Pain processing and pain perception in the human brain: a neural signals approach

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Pain is an almost universal experience. Its importance for health, well-being and disease processes is undeniable. One can experience more or less pain, and measuring pain intensity is important in diagnosis, assessment and therapy. However, this measurement is surprisingly difficult, because pain levels depend on complex factors such as expectation, attention, and even personality. Moreover, robust, valid measures of pain intensity are elusive. Current methods, such as numerical pain rating scales, rely strongly on patients' verbal understanding - e.g., the phrase "worst pain imaginable" is generally used to define the top of the scale. Perhaps for these reasons, ratings show notoriously poor correlation with the energy of a noxious stimulus, and also with activation of putative 'pain centres' or 'pain networks' in the brain.This project develops a novel approach to understanding pain perception. Using a state-of-the-art feedback-controlled laser stimulator, we expose the skin on the back of the hand of healthy volunteers to brief, quantified pulses of radiant heat, causing a sharp 'pinprick' pain. This reflects signals in a specific neurophysiological pain pathway ("A-delta pathway"). Participants are stimulated randomly with either of two energies, both above the individual's threshold to activate the A-delta pathway. They judge whether they experienced 'higher' or 'lower' intensity. We use standard methods to calculate two distinct aspects of pain perception: the SENSITIVITY with which a person's judgements track the actual stimulation energy, and their BIAS in preferring to respond 'higher', or 'lower', irrespective of actual stimulation energy. For example, someone who simply fears strong pain might judge ALL pain stimuli as 'higher' intensity: they would then show strong bias and low sensitivity.We also record the brain activity evoked by laser stimulation, using EEG electrodes non-invasively placed on the scalp. By dividing the distribution of EEG amplitudes in two at different cutoff points, we can simulate how effective the EEG signal at that particular moment would be in classifying the higher and lower intensity stimuli. We will thus identify the components of the brain's response to noxious stimulation that best approximate the sensitivity and bias components of pain perception. This provides a novel, well-controlled, physiologically-specific, and fully objective method to search for the neural basis of pain perception. It does not require any subjective definition or instruction regarding what counts as 'pain', and merely requires participants to judge whether a stimulus is more or less intense. By testing a large sample of participants, we address individual differences between people in pain perception. We may identify psychological profiles associated with high and low pain bias, and with high and low pain sensitivity.Two further large experiments leverage these important methodological developments. Experiment 2 aims to show how our method can be used to quantify and understand the potency of a popular analgesic drug (remifentanil). Double-blind infusions of drug or placebo are compared to address whether the drug influences bias or sensitivity, and which EEG components underlie this change.Experiment 3 uses these new measurement approaches to investigate the basis of the well-known placebo effect - perhaps the most striking finding in pain research. Participants learn that a specific visual stimulus, presented before laser stimulation, predicts whether the next stimulus will be more or less intense. Again, we assess whether this predictive cue changes sensitivity or bias. We will identify the EEG components that are responsible for how the cue influences these two aspects of pain perception.Overall, the results provide a novel and objective approach to pain perception, useful for future clinical studies of pain and analgesia.