From movement to motivation: a proposed framework to understand the antidepressant effect of exercise.

Depression is the leading cause of disability worldwide, exerting a profound negative impact on quality of life in those who experience it. Depression is associated with disruptions to several closely related neural and cognitive processes, including dopamine transmission, fronto-striatal brain activity and connectivity, reward processing and motivation. Physical activity, especially aerobic exercise, reduces depressive symptoms, but the mechanisms driving its antidepressant effects are poorly understood. Here we propose a novel hypothesis for understanding the antidepressant effects of exercise, centred on motivation, across different levels of explanation. There is robust evidence that aerobic exercise decreases systemic inflammation. Inflammation is known to reduce dopamine transmission, which in turn is strongly implicated in effort-based decision making for reward. Drawing on a broad range of research in humans and animals, we propose that by reducing inflammation and boosting dopamine transmission, with consequent effects on effort-based decision making for reward, exercise initially specifically improves 'interest-activity' symptoms of depression-namely anhedonia, fatigue and subjective cognitive impairment - by increasing propensity to exert effort. Extending this framework to the topic of cognitive control, we explain how cognitive impairment in depression may also be conceptualised through an effort-based decision-making framework, which may help to explain the impact of exercise on cognitive impairment. Understanding the mechanisms underlying the antidepressant effects of exercise could inform the development of novel intervention strategies, in particular personalised interventions and boost social prescribing.

Author Correction: Boundary effects of expectation in human pain perception.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Boundary effects of expectation in human pain perception.

Perception of sensory stimulation is influenced by numerous psychological variables. One example is placebo analgesia, where expecting low pain causes a painful stimulus to feel less painful. Yet, because pain evolved to signal threats to survival, it should be maladaptive for highly-erroneous expectations to yield unrealistic pain experiences. Therefore, we hypothesised that a cue followed by a highly discrepant stimulus intensity, which generates a large prediction error, will have a weaker influence on the perception of that stimulus. To test this hypothesis we collected two independent pain-cueing datasets. The second dataset and the analysis plan were preregistered ( https://osf.io/5r6z7/ ). Regression modelling revealed that reported pain intensities were best explained by a quartic polynomial model of the prediction error. The results indicated that the influence of cues on perceived pain decreased when stimulus intensity was very different from expectations, suggesting that prediction error size has an immediate functional role in pain perception.

A comparison between the neural correlates of laser and electric pain stimulation and their modulation by expectation.

BACKGROUND: Pain is modulated by expectation. Event-related potential (ERP) studies of the influence of expectation on pain typically utilise laser heat stimulation to provide a controllable nociceptive-specific stimulus. Painful electric stimulation has a number of practical advantages, but is less nociceptive-specific. We compared the modulation of electric versus laser-evoked pain by expectation, and their corresponding pain-evoked and anticipatory ERPs. NEW METHOD: We developed understanding of recognised methods of laser and electric stimulation. We tested whether pain perception and neural activity induced by electric stimulation was modulated by expectation, whether this expectation elicited anticipatory neural correlates, and how these measures compared to those associated with laser stimulation by eliciting cue-evoked expectations of high and low pain in a within-participant design. RESULTS: Despite sensory and affective differences between laser and electric pain, intensity ratings and pain-evoked potentials were modulated equivalently by expectation, though ERPs only correlated with pain ratings in the laser pain condition. Anticipatory correlates differentiated pain intensity expectation to laser but not electric pain. COMPARISON WITH EXISTING METHOD: Previous studies show that laser-evoked potentials are modulated by expectation. We extend this by showing electric pain-evoked potentials are equally modulated by expectation, within the same participants. We also show a difference between the pain types in anticipation. CONCLUSIONS: Though laser-evoked potentials express a stronger relationship with pain perception, both laser and electric stimulation may be used to study the modulation of pain-evoked potentials by expectation. Anticipatory-evoked potentials are elicited by both pain types, but they may reflect different processes.

Temporal dissociation of salience and prediction error responses to appetitive and aversive taste.

The feedback-related negativity (FRN), a frontocentral ERP occurring 200-350 ms after emotionally valued outcomes, has been posited as the neural correlate of reward prediction error, a key component of associative learning. Recent evidence challenged this interpretation and has led to the suggestion that this ERP expresses salience instead. Here, we distinguish between utility prediction error and salience by delivering or withholding hedonistically matched appetitive and aversive tastes, and measure ERPs to cues signaling each taste. We observed a typical FRN (computed as the loss-minus-gain difference wave) to appetitive taste, but a reverse FRN to aversive taste. When tested axiomatically, frontocentral ERPs showed a salience response across tastes, with a particularly early response to outcome delivery, supporting recent propositions of a fast, unsigned, and unspecific response to salient stimuli. ERPs also expressed aversive prediction error peaking at 285 ms, which conformed to the logic of an axiomatic model of prediction error. With stimuli that most resemble those used in animal models, we did not detect any frontocentral ERP signal for utility prediction error, in contrast with dominant views of the functional role of the FRN ERP. We link the animal and human literature and present a challenge for current perspectives on associative learning research using ERPs.

Radiological predictors of cytoreductive outcomes in patients with advanced ovarian cancer.

OBJECTIVE: To assess site of disease on preoperative computed tomography (CT) to predict surgical debulking in patients with ovarian cancer. DESIGN: Two-phase retrospective cohort study. SETTING: West London Gynaecological Cancer Centre, UK. POPULATION: Women with stage 3 or 4, ovarian, fallopian or primary peritoneal cancer undergoing cytoreductive surgery. METHODS: Preoperative CT images were reviewed by experienced radiologists to assess the presence or absence of disease at predetermined sites. Multivariable stepwise logistic regression models determined sites of disease which were significantly associated with surgical outcomes in the test (n = 111) and validation (n = 70) sets. MAIN OUTCOME MEASURES: Sensitivity and specificity of CT in predicting surgical outcome. RESULTS: Stepwise logistic regression identified that the presence of lung metastasis, pleural effusion, deposits on the large-bowel mesentery and small-bowel mesentery, and infrarenal para-aortic nodes were associated with debulking status. Logistic regression determined a surgical predictive score which was able to significantly predict suboptimal debulking (n = 94, P = 0.0001) with an area under the curve (AUC) of 0.749 (95% confidence interval [95% CI]: 0.652, 0.846) and a sensitivity of 69.2%, specificity of 71.4%, positive predictive value of 75.0% and negative predictive value of 65.2%. These results remained significant in a recent validation set. There was a significant difference in residual disease volume in the test and validation sets (P < 0.001) in keeping with improved optimal debulking rates. CONCLUSIONS: The presence of disease at some sites on preoperative CT scan is significantly associated with suboptimal debulking and may be an indication for a change in surgical planning.