reorganization in the brain and ectopic mechanical hypersensitivity after peripheral sensory nerve injury. eNeuro 4, ENEURO.0345-16.2017 (2017).

  72. Jutzeler, C. R., Freund, P., Huber, E., Curt, A. & Kramer, J. L. K. Neuropathic pain and functional reorganization in the primary sensorimotor cortex after spinal cord injury. J. Pain 16, 1256–1267 (2015).

    Article  PubMed  Google Scholar 

  73. Huynh, V. et al. Supraspinal nociceptive networks in neuropathic pain after spinal cord injury. Hum. Brain Mapp. 42, 3733–3749 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Contreras-Hernández, E. et al. Supraspinal modulation of neuronal synchronization by nociceptive stimulation induces an enduring reorganization of dorsal horn neuronal connectivity. J. Physiol. 596, 1747–1776 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Courtine, G. et al. Recovery of supraspinal control of stepping via indirect propriospinal relay connections after spinal cord injury. Nat. Med. 14, 69–74 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Martelli, D., Yao, S. T., McKinley, M. J. & McAllen, R. M. Reflex control of inflammation by sympathetic nerves, not the vagus. J. Physiol. 592, 1677–1686 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Denrell, J. Adaptive learning and risk taking. Psychol. Rev. 114, 177 (2007).

    Article  PubMed  Google Scholar 

  78. Wang, J. X. Meta-learning in natural and artificial intelligence. Curr. Opin. Behav. Sci. 38, 90–95 (2021).

    Article  Google Scholar 

  79. Eppinger, B., Goschke, T. & Musslick, S. Meta-control: from psychology to computational neuroscience. Cogn. Affect. Behav. Neurosci. 21, 447–452 (2021).

    Article  PubMed  Google Scholar 

  80. Marković, D., Goschke, T. & Kiebel, S. J. Meta-control of the exploration-exploitation dilemma emerges from probabilistic inference over a hierarchy of time scales. Cogn. Affect. Behav. Neurosci. 21, 509–533 (2021).

    Article  PubMed  Google Scholar 

  81. Rudy, T. E., Kerns, R. D. & Turk, D. C. Chronic pain and depression: toward a cognitive-behavioral mediation model. Pain 35, 129–140 (1988).

    Article  PubMed  Google Scholar 

  82. Barrett, L. & Simmons, W. Interoceptive predictions in the brain. Nat. Rev. Neurosci. 16, 419–429 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Fermin, A. S., Friston, K. & Yamawaki, S. An insula hierarchical network architecture for active interoceptive inference. R. Soc. Open. Sci. 9, 220226 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Namkung, H., Kim, S.-H. & Sawa, A. The insula: an underestimated brain area in clinical neuroscience, psychiatry, and neurology. Trends Neurosci. 40, 200–207 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Craig, A. How do you feel — now? The anterior insula and human awareness. Nat. Rev. Neurosci. 10, 59–70 (2009).

    Article  CAS  PubMed  Google Scholar 

  86. Gogolla, N. The insular cortex. Curr. Biol. 27, R580–R586 (2017).

    Article  CAS  PubMed  Google Scholar 

  87. Craig, A. D., Chen, K., Bandy, D. & Reiman, E. M. Thermosensory activation of insular cortex. Nat. Neurosci. 3, 184–190 (2000).

    Article  CAS  PubMed  Google Scholar 

  88. Wright, P., He, G., Shapira, N. A., Goodman, W. K. & Liu, Y. Disgust and the insula: fMRI responses to pictures of mutilation and contamination. Neuroreport 15, 2347–2351 (2004).

    Article  CAS  PubMed  Google Scholar 

  89. Zhou, F. et al. A distributed fMRI-based signature for the subjective experience of fear. Nat. Commun. 12, 6643 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Koren, T. et al. Insular cortex neurons encode and retrieve specific immune responses. Cell 184, 5902–5915 (2021).

    Article  CAS  PubMed  Google Scholar 

  91. Katayama, O. et al. Neural activities behind the influence of sensorimotor incongruence on dysesthesia and motor control. Neurosci. Lett. 698, 19–26 (2019).

    Article  CAS  PubMed  Google Scholar 

  92. Evrard, H. C. The organization of the primate insular cortex. Front. Neuroanat. 13, 43 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Gehrlach, D. A. et al. Aversive state processing in the posterior insular cortex. Nat. Neurosci. 22, 1424–1437 (2019).

