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      Placebos in chronic pain: evidence, theory, ethics, and use in clinical practice

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          ABSTRACT

          Despite their ubiquitous presence, placebos and placebo effects retain an ambiguous and unsettling presence in biomedicine. Specifically focused on chronic pain, this review examines the effect of placebo treatment under three distinct frameworks: double blind, deception, and open label honestly prescribed. These specific conditions do not necessarily differentially modify placebo outcomes. Psychological, clinical, and neurological theories of placebo effects are scrutinized. In chronic pain, conscious expectation does not reliably predict placebo effects. A supportive patient-physician relationship may enhance placebo effects. This review highlights “predictive coding” and “bayesian brain” as emerging models derived from computational neurobiology that offer a unified framework to explain the heterogeneous evidence on placebos. These models invert the dogma of the brain as a stimulus driven organ to one in which perception relies heavily on learnt, top down, cortical predictions to infer the source of incoming sensory data. In predictive coding/bayesian brain, both chronic pain (significantly modulated by central sensitization) and its alleviation with placebo treatment are explicated as centrally encoded, mostly non-conscious, bayesian biases. The review then evaluates seven ways in which placebos are used in clinical practice and research and their bioethical implications. In this way, it shows that placebo effects are evidence based, clinically relevant, and potentially ethical tools for relieving chronic pain.

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          Interoceptive predictions in the brain.

          Intuition suggests that perception follows sensation and therefore bodily feelings originate in the body. However, recent evidence goes against this logic: interoceptive experience may largely reflect limbic predictions about the expected state of the body that are constrained by ascending visceral sensations. In this Opinion article, we introduce the Embodied Predictive Interoception Coding model, which integrates an anatomical model of corticocortical connections with Bayesian active inference principles, to propose that agranular visceromotor cortices contribute to interoception by issuing interoceptive predictions. We then discuss how disruptions in interoceptive predictions could function as a common vulnerability for mental and physical illness.
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            How to grow a mind: statistics, structure, and abstraction.

            In coming to understand the world-in learning concepts, acquiring language, and grasping causal relations-our minds make inferences that appear to go far beyond the data available. How do we do it? This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of flexibly structured representations can address some of the deepest questions about the nature and origins of human thought: How does abstract knowledge guide learning and reasoning from sparse data? What forms does our knowledge take, across different domains and tasks? And how is that abstract knowledge itself acquired?
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              Shape shifting pain: chronification of back pain shifts brain representation from nociceptive to emotional circuits.

              Chronic pain conditions are associated with abnormalities in brain structure and function. Moreover, some studies indicate that brain activity related to the subjective perception of chronic pain may be distinct from activity for acute pain. However, the latter are based on observations from cross-sectional studies. How brain activity reorganizes with transition from acute to chronic pain has remained unexplored. Here we study this transition by examining brain activity for rating fluctuations of back pain magnitude. First we compared back pain-related brain activity between subjects who have had the condition for ∼2 months with no prior history of back pain for 1 year (early, acute/subacute back pain group, n = 94), to subjects who have lived with back pain for >10 years (chronic back pain group, n = 59). In a subset of subacute back pain patients, we followed brain activity for back pain longitudinally over a 1-year period, and compared brain activity between those who recover (recovered acute/sub-acute back pain group, n = 19) and those in which the back pain persists (persistent acute/sub-acute back pain group, n = 20; based on a 20% decrease in intensity of back pain in 1 year). We report results in relation to meta-analytic probabilistic maps related to the terms pain, emotion, and reward (each map is based on >200 brain imaging studies, derived from neurosynth.org). We observed that brain activity for back pain in the early, acute/subacute back pain group is limited to regions involved in acute pain, whereas in the chronic back pain group, activity is confined to emotion-related circuitry. Reward circuitry was equally represented in both groups. In the recovered acute/subacute back pain group, brain activity diminished in time, whereas in the persistent acute/subacute back pain group, activity diminished in acute pain regions, increased in emotion-related circuitry, and remained unchanged in reward circuitry. The results demonstrate that brain representation for a constant percept, back pain, can undergo large-scale shifts in brain activity with the transition to chronic pain. These observations challenge long-standing theoretical concepts regarding brain and mind relationships, as well as provide important novel insights regarding definitions and mechanisms of chronic pain.
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                Author and article information

                Journal
                BMJ
                BMJ
                BMJ
                1756-1833
                July 20 2020
                : m1668
                Article
                10.1136/bmj.m1668
                32690477
                f2b03624-7d87-4ec4-859a-7a957f1ddd27
                © 2020

                http://www.bmj.com/company/legal-information/terms-conditions/legal-information/tdm-licencepolicy

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