Exploiting the intra-subject latency variability from single-trial event-related potentials in the P3 time range: A review and comparative evaluation of methods

The late positive event-related potential component is time locked to the decision in recognition memory tasks

Two event-related potential (ERP) components are commonly observed in recognition memory tasks: the Frontal Negativity (FN400) and the Late Positive Component (LPC). These components are widely interpreted as neural correlates of familiarity and recollection, respectively. However, the interpretation of LPC effects is complicated by inconsistent results regarding the timing of ERP amplitude differences. There are also mixed findings regarding how LPC amplitudes covary with decision confidence. Critically, LPC effects have almost always been measured using fixed time windows relative to memory probe stimulus onset, yet it has not been determined whether LPC effects are time locked to the stimulus or the recognition memory decision. To investigate this, we analysed a large (n = 132) existing dataset recorded during recognition memory tasks with old/new decisions followed by post-decisional confidence ratings. We used ERP deconvolution to disentangle contributions to LPC effects (defined as differences between hits and correct rejections) that were time locked to either the stimulus or the vocal old/new response. We identified a left-lateralised parietal LPC effect that was time locked to the vocal response rather than probe stimulus onset. We also isolated a response-locked, midline parietal ERP correlate of confidence that influenced measures of LPC amplitudes at left parietal electrodes. Our findings demonstrate that, contrary to widespread assumptions, the LPC effect is time locked to the recognition memory decision and is best measured using response-locked ERPs. By extension, differences in response time distributions across conditions of interest may lead to substantial measurement biases when analysing stimulus-locked ERPs. Our findings highlight important confounding factors that further complicate the interpretation of existing stimulus-locked LPC effects as neural correlates of recollection. We recommend that future studies adopt our analytic approach to better isolate LPC effects and their sensitivity to manipulations in recognition memory tasks.

Analysis of modulations of mental fatigue on intra-individual variability from single-trial event related potentials

BACKGROUND

Intra-individual variability (IIV), a measure of variance within an individual's performance, has been demonstrated as metrics of brain responses for neural functionality. However, how mental fatigue modulates IIV remains unclear. Consequently, the development of robust mental fatigue detection methods at the single-trial level is challenging.

NEW METHODS

Based on a long-duration flanker task EEG dataset, the modulations of mental fatigue on IIV were explored in terms of response time (RT) and trial-to-trial latency variations of event-related potentials (ERPs). Specifically, latency variations were quantified using residue iteration decomposition (RIDE) to reconstruct latency-corrected ERPs. We compared reconstructed ERPs with raw ERPs by means of temporal principal component analysis (PCA). Furthermore, a single-trial classification pipeline was developed to detect the changes of mental fatigue levels.

RESULTS

We found an increased IIV in the RT metric in the fatigue state compared to the alert state. The same sequence of ERPs (N1, P2, N2, P3a, P3b, and slow wave, or SW) was separated from both raw and reconstructed ERPs using PCA, whereas differences between raw and reconstructed ERPs in explained variances for separated ERPs were found owing to IIV. Particularly, a stronger N2 was detected in the fatigue than alert state after RIDE. The single-trial fatigue detection pipeline yielded an acceptable accuracy of 73.3%.

COMPARISON WITH EXISTING METHODS

The IIV has been linked to aging and brain disorders, and as an extension, our finding demonstrates IIV as an efficient indicator of mental fatigue.

CONCLUSIONS

This study reveals significant modulations of mental fatigue on IIV at the behavioral and neural levels and establishes a robust mental fatigue detection pipeline.

Modeling intra-individual inter-trial EEG response variability in autism

Autism spectrum disorder (autism) is a prevalent neurodevelopmental condition characterized by early emerging impairments in social behavior and communication. EEG represents a powerful and non-invasive tool for examining functional brain differences in autism. Recent EEG evidence suggests that greater intra-individual trial-to-trial variability across EEG responses in stimulus-related tasks may characterize brain differences in autism. Traditional analysis of EEG data largely focuses on mean trends of the trial-averaged data, where trial-level analysis is rarely performed due to low neural signal to noise ratio. We propose to use nonlinear (shape-invariant) mixed effects (NLME) models to study intra-individual inter-trial EEG response variability using trial-level EEG data. By providing more precise metrics of response variability, this approach could enrich our understanding of neural disparities in autism and potentially aid the identification of objective markers. The proposed multilevel NLME models quantify variability in the signal's interpretable and widely recognized features (e.g., latency and amplitude) while also regularizing estimation based on noisy trial-level data. Even though NLME models have been studied for more than three decades, existing methods cannot scale up to large data sets. We propose computationally feasible estimation and inference methods via the use of a novel minorization-maximization (MM) algorithm. Extensive simulations are conducted to show the efficacy of the proposed procedures. Applications to data from a large national consortium find that children with autism have larger intra-individual inter-trial variability in P1 latency in a visual evoked potential (VEP) task, compared to their neurotypical peers.

Temporal dynamics and neural variabilities underlying the interplay between emotion and inhibition in Chinese autistic children

This study investigated the neural dynamics underlying the interplay between emotion and inhibition in Chinese autistic children. Electroencephalography (EEG) signals were recorded from 50 autistic and 46 non-autistic children during an emotional Go/Nogo task. Based on single-trial ERP analyses, autistic children, compared to their non-autistic peers, showed a larger Nogo-N170 for angry faces and an increased Nogo-N170 amplitude variation for happy faces during early visual perception. They also displayed a smaller N200 for all faces and a diminished Nogo-N200 amplitude variation for happy and neutral faces during inhibition monitoring and preparation. During the late stage, autistic children showed a larger posterior-Go-P300 for angry faces and an augmented posterior-Nogo-P300 for happy and neutral faces. These findings clarify the differences in neural processing of emotional stimuli and inhibition between Chinese autistic and non-autistic children, highlighting the importance of considering these dynamics when designing intervention to improve emotion regulation in autistic children.

Response stopping under conflict: The integrative role of representational dynamics associated with the insular cortex

Coping with distracting inputs during goal-directed behavior is a common challenge, especially when stopping ongoing responses. The neural basis for this remains debated. Our study explores this using a conflict-modulation Stop Signal task, integrating group independent component analysis (group-ICA), multivariate pattern analysis (MVPA), and EEG source localization analysis. Consistent with previous findings, we show that stopping performance is better in congruent (nonconflicting) trials than in incongruent (conflicting) trials. Conflict effects in incongruent trials compromise stopping more due to the need for the reconfiguration of stimulus-response (S-R) mappings. These cognitive dynamics are reflected by four independent neural activity patterns (ICA), each coding representational content (MVPA). It is shown that each component was equally important in predicting behavioral outcomes. The data support an emerging idea that perception-action integration in action-stopping involves multiple independent neural activity patterns. One pattern relates to the precuneus (BA 7) and is involved in attention and early S-R processes. Of note, three other independent neural activity patterns were associated with the insular cortex (BA13) in distinct time windows. These patterns reflect a role in early attentional selection but also show the reiterated processing of representational content relevant for stopping in different S-R mapping contexts. Moreover, the insular cortex's role in automatic versus complex response selection in relation to stopping processes is shown. Overall, the insular cortex is depicted as a brain hub, crucial for response selection and cancellation across both straightforward (automatic) and complex (conditional) S-R mappings, providing a neural basis for general cognitive accounts on action control.

