Lapses in a prefrontal-extrastriate preparatory attention network predict mistakes

Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks

Humans' ability to adapt and learn relies on reflecting on past performance. These experiences form latent representations called internal states that induce movement variability that improves how we interact with our environment. Our study uncovered temporal dynamics and neural substrates of two states from ten subjects implanted with intracranial depth electrodes while they performed a goal-directed motor task with physical perturbations. We identified two internal states using state-space models: one tracking past errors and the other past perturbations. These states influenced reaction times and speed errors, revealing how subjects strategize from trial history. Using local field potentials from over 100 brain regions, we found large-scale brain networks such as the dorsal attention and default mode network modulate visuospatial attention based on recent performance and environmental feedback. Notably, these networks were more prominent in higher-performing subjects, emphasizing their role in improving motor performance by regulating movement variability through internal states.

Sleep-like changes in neural processing emerge during sleep deprivation in early auditory cortex

Insufficient sleep is commonplace in modern lifestyle and can lead to grave outcomes, yet the changes in neuronal activity accumulating over hours of extended wakefulness remain poorly understood. Specifically, which aspects of cortical processing are affected by sleep deprivation (SD), and whether they also affect early sensory regions, remain unclear. Here, we recorded spiking activity in the rat auditory cortex along with polysomnography while presenting sounds during SD followed by recovery sleep. We found that frequency tuning, onset responses, and spontaneous firing rates were largely unaffected by SD. By contrast, SD decreased entrainment to rapid (≥20 Hz) click trains, increased population synchrony, and increased the prevalence of sleep-like stimulus-induced silent periods, even when ongoing activity was similar. Recovery NREM sleep was associated with similar effects as SD with even greater magnitude, while auditory processing during REM sleep was similar to vigilant wakefulness. Our results show that processes akin to those in NREM sleep invade the activity of cortical circuits during SD, even in the early sensory cortex.

Dissociable brainstem functional connectivity changes correlate with objective and subjective vigilance decline after total sleep deprivation in healthy male subjects

The maintenance of vigilance relies on the activation of the cerebral cortex by the arousal system centered on the brainstem. Previous studies have suggested that both objective and subjective vigilance are susceptible to sleep deprivation. This study aims to explore the alterations in brainstem arousal system functional connectivity (FC) and its involvement in these two types of vigilance decline following total sleep deprivation (TSD). Thirty-seven healthy male subjects underwent two counterbalanced resting-state fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. The pontine tegmental area and caudal midbrain (PTA-cMidbrain), the core regions of the brainstem arousal system, were chosen as the seeds for FC analysis. The difference in PTA-cMidbrain FC between RW and TSD conditions was then investigated, as well as its associations with objective vigilance measured by psychomotor vigilance task (PVT) and subjective vigilance measured by Stanford Sleepiness Scale. The sleep-deprived subjects showed increased PTA-cMidbrain FC with the thalamus and cerebellum and decreased PTA-cMidbrain FC with the occipital, parietal, and sensorimotor regions. TSD-induced increases in PVT reaction time were negatively correlated with altered PTA-cMidbrain FC in the dorsolateral prefrontal cortex, extrastriate visual cortex, and precuneus. TSD-induced increases in subjective sleepiness were positively correlated with altered PTA-cMidbrain FC in default mode regions including the medial prefrontal cortex and precuneus. Our results suggest that different brainstem FC patterns underlie the objective and subjective vigilance declines induced by TSD.

The influence of working memory capacity and lapses of attention for variation in error monitoring

In two experiments, individual differences in working memory capacity (WMC), lapses of attention, and error monitoring were examined. Participants completed multiple WMC tasks along with a version of the Stroop task. During the Stroop, pupil diameter was continuously monitored. In both experiments, error phasic pupillary responses were larger than phasic pupillary responses associated with correct incongruent and correct congruent trials. WMC and indicators of lapses of attention were correlated with error pupillary response, suggesting that high WMC and low lapse individuals had enhanced error monitoring abilities compared with low WMC and high lapse individuals. Furthermore, in Experiment 2 error awareness abilities were associated with WMC, lapses of attention, and the error phasic pupillary responses. Importantly, individual differences in the susceptibility to lapses of attention largely accounted for the relationship between WMC and error monitoring in both experiments. Collectively, these results suggest that WMC is related to error monitoring abilities, but this association is largely due to individual differences in the ability to consistently maintain task engagement and avoid lapses of attention.

