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The specific role of serotonin and its interplay with dopamine (DA) in adaptive, reward guided behavior as well as drug dependance, still remains elusive. Recently, novel methods allowed cell type specific anatomical, functional and interventional analyses of serotonergic and dopaminergic circuits, promising significant advancement in understanding their functional roles. Furthermore, it is increasingly recognized that co-release of neurotransmitters is functionally relevant, understanding of which is required in order to interpret results of pharmacological studies and their relationship to neural recordings. Here, we review recent animal studies employing such techniques with the aim to connect their results to effects observed in human pharmacological studies and subjective effects of drugs. It appears that the additive effect of serotonin and DA conveys significant reward related information and is subjectively highly euphorizing. Neither DA nor serotonin alone have such an effect. This coincides with optogenetically targeted recordings in mice, where the dopaminergic system codes reward prediction errors (PE), and the serotonergic system mainly unsigned PE. Overall, this pattern of results indicates that joint activity between both systems carries essential reward information and invites parallel investigation of both neurotransmitter systems.

Decision making often requires accumulating evidence in favour of a particular option. When choices are expressed with a motor response, these actions are preceded by reductions in the power of oscillations in the alpha and beta range in motor cortices. For unimanual movements, these reductions are greater over the hemisphere contralateral to the response side. Such lateralizations are hypothesized to be an online index of the neural state of decisions as they develop over time of processing. In contrast, the lateralized readiness potential (LRP) is considered to selectively activate a response and appears shortly before the motor output. We investigated to what extent these neural signals reflect integration of decision evidence or more motor-related action preparation. Using two different experiments, we found that lateralization of alpha and beta power (APL and BPL, respectively) rapidly emerged after stimulus presentation, even when making an overt response was not yet possible. In contrast, we show that even after prolonged stimulus presentation, no LRP was present. Instead, the LRP emerged only after an imperative cue, prompting participants to indicate their choice. Furthermore, we could show that variations in sensory evidence strength modulate APL and BPL onset times, suggesting that integration of evidence is represented in these motor cortical signals. We conclude that APL and BPL reflect higher cognitive processes rather than pure action preparation, whereas LRP is more closely tied to motor performance. APL and BPL potentially encode decision information in motor areas serving the later preparation of overt decision output.

Both conflict and error processing have been linked to the midfrontal theta power (4–8 Hz) increase as indicated by EEG studies and greater hemodynamic activity in the anterior midcingulate cortex (aMCC) as indicated by fMRI studies. Conveniently, the source of the midfrontal theta power was estimated in or nearby aMCC. However, previous studies using concurrent EEG and fMRI recordings in resting-state or other cognitive tasks observed only a negative relationship between theta power and BOLD signal in the brain regions typically showing task-related deactivations. In this study, we used a simultaneous EEG-fMRI technique to investigate a trial-by-trial coupling between theta power and hemodynamic activity during the performance of two conflict tasks. Independent component analysis (ICA) was applied to denoise the EEG signal and select individual midfrontal EEG components, whereas group ICA was applied to fMRI data to obtain a functional parcellation of the frontal cortex. Using a linear mixed-effect model, theta power was coupled with the peak of hemodynamic responses from various frontal, cingulate, and insular cortical sites to unravel the potential brain sources that contribute to conflict- and error-related theta variability. Although several brain regions exhibited conflict-related increases in hemodynamic activity, the conflict pre-response theta showed only a negative correlation to BOLD signal in the midline area 9 (MA9), a region exhibiting conflict-sensitive deactivation. Conversely, and more expectedly, error-related theta showed a positive relationship to activity in the aMCC. Our results provide novel evidence suggesting that the amplitude of pre-response theta reflects the process of active inhibition that suppresses the MA9 activity. This process is affected independently by the stimulus congruency, reaction times variance, and is susceptible to the time-on-task effect. Finally, it predicts the commitment of an omission error. Together, our findings highlight that conflict- and error-related theta oscillations represent fundamentally different processes. [Display omitted]

Goal-directed behavior requires the ability to adapt performance strategies based on the attribution of unintended outcomes to internal or external causes. Using event-related brain potentials, the present research compared neural activity following self-generated errors induced by a flanker task and following externally generated errors induced by supposed “technical malfunctions”. Errors and malfunctions were associated with temporally dissociable ERP components, the short-latency error-related negativity (ERN) and the longer-latency feedback-related negativity (FRN), respectively. Independent component analysis (ICA) was applied to compare the underlying neural components of ERN and FRN. ICA results revealed that the FRN is attributable to the neural sources of the ERN, suggesting that the two components share a source network. Furthermore, single-trial amplitudes of ERN and FRN were specifically related to the implementation of error correction and malfunction compensation: the stronger the failure signal, the more efficient was remedial behavior. Together the results demonstrate that internally and externally generated unintended action outcomes engage a common monitoring mechanism that manifests in two temporally distinct ERP components and induces similar compensatory processes. The temporal dissociation of the ERP components might provide the basis for further processes of outcome attribution underlying action selection and changes in performance strategy. In line with recent neuroimaging findings, ERN and FRN appear to reflect the use of different sources of information about action outcome to update action value.