Effects of an acute bout of cycling on different domains of cognitive function

The literature suggesting acute exercise benefits cognitive function has been largely confined to single cognitive domains and measures of reliant on measures of central tendencies. Furthermore, studies suggest cognitive intra-individual variability (IIV) to reflect cognitive efficiency and provide unique insights into cognitive function, but there is limited knowledge on the effects of acute exercise on IIV. To this end, this study examined the effects of acute exercise on three different cognitive domains, executive function, implicit learning, and hippocampal-dependent memory function using behavioral performance and event-related potentials (ERPs). Furthermore, this study also sought to explore the effects of an acute bout of exercise on IIV using the RIDE algorithm to separate signals into individuals components based on latency variability. Healthy adult participants (N=20; 26.3±4.8years) completed a randomized cross-over trial with seated rest or 30min of high intensity cycling. Before and after each condition, participants completed a cognitive battery consisting of the Eriksen Flanker task, implicit statistical learning task, and a spatial reconstruction task. While exercise did not affect Flanker or spatial reconstruction performance, there were exercise related decreases in accuracy (F=5.47; P=0.040), slowed reaction time (F=5.18; P=0.036), and decreased late parietal positivity (F=4.26; P=0.046). However, upon adjusting for performance and ERP variability, there were exercise related decreases in Flanker reaction time (F=24.00; P<0.001), and reduced N2 amplitudes (F=13.03; P=0.002), and slower P3 latencies (F=3.57; P=0.065) for incongruent trials. These findings suggest that acute exercise may impact cognitive IIV as an adaptation to maintain function following exercise.

Domain-Specific Processing Stage for Estimating Single-Trail Evoked Potential Improves CNN Performance in Detecting Error Potential

We present a novel architecture designed to enhance the detection of Error Potential (ErrP) signals during ErrP stimulation tasks. In the context of predicting ErrP presence, conventional Convolutional Neural Networks (CNNs) typically accept a raw EEG signal as input, encompassing both the information associated with the evoked potential and the background activity, which can potentially diminish predictive accuracy. Our approach involves advanced Single-Trial (ST) ErrP enhancement techniques for processing raw EEG signals in the initial stage, followed by CNNs for discerning between ErrP and NonErrP segments in the second stage. We tested different combinations of methods and CNNs. As far as ST ErrP estimation is concerned, we examined various methods encompassing subspace regularization techniques, Continuous Wavelet Transform, and ARX models. For the classification stage, we evaluated the performance of EEGNet, CNN, and a Siamese Neural Network. A comparative analysis against the method of directly applying CNNs to raw EEG signals revealed the advantages of our architecture. Leveraging subspace regularization yielded the best improvement in classification metrics, at up to 14% in balanced accuracy and 13.4% in F1-score.

Single-trial ERP Quantification Using Neural Networks

Traditional approaches to quantify components in event-related potentials (ERPs) are based on averaging EEG responses. However, this method ignores the trial-to-trial variability in the component's latency, resulting in a smeared version of the component and underestimates of its amplitude. Different techniques to quantify ERP components in single trials have therefore been described in literature. In this study, two approaches based on neural networks are proposed and their performance was compared with other techniques using simulated data and two experimental datasets. On the simulated dataset, the neural networks outperformed other techniques for most signal-to-noise ratios and resulted in better estimates of the topography and shape of the ERP component. In the first experimental dataset, the highest correlation values between the estimated latencies of the P300 component and the reaction times were obtained using the neural networks. In the second dataset, the single-trial latency estimation techniques showed an amplitude reduction of the N400 effect with age and ascertained this effect could not be attributed to differences in latency variability. These results illustrate the applicability and the added value of neural networks for the quantification of ERP components in individual trials. A limitation, however, is that simulated data is needed to train the neural networks, which can be difficult when the ERP components to be found are not known a priori. Nevertheless, the neural networks-based approaches offer more information on the variability of the timing of the component and result in better estimates of the shape and topography of ERP components.

Preserved perception-action integration in adolescents after a COVID-19 infection

Evidence is accumulating that the Coronavirus disease (COVID-19) can bring forth deficits in executive functioning via alterations in the dopaminergic system. Importantly, dopaminergic pathways have been shown to modulate how actions and perceptions are integrated within the brain. Such alterations in event file binding could thus underlie the cognitive deficits developing after a COVID-19 infection. We examined action-perception integration in a group of young people (11-19 years of age) that had been infected with COVID-19 before study participation (n = 34) and compared them to a group of uninfected healthy controls (n = 29) on the behavioral (i.e., task accuracy, reaction time) and neurophysiological (EEG) level using an established event file binding paradigm. Groups did not differ from each other regarding demographic variables or in reporting psychiatric symptoms. Overall, multiple lines of evidence (behavioral and neurophysiological) suggest that action-perception integration is preserved in adolescents who suffered from COVID-19 prior to study participation. Event file binding processes were intact in both groups on all levels. While cognitive impairments can occur following a COVID-19 infection, the study demonstrates that action-perception integration as one of the basic building blocks of cognition seems to be largely unaffected in adolescents with a rather mild course of the disease.

Perception-Action Integration Is Altered in Functional Movement Disorders

BACKGROUND

Although functional neurological movement disorders (FMD) are characterized by motor symptoms, sensory processing has also been shown to be disturbed. However, how the integration of perception and motor processes, essential for the control of goal-directed behavior, is altered in patients with FMD is less clear. A detailed investigation of these processes is crucial to foster a better understanding of the pathophysiology of FMD and can systematically be achieved in the framework of the theory of event coding (TEC).

OBJECTIVE

The aim was to investigate perception-action integration processes on a behavioral and neurophysiological level in patients with FMD.

METHODS

A total of 21 patients and 21 controls were investigated with a TEC-related task, including concomitant electroencephalogram (EEG) recording. We focused on EEG correlates established to reflect perception-action integration processes. Temporal decomposition allowed to distinguish between EEG codes reflecting sensory (S-cluster), motor (R-cluster), and integrated sensory-motor processing (C-cluster). We also applied source localization analyses.

RESULTS

Behaviorally, patients revealed stronger binding between perception and action, as evidenced by difficulties in reconfiguring previously established stimulus-response associations. Such hyperbinding was paralleled by a modulation of neuronal activity clusters, including reduced C-cluster modulations of the inferior parietal cortex and altered R-cluster modulations in the inferior frontal gyrus. Correlations of these modulations with symptom severity were also evident.