    Article  CAS  PubMed  Google Scholar 

  94. Krockenberger, M., Saleh, T. O., Logothetis, N. K. & Evrard, H. C. Connection “stripes” in the primate insula. Preprint at bioRxiv https://doi.org/10.1101/2020.11.03.361055 (2020).

    Article  Google Scholar 

  95. Uddin, L. Q., Nomi, J. S., Hebert-Seropian, B., Ghaziri, J. & Boucher, O. Structure and function of the human insula. J. Clin. Neurophysiol. 34, 300–306 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  96. Koban, L. et al. The self in context: brain systems linking mental and physical health. Nat. Rev. Neurosci. 22, 309–322 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Shackman, A. J. et al. The integration of negative affect, pain and cognitive control in the cingulate cortex. Nat. Rev. Neurosci. 12, 154–167 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Meda, K. S. et al. Microcircuit mechanisms through which mediodorsal thalamic input to anterior cingulate cortex exacerbates pain-related aversion. Neuron 102, 944–959 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Rao, R. P. Bayesian computation in recurrent neural circuits. Neural Comput. 16, 1–38 (2004).

    Article  PubMed  Google Scholar 

  100. Orhan, A. & Ma, W. J. Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback. Nat. Commun. 8, 138 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Sohn, H. & Narain, D. Neural implementations of Bayesian inference. Curr. Opin. Neurobiol. 70, 121–129 (2021).

    Article  CAS  PubMed  Google Scholar 

  102. Pachitariu, M., Petreska, B., & Sahani, M. Recurrent linear models of simultaneously-recorded neural populations. Advances in Neural Information Processing Systems (MIT Press, 2013).

  103. Pecevski, D. & Maass, W. Learning probabilistic inference through spike-timing-dependence plasticity. eNeuro 3, ENEURO.0048-15.2016 (2016).

  104. Aitchison, L. et al. Synaptic plasticity as Bayesian inference. Nat. Neurosci. 24, 565–571 (2021).

    Article  CAS  PubMed  Google Scholar 

  105. Pitkow, X. & Angelaki, D. E. Inference in the brain: statistics flowing in redundant population codes. Neuron 94, 943–953 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Bastos, A. M. et al. Canonical microcircuits for predictive coding. Neuron 76, 695–711 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Song, Y. et al. Predictive coding models for pain perception. J. Comp. Neurosci. 49, 107–127 (2021).

    Article  Google Scholar 

  108. Bannister, K. Descending pain modulation: influence and impact. Curr. Opin. Physiol. 11, 62–66 (2019).

    Article  Google Scholar 

  109. Wright, H. et al. Heightened eating drive and visual food stimuli attenuate central nociceptive processing. J. Neurophysiol. 113, 1323–1333 (2015).

    Article  PubMed  Google Scholar 

  110. Wright, H. et al. Differential effects of hunger and satiety on insular cortex and hypothalamic functional connectivity. Eur. J. Neurosci. 43, 1181–1189 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  111. Zhou, W. et al. Activation of orexin system facilitates anesthesia emergence and pain control. Proc. Natl Acad. Sci. USA 115, E10740–E10747 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Ito, H. et al. Chronic pain recruits hypothalamic dynorphin/kappa opioid receptor signalling to promote wakefulness and vigilance. Brain https://doi.org/10.1093/brain/awac153 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  113. Ahmadi-Soleimani, S. M. et al. Coregulation of sleep-pain physiological interplay by orexin system: An unprecedented review. Behavioural Brain Res. 391, 112650 (2020).

    Article  CAS  Google Scholar 

  114. Phua, S. C. et al. A distinct parabrachial–to–lateral hypothalamus circuit for motivational suppression of feeding by nociception. Sci. Adv. 7, eabe4323 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Schiller, M., Ben-Shaanan, T. L. & Rolls, A. Neuronal regulation of immunity: why, how and where? Nat. Rev. Immunol. 21, 20–36 (2021).

    Article  CAS  PubMed  Google Scholar 

  116. Seymour, B. et al. Opponent appetitive-aversive neural processes underlie predictive learning of pain relief. Nat. Neurosci. 8, 1234–1240 (2005).

    Article  CAS  PubMed  Google Scholar 

  117. Zhang, S. et al. The control of tonic pain by active relief learning. eLife 7, e31949 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  118. Baliki, M. et al. Corticostriatal functional connectivity predicts transition to chronic back pain. Nat. Neurosci. 15, 1117–1119 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Buzsaki, G. & Draguhn, A. Neuronal oscillations in cortical networks. Science 304, 1926–1929 (2004).