Monitoring for errors and behavioral adjustments after errors are essential for daily life. A question that has not been addressed systematically yet, is whether consciously perceived errors lead to different behavioral adjustments compared to unperceived errors. Our goal was to develop a task that would enable us to study different commonly observed neural correlates of error processing and post-error adjustments in their relation to error awareness and accuracy confidence in a single experiment. We assessed performance in a new number judgement error awareness task in 70 participants. We used multiple, robust, single-trial EEG regressions to investigate the link between neural correlates of error processing (e.g., error-related negativity (ERN) and error positivity (Pe)) and error awareness. We found that only aware errors had a slowing effect on reaction times in consecutive trials, but this slowing was not accompanied by post-error increases in accuracy. On a neural level, error awareness and confidence had a modulating effect on both the ERN and Pe, whereby the Pe was most predictive of participants’ error awareness. Additionally, we found partial support for a mediating role of error awareness on the coupling between the ERN and behavioral adjustments in the following trial. Our results corroborate previous findings that show both an ERN/Pe and a post-error behavioral adaptation modulation by error awareness. This suggests that conscious error perception can support meta-control processes balancing the recruitment of proactive and reactive control. Furthermore, this study strengthens the role of the Pe as a robust neural index of error awareness.

A study in Nature Human Behaviour proposes a biologically plausible algorithm producing near-optimal behaviour in uncertain and volatile environments through computational imprecision. A complementary study in the same issue shows that, depending on context, uncertainty itself guides different decisions and is differentially represented in the brain.

To decide optimally between available options, organisms need to learn the values associated with these options. Reinforcement learning models offer a powerful explanation of how these values are learnt from experience. However, human choices often violate normative principles. We suggest that seemingly counterintuitive decisions may arise as a natural consequence of the learning mechanisms deployed by humans. Here, using fMRI and a novel behavioural task, we show that, when suddenly switched to novel choice contexts, participants’ choices are incongruent with values learnt by standard learning algorithms. Instead, behaviour is compatible with the decisions of an agent learning how good an option is relative to an option with which it had previously been paired. Striatal activity exhibits the characteristics of a prediction error used to update such relative option values. Our data suggest that choices can be biased by a tendency to learn option values with reference to the available alternatives. Though people learn that certain choices may be more advantageous, they often do not choose this option. Here, the authors explain this behaviour: people learn how good a choice is relative to the choices it has been associated with previously, and this learning takes place in the striatum.

Becoming aware of errors that one has committed might be crucial for strategic behavioral and neuronal adjustments to avoid similar errors in the future. This review addresses conscious error perception (\"error awareness\") in healthy subjects as well as the relationship between error awareness and neurological and psychiatric diseases. We first discuss the main findings on error awareness in healthy subjects. A brain region, that appears consistently involved in error awareness processes, is the insula, which also provides a link to the clinical conditions reviewed here. Then we focus on a neurological condition whose core element is an impaired awareness for neurological consequences of a disease: anosognosia for hemiplegia (AHP). The insular cortex has been implicated in both error awareness and AHP, with anterior insular regions being involved in conscious error processing and more posterior areas being related to AHP. In addition to cytoarchitectonic and connectivity data, this reflects a functional and structural gradient within the insula from anterior to posterior. Furthermore, studies dealing with error awareness and lack of insight in a number of psychiatric diseases are reported. Especially in schizophrenia, attention-deficit hyperactivity disorder, (ADHD) and autism spectrum disorders (ASD) the performance monitoring system seems impaired, thus conscious error perception might be altered.

When we perform an action, the outcome that follows it can change the value we place on that behaviour, making it more or less likely to be repeated in the future. However, the values that we learn are not objective: we interpret the outcomes that we receive for ourselves relative to those that share our environment, i.e. we engage in social comparison. The temporal dynamics of physiological responses to stimulus valuation in social learning tasks are poorly understood, particularly in human participants. Therefore, we recorded stimulus-locked event-related potentials with 64-channel EEG to examine stimulus valuation, following the design of a study previously used in macaques. Pairs of participants performed a social learning task in which they received outcomes sequentially for a presented stimulus (partner first) by pressing a button in response to a cue. There were two conditions: one in which stimulus values varied for the participant but output a constant rate of reward for the partner (self-variable blocks), and another condition in which this payout was reversed (other-variable blocks). We then measured participants' self-reported competitiveness. Approximately 200 ms post-stimulus, an ERP related to stimulus evaluation and attentional processing appeared to encode own stimulus value in self-variable blocks. In other-variable blocks the same pattern of activity was reversed, even though the value of the stimulus for the participant did not depend on the stimulus presented. Outcome-locked analyses further showed that attention dedicated to the partner's outcome was greater in more competitive participants. We conclude that subjective stimulus value can be reflected in early stimulus-locked ERP responses and that competitive participants may be more invested in their own performance relative to the other player, hence their increased interest in the outcome of their partner.

•We examined how task-irrelevant information biases our decisions.•Task-irrelevant information biases learning and behaviour despite explicit knowledge of its irrelevance.•These biases are represented in a dynamic and spatiotemporally dissociable sequence of feedback-related EEG activity.•A common centroparietal positivity reflects a signal that is interpreted by downstream learning processes that adjust future behaviour. Optimal decision making in complex environments requires dynamic learning from unexpected events. To speed up learning, we should heavily weight information that indicates state-action-outcome contingency changes and ignore uninformative fluctuations in the environment. Often, however, unrelated information is hard to ignore and can potentially bias our learning. Here we used computational modelling and EEG to investigate learning behaviour in a modified probabilistic choice task that introduced two task-irrelevant factors that were uninformative for optimal task performance, but nevertheless could potentially bias learning: pay-out magnitudes were varied randomly and, occasionally, feedback presentation was enhanced by visual surprise. We found that participants’ overall good learning performance was biased by distinct effects of these non-normative factors. On the neural level, these parameters are represented in a dynamic and spatiotemporally dissociable sequence of EEG activity. Later in feedback processing the different streams converged on a central to centroparietal positivity reflecting a signal that is interpreted by downstream learning processes that adjust future behaviour.