Moment-to-Moment Continuous Attention Fluctuation Monitoring through Consumer-Grade EEG Device

While numerous studies have explored using various sensing techniques to measure attention states, moment-to-moment attention fluctuation measurement is unavailable. To bridge this gap, we applied a novel paradigm in psychology, the gradual-onset continuous performance task (gradCPT), to collect the ground truth of attention states. GradCPT allows for the precise labeling of attention fluctuation on an 800 ms time scale. We then developed a new technique for measuring continuous attention fluctuation, based on a machine learning approach that uses the spectral properties of EEG signals as the main features. We demonstrated that, even using a consumer grade EEG device, the detection accuracy of moment-to-moment attention fluctuations was 73.49%. Next, we empirically validated our technique in a video learning scenario and found that our technique match with the classification obtained through thought probes, with an average F1 score of 0.77. Our results suggest the effectiveness of using gradCPT as a ground truth labeling method and the feasibility of using consumer-grade EEG devices for continuous attention fluctuation detection.

The Neuro Patterns Prior to Error Responses in Long-Lasting Working Memory Task: An Event-Related Potential Study

Few studies exist regarding the mechanism prior to response by which cognitive impairment may induce error in a single long-lasting task. The present study intends to clarify the changes in cognition at the electrophysiological level. Changes in amplitude and latency of N1, P2, N2, and P3 components of event-related potentials (ERPs) were analyzed for error and correct trials during normal and fatigue. Twenty-nine participants had to perform a 2-back working memory (WM) task for 100 min. The first 10 min and the last 10 min of the task were used as the normal state and fatigue state of the participant, respectively. EEG data were obtained from the first 10-min period and the final 10-min period. The results revealed smaller P3 and P2 amplitudes and longer P2 and N2 latency in the final 10-min which was after a long-lasting time task. Moreover, smaller P3 and P2 amplitudes but larger N2 amplitudes were observed in error trials for both states. Our results indicated that: (1) long lasting involvement in a cognitive task had a detrimental effect on attention, memory updating and cognitive control; and (2) impaired attention, impairments in memory updating and cognitive control were related to task errors. Our results imply that several impaired cognitive processes were consistently associated with the error and the altered ERP represents the neural patterns prior to error response in mental fatigue state.

Cognition Impairment Prior to Errors of Working Memory Based on Event-Related Potential

Cognitive impairment contributes to errors in different tasks. Poor attention and poor cognitive control are the two neural mechanisms for performance errors. A few studies have been conducted on the error mechanism of working memory. It is unclear whether the changes in memory updating, attention, and cognitive control can cause errors and, if so, whether they can be probed at the same time in one single task. Therefore, this study analyzed event-related potentials in a two-back working memory task. A total of 40 male participants finished the task. The differences between the error and the correct trials in amplitudes and latencies of N1, P2, N2, and P3 were analyzed. The P2 and P3 amplitudes decreased significantly in the error trials, while the N2 amplitude increased. The results showed that impaired attention, poor memory updating, and impaired cognitive control were consistently associated with the error in working memory. Furthermore, the results suggested that monitoring the neurophysiological characteristics associated with attention and cognitive control was important for studying the error mechanism and error prediction. The results also suggested that the P3 and N2 amplitudes could be used as indexes for error foreshadowing.

Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects

Recent advances in neuroscience have paved the way to innovative applications that cognitively augment and enhance humans in a variety of contexts. This paper aims at providing a snapshot of the current state of the art and a motivated forecast of the most likely developments in the next two decades. Firstly, we survey the main neuroscience technologies for both observing and influencing brain activity, which are necessary ingredients for human cognitive augmentation. We also compare and contrast such technologies, as their individual characteristics (e.g., spatio-temporal resolution, invasiveness, portability, energy requirements, and cost) influence their current and future role in human cognitive augmentation. Secondly, we chart the state of the art on neurotechnologies for human cognitive augmentation, keeping an eye both on the applications that already exist and those that are emerging or are likely to emerge in the next two decades. Particularly, we consider applications in the areas of communication, cognitive enhancement, memory, attention monitoring/enhancement, situation awareness and complex problem solving, and we look at what fraction of the population might benefit from such technologies and at the demands they impose in terms of user training. Thirdly, we briefly review the ethical issues associated with current neuroscience technologies. These are important because they may differentially influence both present and future research on (and adoption of) neurotechnologies for human cognitive augmentation: an inferior technology with no significant ethical issues may thrive while a superior technology causing widespread ethical concerns may end up being outlawed. Finally, based on the lessons learned in our analysis, using past trends and considering other related forecasts, we attempt to forecast the most likely future developments of neuroscience technology for human cognitive augmentation and provide informed recommendations for promising future research and exploitation avenues.

