EEG oscillatory activity associated to monetary gain and loss signals in a learning task: effects of attentional impulsivity and learning ability

Different Faces of Medial Beta-Band Activity Reflect Distinct Visuomotor Feedback Signals

Beta-band (13-35 Hz) modulations following reward, task outcome feedback, and error have been described in cognitive and/or motor adaptation tasks. Observations from different studies are, however, difficult to conciliate. Among the studies that used cognitive response selection tasks, several reported an increase in beta-band activity following reward, whereas others observed increased beta power after negative feedback. Moreover, in motor adaptation tasks, an attenuation of the postmovement beta rebound follows a movement execution error induced by visual or mechanical perturbations. Given that kinematic error typically leads to negative task-outcome feedback (e.g., target missed), one may wonder how contradictory modulations, beta power decrease with movement error versus beta power increase with negative feedback, may coexist. We designed a motor adaptation task in which female and male participants experience varied feedbacks-binary success/failure feedback, kinematic error, and sensory-prediction error-and demonstrate that beta-band modulations in opposite directions coexist at different spatial locations, time windows, and frequency ranges. First, high beta power in the medial frontal cortex showed opposite modulations well separated in time when compared in success and failure trials; that is, power was higher in success trials just after the binary success feedback, whereas it was lower in the postmovement period compared with failure trials. Second, although medial frontal high-beta activity was sensitive to task outcome, low-beta power in the medial parietal cortex was strongly attenuated following movement execution error but was not affected by either the outcome of the task or sensory-prediction error. These findings suggest that medial beta activity in different spatio-temporal-spectral configurations play a multifaceted role in encoding qualitatively distinct feedback signals.SIGNIFICANCE STATEMENT Beta-band activity reflects neural processes well beyond sensorimotor functions, including cognition and motivation. By disentangling alternative spatio-temporal-spectral patterns of possible beta-oscillatory activity, we reconcile a seemingly discrepant literature. First, high-beta power in the medial frontal cortex showed opposite modulations separated in time in success and failure trials; power was higher in success trials just after success feedback and lower in the postmovement period compared with failure trials. Second, although medial frontal high-beta activity was sensitive to task outcome, low-beta power in the medial parietal cortex was strongly attenuated following movement execution error but was not affected by the task outcome or the sensory-prediction error. We propose that medial beta activity reflects distinct feedback signals depending on its anatomic location, time window, and frequency range.

Resting State EEG Activity Related to Impulsivity in People with Prescription Opioid Use Disorder

Previous studies on EEG activity in prescription opioid use disorder (OUD) have reported neuronal dysfunction related to heroin use, most consistently reflected by increases in β-brain oscillations. As similar research has yet to examine EEG associated with non-medical use of prescription opioid and as inhibitory deficits are associated with OUD, this pilot study compared quantitative EEGs of 18 patients with prescription OUD and 18 healthy volunteers and assessed relationships between oscillatory activity and impulsivity with the Barratt Impulsiveness Scale (BIS-11). Spectral EEGs showed greater amplitude density in β₁, β₂, and β₃ frequencies across frontal, temporal-central and posterior recording areas in patients. Similar abnormal amplitude density increases were seen in δ but not in θ or α frequency bands. Patients exhibited greater scores (impaired impulse control) on BIS-11 subscales (attention, motor, self-control) and impairment of these impulsive subtypes was associated with increases in β and δ oscillations. In patients, β1, β2, and δ activity was positively associated with disorder severity. Taken together, the results suggest that altered brain oscillations in persons with prescription OUD show some similarities with reported oscillatory changes in heroin use and may indicate a chronic state of imbalance in neuronal networks regulating impulsive and inhibitory control systems.

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.