    Article  CAS  PubMed  Google Scholar 

  120. Muller, L. et al. Cortical travelling waves: mechanisms and computational principles. Nat. Rev. Neurosci. 19, 255–268 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Buzsaki, G. Theta oscillations in the hippocampus. Neuron 33, 325–340 (2002).

    Article  CAS  PubMed  Google Scholar 

  122. Tendler, A. & Wagner, S. Different types of theta rhythmicity are induced by social and fearful stimuli in a network associated with social memory. eLife 4, e03614 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Stern, J., Jeanmonod, D. & Sarnthein, J. Persistent EEG overactivation in the cortical pain matrix of neurogenic pain patients. Neuroimage 31, 721–731 (2006).

    Article  PubMed  Google Scholar 

  124. Sarnthein, J., Stern, J., Aufenberg, C., Rousson, V. & Jeanmonod, D. Increased EEG power and slowed dominant frequency in patients with neurogenic pain. Brain 129, 55–64 (2006).

    Article  PubMed  Google Scholar 

  125. Kisler, L. B. et al. Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component. Neuroimage Clin. 26, 102241 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  126. Kim, J. A. et al. Neuropathic pain and pain interference are linked to alpha-band slowing and reduced beta-band magnetoencephalography activity within the dynamic pain connectome in patients with multiple sclerosis. Pain 160, 187–197 (2019).

    Article  PubMed  Google Scholar 

  127. Tan, L. L., Oswald, M. J. & Kuner, R. Neurobiology of brain oscillations in acute and chronic pain. Trends Neurosci. 44, 629–642 (2021).

    Article  CAS  PubMed  Google Scholar 

  128. Leblanc, B. W., Lii, T. R., Silverman, A. E., Alleyne, R. T. & Saab, C. Y. Cortical theta is increased while thalamocortical coherence is decreased in rat models of acute and chronic pain. Pain 155, 773–782 (2014).

    Article  PubMed  Google Scholar 

  129. Iwamoto, S., Tamura, M. & Nawano, M. Dynamics of neuronal oscillations underlying nociceptive response in the mouse primary somatosensory cortex. Sci. Rep. 11, 1667 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Taesler, P. & Rose, M. Prestimulus theta oscillations and connectivity modulate pain perception. J. Neurosci. 36, 5026–5033 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Walton, K. D., Dubois, M. & Llinas, R. R. Abnormal thalamocortical activity in patients with complex regional pain syndrome (CRPS) type I. Pain 150, 41–51 (2010).

    Article  CAS  PubMed  Google Scholar 

  132. Edhi, M. M. et al. Time-dynamic pulse modulation of spinal cord stimulation reduces mechanical hypersensitivity and spontaneous pain in rats. Sci. Rep. 10, 20358 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Taesler, P. & Rose, M. The modulation of neural insular activity by a brain computer interface differentially affects pain discrimination. Sci. Rep. 11, 9795 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Das, A. et al. Spontaneous neuronal oscillations in the human insula are hierarchically organized traveling waves. eLife 11, e76702 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Liberati, G. et al. Gamma-band oscillations preferential for nociception can be recorded in the human insula. Cereb. Cortex 28, 3650–3664 (2018).

    Article  PubMed  Google Scholar 

  136. Gélébart, J., Garcia-Larrea, L. & Frot, M. Amygdala and anterior insula control the passage from nociception to pain.Cereb. Cortex. 33, 3538–3547 (2023).

    Article  PubMed  Google Scholar 

  137. Zhang, H., Watrous, A. J., Patel, A. & Jacobs, J. Theta and alpha oscillations are traveling waves in the human neocortex. Neuron 98, 1269–1281 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Bahramisharif, A. et al. Propagating neocortical gamma bursts are coordinated by traveling alpha waves. J. Neurosci. 33, 18849–18854 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Menon, V. & Uddin, L. Q. Saliency, switching, attention and control: a network model of insula function. Brain Struct. Funct. 214, 655–667 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  140. Segerdahl, A. R., Mezue, M., Okell, T. W., Farrar, J. T. & Tracey, I. The dorsal posterior insula subserves a fundamental role in human pain. Nat. Neurosci. 18, 499–500 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Huang, Z. et al. Anterior insula regulates brain network transitions that gate conscious access. Cell Rep. 35, 109081 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Chouchou, F. et al. How the insula speaks to the heart: cardiac responses to insular stimulation in humans. Hum. Brain Mapp. 40, 2611–2622 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  143. Apkarian, A. V., Baliki, M. N. & Geha, P. Y. Towards a theory of chronic pain. Prog. Neurobiol. 87, 81–97 (2009).