Pupillary Correlates of Fluctuations in Sustained Attention

The current study examined pupillary correlates of fluctuations and lapses of sustained attention. Participants performed a sustained attention task with either a varied ISI or a fixed ISI (fixed at 2 or 8 sec) while pupil responses were continuously recorded. The results indicated that performance was worse when the ISI was varied or fixed at 8 sec compared with when the ISI was fixed at 2 sec, suggesting that varied or long ISI conditions require greater intrinsic alertness compared with constant short ISIs. In terms of pupillary responses, the results demonstrated that slow responses (indicative of lapses) were associated with greater variability in tonic pupil diameter, smaller dilation responses during the ISI, and subsequently smaller dilation responses to stimulus onset. These results suggest that lapses of attention are associated with lower intrinsic alertness, resulting in a lowered intensity of attention to task-relevant stimuli. Following a lapse of attention, performance, tonic pupil diameter, and phasic pupillary responses, all increased, suggesting that attention was reoriented to the task. These results are consistent with the notion that pupillary responses track fluctuations in sustained attention.

Selective neuronal lapses precede human cognitive lapses following sleep deprivation

Sleep deprivation is a major source of morbidity with widespread health effects, including increased risk of hypertension, diabetes, obesity, heart attack, and stroke. Moreover, sleep deprivation brings about vehicle accidents and medical errors and is therefore an urgent topic of investigation. During sleep deprivation, homeostatic and circadian processes interact to build up sleep pressure, which results in slow behavioral performance (cognitive lapses) typically attributed to attentional thalamic and frontoparietal circuits, but the underlying mechanisms remain unclear. Recently, through study of electroencephalograms (EEGs) in humans and local field potentials (LFPs) in nonhuman primates and rodents it was found that, during sleep deprivation, regional 'sleep-like' slow and theta (slow/theta) waves co-occur with impaired behavioral performance during wakefulness. Here we used intracranial electrodes to record single-neuron activities and LFPs in human neurosurgical patients performing a face/nonface categorization psychomotor vigilance task (PVT) over multiple experimental sessions, including a session after full-night sleep deprivation. We find that, just before cognitive lapses, the selective spiking responses of individual neurons in the medial temporal lobe (MTL) are attenuated, delayed, and lengthened. These 'neuronal lapses' are evident on a trial-by-trial basis when comparing the slowest behavioral PVT reaction times to the fastest. Furthermore, during cognitive lapses, LFPs exhibit a relative local increase in slow/theta activity that is correlated with degraded single-neuron responses and with baseline theta activity. Our results show that cognitive lapses involve local state-dependent changes in neuronal activity already present in the MTL.

Effects of reaction time variability and age on brain activity during Stroop task performance

Variability in reaction time during task performance may reflect fluctuations in attention and cause reduced performance in goal-directed tasks, yet it is unclear whether the mechanisms behind this phenomenon change with age. Using fMRI, we tested young and cognitively healthy older adults with the Stroop task to determine whether aging affects the neural mechanisms underlying intra-individual reaction time variability. We found significant between-group differences in BOLD activity modulated by reaction time. In older adults, longer reaction times were associated with greater activity in frontoparietal attentional areas, while in younger adults longer reaction times were associated with greater activity in default mode network areas. Our results suggest that the neural correlates of reaction time variability change with healthy aging, reinforcing the concept of functional plasticity to maintain high cognitive function throughout the lifespan.

Modulation of ERP components by task instructions in a cued go/no-go task

The present study investigated how components of ERPs are modulated when participants optimize speed versus accuracy in a cued go/no-go task. Using a crossover design, 35 participants received instructions to complete the task prioritizing response speed in half of the task, and accurate responding in the other half of the task. Analysis was performed on the contingent negative variation (CNV), P3go, and P3no-go and the corresponding independent components (IC), as identified by group independent component analysis. After speed instructions, the IC CNV(late), P3go(anterior), P3no-go(early), and P3no-go(late) all had larger amplitudes than after accuracy instructions. Furthermore, both the IC P3go(posterior) and IC P3go(anterior) had shorter latencies after speed than after accuracy instructions. The results demonstrate that components derived from the CNV and P3 components are facilitated when participants optimize response speed. These findings indicate that these ERP components reflect executive processes enabling adjustment of behavior to changing demands.

Dynamic scalp topography reveals neural signs just before performance errors

Performance errors may cause serious consequences. It has been reported that ongoing activity of the frontal control regions across trials associates with the occurrence of performance errors. However, neural mechanisms that cause performance errors remain largely unknown. In this study, we hypothesized that some neural functions required for correct outcomes are lacking just before performance errors, and to determine this lack of neural function we applied a spatiotemporal analysis to high-density electroencephalogram signals recorded during a visual discrimination task, a d2 test of attention. To our knowledge, this is the first report of a difference in the temporal development of scalp ERP between trials with error, and correct outcomes as seen by topography during the d2 test of attention. We observed differences in the signal potential in the frontal region and then the occipital region between reaction times matched with correct and error outcomes. Our observations suggest that lapses of top-down signals from frontal control regions cause performance errors just after the lapses.

