Modulations of the feedback-related negativity (FRN) event-related potential (ERP) have been suggested as a potential biomarker in psychopathology.A dominant theory about this signal contends that it reflects the operation of the neural system underlying reinforcement learning in humans. The theory suggests that this frontocentral negative deflection in the ERP 230 -270 ms after the delivery of a probabilistic reward expresses a prediction error signal derived from midbrain dopaminergic projections to the anterior cingulate cortex. We tested this theory by investigating whether FRN will also be observed for an inherently aversive outcome: physical pain. In another session, the outcome was monetary reward instead of pain. As predicted, unexpected reward omissions (a negative reward prediction error) yielded a more negative deflection relative to unexpected reward delivery. Surprisingly, unexpected pain omission (a positive reward prediction error) also yielded a negative deflection relative to unexpected pain delivery. Our data challenge the theory by showing that the FRN expresses aversive prediction errors with the same sign as reward prediction errors. Both FRNs were spatiotemporally and functionally equivalent. We suggest that FRN expresses salience prediction errors rather than reward prediction errors.

Expectations about the magnitude of impending pain exert a substantial effect on subsequent perception. However, the neural mechanisms that underlie the predictive processes that modulate pain are poorly understood. In a combined behavioral and high-density electrophysiological study we measured anticipatory neural responses to heat stimuli to determine how predictions of pain intensity, and certainty about those predictions, modulate brain activity and subjective pain ratings. Prior to receiving randomized laser heat stimuli at different intensities (low, medium or high) subjects (n=15) viewed cues that either accurately informed them of forthcoming intensity (certain expectation) or not (uncertain expectation). Pain ratings were biased towards prior expectations of either high or low intensity. Anticipatory neural responses increased with expectations of painful vs. non-painful heat intensity, suggesting the presence of neural responses that represent predicted heat stimulus intensity. These anticipatory responses also correlated with the amplitude of the Laser-Evoked Potential (LEP) response to painful stimuli when the intensity was predictable. Source analysis (LORETA) revealed that uncertainty about expected heat intensity involves an anticipatory cortical network commonly associated with attention (left dorsolateral prefrontal, posterior cingulate and bilateral inferior parietal cortices). Relative certainty, however, involves cortical areas previously associated with semantic and prospective memory (left inferior frontal and inferior temporal cortex, and right anterior prefrontal cortex). This suggests that biasing of pain reports and LEPs by expectation involves temporally precise activity in specific cortical networks.

Objective. Functional neuroimaging studies have shown that experimentally induced acute pain is processed within at least 2 parallel networks of brain structures collectively known as the pain matrix. The relevance of this finding to clinical pain is not known, because no direct comparisons of experimental and clinical pain have been performed in the same group of patients. The aim of this study was to compare directly the brain areas involved in processing arthritic pain and experimental pain in a group of patients with osteoarthritis (OA).Methods. Twelve patients with knee OA underwent positron emission tomography of the brain, using 18 F-fluorodeoxyglucose (FDG). Scanning was performed during 3 different pain states: arthritic knee pain, experimental knee pain, and pain-free. Significant differences in the neuronal uptake of FDG between different pain states were investigated using statistical parametric mapping software.Results. Both pain conditions activated the pain matrix, but arthritic pain was associated with increased activity in the cingulate cortex, the thalamus, and the amygdala; these areas are involved in the processing of fear, emotions, and in aversive conditioning.Conclusion. Our results suggest that studies of experimental pain provide a relevant but quantitatively incomplete picture of brain activity during arthritic pain. The search for new analgesics for arthritis that act on the brain should focus on drugs that modify this circuitry.

INTRODUCTION. When deciding about the cause underlying serially presented events, patients with delusions utilise fewer events than controls, showing a "Jumping-to-Conclusions" bias. This has been widely hypothesised to be because patients expect to incur higher costs if they sample more information. This hypothesis is, however, unconfirmed. METHODS. The hypothesis was tested by analysing patient and control data using two models. The models provided explicit, quantitative variables characterising decision making. One model was based on calculating the potential costs of making a decision; the other compared a measure of certainty to a fixed threshold. RESULTS. Differences between paranoid participants and controls were found, but not in the way that was previously hypothesised. A greater "noise" in decision making (relative to the effective motivation to get the task right), rather than greater perceived costs, best accounted for group differences. Paranoid participants also deviated from ideal Bayesian reasoning more than healthy controls. CONCLUSIONS. The Jumping-to-Conclusions Bias is unlikely to be due to an overestimation of the cost of gathering more information. The analytic approach we used, involving a Bayesian model to estimate the parameters characterising different participant populations, is well suited to testing hypotheses regarding "hidden" variables underpinning observed behaviours.

