Evan J. Livesey’s research while affiliated with The University of Sydney and other places

When sensory inputs can be predicted by an organism's own actions or external environmental cues, neural activity is often attenuated compared to sensory inputs that are unpredictable. We have recently demonstrated that attenuation to predictable inputs is also observed when stimulating the motor system with transcranial magnetic stimulation (TMS). Akin to sensory attenuation, predictable TMS excites the motor system less effectively than unpredicted TMS. However, it remains unclear whether these motor prediction signals are related to, or even dependent on, sensory prediction. Using dual-site TMS to target two brain regions, we arranged different warning cues to predict different regions of stimulation and measured motor attenuation using motor-evoked potentials. We found that expecting TMS over the motor cortex produced stronger attenuation than expecting TMS over a non-motor region, confirming that the attenuation observed is directly linked to activation of the motor system and not due to the sensory by-products of TMS. Using combined TMS-EEG, we measured motor attenuation with motor-evoked potentials, and simultaneously measured sensory attenuation to the sound of TMS (a coil "click") with auditory-evoked potentials. We found that both motor and auditory potentials were attenuated to predictable TMS compared to unpredictable TMS. Critically, the magnitude of auditory attenuation predicted the magnitude of motor attenuation. Our results reveal a close correspondence between error processing in the sensory and motor systems. The findings provide compelling evidence that predictive coding is governed by domain-general properties across distinct neural systems, which share common mechanisms responsible for all forms of predictive learning.

The learned predictiveness effect refers to the tendency for predictive cues to attract greater attention and show faster learning in subsequent tasks. However, in typical designs, the predictiveness of each cue (its objective cue–outcome correlation) is confounded with the degree to which it is informative for making the correct response on each trial (a feature we term choice relevance). In four experiments, we tested the unique contributions of cue–outcome correlation and choice relevance to the learned predictiveness effect by manipulating the outcome choices available on each trial. Experiments 1A and 1B compared two sets of partially predictive cues and found that participants learned more in a transfer phase about the set of cues that were previously choice-relevant. Experiments 2A and 2B used a design in which the cue–outcome correlation was stronger for one set of cues (perfect predictors) than the other set (imperfect predictors). Manipulating the choice relevance of the imperfect predictors in this design did not influence the magnitude of the learning bias toward the perfect predictor. Unlike cue–outcome correlation, choice relevance did not seem to correspond to biases in eye-gaze, suggesting that it operates via a distinct mechanism. Simulations with a modified EXIT model successfully predicted cue–outcome correlation and choice relevance effects by assuming that participants update learning for present outcomes only, but incorrectly predicted additive effects. We conclude that cue–outcome correlation and choice relevance are important factors that can lead to biases in future learning; both were individually sufficient but neither was necessary.

People tend to overestimate the efficacy of an ineffective treatment when they experience the treatment and its supposed outcome co-occurring frequently. This is referred to as the outcome density effect. Here, we attempted to improve the accuracy of participants’ assessments of an ineffective treatment by instructing them about the scientific practice of comparing treatment effects against a relevant base-rate, i.e., when no treatment is delivered. The effect of these instructions was assessed in both a trial-by-trial contingency learning task, where cue administration was either decided by the participant (Experiments 1 & 2) or pre-determined by the experimenter (Experiment 3), as well as in summary format where all information was presented on a single screen (Experiment 4). Overall, we found two means by which base-rate instructions influence efficacy ratings for the ineffective treatment: 1) When information was presented sequentially, the benefit of base-rate instructions on illusory belief was mediated by reduced sampling of cue-present trials, and 2) When information was presented in summary format, we found a direct effect of base-rate instruction on reducing causal illusion. Together, these findings suggest that simple instructions on the scientific method were able to decrease participants’ (over-)weighting of cue-outcome coincidences when making causal judgements, as well as decrease their tendency to over-sample cue-present events. However, the effect of base-rate instructions on correcting illusory beliefs was incomplete, and participants still showed illusory causal judgements when the probability of the outcome occurring was high. Thus, simple textual information about assessing causal relationships is partially effective in influencing people’s judgements of treatment efficacy, suggesting an important role of scientific instruction in debiasing cognitive errors.

