Error-related medial frontal theta activity predicts cingulate-related structural connectivity

Attentional and cognitive monitoring brain networks in long-term meditators depend on meditation states and expertise

Meditation practice is suggested to engage training of cognitive control systems in the brain. To evaluate the functional involvement of attentional and cognitive monitoring processes during meditation, the present study analysed the electroencephalographic synchronization of fronto-parietal (FP) and medial-frontal (MF) brain networks in highly experienced meditators during different meditation states (focused attention, open monitoring and loving kindness meditation). The aim was to assess whether and how the connectivity patterns of FP and MF networks are modulated by meditation style and expertise. Compared to novice meditators, (1) highly experienced meditators exhibited a strong theta synchronization of both FP and MF networks in left parietal regions in all mediation styles, and (2) only the connectivity of lateralized beta MF networks differentiated meditation styles. The connectivity of intra-hemispheric theta FP networks depended non-linearly on meditation expertise, with opposite expertise-dependent patterns found in the left and the right hemisphere. In contrast, inter-hemispheric FP connectivity in faster frequency bands (fast alpha and beta) increased linearly as a function of expertise. The results confirm that executive control systems play a major role in maintaining states of meditation. The distinctive lateralized involvement of FP and MF networks appears to represent a major functional mechanism that supports both generic and style-specific meditation states. The observed expertise-dependent effects suggest that functional plasticity within executive control networks may underpin the emergence of unique meditation states in expert meditators.

Doing it Wrong: A Systematic Review on Electrocortical and Behavioral Correlates of Error Monitoring in Patients with Neurological Disorders

Detecting errors in one's own and other's actions is a crucial ability for learning and adapting behavior to everchanging, highly volatile environments. Studies in healthy people demonstrate that monitoring errors in one's own and others' actions are underpinned by specific neural systems that are dysfunctional in a variety of neurological disorders. In this review, we first briefly discuss the main findings concerning error detection and error awareness in healthy subjects, the current theoretical models, and the tasks usually applied to investigate these processes. Then, we report a systematic search for evidence of dysfunctional error monitoring among neurological populations (basal ganglia, neurodegenerative, white-matter diseases and acquired brain injury). In particular, we examine electrophysiological and behavioral evidence for specific alterations of error processing in neurological disorders. Error-related negativity (ERN) amplitude were reduced in most (although not all) neurological patient groups, whereas Positivity Error (Pe) amplitude appeared not to be affected in most patient groups. Also theta activity was reduced in some neurological groups, but consistent evidence on the oscillatory activity has not been provided thus far. Behaviorally, we did not observe relevant patterns of pronounced dysfunctional (post-) error processing. Finally, we discuss limitations of the existing literature, conclusive points, open questions and new possible methodological approaches for clinical studies.

Joint analysis of frontal theta synchrony and white matter following mild traumatic brain injury

Some of the most disabling aspects of mild traumatic brain injury (mTBI) include lingering deficits in executive functioning. It is known that mTBI can damage white matter tracts, but it remains unknown how this structural brain damage translates into cognitive deficits. This experiment utilized theta band phase synchrony to identify the dysfunctional neural operations that contribute to cognitive problems following mTBI. Sub-acute stage (< 2 weeks) mTBI patients (N = 52) and healthy matched controls (N = 32) completed a control-demanding task with concurrent EEG. Structural MRI was also collected. While there were no performance-specific behavioral differences between groups in the dot probe expectancy task, the degree of theta band phase synchrony immediately following injury predicted the degree of symptom recovery two months later. Although there were no differences in fractional anisotropy (FA) between groups, joint independent components analysis revealed that a smaller network of lower FA-valued voxels contributed to a diminished frontal theta phase synchrony network in the mTBI group. This finding suggests that frontal theta band markers of cognitive control are sensitive to sub-threshold structural aberrations following mTBI.

Learning something new versus changing your ways: Distinct effects on midfrontal oscillations and cardiac activity for learning and flexible adjustments

We need to be able to learn new behaviour, but also be capable of changing existing routines, when they start conflicting with our long-term goals. Little is known about to what extent blank-slate learning of new and adjustment of existing behavioural routines rely on different neural and bodily mechanisms. In the current study, participants first acquired novel stimulus-response contingencies, which were subsequently randomly changed to create the need for flexible adjustments. We measured midfrontal theta oscillations via EEG as an indicator of neural conflict processing, as well as heart rate as a proxy of autonomic activity. Participants' trial-wise learning progress was estimated via computation modelling. Theta power and heart rate significantly differed between correct and incorrect trials. Differences between correct and incorrect trials in both neural and cardiac feedback processing were more pronounced for adjustments compared to blank-slate learning. This indicates that both midfrontal and cardiac processing are sensitive to changes in stimulus-response contingencies. Increases in individual learning rates predicted lower impact of performance feedback on midfrontal theta power, but higher impact on heart rate. This suggests that cardiac and midfrontal reactivity are partially reflective of different mechanisms related to feedback learning. Our results shed new light on the role of neural and autonomic mechanisms for learning and behavioural adjustments.

