Aversive cognition and pain: from theory to neuroengineering

Aversive cognition and pain: from theory to neuroengineering
Theme: Cognition and behaviour

Tuesday 25th April, 09:30 - 11:10

Aversive cognition refers to the mental processes through which we detect, predict, control and learn from adversities, such as pain and other punishments. Aversive cognition allows us to adapt to adversities and maximize our wellbeing. How we learn from adversities can underscore resilience against the development of chronic pain, disability and affective disorders. State-of-the-art computational models of cognition consider how the brain learns to predict aversive states in order to control perception and behaviour. We present work combining Bayesian inference, reinforcement learning approaches and neuroimaging, applied to: statistical learning [FM]; priming, perceptual and associative learning [CB]; stability and generalisability of the model parameters [ADS]. These methods can be used to derive individual learning signatures, providing a fine-grained, computational phenotype of aversive cognition. These measures quantify individual differences in how people perceive and respond to aversive states, such as pain and other punishments. We will discuss how they can translate to precision medicine, improving: (1) the assessment and monitoring of chronic pain and affective disorders at scale and (2) the targeting/development of treatments. We conclude by presenting new advances in neurotechnologies (virtual reality, brain-computer interfaces) to improve how people learn from pain and other adversities [BS].

  • Deborah Talmi, University of Cambridge, UK: (non-speaking co-chair)
  • Dounia Mulders, Universite' Catholique de Louvain, Belgium: Inference and control of aversive states in the human brain
  • Ariane Delgado-Sanchez, University of Manchester, UK: Pain phenotyping using Bayesian modelling (co-chair)
  • Christopher Brown, University of Liverpool, UK: Joint modelling of priming, perceptual and aversive learning within a Bayesian framework
  • Ben Seymour, University of Oxford, UK: Neuroengineering for chronic pain

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