Nocebo hyperalgesia is a pervasive problem in which the treatment context triggers negative expectations that exacerbate pain. Thus, developing ethical strategies to mitigate nocebo hyperalgesia is crucial. Emerging research suggests that choice has the capacity to reduce nocebo side effects, but choice effects on nocebo hyperalgesia have not been explored. This study investigated the impact of choice on conditioned nocebo hyperalgesia using a well-established electrocutaneous pain paradigm where increases in noxious stimulation were surreptitiously paired with the activation of a sham device. In study 1, healthy volunteers (N = 104) were randomised to choice over (nocebo) treatment administration, nocebo administration without choice, or a natural history control group. Nocebo hyperalgesia was greater for those with choice than no choice, suggesting that choice increased rather than diminished nocebo hyperalgesia. Study 2 tested whether providing positive information about the benefits of choice in coping with pain could counteract heightened nocebo hyperalgesia caused by choice. A different sample of healthy adults (N = 137) were randomised to receive nocebo treatment with choice and positive choice information, choice only, or no choice. The positive choice information failed to attenuate the effect of choice on nocebo hyperalgesia. The current results suggest that, rather than decreasing nocebo hyperalgesia, treatment choice may exacerbate pain outcomes when a painful procedure is repeatedly administered. As such, using choice as a strategy to mitigate nocebo outcomes should be treated with caution.

Many studies indicate that deceptively administered placebos can improve pain outcomes. However, the deception involved presents an ethical barrier to translation because it violates informed consent and patient autonomy. Open-label placebos (OLPs), inert treatments that are openly administered as placebos, have been proposed as an ethically acceptable alternative. Early studies have suggested that OLP can improve pain outcomes, but important questions remain as to how to maximise OLP hypoalgesia to improve treatment outcomes in pain patients. This study investigated whether providing choice over when to administer an OLP treatment has the capacity to enhance OLP hypoalgesia using an electrocutaneous pain paradigm. One hundred thirty-two healthy volunteers were randomised to 3 types of treatment: OLP with choice, OLP without choice, and no treatment (natural history). The OLP groups were further randomised such that half were tested with a consistent pain intensity and the other half were tested with variable pain intensity to mimic day-to-day variability in pain intensity in health settings. The results indicated that treatment provided with choice exhibited greater OLP hypoalgesia than that provided without choice and that greater expectancy mediated this effect. Of interest, there was no evidence for OLP hypoalgesia without choice relative to natural history. Furthermore, variability in pain intensity did not affect OLP hypoalgesia. The current findings present novel evidence that choice over treatment administration may be a cheap and effective strategy for boosting the efficacy of OLPs in the clinical care of pain.

Detecting covariation in sequential events provides us with a powerful means of inferring the causal structure of our world. However, people often overestimate the causal relationship between unrelated events, a phenomenon referred to as illusory causation. This tendency is greatest when the putative effect occurs frequently; the widely replicated outcome density (OD) effect. Most laboratory research on illusory causation and the OD effect has focused on possible causes of a positive outcome, such as a drug that causes patient recovery. Despite its relevance, relatively few studies have examined illusory causation in cases where a cue is hypothesized to generate an unfavorable (negative) outcome, such as a drug that produces unwanted side effects. Here, we directly compared how people develop illusory beliefs about the generation of positive versus negative outcomes. We presented all participants with a drug treatment that was hypothesized to cause high readings of a fictitious cell count (but had no effect on cell count across a series of learning trials). We manipulated whether a high cell count occurred frequently or infrequently and whether a high cell count should be considered a beneficial medical outcome or an undesirable side effect. We found consistent evidence of an OD effect but no effect of the valence of the high cell count outcome. This suggests that illusory beliefs are not controlled by the desirability of the cause-effect relationship. We discuss implications for theories of applied causal reasoning.