Using eye-tracking and EEG to study the mental processing demands during learning of text-picture combinations

Using and combining eye-tracking and EEG frequency band power as process measures, in the current study we were interested in the mental processing demands during learning of text-picture combinations that either enabled or prohibited text-picture integration (TPI). In the mismatch condition, the textual and pictorial information being dissimilar, TPI was not possible, whereas in the match and the partial-match condition, the textual and pictorial information being identical respective complementary, TPI was possible. We expected mental processing demands to be higher in the mismatch condition, when pictorial and textual information had to be processed and memorized as separate representations, compared to the match and partial-match conditions when TPI was possible. As expected, on virtually all process measures we observed increased mental processing demands when two mental representations had to be processed and memorized compared to the two conditions where TPI was possible. The EEG alpha and theta frequency band power data corroborated and extended the eye-tracking measures of mental processing demands. In addition, we performed a fixation-related EEG frequency band power analysis that also corroborated the results of the classic stimulus-locked EEG frequency band power analysis, exemplifying the use of this former methodology in the context of complex multimedia task materials.

Cingulate oscillatory activity reflects the quality of memory representations in visuospatial working memory

The human brain has the high likelihood for committing errors when confronted by a day-to-day situation that demands to process more than four integrated items in working memory, for example driving a car to a new destination in high traffic. However, neural mechanisms underlying the response outcome in working memory is still unclear. High temporal resolution and improved spatial resolution of dense array electroencephalogram (EEG) make it an ideal tool to investigate the dynamics of brain networks. In the present study, the brain activity of twenty healthy male volunteers was investigated during correct and error trials of visuospatial working memory task using dense array EEG. Independent brain components were identified using independent component analysis (ICA). Event-related spectral perturbations (ERSP) were computed for each independent component using Morlet wavelet transform for the frequency range of 3-70 Hz. ERSP of independent component clusters identified using K-means algorithm were statistically compared between correct and error trials. Delta and theta power increased in the component cluster located at cingulate gyrus before the error response of visuospatial working memory task. The current study findings suggest that cingulate oscillatory activity might reflect the quality of memory representation and intensity of target uncertainty during the visuospatial search.

Aiming at ecological validity-Midfrontal theta oscillations in a toy gun shooting task

Laboratory electroencephalography (EEG) studies have already provided important insights into the neuronal mechanisms of performance monitoring. However, to our knowledge no study so far has examined neuronal correlates of performance monitoring using an ecologically valid task outside a typical laboratory setting. Therefore, we examined midfrontal theta and the feedback-related negativity (FRN) using mobile EEG in a physical shooting task within an ecologically valid environment with highly dynamical visual feedback. Participants shot a target using a toy gun while moving and looking around freely. Shots that missed the target evoked stronger midfrontal theta activity than hits and this response was rather phase-unlocked. There was no difference between misses and hits in the FRN. The results raise the question whether the absence of certain ERP components like the FRN could be due to methodological reasons or to the fact that partially different neuronal processes may be activated in the laboratory as compared to more ecologically valid tasks. Overall, our results indicate that crucial neurocognitive processes of performance monitoring can be assessed in highly dynamic and ecologically valid settings by mobile EEG.

Closed-Loop Frontal Midlineθ Neurofeedback: A Novel Approach for Training Focused-Attention Meditation

Cortical oscillations serve as an index of both sensory and cognitive processes and represent one of the most promising candidates for training and targeting the top-down mechanisms underlying executive functions. Research findings suggest that theta (θ) oscillations (3-7 Hz) recorded over frontal-midline electrodes are broadly associated with a number of higher-order cognitive processes and may serve as the mechanistic backbone for cognitive control. Frontal-midline theta (FMθ) oscillations have also been shown to inversely correlate with activity in the default mode network (DMN), a network in the brain linked to spontaneous thought processes such as mind-wandering and rumination. In line with these findings, we previously observed increased FMθ oscillations in expert meditation practitioners during reported periods of focused-attention meditation practice when compared to periods of mind-wandering. In an effort to narrow the explanatory gap by directly connecting observed neurophysiological activity in the brain to the phenomenological nature of reported experience, we designed a methodologically novel and adaptive neurofeedback protocol with the aim of modulating FMθ while having meditation novice participants implement breath-focus strategies derived from focused-attention mediation practices. Participants who received eight sessions of the adaptive FMθ-meditation neurofeedback protocol were able to significantly modulate FMθ over frontal electrodes using focused-attention meditation strategies relative to their baseline by the end of the training and demonstrated significantly faster reaction times on correct trials during the n-back working memory task assessed before and after the FMθ-meditation neurofeedback protocol. No significant differences in frontal theta activity or behavior were observed in the active control participants who received age and gender matched sham neurofeedback. These findings help lay the groundwork for the development of brain training protocols and neurofeedback applications that aim to train features of the mental states and traits associated with focused-attention meditation.

Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback

This article proposes what we call an "EEG-Copeia" for neurofeedback, like the "Pharmacopeia" for psychopharmacology. This paper proposes to define an "EEG-Copeia" as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

It's costly punishment, not altruistic: Low midfrontal theta and state anger predict punishment

Punishment in economic games has been interpreted as "altruistic." However, it was shown that punishment is related to trait anger instead of trait altruism in a third-party dictator game if compensation is also available. Here, we investigated the influence of state anger on punishment and compensation in the third-party dictator game. Therefore, we used movie sequences for emotional priming, including the target states anger, happy, and neutral. We measured the Feedback-Related Negativity (FRN) and midfrontal theta band activation, to investigate an electro-cortical correlate of the processing of fair and unfair offers. Also, we assessed single-trial FRN and midfrontal theta band activation as a predictor for punishment and compensation. We found that punishment was linked to state anger. Midfrontal theta band activation, which has previously been linked to altruistic acts and cognitive control, predicted less punishment. Additionally, trait anger led to enhanced FRN for unfair offers. This led to the interpretation that the FRN depicts the evaluation of fairness, while midfrontal theta band activation captures an aspect of cognitive control and altruistic motivation. We conclude that we need to redefine "altruistic punishment" into "costly punishment," as no direct link of altruism and punishment is given. Additionally, midfrontal theta band activation complements the FRN and offers additional insights into complex responses and decision processes, especially as a single trial predictor.