Electrophysiological Correlates of Shyness Affected by Facial Attractiveness

Previous neurological studies of shyness have focused on the hemispheric asymmetry of alpha spectral power. To the best of our knowledge, few studies have focused on the interaction between different frequencies bands in the brain of shyness. Additionally, shy individuals are even shyer when confronted with a group of people they consider superior to them. This study aimed to reveal the neural basis of shy individuals using the delta-beta correlation. Further, it aimed to investigate the effect of evaluators’ facial attractiveness on the delta-beta correlation of shyness during the speech anticipation phase. We recorded electroencephalogram (EEG) activity of 94 participants during rest and anticipation of the public speaking phase. Moreover, during the speech anticipation phase, participants were presented with high or low facial attractiveness. The results showed that, as predicted, the delta-beta correlation in the frontal region was more robust for high shyness than for low shyness during the speech anticipation phase. However, no significant differences were observed in the delta-beta correlation during the baseline phase. Further exploration found that the delta-beta correlation was more robust for high facial attractiveness than low facial attractiveness in the high shyness group. However, no significant difference was found in the low-shyness group. This study suggests that a stronger delta-beta correlation might be the neural basis for shy individuals. Moreover, high facial attractiveness might enhance the delta-beta correlation of high shyness in anticipation of public speaking.

Special Report on the Impact of the COVID-19 Pandemic on Clinical EEG and Research and Consensus Recommendations for the Safe Use of EEG

INTRODUCTION

The global COVID-19 pandemic has affected the economy, daily life, and mental/physical health. The latter includes the use of electroencephalography (EEG) in clinical practice and research. We report a survey of the impact of COVID-19 on the use of clinical EEG in practice and research in several countries, and the recommendations of an international panel of experts for the safe application of EEG during and after this pandemic.

METHODS

Fifteen clinicians from 8 different countries and 25 researchers from 13 different countries reported the impact of COVID-19 on their EEG activities, the procedures implemented in response to the COVID-19 pandemic, and precautions planned or already implemented during the reopening of EEG activities.

RESULTS

Of the 15 clinical centers responding, 11 reported a total stoppage of all EEG activities, while 4 reduced the number of tests per day. In research settings, all 25 laboratories reported a complete stoppage of activity, with 7 laboratories reopening to some extent since initial closure. In both settings, recommended precautions for restarting or continuing EEG recording included strict hygienic rules, social distance, and assessment for infection symptoms among staff and patients/participants.

CONCLUSIONS

The COVID-19 pandemic interfered with the use of EEG recordings in clinical practice and even more in clinical research. We suggest updated best practices to allow safe EEG recordings in both research and clinical settings. The continued use of EEG is important in those with psychiatric diseases, particularly in times of social alarm such as the COVID-19 pandemic.

Synchronization of Independent Neural Ensembles in Human EEG during Choice Tasks

During behavioral experiments, humans placed in a situation of having to choose between a more valuable but risky reward and a less valuable but guaranteed reward make their decisions in accordance with external situational factors and individual characteristics, such as inclination to risk or caution. In such situations, humans can be divided into “risk-inclined” and “risk-averse” (or “cautious”) subjects. In this work, characteristics of EEG rhythms, such as phase–phase relationships and time lags between rhythms, were studied in pairs of alpha–beta and theta–beta rhythms. Phase difference can also be expressed as a time lag. It has been suggested that statistically significant time lags between rhythms are due to the combined neural activity of anatomically separate, independent (in activation/inhibition processes) ensembles. The extents of synchronicity between rhythms were compared as percentages between risk-inclined and risk-averse subjects. The results showed that synchronicity in response to stimuli was more often observed in pairs of alpha–beta rhythms of risk-averse subjects compared with risk-inclined subjects during the choice of a more valuable but less probable reward. In addition, significant differences in the percentage ratio of alpha and beta rhythms were revealed between (i) cases of synchronization without long time lags and (ii) cases with long time lags between rhythms (from 0.08 to 0.1 s).

