Binary sensitivity of theta activity for gain and loss when monitoring parametric prediction errors

Neural correlates of evaluations of non-binary social feedback: An EEG study

PURPOSE

In complex and diverse social circumstances, decision making is affected by social feedback. Although previous studies have examined the electrophysiological correlates of social feedback with a binary valence, those related to non-binary feedback, or the magnitude of social feedback, remain unclear. This study investigated the electrophysiological correlates of non-binary social feedback and subsequent action selection processing.

METHODS

Participants were asked to complete a Gabor patch direction judgment task in which they were required to make judgments before and after receiving social feedback. They were informed that the feedback stimuli represented the degree to which other participants made the same choice.

RESULTS & CONCLUSION

The results revealed that feedback that was highly concordant with the participant's judgments elicited greater P300 activity, which was associated with the fulfillment of expectations regarding social reward. Moreover, moderately concordant feedback induced stronger theta band power, which may indicate monitoring of subjective conflict. Temporal changes in theta power during feedback phase may also relate to adjustments in prediction error. Additionally, when an initial judgment was maintained following social feedback, we observed a stronger increase in beta power, indicating an association with post-social-feedback action processing.

The modulation of pain in reward processing is reflected by increased P300 and delta oscillation

Pain elicits the desire for a reward to alleviate the unpleasant sensation. This may be a consequence of facilitated neural activities in the reward circuit. However, the temporal modulation of pain on reward processing remains unclear. We addressed this issue by recording electroencephalogram when participants received win or loss feedback in a simple gambling task. Pain treatment was conducted on 33 participants with topical capsaicin cream and on 33 participants with hand cream as a control. Results showed that pain generally increased the P300 amplitude for both types of feedback but did not affect feedback-related negativity (FRN). A significant interaction effect of treatment (painful, non-painful) and outcome (win, loss) was observed on delta oscillation as pain only enhanced the power of win feedback. In addition, the FRN and theta oscillation responded more to loss feedback, but this effect was unaffected by pain. These findings indicate that pain may enhance secondary value representation and evaluation processes of rewards, but does not influence primary distinction of reward or reward expectation. The temporal unfolding of how pain affects reward-related neural activities highlights the prominent impact of pain on high-level cognitive processes associated with reward.

Valence precedes value in neural encoding of prediction error

Event-related potentials that follow feedback in reinforcement learning tasks have been proposed to reflect neural encoding of prediction errors. Prior research has shown that in the interval of 240-340 ms multiple different prediction error encodings appear to co-occur, including a value signal carrying signed quantitative prediction error and a valence signal merely carrying sign. The effects used to identify these two encoders, respectively a sign main effect and a sign × size interaction, do not reliably discriminate them. A full discrimination is made possible by comparing tasks in which the reinforcer available on a given trial is set to be either appetitive or aversive against tasks where a trial allows the possibility of either. This study presents a meta-analysis of reinforcement learning experiments, the majority of which presented the possibility of winning or losing money. Value and valence encodings were identified by conventional difference wave methodology but additionally by an analysis of their predicted behavior using a Bayesian analysis that incorporated nulls into the evidence for each encoder. The results suggest that a valence encoding, sensitive only to the available outcomes on the trial at hand precedes a later value encoding sensitive to the outcomes available in the wider experimental context. The implications of this for modeling computational processes of reinforcement learning in humans are discussed.

Reward-based decision-making in mesial temporal lobe epilepsy patients with unilateral hippocampal sclerosis pre- and post-surgery

BACKGROUND

Correct functioning of the reward processing system is critical for optimizing decision-making as well as preventing the development of addictions and/or neuropsychiatric symptoms such as depression, apathy, and anhedonia. Consequently, patients with mesial temporal lobe epilepsy due to unilateral hippocampal sclerosis (mTLE-UHS) represent an excellent opportunity to study the brain networks involved in this system.

OBJECTIVE

The aim of the current study was to evaluate decision-making and the electrophysiological correlates of feedback processing in a sample of mTLE-UHS patients, compared to healthy controls. In addition, we assessed the impact of mesial temporal lobe surgical resection on these processes, as well as general, neuropsychological functioning.

METHOD

17 mTLE-UHS patients and 17 matched healthy controls completed: [1] a computerized version of the Game of Dice Task, [2] a Standard Iowa Gambling Task, and [3] a modified ERP version of a probabilistic gambling task coupled with multichannel electroencephalography. Neuropsychological scores were also obtained both pre- and post-surgery.

