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How pain fools everyone: An inference to the best explanation
1School of Biomedical Sciences, University of Queensland, Brisbane 4072, Australia; Centre for Innovation in Pain and Health Research (CIPHeR), University of Queensland, Brisbane 4072, Australia.
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There is a commonly held assumption that feelings such as pain are causes of behaviour. We say we withdrew our hand from the hotplate because it hurt or that we flinched at the needle because it stung. The causal role of pain is widely implicated in theories of learning and decision-making. But what if this commonsense idea that feelings cause behaviour is just wrong? To date, there is no known mechanism for how subjectively experienced pain directly modulates neural activity and it is hard to see how there could be. There is no known mechanism by which pain could directly gate ion channels. On this basis, we contend that the real cause of behaviour is neural activity and that feelings of pain have no known causal role. This raises the question of whether pain has any function at all-i.e., whether it has causal powers or is merely epiphenomenal. Epiphenomenalism faces the intractable problem of explaining how such an attention-consuming feeling as pain could be epiphenomenal and yet still have survived evolutionary selection. In response, we infer from the available neuroscientific evidence that the best explanation is that pain has a novel, non-causal function and that decisions to act are instead caused by an internal decoding process involving threshold detection of accumulated evidence of pain rather than by pain per se. Because pain is necessarily implicated in the best explanation of subsequent decision-making, we do not conclude that pain is epiphenomenal or functionless even if it has no causal influence over decisions or subsequent actions. On this view, pain functions to mark neural pathways that are the causes of behaviour as salient, serving as a ground but not a cause of subsequent decision-making and action. This perspective has far-reaching implications for diverse fields including neuropsychiatry, biopsychosocial modelling, robotics, and brain-computer interfaces.
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