The high-working load states induced by action real-time strategy gaming: An EEG power spectrum and network study

Action Real-time Strategy Gaming (ARSG) is a cognitively demanding task that requires attention, sensorimotor skills, high-level team coordination, and strategy-making abilities. Thus, ARSG can offer important, new insights into learning-related neural plasticity. However, little research has examined how the brain allocates cognitive resources in ARSG. By analyzing power spectrums and electroencephalograph (EEG) functional connectivity (FC) networks, this study compared multiple conditions (resting, movie watching, ARSG, and Life simulation gaming - LSG) in two experiments. Consistent with previous research, we found that brain waves appeared to be de-assimilated after activation. Furthermore, results showed that ARSG was associated with higher activation and workload as indicated by θ-waves, and required higher attention as reflected by β-waves. Furthermore, as participants began ARSG, the allocation of cognitive resource gradually prioritized the frontal area, which controls attention, decision-making, monitoring, and mnemonic processing, while participants also showed an enhanced ability to process information under the ARSG condition as indicated by network characteristics. These electrophysiological changes observed in ARSG were not found under LSG. Thus, this study applied both power spectrum and EEG FC networks analyses to ARSG research, revealing characteristics of brain waves in typical areas and how the brain gradually changes from low-working load states to high-working load states based on real-time EEG recordings.

Enhanced Theta-Band Coherence Between Midfrontal and Posterior Parietal Areas Reflects Post-feedback Adjustments in the State of Outcome Uncertainty

Medial frontal cortex is currently viewed as the main hub of the performance monitoring system; upon detection of an error committed, it establishes functional connections with brain regions involved in task performance, thus leading to neural adjustments in them. Previous research has identified targets of such adjustments in the dorsolateral prefrontal cortex, posterior cortical regions, motor cortical areas, and subthalamic nucleus. Yet most of such studies involved visual tasks with relatively moderate cognitive load and strong dependence on motor inhibition - thus highlighting sensory, executive and motor effects while underestimating sensorimotor transformation and related aspects of decision making. Currently there is ample evidence that posterior parietal cortical areas are involved in task-specific neural processes of decision making (including evidence accumulation, sensorimotor transformation, attention, etc.) - yet, to our knowledge, no EEG studies have demonstrated post-error increase in functional connectivity in the theta-band between midfrontal and posterior parietal areas during performance on non-visual tasks. In the present study, we recorded EEG while subjects were performing an auditory version of the cognitively demanding attentional condensation task; this task involves rather non-straightforward stimulus-to-response mapping rules, thus, creating increased load on sensorimotor transformation. We observed strong pre-response alpha-band suppression in the left parietal area, which presumably reflected involvement of the posterior parietal cortex in task-specific decision-making processes. Negative feedback was followed by increased midfrontal theta-band power and increased functional coupling in the theta band between midfrontal and left parietal regions. This could be interpreted as activation of the performance monitoring system and top-down influence of this system on the posterior parietal regions involved in decision making, respectively. This inter-site coupling related to negative feedback was stronger for subjects who tended to commit errors with slower response times. Generally, current findings support the idea that slower errors are related to the state of outcome uncertainty caused by failures of task-specific processes, associated with posterior parietal regions.

Interactions between frontal and posterior oscillatory dynamics support adjustment of stimulus processing during reinforcement learning

Reinforcement learning (RL) in humans is subserved by a network of striatal and frontal brain areas. The electrophysiological signatures of feedback evaluation are increasingly well understood, but how those signatures relate to the use of feedback to guide subsequent behavioral adjustment remains unclear. One mechanism for post-feedback behavioral optimization is the modulation of sensory processing. We used source-reconstructed MEG to test whether feedback affects the interactions between sources of oscillatory activity in the learning network and task-relevant stimulus-processing areas. Participants performed a probabilistic RL task in which they learned associations between colored faces and response buttons using trial-and-error feedback. Delta-band (2-4 Hz) and theta-band (4-8 Hz) power in multiple frontal regions were sensitive to feedback valence. Low and high beta-band power (12-20 and 20-30 Hz) in occipital, parietal, and temporal regions differentiated between color and face information. Consistent with our hypothesis, single-trial power-power correlations between frontal and posterior-sensory areas were modulated by the interaction between feedback valence and the relevant stimulus characteristic (color versus identity). These results suggest that long-range oscillatory coupling supports post-feedback updating of stimulus processing.