RESULTS

Behavioral analyses showed a pattern of increased risk for the mTLE-UHS group in decision-making under ambiguity compared to the control group. A decrease in the amplitude of the Feedback Related Negativity (FRN), a weaker effect of valence on delta power, and a general reduction of delta and theta power in the mTLE-UHS group, as compared to the control group, were also found. The beta-gamma activity associated with the delivery of positive reward was similar in both groups. Behavioral performance and electrophysiological measures did not worsen post-surgery.

CONCLUSIONS

Patients with mTLE-UHS showed impairments in decision-making under ambiguity, particularly when they had to make decisions based on the outcomes of their choices, but not in decision-making under risk. No group differences were observed in decision-making when feedbacks were random. These results might be explained by the abnormal feedback processing seen in the EEG activity of patients with mTLE-UHS, and by concomitant impairments in working memory, and memory. These impairments may be linked to the disruption of mesial temporal lobe networks. Finally, feedback processing and decision-making under ambiguity were already affected in mTLE-UHS patients pre-surgery and did not show evidence of clear worsening post-surgery.

Utility of Cognitive Neural Features for Predicting Mental Health Behaviors

Cognitive dysfunction underlies common mental health behavioral symptoms including depression, anxiety, inattention, and hyperactivity. In this study of 97 healthy adults, we aimed to classify healthy vs. mild-to-moderate self-reported symptoms of each disorder using cognitive neural markers measured with an electroencephalography (EEG). We analyzed source-reconstructed EEG data for event-related spectral perturbations in the theta, alpha, and beta frequency bands in five tasks, a selective attention and response inhibition task, a visuospatial working memory task, a Flanker interference processing task, and an emotion interference task. From the cortical source activation features, we derived augmented features involving co-activations between any two sources. Logistic regression on the augmented feature set, but not the original feature set, predicted the presence of psychiatric symptoms, particularly for anxiety and inattention with >80% sensitivity and specificity. We also computed current flow closeness and betweenness centralities to identify the “hub” source signal predictors. We found that the Flanker interference processing task was the most useful for assessing the connectivity hubs in general, followed by the inhibitory control go-nogo paradigm. Overall, these interpretable machine learning analyses suggest that EEG biomarkers collected on a rapid suite of cognitive assessments may have utility in classifying diverse self-reported mental health symptoms.

Social Context and Rejection Expectations Modulate Neural and Behavioral Responses to Social Feedback

When meeting other people, some are optimistic and expect to be accepted by others, whereas others are pessimistic and expect mostly rejections. How social feedback is evaluated in situations that meet or do not meet these biases and how people differ in their response to rejection and acceptance depending on the social situation are unknown. In this study, participants experienced rejection and acceptance by peers in two different social contexts, one with high (negative context) and the other with low probability of rejection (positive context). We examined how the neural and behavioral responses to rejection are altered by this context and whether it depends on the individual's sensitivity to rejection. Behavioral results show that, on average, people maintain an optimistic bias even when mostly experiencing rejection. Importantly, personality differences in rejection sensitivity affected both prior expectations to be rejected in the paradigm and the extent to which expectations changed during the paradigm. The context also strongly modulated ERPs and theta responses to rejection and acceptance feedback. Specifically, valence effects on neural responses were enhanced in the negative context, suggesting a greater relevance to monitor social feedback in such a situation. Moreover, midfrontal theta predicted how expectations were changed in response to prediction errors, stressing a role for theta in learning from social feedback. Surprisingly, interindividual differences in rejection sensitivity did not affect neural responses to feedback. Our results stress the importance of considering the interaction between subjective expectations and the social context for behavioral and neural responses to social rejection.

Neural correlates of acceptance and rejection in online speed dating: An electroencephalography study

Pursuing dating relationships is important for many people's well-being, because it helps them fulfill the need for stable social relationships. However, the neural underpinnings of decision-making processes during the pursuit of dating interactions are unclear. In the present study, we used a novel online speed dating paradigm where participants (undergraduate students, N = 25, aged 18-25 years, 52% female) received direct information about acceptance or rejection of their various speed dates. We recorded EEG measurements during speed dating feedback anticipation and feedback processing stages to examine the stimulus preceding negativity (SPN) and feedback-related brain activity (Reward Positivity, RewP, and theta oscillatory power). The results indicated that the SPN was larger when participants anticipated interest versus disinterest from their speed dates. A larger RewP was observed when participants received interest from their speed dates. Theta power was increased when participants received rejection from their speed dates. This theta response could be source-localized to brain areas that overlap with the physical pain matrix (anterior cingulate cortex, dorsolateral prefrontal cortex, and the supplementary motor area). This study demonstrates that decision-making processes-as evident in a speed date experiment-are characterized by distinct neurophysiological responses during anticipating an evaluation and processing thereof. Our results corroborate the involvement of the SPN in reward anticipation, RewP in reward processing and mid-frontal theta power in processing of negative social-evaluative feedback. These findings contribute to a better understanding of the neurocognitive mechanisms implicated in decision-making processes when pursuing dating relationships.