CONCLUSIONS

Our study shows that FMD is characterized by altered integration of sensory information with motor processes. Relations between clinical severity and both behavioral performance and neurophysiological abnormalities indicate that perception-action integration processes are central and a promising concept for the understanding of FMD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Neurophysiological mechanisms underlying the differential effect of reward prospect on response selection and inhibition

Reward and cognitive control play crucial roles in shaping goal-directed behavior. Yet, the behavioral and neural underpinnings of interactive effects of both processes in driving our actions towards a particular goal have remained rather unclear. Given the importance of inhibitory control, we investigated the effect of reward prospect on the modulatory influence of automatic versus controlled processes during response inhibition. For this, a performance-contingent monetary reward for both correct response selection and response inhibition was added to a Simon NoGo task, which manipulates the relationship of automatic and controlled processes in Go and NoGo trials. A neurophysiological approach was used by combining EEG temporal signal decomposition and source localization methods. Compared to a non-rewarded control group, rewarded participants showed faster response execution, as well as overall lower response selection and inhibition accuracy (shifted speed-accuracy tradeoff). Interestingly, the reward group displayed a larger interference of the interactive effects of automatic versus controlled processes during response inhibition (i.e., a larger Simon NoGo effect), but not during response selection. The reward-specific behavioral effect was mirrored by the P3 amplitude, underlining the importance of stimulus-response association processes in explaining variability in response inhibition performance. The selective reward-induced neurophysiological modulation was associated with lower activation differences in relevant structures spanning the inferior frontal and parietal cortex, as well as higher activation differences in the somatosensory cortex. Taken together, this study highlights relevant neuroanatomical structures underlying selective reward effects on response inhibition and extends previous reports on the possible detrimental effect of reward-triggered performance trade-offs on cognitive control processes.

Cognitive and Neural Mechanisms of Behavior Therapy for Tics: A Perception-Action Integration Approach

European clinical guidelines recommend the use of Exposure and Response Prevention (ERP) and Comprehensive Behavioral Intervention for Tics (CBIT) as first-line treatments for tic disorders. Although ongoing efforts in research are being made to understand the mechanisms underlying these behavioral approaches, as of yet, the neurophysiological mechanisms behind behavioral interventions are poorly understood. However, this is essential to tailor interventions to individual patients in order to increase compliance and efficacy. The Theory of Event Coding (TEC) and its derivative BRAC (Binding and Retrieval in Action Control) provide a theoretical framework to investigate cognitive and neural processes in the context of tic disorders. In this context, tics are conceptualized as a phenomenon of enhanced perception-action binding, with premonitory urges constituting the perceptual and the motor or vocal expression constituting the action part of an event file. Based on this, CBIT is assumed to strongly affect stimulus-response binding in the context of response selection, whereas the effects of ERP presumably unfold during stimulus-response binding in the response inhibition context. Further studies are needed to clarify the neurophysiological processes underlying behavioral interventions to enable the individualization and further development of therapeutic approaches for tic disorders.

The role of single trial variability in event related potentials in children with attention deficit hyperactivity disorder

OBJECTIVE

Children with attention deficit hyperactivity disorder (ADHD) show attenuated mean P3 component amplitudes compared to typically developing (TD) children. This finding may be the result of individual differences in P3 amplitudes, P3 latencies, and/or greater single trial variability (STV) in amplitude or latency, suggesting neural "noise."

METHODS

Event related potentials (ERPs) from 75 children with ADHD and 29 TD children were recorded with electroencephalography (EEG). Caregivers provided ratings on child ADHD symptoms. Single-trial ERP amplitudes and latencies were extracted from the P3 component time window during a visual oddball task. Additionally, we computed individual-centered and trial-centered P3 amplitudes to account for inter-individual and inter-trial variability in the timing of the P3 peak.

RESULTS

In line with prior research, greater ADHD symptom severity was associated with reduced mean P3 amplitude. This correlation was no longer significant after correcting for inter-trial differences in P3 latency. In contrast, greater ADHD symptom severity was associated with reduced STV in P3 amplitude.

CONCLUSIONS

Our results suggest that attenuated average P3 amplitude in ADHD samples is due to a consistent reduction in strength of the neurophysiological signal at the single trial level, as well as increased inter-trial variability in the timing of P3 peak amplitudes. The traditional method of extracting P3 amplitudes based on a single time window for all trials may not adequately capture variability in P3 latencies associated with ADHD.

SIGNIFICANCE

Inter- and intra-individual differences in brain signatures should be considered in models of neurobiological differences in neurodevelopmental samples.

Perception-action integration during inhibitory control is reflected in a concomitant multi-region processing of specific codes in the neurophysiological signal

The integration of perception and action has long been studied in psychological science using overarching cognitive frameworks. Despite these being very successful in explaining perception-action integration, little is known about its neurophysiological and especially the functional neuroanatomical foundations. It is unknown whether distinct brain structures are simultaneously involved in the processing of perception-action integration codes and also to what extent demands on perception-action integration modulate activities in these structures. We investigate these questions in an EEG study integrating temporal and ICA-based EEG signal decomposition with source localization. For this purpose, we used data from 32 healthy participants who performed a 'TEC Go/Nogo' task. We show that the EEG signal can be decomposed into components carrying different informational aspects or processing codes relevant for perception-action integration. Importantly, these specific codes are processed independently in different brain structures, and their specific roles during the processing of perception-action integration differ. Some regions (i.e., the anterior cingulate and insular cortex) take a 'default role' because these are not modulated in their activity by demands or the complexity of event file coding processes. In contrast, regions in the motor cortex, middle frontal, temporal, and superior parietal cortices were not activated by 'default' but revealed modulations depending on the complexity of perception-action integration (i.e., whether an event file has to be reconfigured). Perception-action integration thus reflects a multi-region processing of specific fractions of information in the neurophysiological signal. This needs to be taken into account when further developing a cognitive science framework detailing perception-action integration.

The role of visual association cortices during response selection processes in interference-modulated response stopping

Response inhibition and the ability to navigate distracting information are both integral parts of cognitive control and are imperative to adaptive behavior in everyday life. Thus far, research has only inconclusively been able to draw inferences regarding the association between response stopping and the effects of interfering information. Using a novel combination of the Simon task and a stop signal task, the current study set out to investigate the behavioral as well as the neurophysiological underpinnings of the relationship between response stopping and interference processing. We tested n = 27 healthy individuals and combined temporal EEG signal decomposition with source localization methods to delineate the precise neurophysiological dynamics and functional neuroanatomical structures associated with conflict effects on response stopping. The results showed that stopping performance was compromised by conflicts. Importantly, these behavioral effects were reflected by specific aspects of information coded in the neurophysiological signal, indicating that conflict effects during response stopping are not mediated via purely perceptual processes. Rather, it is the processing of specific, stop-relevant stimulus features in the sensory regions during response selection, which underlies the emergence of conflict effects in response stopping. The findings connect research regarding response stopping with overarching theoretical frameworks of perception-action integration.