    Article  PubMed  Google Scholar 

  144. Crombez, G., Eccleston, C., Van Damme, S., Vlaeyen, J. W. S. & Karoly, P. Fear-avoidance model of chronic pain: the next generation. Clin. J. Pain. 28, 475–483 (2012).

    Article  PubMed  Google Scholar 

  145. Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N. & Turk, D. C. The biopsychosocial approach to chronic pain: scientific advances and future directions. Psychol. Bull. 133, 581 (2007).

    Article  PubMed  Google Scholar 

  146. Meulders, A. From fear of movement-related pain and avoidance to chronic pain disability: a state-of-the-art review. Curr. Opin. Behav. Sci. 26, 130–136 (2019).

    Article  Google Scholar 

  147. Leeuw, M. et al. The fear-avoidance model of musculoskeletal pain: current state of scientific evidence. J. Behav. Med. 30, 77–94 (2007).

    Article  PubMed  Google Scholar 

  148. Thapa, T., Graven-Nielsen, T. & Schabrun, S. M. Aberrant plasticity in musculoskeletal pain: a failure of homeostatic control? Exp. Brain Res. 239, 1317–1326 (2021).

    Article  CAS  PubMed  Google Scholar 

  149. Zaman, J., Vlaeyen, J. W., Van Oudenhove, L., Wiech, K. & Van Diest, I. Associative fear learning and perceptual discrimination: a perceptual pathway in the development of chronic pain. Neurosci. Biobehav. Rev. 51, 118–125 (2015).

    Article  PubMed  Google Scholar 

  150. Flor, H. Maladaptive plasticity, memory for pain and phantom limb pain: review and suggestions for new therapies. Expert Rev. Neurother. 8, 809–818 (2008).

    Article  PubMed  Google Scholar 

  151. Arendt-Nielsen, L., Graven-Nielsen, T., Svarrer, H. & Svensson, P. The influence of low back pain on muscle activity and coordination during gait: a clinical and experimental study. Pain 64, 231–240 (1996).

    Article  PubMed  Google Scholar 

  152. Nees, F. & Becker, S. Psychological processes in chronic pain: influences of reward and fear learning as key mechanisms–behavioral evidence, neural circuits, and maladaptive changes. Neuroscience 387, 72–84 (2018).

    Article  CAS  PubMed  Google Scholar 

  153. Neugebauer, V. et al. Amygdala, neuropeptides, and chronic pain-related affective behaviors. Neuropharmacology 170, 108052 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Edwards, R. R., Dworkin, R. H., Sullivan, M. D., Turk, D. C. & Wasan, A. D. The role of psychosocial processes in the development and maintenance of chronic pain. J. Pain 17, T70–T92 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  155. Staud, R. Abnormal endogenous pain modulation is a shared characteristic of many chronic pain conditions. Expert Rev. Neurother. 12, 577–585 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  156. Bushnell, M. C., Čeko, M. & Low, L. A. Cognitive and emotional control of pain and its disruption in chronic pain. Nat. Rev. Neurosci. 14, 502–511 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Chapman, C. R. & Vierck, C. J. The transition of acute postoperative pain to chronic pain: an integrative overview of research on mechanisms. J. Pain. 18, 359 (2017).

    Article  Google Scholar 

  158. Friston, K. Computational psychiatry: from synapses to sentience. Mol. Psychiatry https://doi.org/10.1038/s41380-022-01743-z (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  159. Tabor, A. & Burr, C. Bayesian learning models of pain: a call to action. Curr. Opin. Behav. Sci. 26, 54–61 (2019).

    Article  Google Scholar 

  160. Walters, E. T. Adaptive mechanisms driving maladaptive pain: how chronic ongoing activity in primary nociceptors can enhance evolutionary fitness after severe injury. Philos. Trans. R. Soc. B 374, 20190277 (2019).

    Article  CAS  Google Scholar 

  161. Fields, H. L. How expectations influence pain. Pain 159, S3–S10 (2018).

    Article  PubMed  Google Scholar 

  162. Kato, F., Sugimura, Y. K. & Takahashi, Y. Pain-associated neural plasticity in the parabrachial to central amygdala circuit: pain changes the brain, and the brain changes the pain. Adv. Exp. Med. Biol. 1099, 157–166 (2018).