Placebo has been shown to be a powerful analgesic with corresponding reduction in the activation of the pain matrix in the brain. However it is not clear whether the placebo response is reproducible within individuals and what role personality traits might play in predicting it. We induced placebo analgesia by conditioning subjects to expect pain reduction following a sham-treatment in the guise of a local anaesthetic cream applied to one arm. Pain ratings were assessed before, during and after treatment. The procedure was repeated in a second session to assess the degree of reproducibility of the response. A high degree of correlation was found between the two sessions for the sham-treatment group (R(2) = 0.55; p < 0.001). Personality questionnaires were given during both experimental sessions to assess key traits such as optimism and state and trait anxiety. A regression model was used to statistically define a placebo responder in terms of personality scores. High dispositional optimism and low state anxiety were found to be significant predictors of placebo response. We suggest that repeated placebo responders are high in dispositional optimism and having a placebo response in the first session causes a drop in state anxiety at the beginning of the repeat session.

Memories are gradually consolidated after initial encoding, and this can sometimes lead to a transition from implicit to explicit knowledge. The exact physiological processes underlying this reorganization remain unclear. Here, we used a serial reaction time task to determine whether targeted memory reactivation (TMR) of specific memory traces during slow-wave sleep promotes the emergence of explicit knowledge. Human participants learned two 12-item sequences of button presses (A and B). These differed in both cue order and in the auditory tones associated with each of the four fingers (one sequence had four higher-pitched tones). Subsequent overnight sleep was monitored, and the tones associated with one learned sequence were replayed during slow-wave sleep. After waking, participants demonstrated greater explicit knowledge (p ϭ 0.005) and more improved procedural skill (p ϭ 0.04) for the cued sequence relative to the uncued sequence. Furthermore, fast spindles (13.5-15 Hz) at task-related motor regions predicted overnight enhancement in procedural skill (r ϭ 0.71, p ϭ 0.01). Auditory cues had no effect on post-sleep memory performance in a control group who received TMR before sleep. These findings suggest that TMR during sleep can alter memory representations and promote the emergence of explicit knowledge, supporting the notion that reactivation during sleep is a key mechanism in this process.

Sleep plays a role in memory consolidation. This is demonstrated by improved performance and neural plasticity underlying that improvement after sleep. Targeted memory reactivation (TMR) allows the manipulation of sleep-dependent consolidation through intentionally biasing the replay of specific memories in sleep, but the underlying neural basis of these altered memories remains unclear. We use functional magnetic resonance imaging (fMRI) to show a change in the neural representation of a motor memory after targeted reactivation in slow-wave sleep (SWS). Participants learned two serial reaction time task (SRTT) sequences associated with different auditory tones (high or low pitch). During subsequent SWS, one sequence was reactivated by replaying the associated tones. Participants were retested on both sequences the following day during fMRI. As predicted, they showed faster reaction times for the cued sequence after targeted memory reactivation. Furthermore, increased activity in bilateral caudate nucleus and hippocampus for the cued relative to uncued sequence was associated with time in SWS, while increased cerebellar and cortical motor activity was related to time in rapid eye movement (REM) sleep. Functional connectivity between the caudate nucleus and hippocampus was also increased after targeted memory reactivation. These findings suggest that the offline performance gains associated with memory reactivation are supported by altered functional activity in key cognitive and motor networks, and that this consolidation is differentially mediated by both REM sleep and SWS.

The neural mechanisms whereby placebo conditioning leads to placebo analgesia remain unclear. In this study we aimed to identify the brain structures activated during placebo conditioning and subsequent placebo analgesia. We induced placebo analgesia by associating a sham treatment with pain reduction and used fMRI to measure brain activity associated with three stages of the placebo response: before, during and after the sham treatment, while participants anticipated and experienced brief laser pain. In the control session participants were explicitly told that the treatment was inactive. The sham treatment group reported a significant reduction in pain rating (p = 0.012). Anticipatory brain activity was modulated during placebo conditioning in a fronto-cingulate network involving the left dorsolateral prefrontal cortex (DLPFC), medial frontal cortex and the anterior mid-cingulate cortex (aMCC). Identical areas were modulated during anticipation in the placebo analgesia phase with the addition of the orbitofrontal cortex (OFC). However, during altered pain experience only aMCC, post-central gyrus and posterior cingulate demonstrated altered activity. The common frontal cortical areas modulated during anticipation in both the placebo conditioning and placebo analgesia phases have previously been implicated in placebo analgesia. Our results suggest that the main effect of placebo arises from the reduction of anticipation of pain during placebo conditioning that is subsequently maintained during placebo analgesia.