Midline frontal and occipito-temporal activity during error monitoring in dyadic motor interactions

Discrepancies between sensory predictions and action outcome are at the base of error coding. However, these phenomena have mainly been studied focussing on individual performance. Here, we explored EEG responses to motor prediction errors during a human-avatar interaction and show that Theta/Alpha activity of the frontal error-monitoring system works in phase with activity of the occipito-temporal node of the action observation network. Our motor interaction paradigm required healthy individuals to synchronize their reach-to-grasp movements with those of a virtual partner in conditions that did (Interactive) or did not require (Cued) movement prediction and adaptation to the partner's actions. Crucially, in 30% of the trials the virtual partner suddenly and unpredictably changed its movement trajectory thereby violating the human participant's expectation. These changes elicited error-related neuromarkers (ERN/Pe - Theta/Alpha modulations) over fronto-central electrodes during the Interactive condition. Source localization and connectivity analyses showed that the frontal Theta/Alpha activity induced by violations of the expected interactive movements was in phase with occipito-temporal Theta/Alpha activity. These results expand current knowledge about the neural correlates of on-line interpersonal motor interactions linking the frontal error-monitoring system to visual, body motion-related, responses.

A condition-independent framework for the classification of error-related brain activity

The cognitive processing and detection of errors is important in the adaptation of the behavioral and learning processes. This brain activity is often reflected as distinct patterns of event-related potentials (ERPs) that can be employed in the detection and interpretation of the cerebral responses to erroneous stimuli. However, high-accuracy cross-condition classification is challenging due to the significant variations of the error-related ERP components (ErrPs) between complexity conditions, thus hindering the development of error recognition systems. In this study, we employed support vector machines (SVM) classification methods, based on waveform characteristics of ErrPs from different time windows, to detect correct and incorrect responses in an audio identification task with two conditions of different complexity. Since the performance of the classifiers usually depends on the salience of the features employed, a combination of the sequential forward floating feature selection (SFFS) and sequential forward feature selection (SFS) methods was implemented to detect condition-independent and condition-specific feature subsets. Our framework achieved high accuracy using a small subset of the available features both for cross- and within-condition classification, hence supporting the notion that machine learning techniques can detect hidden patterns of ErrP-based features, irrespective of task complexity while additionally elucidating complexity-related error processing variations. Graphical abstract A schematic of the proposed approach. (a) EEG recordings in an auditory experiment in two conditions of different complexity. (b) Characteristic event related activity feature extraction. (c) Selection of feature vector subsets for easy and hard conditions corresponding to correct (Class1) and incorrect (Class2) responses. (d) Performance for individual and cross-condition classification.

Electrophysiological correlates of feedback processing in subarachnoid hemorrhage patients

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Subarachnoid hemorrhage patients show a reduced sensitivity to negative feedback, depicted by diminished amplitude of the feedback-related negativity (FRN).

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A delayed increase of theta oscillatory activity (4–8 Hz) was found for the patient group in presence of monetary losses compared to the healthy control group.

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No significant differences between groups were found at positive feedback event-related (ERP) components, such as the feedback P300 (FB-P3), neither on the time-frequency domain (beta-gamma band −25–35).

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Damage to medial prefrontal cortex (mPFC) regions might be altering the performance monitoring mechanisms associated to feedback processing and belief updating, resulting in altered day-to-day decision-making functioning.

Patients with subarachnoid hemorrhage (SAH) secondary to anterior communicating artery (AComA) aneurysm rupture often experience deficits in executive functioning and decision-making. Effective decision-making is based on the subjects’ ability to adjust their performance based on feedback processing, ascribing either positive or negative value to the actions performed reinforcing the most adaptive behavior in an appropriate temporal framework. A crucial brain structure associated to feedback processing is the medial prefrontal cortex (mPFC), a brain region frequently damaged after AComA aneurysm rupture. In the present study, we recorded electrophysiological responses (event-related potentials (ERPs') and oscillatory activity (time frequency analysis) during a gambling task in a series of 15 SAH patients. Previous studies have identified a feedback related negativity (FRN) component associated with an increase on frontal medial theta power in response to negative feedback or monetary losses, which is thought to reflect the degree of negative prediction error. Our findings show a decreased FRN component in response to negative feedback and a delayed increase of theta oscillatory activity in the SAH patient group when compared to the healthy controls, indicating a reduced sensitivity to negative feedback processing and an effortful signaling of cognitive control and monitoring processes lengthened in time, respectively. These results provide us with novel neurophysiological markers regarding feedback processing and performance monitoring patterns in SAH patients, illustrating a dysfunctional reinforcement learning system probably contributing to the maladaptive day-to-day functioning in these patients.