Added value of money on motor performance feedback: Increased left central beta-band power for rewards and fronto-central theta-band power for punishments

Monetary rewards and punishments have been shown to respectively enhance retention of motor memories and short-term motor performance, but their underlying neural bases in the context of motor control tasks remain unclear. Using electroencephalography (EEG), the present study tested the hypothesis that monetary rewards and punishments are respectively reflected in post-feedback beta-band (20-30 Hz) and theta-band (3-8 Hz) oscillatory power. While participants performed upper limb reaching movements toward visual targets using their right hand, the delivery of monetary rewards and punishments was manipulated as well as their probability (i.e., by changing target size). Compared to unrewarded and unpunished trials, monetary rewards and the successful avoidance of punishments both entailed greater beta-band power at left central electrodes overlaying contralateral motor areas. In contrast, monetary punishments and reward omissions both entailed increased theta-band power at fronto-central scalp sites. Additional analyses revealed that beta-band power was further increased when rewards were lowly probable. In light of previous work demonstrating similar beta-band modulations in basal ganglia during reward processing, the present results may reflect functional communication of reward-related information between the basal ganglia and motor cortical regions. In turn, the increase in fronto-central theta-band power after monetary punishments may reflect an emphasized cognitive need for behavioral adjustments. Globally, the present work identifies possible neural substrates for the growing behavioral evidence showing beneficial effects of monetary feedback on motor learning and performance.

Neural connectivity in Internet gaming disorder and alcohol use disorder: A resting-state EEG coherence study

The present study compared neural connectivity and the level of phasic synchronization between neural populations in patients with Internet gaming disorder (IGD), patients with alcohol use disorder (AUD), and healthy controls (HCs) using resting-state electroencephalography (EEG) coherence analyses. For this study, 92 adult males were categorized into three groups: IGD (n = 30), AUD (n = 30), and HC (n = 32). The IGD group exhibited increased intrahemispheric gamma (30-40 Hz) coherence compared to the AUD and HC groups regardless of psychological features (e.g., depression, anxiety, and impulsivity) and right fronto-central gamma coherence positively predicted the scores of the Internet addiction test in all groups. In contrast, the AUD group showed marginal tendency of increased intrahemispheric theta (4-8 Hz) coherence relative to the HC group and this was dependent on the psychological features. The present findings indicate that patients with IGD and AUD exhibit different neurophysiological patterns of brain connectivity and that an increase in the fast phasic synchrony of gamma coherence might be a core neurophysiological feature of IGD.

Theta and high-beta networks for feedback processing: a simultaneous EEG-fMRI study in healthy male subjects

The reward system is important in assessing outcomes to guide behavior. To achieve these purposes, its core components interact with several brain areas involved in cognitive and emotional processing. A key mechanism suggested to subserve these interactions is oscillatory activity, with a prominent role of theta and high-beta oscillations. The present study used single-trial coupling of simultaneously recorded electroencephalography and functional magnetic resonance imaging data to investigate networks associated with oscillatory responses to feedback during a two-choice gambling task in healthy male participants (n=19). Differential associations of theta and high-beta oscillations with non-overlapping brain networks were observed: Increase of high-beta power in response to positive feedback was associated with activations in a largely subcortical network encompassing core areas of the reward network. In contrast, theta-band power increase upon loss was associated with activations in a frontoparietal network that included the anterior cingulate cortex. Trait impulsivity correlated significantly with activations in areas of the theta-associated network. Our results suggest that positive and negative feedback is processed by separate brain networks associated with different cognitive functions. Communication within these networks is mediated by oscillations of different frequency, possibly reflecting different modes of dopaminergic signaling.