Neurophysiological principles of inhibitory control processes during cognitive flexibility

Inhibitory control plays an indispensable role in cognitive flexibility. Nevertheless, the neurophysiological principles underlying this are incompletely understood. This owes to the fact that the representational dynamics, as coded in oscillatory neural activity of different frequency bands has not been considered until now-despite being of conceptual relevance. Moreover, it is unclear in how far distinct functional neuroanatomical regions are concomitantly involved in the processing of representational dynamics. We examine these questions using a combination of EEG methods. We show that theta-band activity plays an essential role for inhibitory control processes during cognitive flexibility across informational aspects coded in distinct fractions of the neurophysiological signal. It is shown that posterior parietal structures and the inferior parietal cortex seem to be the most important cortical region for inhibitory control processes during cognitive flexibility. Theta-band activity plays an essential role in processes of retrieving the previously inhibited representations related to the current task during cognitive flexibility. The representational content relevant for inhibitory processes during cognitive flexibility is coded in the theta frequency band. We outline how the observed neural mechanisms inform recent overarching cognitive frameworks on how flexible action control is accomplished.

On the Role of Stimulus-Response Context in Inhibitory Control in Alcohol Use Disorder

The behavioral and neural dynamics of response inhibition deficits in alcohol use disorder (AUD) are still largely unclear, despite them possibly being key to the mechanistic understanding of the disorder. Our study investigated the effect of automatic vs. controlled processing during response inhibition in participants with mild-to-moderate AUD and matched healthy controls. For this, a Simon Nogo task was combined with EEG signal decomposition, multivariate pattern analysis (MVPA), and source localization methods. The final sample comprised n = 59 (32♂) AUD participants and n = 64 (28♂) control participants. Compared with the control group, AUD participants showed overall better response inhibition performance. Furthermore, the AUD group was less influenced by the modulatory effect of automatic vs. controlled processes during response inhibition (i.e., had a smaller Simon Nogo effect). The neurophysiological data revealed that the reduced Simon Nogo effect in the AUD group was associated with reduced activation differences between congruent and incongruent Nogo trials in the inferior and middle frontal gyrus. Notably, the drinking frequency (but not the number of AUD criteria we had used to distinguish groups) predicted the extent of the Simon Nogo effect. We suggest that the counterintuitive advantage of participants with mild-to-moderate AUD over those in the control group could be explained by the allostatic model of drinking effects.

Evidence for independent representational contents in inhibitory control subprocesses associated with frontoparietal cortices

Inhibitory control processes have intensively been studied in cognitive science for the past decades. Even though the neural dynamics underlying these processes are increasingly better understood, a critical open question is how the representational dynamics of the inhibitory control processes are modulated when engaging in response inhibition in a relatively automatic or a controlled mode. Against the background of an overarching theory of perception-action integration, we combine temporal and spatial EEG signal decomposition methods with multivariate pattern analysis and source localization to obtain fine-grained insights into the neural dynamics of the representational content of response inhibition. For this purpose, we used a sample of N = 40 healthy adult participants. The behavioural data suggest that response inhibition was better in a more controlled than a more automated response execution mode. Regarding neural dynamics, effects of response inhibition modes relied on a concomitant coding of stimulus-related information and rules of how stimulus information is related to the appropriate motor programme. Crucially, these fractions of information, which are encoded at the same time in the neurophysiological signal, are based on two independent spatial neurophysiological activity patterns, also showing differences in the temporal stability of the representational content. Source localizations revealed that the precuneus and inferior parietal cortex regions are more relevant than prefrontal areas for the representation of stimulus-response selection codes. We provide a blueprint how a concatenation of EEG signal analysis methods, capturing distinct aspects of neural dynamics, can be connected to cognitive science theory on the importance of representations in action control.

The neural stability of perception-motor representations affects action outcomes and behavioral adaptation

Actions can fail - even though this is well known, little is known about what distinguishes neurophysiological processes preceding errors and correct actions. In this study, relying on the Theory of Event Coding, we test the assumption that only specific aspects of information coded in EEG activity are relevant for understanding processes leading to response errors. We examined N = 69 healthy participants who performed a mental rotation task and combined temporal EEG signal decomposition with multivariate pattern analysis (MVPA) and source localization analyses. We show that fractions of the EEG signal, primarily representing stimulus-response translation (event file) processes and motor response representations, are essential. Stimulus representations were less critical. The source localization results revealed widespread activity modulations in structures including the frontopolar, the middle and superior frontal, the anterior cingulate cortex, the cuneus, the inferior parietal cortex, and the ventral stream regions. These are associated with differential effects of the neural dynamics preceding correct/erroneous responses. The temporal-generalization MVPA showed that event file representations and representations of the motor response were already distinct 200 ms after stimulus presentation and this lasted till around 700 ms. The stability of this representational content was predictive for the magnitude of posterror slowing, which was particularly strong when there was no clear distinction between the neural activity profile of event file representations associated with a correct or an erroneous response. The study provides a detailed analysis of the dynamics leading to an error/correct response in connection to an overarching framework on action control.

On the Role of Memory Representations in Action Control: Neurophysiological Decoding Reveals the Reactivation of Integrated Stimulus-Response Feature Representations

Efficient response selection is essential to flexible, goal-directed behavior. Prominent theoretical frameworks such as the Theory of Event Coding and Binding and Retrieval in Action Control have provided insights regarding the dynamics of perception-action integration processes. According to Theory of Event Coding and Binding and Retrieval in Action Control, encoded representations of stimulus-response bindings influence later retrieval processes of these bindings. However, this concept still lacks conclusive empirical evidence. In the current study, we applied representational decoding to EEG data. On the behavioral level, the findings replicated binding effects that have been established in previous studies: The task performance was impaired when an event file had to be reconfigured. The EEG-decoding results showed that retrieval processes of stimulus-response bindings could be decoded using the representational content developed after the initial establishment of these stimulus-response bindings. We showed that stimulus-related properties became immediately reactivated when re-encountering the respective stimulus-response association. These reactivations were temporally stable. In contrast, representations of stimulus-response mappings revealed a transient pattern of activity and could not successfully be decoded directly after stimulus-response binding. Information detailing the bindings between stimuli and responses were also retrieved, but only after having been loaded into a memory system. The current study supports the notion that stimulus-response integration and memory processes are intertwined at multiple levels.

Study of the human brain potentials variability effects in P300 based brain–computer interface

The P300-based brain–computer interfaces (P300 BCI) allow the user to select commands by focusing on them. The technology involves electroencephalographic (EEG) representation of the event-related potentials (ERP) that arise in response to repetitive external stimulation. Conventional procedures for ERP extraction and analysis imply that identical stimuli produce identical responses. However, the floating onset of EEG reactions is a known neurophysiological phenomenon. A failure to account for this source of variability may considerably skew the output and undermine the overall accuracy of the interface. This study aimed to analyze the effects of ERP variability in EEG reactions in order to minimize their influence on P300 BCI command classification accuracy. Healthy subjects aged 21–22 years (n = 12) were presented with a modified P300 BCI matrix moving with specified parameters within the working area. The results strongly support the inherent significance of ERP variability in P300 BCI environments. The correction of peak latencies in single EEG reactions provided a 1.5–2 fold increase in ERP amplitude with a concomitant enhancement of classification accuracy (from 71–78% to 92–95%, p < 0.0005). These effects were particularly pronounced in attention-demanding tasks with the highest matrix velocities. The findings underscore the importance of accounting for ERP variability in advanced BCI systems.