Error-Related Dynamics of Reaction Time and Frontal Midline Theta Activity in Attention Deficit Hyperactivity Disorder (ADHD) During a Subliminal Motor Priming Task

Post-error slowing (PES) is an established performance monitoring readout. Several previous studies have found that PES is reduced in children and adolescents with attention-deficit hyperactivity disorder (ADHD). We analyzed reaction time data, along with electroencephalography (EEG) data, from a response priming experiment in children and adolescents with ADHD (N = 28) and typically developing (TD) controls (N = 15) between 10 and 17 years of age. We report dynamic reaction time changes before and after errors: whereas TD controls readjusted their response speed to their individual average speed after committing an error, this reaction time adjustment appeared to be delayed and decreased in ADHD patients. In the EEG, error trials were accompanied by increased frontal midline theta activity, which was attenuated in ADHD compared to TD. We conclude that PES has a different time course rather than being fully absent in ADHD and discuss relationships with our EEG findings and potential implications for performance monitoring in ADHD.

Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity

Prior research has identified two resting EEG biomarkers with potential for predicting functional outcomes in depression: theta current density in frontal brain regions (especially rostral anterior cingulate cortex) and alpha power over posterior scalp regions. As little is known about the discriminant and convergent validity of these putative biomarkers, a thorough evaluation of these psychometric properties was conducted toward the goal of improving clinical utility of these markers. Resting 71-channel EEG recorded from 35 healthy adults at two sessions (1-week retest) were used to systematically compare different quantification techniques for theta and alpha sources at scalp (surface Laplacian or current source density [CSD]) and brain (distributed inverse; exact low resolution electromagnetic tomography [eLORETA]) level. Signal quality was evaluated with signal-to-noise ratio, participant-level spectra, and frequency PCA covariance decomposition. Convergent and discriminant validity were assessed within a multitrait-multimethod framework. Posterior alpha was reliably identified as two spectral components, each with unique spatial patterns and condition effects (eyes open/closed), high signal quality, and good convergent and discriminant validity. In contrast, frontal theta was characterized by one low-variance component, low signal quality, lack of a distinct spectral peak, and mixed validity. Correlations between candidate biomarkers suggest that posterior alpha components constitute reliable, convergent, and discriminant biometrics in healthy adults. Component-based identification of spectral activity (CSD/eLORETA-fPCA) was superior to fixed, a priori frequency bands. Improved quantification and conceptualization of frontal theta is necessary to determine clinical utility.

Midfrontal neural dynamics distinguish between general control and inhibition-specific processes in the stopping of motor actions

Action inhibition, the suppression of action impulses, is crucial for goal-directed behaviour. In order to dissociate neural mechanisms specific to motor stopping from general control processes which are also relevant for other types of conflict adjustments, we compared midfrontal oscillatory activity in human volunteers via EEG between action inhibition and two other types of motor conflicts, unexpected action activation and unexpected action change. Error rates indicated that action activation was significantly easier than the other two equally demanding tasks. Midfrontal brain oscillations were significantly stronger for inhibition than for both other conflict types. This was driven by increases in the delta range (2-3 Hz), which were higher for inhibition than activation and action change. Increases in the theta range (4-7 Hz) were equally high for inhibition and change, but lower for action activation. These findings suggest that inhibition is facilitated by neural mechanisms specific to motor-stopping, with midfrontal delta being a potentially selective marker of motor inhibition.

Graph-to-signal transformation based classification of functional connectivity brain networks

Complex network theory has been successful at unveiling the topology of the brain and showing alterations to the network structure due to brain disease, cognitive function and behavior. Functional connectivity networks (FCNs) represent different brain regions as the nodes and the connectivity between them as the edges of a graph. Graph theoretic measures provide a way to extract features from these networks enabling subsequent characterization and discrimination of networks across conditions. However, these measures are constrained mostly to binary networks and highly dependent on the network size. In this paper, we propose a novel graph-to-signal transform that overcomes these shortcomings to extract features from functional connectivity networks. The proposed transformation is based on classical multidimensional scaling (CMDS) theory and transforms a graph into signals such that the Euclidean distance between the nodes of the network is preserved. In this paper, we propose to use the resistance distance matrix for transforming weighted functional connectivity networks into signals. Our results illustrate how well-known network structures transform into distinct signals using the proposed graph-to-signal transformation. We then compute well-known signal features on the extracted graph signals to discriminate between FCNs constructed across different experimental conditions. Based on our results, the signals obtained from the graph-to-signal transformation allow for the characterization of functional connectivity networks, and the corresponding features are more discriminative compared to graph theoretic measures.

Enhancement of electroencephalogram activity in the theta-band range during unmatched olfactory-taste stimulation

The aim of this study was to investigate how odor stimulation affects taste perception. Electroencephalogram (EEG) signals were measured from the frontal region of the head in normal, healthy subjects, and frequency analyses were performed. Each odor stimulation was delivered while the subject was tasting chocolate, using chocolate paste as the odorant for 'matched odor stimulation,' and garlic paste for 'unmatched odor stimulation.' Differences in EEG signals appeared between the matched and unmatched arms of the study. Comparison of the frequencies of EEGs captured under the condition of unmatched odor stimulation with those captured under the condition of matched odor stimulation showed that the occupancy rate of the theta-frequency band under the condition of unmatched odor stimulation was higher than that under the condition of matched odor stimulation. Interestingly, a negative correlation existed between the occupancy rate of the theta-frequency band and the subjective feeling of chocolate sweetness. The present findings suggest that when humans receive odors that do not match with the foods being consumed, subjective feelings are disturbed and theta-band brain activity is increased while the unmatched information is cross-checked.