Willing to wait: Elevated reward-processing EEG activity associated with a greater preference for larger-but-delayed rewards

While almost everyone discounts the value of future rewards over immediate rewards, people differ in their so-called delay-discounting. One of the several factors that may explain individual differences in delay-discounting is reward-processing. To study individual-differences in reward-processing, however, one needs to consider the heterogeneity of neural-activity at each reward-processing stage. Here using EEG, we separated reward-related neural activity into distinct reward-anticipation and reward-outcome stages using time-frequency characteristics. Thirty-seven individuals first completed a behavioral delay-discounting task. Then reward-processing EEG activity was assessed using a separate reward-learning task, called a reward time-estimation task. During this EEG task, participants were instructed to estimate time duration and were provided performance feedback on a trial-by-trial basis. Participants received monetary-reward for accurate-performance on Reward trials, but not on No-Reward trials. Reward trials, relative to No-Reward trials, enhanced EEG activity during both reward-anticipation (including, cued-locked delta power during cue-evaluation and pre-feedback alpha suppression during feedback-anticipation) and reward-outcome (including, feedback-locked delta, theta and beta power) stages. Moreover, all of these EEG indices correlated with behavioral performance in the time-estimation task, suggesting their essential roles in learning and adjusting performance to maximize winnings in a reward-learning situation. Importantly, enhanced EEG power during Reward trials, as reflected by stronger 1) pre-feedback alpha suppression, 2) feedback-locked theta and 3) feedback-locked beta, was associated with a greater preference for larger-but-delayed rewards in a separate, behavioral delay-discounting task. Results highlight the association between a stronger preference toward larger-but-delayed rewards and enhanced reward-processing. Moreover, our reward-processing EEG indices detail the specific stages of reward-processing where these associations occur.

Oscillatory responses to reward processing in borderline personality disorder

OBJECTIVES

Previous electrophysiological studies have confirmed impaired reward processing in patients with BPD. However, it is not clear which aspects of reward processing are affected and which brain regions are involved. The present study investigated both evoked and induced event-related oscillations (EROs) to feedback events (thought to represent different aspects of feedback processing), and used source localization (sLORETA) to assess activity in two areas known to contribute to reward processing, the dorsomedial prefrontal/anterior cingulate cortex (dmPFC/ACC) and the orbitofrontal cortex (OFC).

METHODS

Eighteen patients with BPD and 22 healthy controls performed a gambling task, while 64-channel electroencephalographic activity was recorded. Evoked and induced theta and high-beta band EROs as well as activity in the two regions of interest were investigated depending on the valence and magnitude of feedback events.

RESULTS

Theta-band responses to negative feedback were reduced in BPD, an effect that involved only evoked responses and the dmPFC/ ACC region, and was associated with trait impulsivity in patients. sLORETA analyses revealed disturbed evoked responses depending on feedback magnitude in the theta (OFC) and high-beta (dmPFC/ACC and OFC) frequency range.

CONCLUSIONS

The results indicate multiple dysfunctions of feedback processing in patients with BPD, implicating several distinct subsets of reward-processing mechanisms.

Why don't you like me? Midfrontal theta power in response to unexpected peer rejection feedback

Social connectedness theory posits that the brain processes social rejection as a threat to survival. Recent electrophysiological evidence suggests that midfrontal theta (4-8Hz) oscillations in the EEG provide a window on the processing of social rejection. Here we examined midfrontal theta dynamics (power and inter-trial phase synchrony) during the processing of social evaluative feedback. We employed the Social Judgment paradigm in which 56 undergraduate women (mean age=19.67 years) were asked to communicate their expectancies about being liked vs. disliked by unknown peers. Expectancies were followed by feedback indicating social acceptance vs. rejection. Results revealed a significant increase in EEG theta power to unexpected social rejection feedback. This EEG theta response could be source-localized to brain regions typically reported during activation of the saliency network (i.e., dorsal anterior cingulate cortex, insula, inferior frontal gyrus, frontal pole, and the supplementary motor area). Theta phase dynamics mimicked the behavior of the time-domain averaged feedback-related negativity (FRN) by showing stronger phase synchrony for feedback that was unexpected vs. expected. Theta phase, however, differed from the FRN by also displaying stronger phase synchrony in response to rejection vs. acceptance feedback. Together, this study highlights distinct roles for midfrontal theta power and phase synchrony in response to social evaluative feedback. Our findings contribute to the literature by showing that midfrontal theta oscillatory power is sensitive to social rejection but only when peer rejection is unexpected, and this theta response is governed by a widely distributed neural network implicated in saliency detection and conflict monitoring.