Predicting moment-to-moment attentional state

Although fluctuations in sustained attention are ubiquitous, most psychological experiments treat them as noise, averaging performance over many trials. The current study uses multi-voxel pattern analysis (MVPA) to decode whether, on each trial of a cognitive task, participants are in an optimal or suboptimal attentional state. During fMRI, participants performed n-back tasks, composed of central face images overlaid on distractor scenes, with low, perceptual, and working memory load. Instructions were to respond to novel faces and withhold response to rare repeats. To index attentional state, reaction time variability was calculated at each correct response. Participants' 50% least variable trials were labeled optimal, or "in the zone," and their 50% most erratic trials were labeled suboptimal, or "out of the zone." Support vector machine classifiers trained on activity in the default mode network (DMN), dorsal attention network (DAN), and task-relevant fusiform face area (FFA) distinguished in-the-zone and out-of-the-zone trials in all tasks. Consistent with evidence that distractors are processed when central task load is low, parahippocampal place area (PPA) classifiers were only successful in the low load task. Classification in anatomical regions across the brain revealed widespread coding of attentional state. In contrast to these robust pattern analyses, univariate signal in DMN, DAN, FFA, and PPA did not distinguish states, suggesting a nuanced relationship to sustained attention. In sum, MVPA can be used to decode trial-by-trial attentional state throughout much of cortex, helping to characterize how attention network fluctuations correlate with performance variability.

Neuropsychological parameters indexing executive processes are associated with independent components of ERPs

Lesion studies have indicated that at least the three executive processes can be differentiated in the frontal lobe: Energization, monitoring and task setting. Event related potentials (ERPs) in Go/NoGo tasks have been widely used in studying executive processes. In this study, ERPs were obtained from EEG recorded during performance of a cued Go/NoGo task. The Contingent Negative Variation (CNV) and P3NoGo waves were decomposed into four independent components (ICs), by applying Independent Component Analysis (ICA) to a collection of ERPs from 193 healthy individuals. The components were named IC CNVearly, IC CNVlate, IC P3NoGoearly and IC P3NoGolate according to the conditions and time interval in which they occurred. A sub-group of 28 individuals was also assessed with neuropsychological tests. The test parameters were selected on the basis of studies demonstrating their sensitivity to executive processes as defined in the ROtman-Baycrest Battery for Investigating Attention (ROBBIA) model. The test scores were categorized into the domain scores of energization, monitoring and task setting and correlated with the amplitudes of the individual ICs from the sub-group of 28 individuals. The energization domain correlated with the IC CNVlate and IC P3NoGoearly. The monitoring domain correlated with the IC P3NoGolate, while the task setting domain correlated with the IC CNVlate. The IC CNVearly was not correlated with any of the neuropsychological domain scores. The correlations between the domains and ICs remained largely unchanged when controlling for full-scale IQ. This is the first study to demonstrate that executive processes, as indexed by neuropsychological test parameters, are associated with particular event-related potentials in a cued Go/NoGo paradigm.

Collaborative brain-computer interface for aiding decision-making

We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making.

Intrinsic fluctuations in sustained attention and distractor processing

Although sustaining a moderate level of attention is critical in daily life, evidence suggests that attention is not deployed consistently, but rather fluctuates from moment to moment between optimal and suboptimal states. To better characterize these states in humans, the present study uses a gradual-onset continuous performance task with irrelevant background distractors to explore the relationship among behavioral fluctuations, brain activity, and, in particular, the processing of visual distractors. Using fMRI, we found that reaction time variability, a continuous measure of attentional instability, was positively correlated with activity in task-positive networks and negatively correlated with activity in the task-negative default mode network. We also observed greater processing of distractor images during more stable and less error prone "in the zone" epochs compared with suboptimal "out of the zone" epochs of the task. Overall, the data suggest that optimal states of attention are accomplished with more efficient and potentially less effortful recruitment of task-relevant resources, freeing remaining resources to process task irrelevant features of the environment.

Dissociation of preparatory attention and response monitoring maturation during adolescence

OBJECTIVE

Substantial brain development occurs during adolescence providing the foundation for functional advancement from stimulus-bound "bottom-up" to more mature executive-driven "top-down" processing strategies. The objective was to assess development of EEG markers of these strategies and their role in both preparatory attention (contingent negative variation, CNV) and response monitoring (Error Related Negativity, ERN, and Correct Related Negativity, CRN).