    Article  CAS  PubMed  Google Scholar 

  163. Yeh, L. F., Watanabe, M., Sulkes-Cuevas, J. & Johansen, J. P. Dysregulation of aversive signaling pathways: a novel circuit endophenotype for pain and anxiety disorders. Curr. Opin. Neurobiol. 48, 37–44 (2018).

    Article  CAS  PubMed  Google Scholar 

  164. Crook, R. J., Lewis, T., Hanlon, R. T. & Walters, E. T. Peripheral injury produces long-term sensitization of responses to tactile and visual stimuli in squid, Loligo pealei. J. Exp. Biol. 214, 3173–3185 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  165. Crook, R. J., Dickson, K. D., Hanlon, R. T. & Walters, E. T. Nociceptive sensitization reduces predation risk. Curr. Biol. 24, 1121–1125 (2014).

    Article  CAS  PubMed  Google Scholar 

  166. Howard, R., Lopes, L., Lardie, C., Perez, P. V. & Crook, R. J. Early-life injury produces life-long neural hyperexcitability, cognitive deficit and altered defensive behavior in squid Euprymna scolopes. Philos. Trans. R. Soc. B 374, 281–289 (2019).

    Article  Google Scholar 

  167. Crook, R. J., Hanlon, R. T. & Walters, E. T. Squid have nociceptors that display long term sensitization and spontaneous activity after bodily injury. J. Neurosci. 33, 10021–10026 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Bazarini, S. & Crook, R. J. Environmental estrogen exposure disrupts sensory processing and nociceptive plasticity in the cephalopod Euprymna scolopes. J. Exp. Biol. 223, jeb218008 (2020).

    Article  PubMed  Google Scholar 

  169. Oshima, M. et al. Peripheral injury alters schooling decisions in injured squid. Behav. Process. 128, 89–95 (2016).

    Article  Google Scholar 

  170. Kalman, R. E. Mathematical description of linear dynamical systems. SIAM J. Ser. A Control. 1, 152–192 (1963).

    Google Scholar 

  171. Pavon, M. & Wets, R. J.-B. The duality between estimation and control from a variational viewpoint: the discrete time case. Math. Program. Study 18, 1–11 (1982).

    Article  Google Scholar 

  172. Todorov, E. In Bayesian Brain: Probabilistic Approaches to Neural Coding (eds Doya, K., Ishi, S., Pouget, A. & Rao, R. P. N.) 12 (MIT Press, 2006).

  173. Suen, J. Y. & Navlakha, S. A feedback control principle common to several biological and engineered systems. J. R. Soc. Interface 19, 20210711 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  174. Levine, S. Reinforcement learning and control as probabilistic inference: tutorial and review. Preprint at arXiv https://doi.org/10.48550/arXiv.1805.00909 (2018).

    Article  Google Scholar 

  175. Attias, H. In Proceedings of the 9th International Workshop on Artificial Intelligence and Statistics, PMLR R4:9-16 (2003).

  176. Todorov, E. Efficient computation of optimal actions. Proc. Natl Acad. Sci. USA 106, 11478–11483 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Tschantz, A., Seth, A. K. & Buckley, C. L. Learning action-oriented models through active inference. PLoS Comput. Biol. 16, e1007805 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  178. Millidge, B., Tschantz, A., Seth, A. K., Buckley, C. L. In Active Inference (eds Verbelen, T., Lanilos, P., Buckley, C. L. & De Boom, C.) 3-11 (Springer, 2020).

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Acknowledgements

We thank P. Mahajan for valuable feedback and comments. The work was partially supported by the US National Science Foundation (CBET-1835000 to Z.S.C. and IOS-2047331 to R.J.C.), the US National Institutes of Health (NS121776 and DA056394 to Z.S.C.), the Wellcome Trust (214251), Versus Arthritis (21357, 21192), the Institute of Information & Communications Technology Planning & Evaluation (IITP) (2019-0-01371), and EPSRC EP/W03509X/1 to B.S., and the Frontiers Group of the Paul G. Allen Foundation to R.J.C.

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Seymour, B., Crook, R.J. & Chen, Z.S. Post-injury pain and behaviour: a control theory perspective. Nat Rev Neurosci 24, 378–392 (2023). https://doi.org/10.1038/s41583-023-00699-5

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