Changepoint Detection in Noisy Data Using a Novel Residuals Permutation-Based Method (RESPERM): Benchmarking and Application to Single Trial ERPs

An important problem in many fields dealing with noisy time series, such as psychophysiological single trial data during learning or monitoring treatment effects over time, is detecting a change in the model underlying a time series. Here, we present a new method for detecting a single changepoint in a linear time series regression model, termed residuals permutation-based method (RESPERM). The optimal changepoint in RESPERM maximizes Cohen’s effect size with the parameters estimated by the permutation of residuals in a linear model. RESPERM was compared with the SEGMENTED method, a well-established and recommended method for detecting changepoints, using extensive simulated data sets, varying the amount and distribution characteristics of noise and the location of the change point. In time series with medium to large amounts of noise, the variance of the detected changepoint was consistently smaller for RESPERM than SEGMENTED. Finally, both methods were applied to a sample dataset of single trial amplitudes of the N250 ERP component during face learning. In conclusion, RESPERM appears to be well suited for changepoint detection especially in noisy data, making it the method of choice in neuroscience, medicine and many other fields.

Resting-state theta activity is linked to information content-specific coding levels during response inhibition

The neurophysiological processes underlying the inhibition of impulsive responses have been studied extensively. While also the role of theta oscillations during response inhibition is well examined, the relevance of resting-state theta activity for inhibitory control processes is largely unknown. We test the hypothesis that there are specific relationships between resting-state theta activity and sensory/motor coding levels during response inhibition using EEG methods. We show that resting theta activity is specifically linked to the stimulus-related fraction of neurophysiological activity in specific time windows during motor inhibition. In contrast, concomitantly coded processes related to decision-making or response selection as well as the behavioral inhibition performance were not associated with resting theta activity. Even at the peak of task-related theta power, where task-related theta activity and resting theta activity differed the most, there was still predominantly a significant correlation between both types of theta activity. This suggests that aspects similar to resting dynamics are evident in the proportion of inhibition-related neurophysiological activity that reflects an “alarm” signal, whose function is to process and indicate the need for cognitive control. Thus, specific aspects of task-related theta power may build upon resting theta activity when cognitive control is necessary.

Time-on-task effects on working memory gating processes—A role of theta synchronization and the norepinephrine system

Performance impairment as an effect of prolonged engagement in a specific task is commonly observed. Although this is a well-known effect in everyday life, little is known about how this affects central cognitive functions such as working memory (WM) processes. In the current study, we ask how time-on-task affects WM gating processes and thus processes regulating WM maintenance and updating. To this end, we combined electroencephalography methods and recordings of the pupil diameter as an indirect of the norepinephrine (NE) system activity. Our results showed that only WM gate opening but not closing processes showed time-on-task effects. On the neurophysiological level, this was associated with modulation of dorsolateral prefrontal theta band synchronization processes, which vanished with time-on-task during WM gate opening. Interestingly, also the modulatory pattern of the NE system, as inferred using pupil diameter data, changed. At the beginning, a strong correlation of pupil diameter data and theta band synchronization processes during WM gate opening is observed. This modulatory effect vanished at the end of the experiment. The results show that time-on-task has very specific effects on WM gate opening and closing processes and suggests an important role of NE system in the time-on-task effect on WM gate opening process.

A role of the norepinephrine system or effort in the interplay of different facets of inhibitory control

Inhibitory control has multiple facets, and one possible distinction can be made between 'inhibition of interferences' and the 'inhibition of actions'. Both facets of inhibitory control show an interdependency. Even though some neurophysiological processes underlying this interdependency have been examined, the role of neuro-modulatory processes in their interplay are not understood. In the current study, we examine the role of the norepinephrine (NE) system in these processes. We did so by combining a Go/Nogo and Simon task. We recorded the EEG and pupil diameter data as an indirect index of NE system activity during the task. EEG theta band activity data and pupil diameter data were then integrated after conducting a temporal signal decomposition of the EEG data. We show that particularly theta band activity coding stimulus-response translation processes associated with middle frontal cortices, but not stimulus-driven processes are modulated by the interplay between the 'inhibition of interferences' and the 'inhibition of actions'. Modulations in stimulus-response translation processes were systematically correlated with pupil-diameter responses. The pattern of correlations suggests that phasic NE system activity particularly modulates stimulus-response mapping processes during conflict monitoring in incongruent Nogo trials, which may explain behavioral performance effects. Phasic NE system activity reflects essential modulators of the interplay between the 'inhibition of interferences' and the 'inhibition of actions'.

A tutorial on the use of temporal principal component analysis in developmental ERP research – opportunities and challenges

Developmental researchers are often interested in event-related potentials (ERPs). Data-analytic approaches based on the observed ERP suffer from major problems such as arbitrary definition of analysis time windows and regions of interest and the observed ERP being a mixture of latent underlying components. Temporal principal component analysis (PCA) can reduce these problems. However, its application in developmental research comes with the unique challenge that the component structure differs between age groups (so-called measurement non-invariance). Separate PCAs for the groups can cope with this challenge. We demonstrate how to make results from separate PCAs accessible for inferential statistics by re-scaling to original units. This tutorial enables readers with a focus on developmental research to conduct a PCA-based ERP analysis of amplitude differences. We explain the benefits of a PCA-based approach, introduce the PCA model and demonstrate its application to a developmental research question using real-data from a child and an adult group (code and data openly available). Finally, we discuss how to cope with typical challenges during the analysis and name potential limitations such as suboptimal decomposition results, data-driven analysis decisions and latency shifts.

Multi-level decoding of task sets in neurophysiological data during cognitive flexibility

Cognitive flexibility is essential to achieve higher level goals. Cognitive theories assume that the activation/deactivation of goals and task rules is central to understand cognitive flexibility. However, how this activation/deactivation dynamic is implemented on a neurophysiological level is unclear. Using EEG-based multivariate pattern analysis (MVPA) methods, we show that activation of relevant information occurs parallel in time at multiple levels in the neurophysiological signal containing aspects of stimulus-related processing, response selection, and motor response execution, and relates to different brain regions. The intensity with which task sets are activated and processed dynamically decreases and increases. The temporal stability of these activations could, however, hardly explain behavioral performance. Instead, task set deactivation processes associated with left orbitofrontal regions and inferior parietal regions selectively acting on motor response task sets are relevant. The study shows how propositions from cognitive theories stressing the importance task set activation/deactivation during cognitive flexibility are implemented on a neurophysiological level.

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Stimulus-related, motor, and response selection aspects of task set were decoded

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Activation of task rule information occurs at multiple neurophysiological levels

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Activation and deactivation of rule sets contributes to cognitive flexibility

Distinguishing Multiple Coding Levels in Theta Band Activity During Working Memory Gating Processes

Cognitive control and working memory (WM) processes are essential for goal-directed behaviour. Cognitive control and WM are probably based on overlapping neurophysiological mechanisms. For example, theta-band activity (TBA) plays an important role in both functions. For cognitive control processes, it is known that different aspects of information about stimulus content, motor processes and stimulus-response relationships are encoded simultaneously in the TBA. All this information is probably processed during WM gating processes and must be controlled during them. However, direct data for this are lacking. This question is investigated in this study by combining methods of EEG temporal signal decomposition, time-frequency decomposition and beamforming. We show that portions of stimulus-related information, motor response-related information and information related to the interaction between the stimulus and motor responses in the TBA are influenced in parallel and to a similar extent by WM gate opening and gate closing processes. Nevertheless, it is stimulus-related information in the theta signal in particular that modulates behavioural performance in WM-gating. The data suggest that the identified processes are implemented in specific neuroanatomical structures. In particular, the medial frontal cortex, temporal cortical regions and insular cortex are involved in these dynamics. The study shows that principles of information coding relevant to cognitive control processes are also crucial for understanding WM gating.