Theta-Band Functional Connectivity and Single-Trial Cognitive Control in Sports-Related Concussion: Demonstration of Proof-of-Concept for a Potential Biomarker of Concussion

OBJECTIVES

This report examined theta-band neurodynamics for potential biomarkers of brain health in athletes with concussion.

METHODS

Participants included college-age contact/collision athletes with (N=24) and without a history of concussion (N=16) in Study 1. Study 2 (N=10) examined changes over time in contact/collision athletes. There were two primary dependent variables: (1) theta-band phase-synchronization (e.g., functional connectivity) between medial and right-lateral electrodes; and (2) the within-subject correlation between synchronization strength on error trials and post-error reaction time (i.e., operationalization of cognitive control).

RESULTS

Head injury history was inversely related with medial-lateral connectivity. Head injury was also related to declines in a neurobehavioral measure of cognitive control (i.e., the single-trial relationship between connectivity and post-error slowing).

CONCLUSIONS

Results align with a theory of connectivity-mediated cognitive control. Mild injuries undetectable by behavioral measures may still be apparent on direct measures of neural functioning. This report demonstrates that connectivity and cognitive control measures may be useful for tracking recovery from concussion. Theoretically relevant neuroscientific findings in healthy adults may have applications in patient populations, especially with regard to monitoring brain health. (JINS 2019, 25, 314-323).

Temporal and spectral profiles of conflict processing among multiple frames of reference

Individuals rely on various frames of reference (FORs), such as an egocentric FOR (EFOR) and intrinsic FOR (IFOR), to represent spatial information. Previous behavioral studies have shown different IFOR-IFOR (II) and EFOR-IFOR (EI) conflict effects and an effect of their interaction. However, the neural mechanism of conflict processing between two FOR-based conflicts is unclear. In the current ERP study, two FOR-based conflicts were manipulated using a two-cannon task to elucidate common and distinct brain mechanisms that underlie FOR-based conflict processing. The behavioral results showed that both conflicts exhibited longer reaction times and larger error rates in the II (180° cannon angle) and EI (target cannon pointed down) incongruent conditions than in the II (0° cannon angle) and EI (target cannon pointed up) congruent conditions and that an interaction existed between the two conflicts. The ERP results indicated that, for both conflicts, more negative N2 amplitudes and less positive P3 amplitudes occurred in the incongruent conditions than in the congruent conditions, and the interactions between the two conflicts during later P3 amplitudes were significant. Time-frequency analysis further indicated that, in the early time window, the II conflict and the EI conflict specifically modulated power in the theta bands and beta bands, respectively. In contrast, in the later time window, both conflicts modulated power in the alpha and beta bands. In summary, our findings provide insights into the potential existence of two specific early conflict monitoring systems and a general late executive control system for FOR-based conflicts.

Impaired Midline Theta Power and Connectivity During Proactive Cognitive Control in Schizophrenia

BACKGROUND

Disrupted proactive cognitive control, a form of early selection and active goal maintenance, is hypothesized to underlie the broad cognitive deficits observed in patients with schizophrenia (SPs). Current research suggests that the disrupted activation within and connectivity between regions of the cognitive control network contribute to disrupted proactive cognitive control; however, no study has examined these mechanisms using an AX Continuous Performance Test task in schizophrenia.

METHODS

Twenty-six SPs (17 male subjects; mean age 34.46 ± 8.77 years) and 28 healthy control participants (HCs; 16 male subjects; mean age 31.43 ± 7.23 years) underwent an electroencephalogram while performing the AX Continuous Performance Test. To examine the extent of activation and level of connectivity within the cognitive control network, power, intertrial phase clustering, and intersite phase clustering metrics were calculated and analyzed.

RESULTS

SPs exhibited expected general decrements in behavioral performance relative to HCs and a more selective deficit in conditions requiring proactive cognitive control. Additionally, SPs exhibited deficits in midline theta power and connectivity during proactive cognitive control trials. Specifically, HCs exhibited significantly greater theta power for B cues relative to A cues, whereas SPs exhibited no significant differences between A- and B-cue theta power. Additionally, differential theta connectivity patterns were observed in SPs and HCs. Behavioral measures of proactive cognitive control predicted functional outcomes in SPs.

CONCLUSIONS

This study suggests that low-frequency midline theta activity is selectively disrupted during proactive cognitive control in SPs. The disrupted midline theta activity may reflect a failure of SPs to proactively recruit cognitive control processes.

Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action

Motivation exerts control over behavior by eliciting Pavlovian responses, which can either match or conflict with instrumental action. We can overcome maladaptive motivational influences putatively through frontal cognitive control. However, the neurocomputational mechanisms subserving this control are unclear; does control entail up-regulating instrumental systems, down-regulating Pavlovian systems, or both? We combined electroencephalography (EEG) recordings with a motivational Go/NoGo learning task (N = 34), in which multiple Go options enabled us to disentangle selective action learning from nonselective Pavlovian responses. Midfrontal theta-band (4 Hz–8 Hz) activity covaried with the level of Pavlovian conflict and was associated with reduced Pavlovian biases rather than reduced instrumental learning biases. Motor and lateral prefrontal regions synchronized to the midfrontal cortex, and these network dynamics predicted the reduction of Pavlovian biases over and above local, midfrontal theta activity. This work links midfrontal processing to detecting Pavlovian conflict and highlights the importance of network processing in reducing the impact of maladaptive, Pavlovian biases.