METHODS

CNV, ERN and CRN were assessed in 38 adolescents (18 girls), age 11-18 years, using a variation of a letter discrimination task.

RESULTS

Accuracy increased with age and developmental stage. Younger adolescents used a posterior attention network involved in inhibiting irrelevant information. Activity in this juvenile network, as indexed by a posteriorly-biased CNV and CRN decreased with age and advancing pubertal development. Although enhanced frontal CNV, known to be predictive of accuracy in adults, was not detected even in the older adolescents, top-down medial frontal response monitoring processes (ERN) showed evidence of development within the age-range studied.

CONCLUSIONS

The data revealed a dissociation of developmental progress, marked by relatively delayed onset of frontal preparatory attention relative to error monitoring.

SIGNIFICANCE

This dissociation may render adolescents vulnerable to excessive risk-taking and disinhibited behavior imposed by asynchronous development of component cognitive control processes.

Network dynamics underlying speed-accuracy trade-offs in response to errors

The ability to dynamically and rapidly adjust task performance based on its outcome is fundamental to adaptive, flexible behavior. Over trials of a task, responses speed up until an error is committed and after the error responses slow down. These dynamic adjustments serve to optimize performance and are well-described by the speed-accuracy trade-off (SATO) function. We hypothesized that SATOs based on outcomes reflect reciprocal changes in the allocation of attention between the internal milieu and the task-at-hand, as indexed by reciprocal changes in activity between the default and dorsal attention brain networks. We tested this hypothesis using functional MRI to examine the pattern of network activation over a series of trials surrounding and including an error. We further hypothesized that these reciprocal changes in network activity are coordinated by the posterior cingulate cortex (PCC) and would rely on the structural integrity of its white matter connections. Using diffusion tensor imaging, we examined whether fractional anisotropy of the posterior cingulum bundle correlated with the magnitude of reciprocal changes in network activation around errors. As expected, reaction time (RT) in trials surrounding errors was consistent with predictions from the SATO function. Activation in the default network was: (i) inversely correlated with RT, (ii) greater on trials before than after an error and (iii) maximal at the error. In contrast, activation in the right intraparietal sulcus of the dorsal attention network was (i) positively correlated with RT and showed the opposite pattern: (ii) less activation before than after an error and (iii) the least activation on the error. Greater integrity of the posterior cingulum bundle was associated with greater reciprocity in network activation around errors. These findings suggest that dynamic changes in attention to the internal versus external milieu in response to errors underlie SATOs in RT and are mediated by the PCC.

Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity

The capacity to focus one's attention for an extended period of time can be increased through training in contemplative practices. However, the cognitive processes engaged during meditation that support trait changes in cognition are not well characterized. We conducted a longitudinal wait-list controlled study of intensive meditation training. Retreat participants practiced focused attention (FA) meditation techniques for three months during an initial retreat. Wait-list participants later undertook formally identical training during a second retreat. Dense-array scalp-recorded electroencephalogram (EEG) data were collected during 6 min of mindfulness of breathing meditation at three assessment points during each retreat. Second-order blind source separation, along with a novel semi-automatic artifact removal tool (SMART), was used for data preprocessing. We observed replicable reductions in meditative state-related beta-band power bilaterally over anteriocentral and posterior scalp regions. In addition, individual alpha frequency (IAF) decreased across both retreats and in direct relation to the amount of meditative practice. These findings provide evidence for replicable longitudinal changes in brain oscillatory activity during meditation and increase our understanding of the cortical processes engaged during meditation that may support long-term improvements in cognition.

In the zone or zoning out? Tracking behavioral and neural fluctuations during sustained attention

Despite growing recognition that attention fluctuates from moment-to-moment during sustained performance, prevailing analysis strategies involve averaging data across multiple trials or time points, treating these fluctuations as noise. Here, using alternative approaches, we clarify the relationship between ongoing brain activity and performance fluctuations during sustained attention. We introduce a novel task (the gradual onset continuous performance task), along with innovative analysis procedures that probe the relationships between reaction time (RT) variability, attention lapses, and intrinsic brain activity. Our results highlight 2 attentional states-a stable, less error-prone state ("in the zone"), characterized by higher default mode network (DMN) activity but during which subjects are at risk of erring if DMN activity rises beyond intermediate levels, and a more effortful mode of processing ("out of the zone"), that is less optimal for sustained performance and relies on activity in dorsal attention network (DAN) regions. These findings motivate a new view of DMN and DAN functioning capable of integrating seemingly disparate reports of their role in goal-directed behavior. Further, they hold potential to reconcile conflicting theories of sustained attention, and represent an important step forward in linking intrinsic brain activity to behavioral phenomena.