Human oscillatory activity in near-miss events

Near-miss events are situations in which an action yields a negative result but is very close to being successful. They are known to influence behavior, especially in gambling scenarios. Previous neuroimaging studies have described an 'anomalous' activity of brain reward areas following these events. The goal of the present research was to study electrophysiological correlates of near-misses in the expectation and outcome phases. Electroencephalography was recorded while participants were playing a simplified version of a slot machine. Four possible outcomes (gain, near-miss, loss and no-information) were presented in a pseudorandom order to ensure fixed proportions. Results from the time-frequency analysis for the theta (4-8 Hz), alpha (9-13 Hz), low beta (15-22 Hz) and beta-gamma (25-35 Hz) frequency-bands presented larger power increases for wins and near-misses compared with losses. In the anticipation phase, power changes were lower than in the resolution phase. The current results are in agreement with previous studies showing that near-miss events recruit brain areas of the reward network. Likewise, the oscillatory activity in near-misses is very similar to the one elicited in the gain condition. In addition, present findings suggest that oscillatory activity in the expectation phase does not play a crucial role in near-miss events.

Dopamine modulates frontomedial failure processing of agentic introverts versus extraverts in incentive contexts

The agency facet of extraversion (aE) describes individual differences in goal-directed behavior and has been linked to dopamine function in incentive contexts. Because dopamine presumably modulates the processing of negative feedback/failure, aE may relate to failure processing in incentive contexts. To test this hypothesis, N = 86 participants performed a virtual ball-catching task. An incentive context was created by displaying potential rewards and subtle manipulations of task performance, which either was (control group) or was not (incentive context group) made explicit. To probe the involvement of dopamine, participants received either placebo or the selective dopamine D2 receptor antagonist sulpiride (200 mg). Failure processing was assessed through negative-feedback-evoked differences in the frontal midline theta electroencephalogram power (DFMT) and in the feedback-related negativity event-related potential component (FRN). Before incentives were introduced, DFMT (but not the FRN) was related to neuroticism/anxiety. Importantly, once incentives were displayed, aE was associated with DFMT, FRN, task performance, and changes in self-reported positive affect, which further depended on incentive context group and/or substance group: In the incentive context group but not in the control group, agentic extraverts showed relatively blunted DFMT after placebo. Sulpiride significantly enhanced DFMT, whereas it reduced FRN amplitudes and performance in agentic extra- versus introverts. These findings provide strong support for current dopamine models of aE and failure processing, and also highlight the importance of task context. Moreover, the dissociations of FRN and DFMT suggest the existence of two nonredundant electrophysiological indices of feedback processing, both relating to dopamine and aE.

Relationship between oscillatory neuronal activity during reward processing and trait impulsivity and sensation seeking

Background

The processing of reward and punishment stimuli in humans appears to involve brain oscillatory activity of several frequencies, probably each with a distinct function. The exact nature of associations of these electrophysiological measures with impulsive or risk-seeking personality traits is not completely clear. Thus, the aim of the present study was to investigate event-related oscillatory activity during reward processing across a wide spectrum of frequencies, and its associations with impulsivity and sensation seeking in healthy subjects.

Methods

During recording of a 32-channel EEG 22 healthy volunteers were characterized with the Barratt Impulsiveness and the Sensation Seeking Scale and performed a computerized two-choice gambling task comprising different feedback options with positive vs. negative valence (gain or loss) and high or low magnitude (5 vs. 25 points).

Results

We observed greater increases of amplitudes of the feedback-related negativity and of activity in the theta, alpha and low-beta frequency range following loss feedback and, in contrast, greater increase of activity in the high-beta frequency range following gain feedback. Significant magnitude effects were observed for theta and delta oscillations, indicating greater amplitudes upon feedback concerning large stakes. The theta amplitude changes during loss were negatively correlated with motor impulsivity scores, whereas alpha and low-beta increase upon loss and high-beta increase upon gain were positively correlated with various dimensions of sensation seeking.

Conclusions

The findings suggest that the processing of feedback information involves several distinct processes, which are subserved by oscillations of different frequencies and are associated with different personality traits.