The anticipation of reward and punishment are key drivers of behavior: we tend to take action for rewards while holding back in the face of punishment. This motivational bias might have an overall evolutionary advantage but can also work against us in specific situations. Here, we first asked whether this motivational bias relies on innate, automatic action tendencies or whether this bias might actually itself be learned. Secondly, we studied which brain processes reduce the impact of these motivational drives when they become dysfunctional. By comparing the actions of human participants to the predictions of several mathematical models, we showed that the motivational bias in action relies partly on automatic tendencies and partly on asymmetric learning from experience. We then observed that activity over the midfrontal cortex specifically increased as a function of how dysfunctional the automatic tendencies were. Additionally, this midfrontal cortex activity was functionally connected to the motor and lateral frontal cortices, which play a role in activating and inhibiting behavior. By incorporating this connectivity into the mathematical models, we showed that stronger midfrontal connectivity predicted reduced impact of dysfunctional automatic tendencies on behavior. We propose that the midfrontal cortex detects dysfunctional action tendencies and implements cognitive control by signaling across the network.

Conflict-related medial frontal theta as an endophenotype for alcohol use disorder

Diminished cognitive control in alcohol use disorder (AUD) is thought to be mediated by prefrontal cortex circuitry dysregulation. Research testing the relationship between AUD and specific cognitive control psychophysiological correlates, such as medial frontal (MF) theta-band EEG power, is scarce, and the etiology of this relationship is largely unknown. The current report tested relationship between pathological alcohol use through young adulthood and reduced conflict-related theta at age 29 in a large prospective population-based twin sample. Greater lifetime AUD symptomatology was associated with reduced MF theta power during response conflict, but not alpha-band visual attention processing. Follow-up analyses using cotwin control analysis and biometric modeling suggested that genetic influences, and not the consequences of sustained AUD symptomatology, explained the theta-AUD association. Results provide strong evidence that AUD is genetically related to diminished conflict-related MF theta, and advance MF theta as a promising electrophysiological correlate of AUD-related dysfunctional frontal circuitry.

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.

Theta oscillations promote temporal sequence learning

Many theoretical models suggest that neural oscillations play a role in learning or retrieval of temporal sequences, but the extent to which oscillations support sequence representation remains unclear. To address this question, we used scalp electroencephalography (EEG) to examine oscillatory activity over learning of different object sequences. Participants made semantic decisions on each object as they were presented in a continuous stream. For three "Consistent" sequences, the order of the objects was always fixed. Activity during Consistent sequences was compared to "Random" sequences that consisted of the same objects presented in a different order on each repetition. Over the course of learning, participants made faster semantic decisions to objects in Consistent, as compared to objects in Random sequences. Thus, participants were able to use sequence knowledge to predict upcoming items in Consistent sequences. EEG analyses revealed decreased oscillatory power in the theta (4-7 Hz) band at frontal sites following decisions about objects in Consistent sequences, as compared with objects in Random sequences. The theta power difference between Consistent and Random only emerged in the second half of the task, as participants were more effectively able to predict items in Consistent sequences. Moreover, we found increases in parieto-occipital alpha (10-13 Hz) and beta (14-28 Hz) power during the pre-response period for objects in Consistent sequences, relative to objects in Random sequences. Linear mixed effects modeling revealed that single trial theta oscillations were related to reaction time for future objects in a sequence, whereas beta and alpha oscillations were only predictive of reaction time on the current trial. These results indicate that theta and alpha/beta activity preferentially relate to future and current events, respectively. More generally our findings highlight the importance of band-specific neural oscillations in the learning of temporal order information.

Cross-frequency interactions between frontal theta and posterior alpha control mechanisms foster working memory

Neural oscillatory activity in the theta (4-8 Hz) and alpha (8-14 Hz) bands has been associated with the implementation of executive function, with theta in midline frontal cortex and alpha in posterior parietal cortex related to working memory (WM) load. To identify how these spatially and spectrally distinct neural phenomena interact within a large-scale fronto-parietal network organized in service of WM, EEG was recorded while subjects performed an N-back WM task. Frontal theta power increase, paralleled by posterior alpha decrease, tracked participants' successful WM performance. These power fluctuations were inversely related both across and within trials and predicted reaction time, suggesting a functionally important communication channel within the fronto-parietal network. Granger causality analysis revealed directed parietal to frontal communication via alpha and frontal to parietal communication via theta. Results encourage consideration of these bidirectional, power-to-power, cross-frequency control mechanisms as an important feature of cerebral network organization supporting executive function.

Utilizing time-frequency amplitude and phase synchrony measure to assess feedback processing in a gambling task

The neurophysiological mechanisms involved in the evaluation of performance feedback have been widely studied in the ERP literature over the past twenty years, but understanding has been limited by the use of traditional time-domain amplitude analytic approaches. Gambling outcome valence has been identified as an important factor modulating event-related potential (ERP) components, most notably the feedback negativity (FN). Recent work employing time-frequency analysis has shown that processes indexed by the FN are confounded in the time-domain and can be better represented as separable feedback-related processes in the theta (3-7 Hz) and delta (0-3 Hz) frequency bands. In addition to time-frequency amplitude analysis, phase synchrony measures have begun to further our understanding of performance evaluation by revealing how feedback information is processed within and between various brain regions. The current study aimed to provide an integrative assessment of time-frequency amplitude, inter-trial phase synchrony, and inter-channel phase synchrony changes following monetary feedback in a gambling task. Results revealed that time-frequency amplitude activity explained separable loss and gain processes confounded in the time-domain. Furthermore, phase synchrony measures explained unique variance above and beyond amplitude measures and demonstrated enhanced functional integration between medial prefrontal and bilateral frontal, motor, and occipital regions for loss relative to gain feedback. These findings demonstrate the utility of assessing time-frequency amplitude, inter-trial phase synchrony, and inter-channel phase synchrony together to better elucidate the neurophysiology of feedback processing.