Foreshadowing of performance accuracy by event-related potentials: evidence from a minimal-conflict task

Background

Recent studies employing stimulus-response compatibility tasks suggest that an increase in the amplitude of the positive deflection of the response-locked event-related potential (ERP) foreshadows errors on forthcoming trials. However, no studies have tested the generalizability of error-foreshadowing positivity to tasks without stimulus-response interference.

Methodology/Principal Findings

The present study adopted an alternating-response task, in which the participants responded to the pointing direction of an arrowhead (up or down). Although the arrowhead direction alternated for the majority of trials (95%), occasionally this pattern was broken by a repeated stimulus, termed a lure trial. We compared the matched-reaction-time correct-preceding ERP with the error-preceding ERP on lure-preceding trials. There was no evidence that errors are foreshadowed by the increase of a positive electroencephalogram (EEG) deflection. To the contrary, analyses of ERPs time-locked to electromyogram (EMG) onset on the five consecutive lure-preceding trials showed larger positive deflections on correct-preceding than error-preceding trials. The post-response negativity did not differ between correct-preceding and error-preceding trials.

Conclusions/Significance

These results suggest that in minimal conflict tasks a decreased positivity may foreshadow incorrect performance several trials prior to the error, possibly reflecting the waning of task-related efforts. Therefore, error-foreshadowing brain signals may be task-specific.

Error-preceding brain activity reflects (mal-)adaptive adjustments of cognitive control: a modeling study

Errors in choice tasks are preceded by gradual changes in brain activity presumably related to fluctuations in cognitive control that promote the occurrence of errors. In the present paper, we use connectionist modeling to explore the hypothesis that these fluctuations reflect (mal-)adaptive adjustments of cognitive control. We considered ERP data from a study in which the probability of conflict in an Eriksen-flanker task was manipulated in sub-blocks of trials. Errors in these data were preceded by a gradual decline of N2 amplitude. After fitting a connectionist model of conflict adaptation to the data, we analyzed simulated N2 amplitude, simulated response times (RTs), and stimulus history preceding errors in the model, and found that the model produced the same pattern as obtained in the empirical data. Moreover, this pattern is not found in alternative models in which cognitive control varies randomly or in an oscillating manner. Our simulations suggest that the decline of N2 amplitude preceding errors reflects an increasing adaptation of cognitive control to specific task demands, which leads to an error when these task demands change. Taken together, these results provide evidence that error-preceding brain activity can reflect adaptive adjustments rather than unsystematic fluctuations of cognitive control, and therefore, that these errors are actually a consequence of the adaptiveness of human cognition.

Independent oscillatory patterns determine performance fluctuations in children with attention deficit/hyperactivity disorder

The maintenance of stable goal-directed behaviour is a hallmark of conscious executive control in humans. Notably, both correct and error human actions may have a subconscious activation-based determination. One possible source of subconscious interference may be the default mode network that, in contrast to attentional network, manifests intrinsic oscillations at very low (<0.1 Hz) frequencies. In the present study, we analyse the time dynamics of performance accuracy to search for multisecond periodic fluctuations of error occurrence. Attentional lapses in attention deficit/hyperactivity disorder are proposed to originate from interferences from intrinsically oscillating networks. Identifying periodic error fluctuations with a frequency<0.1 Hz in patients with attention deficit/hyperactivity disorder would provide a behavioural evidence for such interferences. Performance was monitored during a visual flanker task in 92 children (7- to 16-year olds), 47 with attention deficit/hyperactivity disorder, combined type and 45 healthy controls. Using an original approach, the time distribution of error occurrence was analysed in the frequency and time-frequency domains in order to detect rhythmic periodicity. Major results demonstrate that in both patients and controls, error behaviour was characterized by multisecond rhythmic fluctuations with a period of ∼12 s, appearing with a delay after transition to task. Only in attention deficit/hyperactivity disorder, was there an additional 'pathological' oscillation of error generation, which determined periodic drops of performance accuracy each 20-30 s. Thus, in patients, periodic error fluctuations were modulated by two independent oscillatory patterns. The findings demonstrate that: (i) attentive behaviour of children is determined by multisecond regularities; and (ii) a unique additional periodicity guides performance fluctuations in patients. These observations may re-conceptualize the understanding of attentive behaviour beyond the executive top-down control and may reveal new origins of psychopathological behaviours in attention deficit/hyperactivity disorder.