Temporal division of the decision-making process: An EEG study

Decision-making is a process that allows individuals to choose an option or alternative in order to maximize a subjective gain or achieve a set goal by evaluating and establishing a preference based on contextual and internal information. Ernst and Paulus proposed a three-stage temporal division of this process: 1) the assessment and formation of preferences among possible options; 2) the selection and execution of an action; and 3) the experience or evaluation of an outcome. Each stage involves the participation of several brain regions, including the prefrontal, parietal, and temporal cortices. There are reports of distinct functionalities of these cortices for each stage of decision-making, but those studies focus on individual stages and do not provide any direct comparisons among them. Therefore, using a task that allows the clear temporal separation of the three stages of decision-making, we characterized the electroencephalographic activity (EEG) of those cortices in 30 healthy right-handed men during preference changes that occurred while performing a decision-making task. As the trials progressed, the preference for the stimulus shifted towards maximizing gains on the task. Forty trials sufficed to maintain these behavioral changes. Specific EEG patterns for each stage of decision-making were obtained, and it was possible to associate them with the cognitive processes involved in each one. These EEG data support the temporal division of the decision-making process proposed by Ernest and Paulus and show that the task designed could be a useful tool for determining behavioral and cerebral changes associated with stimuli preference during decision-making.

The role of trait empathy in the processing of observed actions in a false-belief task

Empathic brain responses are characterized by overlapping activations between active experience and observation of an emotion in another person, with the pattern for observation being modulated by trait empathy. Also for self-performed and observed errors, similar brain activity has been described, but findings concerning the role of empathy are mixed. We hypothesized that trait empathy modulates the processing of observed responses if expectations concerning the response are based on the beliefs of the observed person. In the present study, we utilized a false-belief task in which observed person’s and observer’s task-related knowledge were dissociated and errors and correct responses could be expected or unexpected. While theta power was generally modulated by the expectancy of the observed response, a negative mediofrontal event-related potential (ERP) component was more pronounced for unexpected observed actions only in participants with higher trait empathy (assessed by the Empathy Quotient), as revealed by linear mixed effects analyses. Cognitive and affective empathy, assessed by the Interpersonal Reactivity Index, were not significantly related to the ERP component. The results suggest that trait empathy can facilitate the generation of predictions and thereby modulate specific aspects of the processing of observed actions, while the contributions of specific empathy components remain unclear.

Learning to Synchronize: Midfrontal Theta Dynamics during Rule Switching

In recent years, several hierarchical extensions of well-known learning algorithms have been proposed. For example, when stimulus-action mappings vary across time or context, the brain may learn two or more stimulus-action mappings in separate modules, and additionally (at a hierarchically higher level) learn to appropriately switch between those modules. However, how the brain mechanistically coordinates neural communication to implement such hierarchical learning remains unknown. Therefore, the current study tests a recent computational model that proposed how midfrontal theta oscillations implement such hierarchical learning via the principle of binding by synchrony (Sync model). More specifically, the Sync model uses bursts at theta frequency to flexibly bind appropriate task modules by synchrony. The 64-channel EEG signal was recorded while 27 human subjects (female: 21, male: 6) performed a probabilistic reversal learning task. In line with the Sync model, postfeedback theta power showed a linear relationship with negative prediction errors, but not with positive prediction errors. This relationship was especially pronounced for subjects with better behavioral fit (measured via Akaike information criterion) of the Sync model. Also consistent with Sync model simulations, theta phase-coupling between midfrontal electrodes and temporoparietal electrodes was stronger after negative feedback. Our data suggest that the brain uses theta power and synchronization for flexibly switching between task rule modules, as is useful, for example, when multiple stimulus-action mappings must be retained and used.SIGNIFICANCE STATEMENT Everyday life requires flexibility in switching between several rules. A key question in understanding this ability is how the brain mechanistically coordinates such switches. The current study tests a recent computational framework (Sync model) that proposed how midfrontal theta oscillations coordinate activity in hierarchically lower task-related areas. In line with predictions of this Sync model, midfrontal theta power was stronger when rule switches were most likely (strong negative prediction error), especially in subjects who obtained a better model fit. Additionally, also theta phase connectivity between midfrontal and task-related areas was increased after negative feedback. Thus, the data provided support for the hypothesis that the brain uses theta power and synchronization for flexibly switching between rules.