Structural Integrity in the Genu of Corpus Callosum Predicts Conflict-induced Functional Connectivity Between Medial Frontal Cortex and Right Posterior Parietal Cortex

Studies using the flanker task have reported that response conflict is detected by the medial frontal cortex (MFC). As a conflict alert system, the MFC shows enhanced functional communication with task-related regions. Previous studies have revealed individual differences in functional connectivity during cognitive task performance. However, the mechanisms underlying these individual differences remain unclear. In the current study, electroencephalography (EEG) was recorded while 30 subjects performed a flanker task that was modified to exclude feature integration and contingency learning. The diffusion tensor imaging (DTI) data were collected the day before the EEG session. FCz-P3/4 theta phase synchronization was used to measure functional connectivity between the MFC and posterior parietal cortex (PPC). Hierarchical regression analyses were used to assess the relationship between MFC-PPC conflict-induced theta phase synchronization and white matter integrity in significant regions derived from tract-based spatial statistics (TBSS) analysis. As expected, MFC-PPC theta phase synchronization was significantly enhanced during conflict, suggesting a conflict-induced functional connectivity. However, these findings were only found in the right hemisphere, which may be related to the asymmetrical role of the bilateral PPC in response conflict processing. Furthermore, hierarchical regression analyses revealed that 44% of individual variability in FCz-P4 conflict-induced theta phase synchronization could be explained by variations in axial diffusivity (AD) in the genu of the corpus callosum (gCC). These results demonstrated that structural integrity in the gCC predicts conflict-induced functional connectivity between the MFC and right PPC.

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.

Theta- and delta-band EEG network dynamics during a novelty oddball task

While the P3 component during target detection and novelty processing has been widely studied, less is known about its underlying network dynamics. A recent cognitive model suggests that frontal-parietal and frontal-temporal interregional connectivity are related to attention/action selection and target-related memory updating during the P3, respectively, but empirical work testing this model is lacking. Other work suggests the importance of theta- and delta-band connectivity between the medial frontal cortex and distributed cortical regions during attention, stimulus detection, and response selection processes, and similar dynamics may underlie P3-related network connectivity. The present study evaluated the functional connectivity elicited during a visual task, which combined oddball target and novelty stimuli, in a sample of 231 same-sex twins. It was hypothesized that both target and novel conditions would involve theta frontoparietal connectivity and medial frontal theta power, but that target stimuli would elicit the strongest frontotemporal connectivity. EEG time-frequency analysis revealed greater theta-band frontoparietal connectivity and medial frontal power during both target and novel conditions compared to standards, which may index conflict/uncertainty resolution processes. Theta-band frontotemporal connectivity was maximal during the target condition, potentially reflecting context updating or stimulus-response activation. Delta-band frontocentral-parietal connectivity was also strongest following targets, which may be sensitive to response-related demands. These results suggest the existence of functional networks related to P3 that are differentially engaged by target oddballs and novel distractors. Compared to simple P3 amplitude, network measures may provide a more nuanced view of the neural dynamics during target detection/novelty processing in normative and pathological populations.

Cingulate and cerebellar beta oscillations are engaged in the acquisition of auditory-motor sequences

Singing, music performance, and speech rely on the retrieval of complex sounds, which are generated by the corresponding actions and are organized into sequences. It is crucial in these forms of behavior that the serial organization (i.e., order) of both the actions and associated sounds be monitored and learned. To investigate the neural processes involved in the monitoring of serial order during the initial learning of sensorimotor sequences, we performed magnetoencephalographic recordings while participants explicitly learned short piano sequences under the effect of occasional alterations of auditory feedback (AAF). The main result was a prominent and selective modulation of beta (13-30 Hz) oscillations in cingulate and cerebellar regions during the processing of AAF that simulated serial order errors. Furthermore, the AAF-induced modulation of beta oscillations was associated with higher error rates, reflecting compensatory changes in sequence planning. This suggests that cingulate and cerebellar beta oscillations play a role in tracking serial order during initial sensorimotor learning and in updating the mapping of the sensorimotor representations. The findings support the notion that the modulation of beta oscillations is a candidate mechanism for the integration of sequential motor and auditory information during an early stage of skill acquisition in music performance. This has potential implications for singing and speech. Hum Brain Mapp 38:5161-5179, 2017. © 2017 Wiley Periodicals, Inc.

Ipsilateral EEG mu rhythm reflects the excitability of uncrossed pathways projecting to shoulder muscles

BACKGROUND

Motor planning, imagery or execution is associated with event-related desynchronization (ERD) of mu rhythm oscillations (8-13 Hz) recordable over sensorimotor areas using electroencephalography (EEG). It was shown that motor imagery involving distal muscles, e.g. finger movements, results in contralateral ERD correlating with increased excitability of the contralateral corticospinal tract (c-CST). Following the rationale that purposefully increasing c-CST excitability might facilitate motor recovery after stroke, ERD recently became an attractive target for brain-computer interface (BCI)-based neurorehabilitation training. It was unclear, however, whether ERD would also reflect excitability of the ipsilateral corticospinal tract (i-CST) that mainly innervates proximal muscles involved in e.g. shoulder movements. Such knowledge would be important to optimize and extend ERD-based BCI neurorehabilitation protocols, e.g. to restore shoulder movements after stroke. Here we used single-pulse transcranial magnetic stimulation (TMS) targeting the ipsilateral primary motor cortex to elicit motor evoked potentials (MEPs) of the trapezius muscle. To assess whether ERD reflects excitability of the i-CST, a correlation analysis between between MEP amplitudes and ipsilateral ERD was performed.