It's about Time

The purpose of this review/opinion paper is to argue that human cognitive neuroscience has focused too little attention on how the brain may use time and time-based coding schemes to represent, process, and transfer information within and across brain regions. Instead, the majority of cognitive neuroscience studies rest on the assumption of functional localization. Although the functional localization approach has brought us a long way toward a basic characterization of brain functional organization, there are methodological and theoretical limitations of this approach. Further advances in our understanding of neurocognitive function may come from examining how the brain performs computations and forms transient functional neural networks using the rich multi-dimensional information available in time. This approach rests on the assumption that information is coded precisely in time but distributed in space; therefore, measures of rapid neuroelectrophysiological dynamics may provide insights into brain function that cannot be revealed using localization-based approaches and assumptions. Space is not an irrelevant dimension for brain organization; rather, a more complete understanding of how brain dynamics lead to behavior dynamics must incorporate how the brain uses time-based coding and processing schemes.

Phase entrainment of human delta oscillations can mediate the effects of expectation on reaction speed

The more we anticipate a response to a predictable stimulus, the faster we react. This empirical observation has been confirmed and quantified by many investigators suggesting that the processing of behaviorally relevant stimuli is facilitated by probability-based confidence of anticipation. However, the exact neural mechanisms underlying this phenomenon are largely unknown. Here we show that performance changes related to different levels of expectancy originate in dynamic modulation of delta oscillation phase. Our results obtained in rhythmic auditory target detection tasks indicated significant entrainment of the EEG delta rhythm to the onset of the target tones with increasing phase synchronization at higher levels of predictability. Reaction times correlated with the phase of the delta band oscillation at target onset. The fastest reactions occurred during the delta phase that most commonly coincided with the target event in the high expectancy conditions. These results suggest that low-frequency oscillations play a functional role in human anticipatory mechanisms, presumably by modulating synchronized rhythmic fluctuations in the excitability of large neuronal populations and by facilitating efficient task-related neuronal communication among brain areas responsible for sensory processing and response execution.

Mal-adaptation of event-related EEG responses preceding performance errors

Recent EEG and fMRI evidence suggests that behavioral errors are foreshadowed by systematic changes in brain activity preceding the outcome by seconds. In order to further characterize this type of error precursor activity, we investigated single-trial event-related EEG activity from 70 participants performing a modified Eriksen flanker task, in particular focusing on the trial-by-trial dynamics of a fronto-central independent component that previously has been associated with error and feedback processing. The stimulus-locked peaks in the N2 and P3 latency range in the event-related averages showed expected compatibility and error-related modulations. In addition, a small pre-stimulus negative slow wave was present at erroneous trials. Significant error-preceding activity was found in local stimulus sequences with decreased conflict in the form of less negativity at the N2 latency (310–350 ms) accumulating across five trials before errors; concomitantly response times were speeding across trials. These results illustrate that error-preceding activity in event-related EEG is associated with the performance monitoring system and we conclude that the dynamics of performance monitoring contribute to the generation of error-prone states in addition to the more remote and indirect effects in ongoing activity such as posterior alpha power in EEG and default mode drifts in fMRI.

Tonic and phasic EEG and behavioral changes induced by arousing feedback

This study investigates brain dynamics and behavioral changes in response to arousing auditory signals presented to individuals experiencing momentary cognitive lapses during a sustained-attention task. Electroencephalographic (EEG) and behavioral data were simultaneously collected during virtual-reality (VR) based driving experiments, in which subjects were instructed to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel. 30-channel EEG data were analyzed by independent component analysis and the short-time Fourier transform. Across subjects and sessions, intermittent performance during drowsiness was accompanied by characteristic spectral augmentation or suppression in the alpha- and theta-band spectra of a bilateral occipital component, corresponding to brief periods of normal (wakeful) and hypnagogic (sleeping) awareness and behavior. Arousing auditory feedback was delivered to the subjects in half of the non-responded lane-deviation events, which immediately agitated subject's responses to the events. The improved behavioral performance was accompanied by concurrent spectral suppression in the theta- and alpha-bands of the bilateral occipital component. The effects of auditory feedback on spectral changes lasted 30s or longer. The results of this study demonstrate the amount of cognitive state information that can be extracted from noninvasively recorded EEG data and the feasibility of online assessment and rectification of brain networks exhibiting characteristic dynamic patterns in response to momentary cognitive challenges.