Perception-action integration in young age-A cross-sectional EEG study

Humans differ in their capacity for integrating perceived events and related actions. The "Theory of event coding" (TEC) conceptualizes how stimuli and actions are cognitively bound into a common functional representation (or "code"), known as the "event file". To date, however, the neural processes underlying the development of event file coding mechanisms across age are largely unclear. We investigated age-related neural changes of event file coding from late childhood to early adulthood, using EEG signal decompositions methods. We included a group of healthy participants (n = 91) between 10 and 30 years, performing an event file paradigm. Results of this study revealed age-related effects on event file coding processes both at the behavioural and the neurophysiological level. Performance accuracy data showed that event file unbinding und rebinding processes become more efficient from late childhood to early adulthood. These behavioural effects are reflected by age-related effects in two neurophysiological subprocesses associated with the superior parietal cortex (BA7) as revealed in the analyses using EEG signal decomposition. The first process entails mapping and association processes between stimulus and response; whereas, the second comprises inhibitory control subprocesses subserving the selection of the relevant motor programme amongst competing response options.

Neural dynamics of stimulus-response representations during inhibitory control

The investigation of action control processes is one major field in cognitive neuroscience and several theoretical frameworks have been proposed. One established framework is the "Theory of Event Coding" (TEC). However, only rarely, this framework has been used in the context of response inhibition and how stimulus-response association or binding processes modulate response inhibition performance. Particularly the neural dynamics of stimulus-response representations during inhibitory control are elusive. To address this, we examined n = 40 healthy controls and combined temporal EEG signal decomposition with source localization and temporal generalization multivariate pattern analysis (MVPA). We show that overlaps in features of stimuli used to trigger either response execution or inhibition compromised task performance. According to TEC, this indicates that binding processes in event file representations impact response inhibition through partial repetition costs. In the EEG data, reconfiguration of event files modulated processes in time windows well-known to reflect distinct response inhibition mechanisms. Crucially, event file coding processes were only evident in a specific fraction of neurophysiological activity associated with the inferior parietal cortex (BA40). Within that specific fraction of neurophysiological activity, the decoding of the dynamics of event file representations using temporal generalization MVPA suggested that event file representations are stable across several hundred milliseconds, and that event file coding during inhibitory control is reflected by a sustained activation pattern of neural dynamics.NEW & NOTEWORTHY The "mental representation" of how stimulus input translate into the appropriate response is central for goal-directed behavior. However, little is known about the dynamics of such representations on the neurophysiological level when it comes to the inhibition of motor processes. This dynamic is shown in the current study.

Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning

Humans are capable of acquiring multiple types of information presented in the same information stream. It has been suggested that at least two parallel learning processes are important during learning of sequential patterns-statistical learning and rule-based learning. Yet, the neurophysiological underpinnings of these parallel learning processes are not fully understood. To differentiate between the simultaneous mechanisms at the single trial level, we apply a temporal EEG signal decomposition approach together with sLORETA source localization method to delineate whether distinct statistical and rule-based learning codes can be distinguished in EEG data and can be related to distinct functional neuroanatomical structures. We demonstrate that concomitant but distinct aspects of information coded in the N2 time window play a role in these mechanisms: mismatch detection and response control underlie statistical learning and rule-based learning, respectively, albeit with different levels of time-sensitivity. Moreover, the effects of the two learning mechanisms in the different temporally decomposed clusters of neural activity also differed from each other in neural sources. Importantly, the right inferior frontal cortex (BA44) was specifically implicated in visuomotor statistical learning, confirming its role in the acquisition of transitional probabilities. In contrast, visuomotor rule-based learning was associated with the prefrontal gyrus (BA6). The results show how simultaneous learning mechanisms operate at the neurophysiological level and are orchestrated by distinct prefrontal cortical areas. The current findings deepen our understanding on the mechanisms of how humans are capable of learning multiple types of information from the same stimulus stream in a parallel fashion.

Anodal tDCS modulates specific processing codes during conflict monitoring associated with superior and middle frontal cortices

Conflict monitoring processes are central for cognitive control. Neurophysiological correlates of conflict monitoring (i.e. the N2 ERP) likely represent a mixture of different cognitive processes. Based on theoretical considerations, we hypothesized that effects of anodal tDCS (atDCS) in superior frontal areas affect specific subprocesses in neurophysiological activity during conflict monitoring. To investigate this, young healthy adults performed a Simon task while EEG was recorded. atDCS and sham tDCS were applied in a single-blind, cross-over study design. Using temporal signal decomposition in combination with source localization analyses, we demonstrated that atDCS effects on cognitive control are very specific: the detrimental effect of atDCS on response speed was largest in case of response conflicts. This however only showed in aspects of the decomposed N2 component, reflecting stimulus-response translation processes. In contrast to this, stimulus-related aspects of the N2 as well as purely response-related processes were not modulated by atDCS. EEG source localization analyses revealed that the effect was likely driven by activity modulations in the superior frontal areas, including the supplementary motor cortex (BA6), as well as middle frontal (BA9) and medial frontal areas (BA32). atDCS did not modulate effects of proprioceptive information on hand position, even though this aspect is known to be processed within the same brain areas. Physiological effects of atDCS likely modulate specific aspects of information processing during cognitive control.

Affective Dysregulation in Children Is Associated With Difficulties in Response Control in Emotional Ambiguous Situations

BACKGROUND

Affective dysregulation (AD), or synonymously "irritability," is a transdiagnostic construct that serves as a diagnostic criterion in various childhood mental disorders. It is characterized by severe or persistent outbursts of anger and aggression. Emotional self-regulation is highly dependent on the ability to process relevant and ignore conflicting emotional information. Understanding neurophysiological mechanisms underlying impairment in AD may provide a starting point for research on pharmacological treatment options and evaluation of psychotherapeutic intervention.

METHODS

A total of 120 children 8 to 12 years of age (63 with AD and 57 typically developing) were examined using an emotional Stroop task. Signal-decomposed electroencephalographic recordings providing information about the affected sensory-perceptual, response selection, or motor information processing stage were combined with source localization.

RESULTS

Behavioral performance revealed dysfunctional cognitive-emotional conflict monitoring in children with AD, suggesting difficulties in differentiating between conflicting and nonconflicting cognitive-emotional information. This was confirmed by the electroencephalographic data showing that they cannot intensify response selection processes during conflicting cognitive-emotional situations. Typically developing children were able to do so and activated a functional-neuroanatomical network comprising the left inferior parietal cortex (Brodmann area 40), right middle frontal (Brodmann area 10), and right inferior/orbitofrontal (Brodmann area 47) regions. Purely sensory-perceptual selection and motor execution processes were not modulated in AD, as evidenced by Bayesian analyses.