METHODS

Experiment 1 consisted of a motor execution task during which 10 healthy volunteers performed elevations of the shoulder girdle or finger pinching while a 128-channel EEG was recorded. Experiment 2 consisted of a motor imagery task during which 16 healthy volunteers imagined shoulder girdle elevations or finger pinching while an EEG was recorded; the participants simultaneously received randomly timed, single-pulse TMS to the ipsilateral primary motor cortex. The spatial pattern and amplitude of ERD and the amplitude of the agonist muscle's TMS-induced MEPs were analyzed.

RESULTS

ERDs occurred bilaterally during both execution and imagery of shoulder girdle elevations, but were lateralized to the contralateral hemisphere during finger pinching. We found that trapezius MEPs increased during motor imagery of shoulder elevations and correlated with ipsilateral ERD amplitudes.

CONCLUSIONS

Ipsilateral ERD during execution and imagery of shoulder girdle elevations appears to reflect the excitability of uncrossed pathways projecting to the shoulder muscles. As such, ipsilateral ERD could be used for neurofeedback training of shoulder movement, aiming at reanimation of the i-CST.

Parsing the neural signatures of reduced error detection in older age

Recent work has demonstrated that explicit error detection relies on a neural evidence accumulation process that can be traced in the human electroencephalogram (EEG). Here, we sought to establish the impact of natural aging on this process by recording EEG from young (18-35 years) and older adults (65-88 years) during the performance of a Go/No-Go paradigm in which participants were required to overtly signal their errors. Despite performing the task with equivalent accuracy, older adults reported substantially fewer errors, and the timing of their reports were both slower and more variable. These behavioral differences were linked to three key neurophysiological changes reflecting distinct parameters of the error detection decision process: a reduction in medial frontal delta/theta (2-7 Hz) activity, indicating diminished top-down input to the decision process; a slower rate of evidence accumulation as indexed by the rate of rise of a centro-parietal signal, known as the error positivity; and a higher motor execution threshold as indexed by lateralized beta-band (16-30 Hz) activity. Our data provide novel insight into how the natural aging process affects the neural underpinnings of error detection.

Slow and Fast Responses: Two Mechanisms of Trial Outcome Processing Revealed by EEG Oscillations

Cognitive control includes maintenance of task-specific processes related to attention, and non-specific regulation of motor threshold. Depending upon the nature of the behavioral tasks, these mechanisms may predispose to different kinds of errors, with either increased or decreased response time (RT) of erroneous responses relative to correct responses. Specifically, slow responses are related to attentional lapses and decision uncertainty, these conditions tending to delay RTs of both erroneous and correct responses. Here we studied if RT may be a valid approximation distinguishing trials with high and low levels of sustained attention and decision uncertainty. We analyzed response-related and feedback-related modulations in theta, alpha and beta band activity in the auditory version of the two-choice condensation task, which is highly demanding for sustained attention while involves no inhibition of prepotent responses. Depending upon response speed and accuracy, trials were divided into slow correct, slow erroneous, fast correct and fast erroneous. We found that error-related frontal midline theta (FMT) was present only on fast erroneous trials. The feedback-related FMT was equally strong on slow erroneous and fast erroneous trials. Late post-response posterior alpha suppression was stronger on erroneous slow trials. Feedback-related frontal beta was present only on slow correct trials. The data obtained cumulatively suggests that RT allows distinguishing the two types of trials, with fast trials related to higher levels of attention and low uncertainty, and slow trials related to lower levels of attention and higher uncertainty.

Error-related oscillatory activity is modulated by novelty seeking in the reward condition

Behavioural research has revealed the influence of motivation conditions on cognitive task performance and demonstrated that these influences are modulated by temperament factors. Modern neuroimaging methods enable analysis of neuropsychological mechanisms through which individual differences in reinforcement sensitivity may influence cognitive functioning. In the study, fifty-six participants were scored on the Cloninger's Temperament and Character Inventory to assess punishment and reward sensitivity. Then, subjects participated in an EEG experiment using the numerical Stroop task under different motivational conditions. In one condition, they were punished for erroneous responses; in the other, they were rewarded for correct performance. We analysed event related changes in EEG spectral power to investigate the influence of temperamentally driven differences on error-related oscillatory brain activity. In agreement with previous findings, after incorrect responses an increase in frontocentral theta (3-7Hz) and a decrease in occipital alpha (10-11Hz) power were observed. Moreover, a multivariate regression analysis showed that these spectral markers were modulated by temperamental trait Novelty Seeking in the reward condition. To our knowledge, we are the first to demonstrate such a relationship between individual differences and error-related oscillatory activity. This neuronal pattern may explain why participants that score high on Novelty Seeking trait are highly motivated and strongly engaged in a task when a reward might be earned. Thus, in conclusion we emphasise that to understand an individual's response to errors, it is necessary to account simultaneously for motivational conditions as well as temperament traits.