Error, rather than its probability, elicits specific electrocortical signatures: a combined EEG-immersive virtual reality study of action observation

Detecting errors in one’s own actions, and in the actions of others, is a crucial ability for adaptable and flexible behavior. Studies show that specific EEG signatures underpin the monitoring of observed erroneous actions (error-related negativity, error positivity, mid-frontal theta oscillations). However, the majority of studies on action observation used sequences of trials where erroneous actions were less frequent than correct actions. Therefore, it was not possible to disentangle whether the activation of the performance monitoring system was due to an error, as a violation of the intended goal, or to a surprise/novelty effect, associated with a rare and unexpected event. Combining EEG and immersive virtual reality (IVR-CAVE system), we recorded the neural signal of 25 young adults who observed, in first-person perspective, simple reach-to-grasp actions performed by an avatar aiming for a glass. Importantly, the proportion of erroneous actions was higher than correct actions. Results showed that the observation of erroneous actions elicits the typical electrocortical signatures of error monitoring, and therefore the violation of the action goal is still perceived as a salient event. The observation of correct actions elicited stronger alpha suppression. This confirmed the role of the alpha-frequency band in the general orienting response to novel and infrequent stimuli. Our data provide novel evidence that an observed goal error (the action slip) triggers the activity of the performance-monitoring system even when erroneous actions, which are, typically, relevant events, occur more often than correct actions and thus are not salient because of their rarity.

NEW & NOTEWORTHY Activation of the performance-monitoring system (PMS) is typically investigated when errors in a sequence are comparatively rare. However, whether the PMS is activated by errors per se or by their infrequency is not known. Combining EEG-virtual reality techniques, we found that observing frequent (70%) action errors performed by avatars elicits electrocortical error signatures suggesting that deviation from the prediction of how learned actions should correctly deploy, rather than its frequency, is coded in the PMS.

Electrophysiological indices of anterior cingulate cortex function reveal changing levels of cognitive effort and reward valuation that sustain task performance

Successful execution of goal-directed behaviors often requires the deployment of cognitive control, which is thought to require cognitive effort. Recent theories have proposed that anterior cingulate cortex (ACC) regulates control levels by weighing the reward-related benefits of control against its effort-related costs. However, given that the sensations of cognitive effort and reward valuation are available only to introspection, this hypothesis is difficult to investigate empirically. We have proposed that two electrophysiological indices of ACC function, frontal midline theta and the reward positivity (RewP), provide objective measures of these functions. To explore this issue, we recorded the electroencephalogram (EEG) from participants engaged in an extended, cognitively-demanding task. Participants performed a time estimation task for 2 h in which they received reward and error feedback according to their task performance. We observed that the amplitude of the RewP, a feedback-locked component of the event related brain potential associated with reward processing, decreased with time-on-task. Conversely, frontal midline theta power, which consists of 4-8 Hz EEG oscillations associated with cognitive effort, increased with time-on-task. We also explored how these phenomena changed over time by conducting within-participant multi-level modeling analyses. Our results suggest that extended execution of a cognitively-demanding task is characterized by an early phase in which high control levels foster rapid improvements in task performance, and a later phase in which high control levels were necessary to maintain stable task performance, perhaps counteracting waning reward valuation.

Wronger than wrong: Graded mapping of the errors of an avatar in the performance monitoring system of the onlooker

EEG studies show that observing errors in one's own or others' actions triggers specific electro-cortical signatures in the onlooker's brain, but whether the brain error-monitoring system operates according to graded or discrete rules is still largely unknown. To explore this issue, we combined immersive virtual reality with EEG recording in participants who observed an avatar reaching-to-grasp a glass from a first-person perspective. The avatar could perform correct or erroneous actions. Erroneous grasps were defined as small or large depending on the magnitude of the trajectory deviation from the to-be-grasped glass. Results show that electro-cortical indices of error detection (indexed by ERN and mid-frontal theta oscillations), but not those of error awareness (indexed by error-Positivity), were gradually modulated by the magnitude of the observed errors. Moreover, the phase connectivity analysis revealed that enhancement of mid-frontal theta phase synchronization paralleled the magnitude of the observed error. Thus, theta oscillations represent an electro-cortical index of the degree of control exerted by mid-frontal regions whose activation depends on how much an observed action outcome results maladaptive for the onlooker. Our study provides novel neurophysiological evidence that the error monitoring system maps observed errors of different magnitude according to fine-grain, graded rather than all-or-none rules.