CONCLUSIONS

Behavioral and electroencephalogram data suggest that children with AD cannot adequately modulate controlled response selection processes given emotionally ambiguous information. Which neurotransmitter systems underlie these deficits and how they can be improved are important questions for future research.

Pushing to the Limits: What Processes during Cognitive Control are Enhanced by Reaction-Time Feedback?

To respond as quickly as possible in a given task is a widely used instruction in cognitive neuroscience; however, the neural processes modulated by this common experimental procedure remain largely elusive. We investigated the underlying neurophysiological processes combining electroencephalography (EEG) signal decomposition (residue iteration decomposition, RIDE) and source localization. We show that trial-based response speed instructions enhance behavioral performance in conflicting trials, but slightly impair performance in nonconflicting trials. The modulation seen in conflicting trials was found at several coding levels in EEG data using RIDE. In the S-cluster N2 time window, this modulation was associated with modulated activation in the posterior cingulate cortex and the superior frontal gyrus. Furthermore, in the C-cluster P3 time window, this modulation was associated with modulated activation in the middle frontal gyrus. Interestingly, in the R-cluster P3 time window, this modulation was strongest according to statistical effect sizes, associated with modulated activity in the primary motor cortex. Reaction-time feedback mainly modulates response motor execution processes, whereas attentional and response selection processes are less affected. The study underlines the importance of being aware of how experimental instructions influence the behavior and neurophysiological processes.

Neurophysiology of embedded response plans: age effects in action execution but not in feature integration from preadolescence to adulthood

Performing a goal-directed movement consists of a chain of complex preparatory mechanisms. Such planning especially requires integration (or binding) of various action features, a process that has been conceptualized in the "theory of event coding." Theoretical considerations and empirical research suggest that these processes are subject to developmental effects from adolescence to adulthood. The aim of the present study was to investigate age-related modulations in action feature binding processes and to shed light on underlying neurophysiological development from preadolescence to early adulthood. We examined a group of healthy participants (n = 61) between 10 and 30 yr of age, who performed a task that requires a series of bimanual response selections in an embedded paradigm. For an in-depth analysis of the underlying neural correlates, we applied EEG signal decomposition together with source localization analyses. Behavioral results across the whole group did not show binding effects in reaction times but in intraindividual response variability. From age 10 to 30 yr, there was a decrease in reaction times and reaction time variability but no age-related effect in action file binding. The latter were corroborated by Bayesian data analyses. On the brain level, the developmental effects on response selection were associated with activation modulations in the superior parietal cortex (BA7). The results show that mechanisms of action execution and speed, but not those of action feature binding, are subject to age-related changes between the age of 10 and 30 yr.NEW & NOTEWORTHY Different aspects of an action need to be integrated to allow smooth unfolding of behavior. We examine developmental effects in these processes and show that mechanisms of action execution and speed, but not those of action feature binding, are subject to age-related changes between the age of 10 and 30 yr.

Task Switching and the Role of Motor Reprogramming in Parietal Structures

Human behaviour amazes with extraordinary flexibility and the underlying neural mechanisms have often been studied using task switching. Despite extensive research, the relative importance of "cognitive" and "motor" aspects during switching is unclear. In the current study we examine this question combining EEG analysis techniques and source localization to examine whether the selection of the response, or processes during the execution of the response, contribute most to switching effects. A clear dissociation was observed in the signal decomposition, since codes relating to motor aspects play a significant role in task switching and the scope of the switching costs. This was not the case for signals that denote reaction selection or decision processes that respond to selection or basic stimulus processing codes. On a functional neuroanatomical level, these modulations in motor processes showed a clear temporal sequence in that motor codes are processed primarily in superior parietal regions (Brodman area 7) and only then in premotor regions (Brodman area 6). The observed modulations may reflect motor reprogramming processes. The study shows how EEG signal analysis in combination with brain mapping methods can inform debates on theories of human cognitive flexibility.

Resting theta activity is associated with specific coding levels in event-related theta activity during conflict monitoring

Brain electrical activity in the theta frequency band is essential for cognitive control (e.g., during conflict monitoring), but is also evident in the resting state. The link between resting state theta activity and its relevance for theta-related neural mechanisms during cognitive control is still undetermined. Yet, theoretical considerations suggest that there may be a connection. To examine the link between resting state theta activity and conflict-related theta activity, we combined temporal EEG signal decomposition methods with time-frequency decomposition and beamforming methods in N = 86 healthy participants. Results indicate that resting state theta activity is closely associated with the strength of conflict-related neural activity at the level of ERPs and total theta power (consisting of phase-locked and nonphase-locked aspects of theta activity). The data reveal that resting state theta activity is related to a specific aspect of conflict-related theta activity, mainly in superior frontal regions and in the supplemental motor area (SMA, BA6) in particular. The signal decomposition showed that only stimulus-related, but not motor-response-related coding levels in the EEG signal and the event-related total theta activity were associated with resting theta activity. This specificity of effects may explain why the association between resting state theta activity and overt conflict monitoring performance may not be as strong as often assumed. The results suggest that resting state theta activity is particularly important to consider for input integration processes during cognitive control.

P300 latency jitter and its correlates in people with amyotrophic lateral sclerosis

OBJECTIVE

People with amyotrophic lateral sclerosis (ALS) can benefit from brain-computer interfaces (BCIs). However, users with ALS may experience significant variations in BCI performance and event-related potential (ERP) characteristics. This study investigated latency jitter and its correlates in ALS.

METHODS

Electroencephalographic (EEG) responses were recorded from six people with ALS and nine neurotypical controls. ERP amplitudes and latencies were extracted. Classifier-based latency estimation was used to calculate latency jitter. ERP components and latency jitter were compared between groups using Wilcoxon rank-sum tests. Correlations between latency jitter and each of the clinical measures, ERP features, and performance measures were investigated using Spearman and repeated measures correlations.

RESULTS

Latency jitter was significantly increased in participants with ALS and significantly negatively correlated with BCI performance in both ALS and control participants. ERP amplitudes were significantly attenuated in ALS, and significant correlations between ERP features and latency jitter were observed. There was no significant correlation between latency jitter and clinical measures.

CONCLUSIONS

Latency jitter is increased in ALS and correlates with both BCI performance and ERP features.

SIGNIFICANCE

These results highlight the associations of latency jitter with BCI performance and ERP characteristics and could inform future BCI designs for people with ALS.

Gilles de la Tourette Syndrome-A Disorder of Action-Perception Integration

Gilles de la Tourette syndrome is a multifaceted and complex neuropsychiatric disorder. Given that tics as motor phenomena are the defining and cardinal feature of Tourette syndrome, it has long been conceptualized as a motor/movement disorder. However, considering premonitory urges preceding tics, hypersensitivity to external stimuli and abnormalities in sensorimotor integration perceptual processes also seem to be relevant in the pathophysiology of Tourette syndrome. In addition, tic expression depends on attention and tics can, at least partly and transiently, be controlled, so that cognitive processes need to be considered as well. Against this background, explanatory concepts should encompass not only the motor phenomenon tic but also perceptual and cognitive processes. Representing a comprehensive theory of the processing of perceptions and actions paying particular attention to their interdependency and the role of cognitive control, the Theory of Event Coding seems to be a suitable conceptual framework for the understanding of Tourette syndrome. In fact, recent data suggests that addressing the relation between actions (i.e., tics) and perceptions (i.e., sensory phenomena like premonitory urges) in the context of event coding allows to gaining relevant insights into perception-action coding in Tourette syndrome indicating that perception action binding is abnormally strong in this disorder.

Mechanisms of face specificity - Differentiating speed and accuracy in face cognition by event-related potentials of central processing

Given the crucial role of face recognition in social life, it is hardly surprising that cognitive processes specific for faces have been identified. In previous individual differences studies, the speed (measured in easy tasks) and accuracy (difficult tasks) of face cognition (FC, involving perception and recognition of faces) have been shown to form distinct abilities, going along with divergent factorial structures. This result has been replicated, but remained unexplained. To fill this gap, we first parameterized the sub-processes underlying speed vs. accuracy in easy and difficult memory tasks for faces and houses in a large sample. Then, we analyzed event-related potentials (ERPs) extracted from the EEG by using residue iteration decomposition (RIDE), yielding a central (C) component that is comparable to a purified P300. Structural equation modeling (SEM) was applied to estimate face specificity of C component latencies and amplitudes. If performance in easy tasks relies on purely general processes that are insensitive to stimulus content, there should be no specificity of individual differences in the latency recorded in easy tasks. However, in difficult tasks specificity was expected. Results indicated that, contrary to our predictions, specificity occurred in the C component latency of both speed-based and accuracy-based measures, but was stronger in accuracy. Further analyses suggested specific relationships between the face-related C latency and FC ability. Finally, we detected specificity in RTs of easy tasks when single tasks were modeled, but not when multiple tasks were jointly modeled. This suggests that the mechanisms leading to face specificity in performance speed are distinct across tasks.

Fast fronto-parietal cortical dynamics of conflict detection and context updating in a flanker task

Recent research has found that the traditional target P3 consists of a family of P3-like positivities that can be functionally and topographically dissociated from one another. The current study examined target N2 and P3-like subcomponents indexing conflict detection and context updating at low- and high-order levels in the neural hierarchy during cognitive control. Electroencephalographic signals were recorded from 45 young adults while they completed a hybrid go/nogo flanker task, and Residue Iteration Decomposition (RIDE) was applied to functionally dissociate these peaks. Analyses showed a stimulus-locked frontal N2 revealing early detection and fast perceptual categorization of nogo, congruent and incongruent trials, resulting in frontal P3-like activity elicited by nogo trials in the latency-variable RIDE cluster, and by incongruent trials in the response-locked cluster. The congruent trials did not elicit frontal P3-like activity. These findings suggest that behavioral incongruency effects are related to intermediate and later stages of motor response re-programming.

Neurophysiological correlates of perception-action binding in the somatosensory system

Action control requires precisely and flexibly linking sensory input and motor output. This is true for both, visuo-motor and somatosensory-motor integration. However, while perception–action integration has been extensively investigated for the visual modality, data on how somatosensory and action-related information is associated are scarce. We use the Theory of Event Coding (TEC) as a framework to investigate perception–action integration in the somatosensory-motor domain. Based on studies examining the neural mechanisms underlying stimulus–response binding in the visuo-motor domain, the current study investigates binding mechanisms in the somatosensory-motor domain using EEG signal decomposition and source localization analyses. The present study clearly demonstrates binding between somatosensory stimulus and response features. Importantly, repetition benefits but no repetition costs are evident in the somatosensory modality, which differs from findings in the visual domain. EEG signal decomposition indicates that response selection mechanisms, rather than stimulus-related processes, account for the behavioral binding effects. This modulation is associated with activation differences in the left superior parietal cortex (BA 7), an important relay of sensorimotor integration.

Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development

The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.

Short-term Smartphone App–Based Focused Attention Meditation Diminishes Cognitive Flexibility

Cognitive flexibility is an important aspect relevant to daily life situations, and there is an increasing public interest to optimize these functions, for example, using (brief) meditation practices. However, the underlying neurophysiological mechanisms remain poorly understood. On the basis of theoretical considerations, both improvements and deteriorations of cognitive flexibility are possible through focused attention meditation (FAM). We investigated the effect of a brief smartphone app–based FAM on task switching using EEG methods, temporal signal decomposition, and source localization techniques (standardized low-resolution electromagnetic brain tomography). The study was conducted using a crossover study design. We show that even 15 min of FAM practicing modulates memory-based task switching, on a behavioral level and a neurophysiological level. More specifically, FAM hampers response selection and conflict resolution processes and seem to reduce cognitive resources, which are necessary to rapidly adapt to changing conditions. These effects are represented in the N2 and P3 time windows and associated with ACC. It seems that FAM increases the attention to one specific aspect, which may help to focus but carries also the risk that behavior becomes too rigid. FAM thus seems to modulate both the stimulus- and response-related aspects of conflict monitoring in ACC. Motor-related processes were not affected. The results can be explained using a cognitive control dilemma framework, suggesting that particularly alterations in background monitoring may be important to consider when explaining the effects of FAM during task switching.

Increased perception-action binding in Tourette syndrome

Gilles de la Tourette syndrome is a multifaceted neurodevelopmental disorder characterized by multiple motor and vocal tics. Research in Tourette syndrome has traditionally focused on the motor system. However, there is increasing evidence that perceptual and cognitive processes play a crucial role as well. Against this background it has been reasoned that processes linking perception and action might be particularly affected in these patients with the strength of perception-action binding being increased. However, this has not yet been studied experimentally. Here, we investigated adult Tourette patients within the framework of the ‘Theory of Event Coding’ using an experimental approach allowing us to directly test the strength of perception-action binding. We included 24 adult patients with Tourette syndrome and n = 24 healthy control subjects using a previously established visual-motor event file task with four levels of feature overlap requiring repeating or alternating responses. Concomitant to behavioural testing, EEG was recorded and analysed using temporal signal decomposition and source localization methods. On a behavioural level, perception-action binding was increased in Tourette patients. Tic frequency correlated with performance in conditions where unbinding processes of previously established perception-action bindings were required with higher tic frequency being associated with stronger perception-action binding. This suggests that perception-action binding is intimately related to the occurrence of tics. Analysis of EEG data showed that behavioural changes cannot be explained based on simple perceptual or motor processes. Instead, cognitive processes linking perception to action in inferior parietal cortices are crucial. Our findings suggest that motor or sensory processes alone are less relevant for the understanding of Tourette syndrome than cognitive processes engaged in linking and restructuring of perception-action association. A broader cognitive framework encompassing perception and action appears well suited to opening new routes for the understanding of Tourette syndrome.