Anterior cingulate neurons represent errors and preparatory attention within the same behavioral sequence

The anterior cingulate cortex (ACC) has been implicated in both preparatory attention (i.e., selecting behaviorally relevant stimuli) and in detecting errors. We recorded from the rat ACC and medial prefrontal cortex (mPFC), which is functionally homologous to the primate dorsolateral PFC, during an attention task. The three-choice serial reaction time task requires a rat to orient toward and divide attention between three brief (300 ms duration) light stimuli presented in random order across nose poke holes in an operant chamber. In both the ACC and mPFC, we found that neural activity was related to the level of preparatory (precue) attention and subsequent correct or incorrect choice, in that the magnitude of the single units' response to the cue was lower on incorrect trials and was not different than baseline on unattended trials. This preparatory neural activity consisted of both excitatory and inhibitory phasic responses. The number of units responding to the cue was similarly graded, in that fewer units exhibited phasic responses to the cue on incorrect and unattended trials, compared with correct trials. Although preparatory activity was found in both the ACC and mPFC, activity after incorrect nose pokes, which may be related to error detection, were only observed in the ACC. Thus, during the same behavioral sequence, the ACC encodes both error-related events and preparatory attention, whereas the mPFC only participates in preparatory attention. The finding of substantial inhibitory activity during the preparatory period suggests a critical role for inhibition of pyramidal cells in PFC-mediated cognitive functions.

Nobody is perfect: ERP effects prior to performance errors in musicians indicate fast monitoring processes

BACKGROUND

One central question in the context of motor control and action monitoring is at what point in time errors can be detected. Previous electrophysiological studies investigating this issue focused on brain potentials elicited after erroneous responses, mainly in simple speeded response tasks. In the present study, we investigated brain potentials before the commission of errors in a natural and complex situation.

METHODOLOGY/PRINCIPAL FINDINGS

Expert pianists bimanually played scales and patterns while the electroencephalogram (EEG) was recorded. Event-related potentials (ERPs) were computed for correct and incorrect performances. Results revealed differences already 100 ms prior to the onset of a note (i.e., prior to auditory feedback). We further observed that erroneous keystrokes were delayed in time and pressed more slowly.

CONCLUSIONS

Our data reveal neural mechanisms in musicians that are able to detect errors prior to the execution of erroneous movements. The underlying mechanism probably relies on predictive control processes that compare the predicted outcome of an action with the action goal.

The predictive brain state: asynchrony in disorders of attention?

It is postulated that a key function of attention in goal-oriented behavior is to reduce performance variability by generating anticipatory neural activity that can be synchronized with expected sensory information. A network encompassing the prefrontal cortex, parietal lobe, and cerebellum may be critical in the maintenance and timing of such predictive neural activity. Dysfunction of this temporal process may constitute a fundamental defect in attention, causing working memory problems, distractibility, and decreased awareness.

The predictive brain state: timing deficiency in traumatic brain injury?

Attention and memory deficits observed in traumatic brain injury (TBI) are postulated to result from the shearing of white matter connections between the prefrontal cortex, parietal lobe, and cerebellum that are critical in the generation, maintenance, and precise timing of anticipatory neural activity. These fiber tracts are part of a neural network that generates predictions of future states and events, processes that are required for optimal performance on attention and working memory tasks. The authors discuss the role of this anticipatory neural system for understanding the varied symptoms and potential rehabilitation interventions for TBI. Preparatory neural activity normally allows the efficient integration of sensory information with goal-based representations. It is postulated that an impairment in the generation of this activity in traumatic brain injury (TBI) leads to performance variability as the brain shifts from a predictive to reactive mode. This dysfunction may constitute a fundamental defect in TBI as well as other attention disorders, causing working memory deficits, distractibility, a loss of goal-oriented behavior, and decreased awareness.

Lapsing during sleep deprivation is associated with distributed changes in brain activation

Lapses of attention manifest as delayed behavioral responses to salient stimuli. Although they can occur even after a normal night's sleep, they are longer in duration and more frequent after sleep deprivation (SD). To identify changes in task-associated brain activation associated with lapses during SD, we performed functional magnetic resonance imaging during a visual, selective attention task and analyzed the correct responses in a trial-by-trial manner modeling the effects of response time. Separately, we compared the fastest 10% and slowest 10% of correct responses in each state. Both analyses concurred in finding that SD-related lapses differ from lapses of equivalent duration after a normal night's sleep by (1) reduced ability of frontal and parietal control regions to raise activation in response to lapses, (2) dramatically reduced visual sensory cortex activation, and (3) reduced thalamic activation during lapses that contrasted with elevated thalamic activation during nonlapse periods. Despite these differences, the fastest responses after normal sleep and after SD elicited comparable frontoparietal activation, suggesting that performing a task while sleep deprived involves periods of apparently normal neural activation interleaved with periods of depressed cognitive control, visual perceptual functions, and arousal. These findings reveal for the first time some of the neural consequences of the interaction between efforts to maintain wakefulness and processes that initiate involuntary sleep in sleep-deprived persons.

Prediction of human errors by maladaptive changes in event-related brain networks

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Response anticipation and response conflict: an event-related potential and functional magnetic resonance imaging study

Response anticipation and response conflict processes are supported by executive control. However, few neuroimaging studies have attempted to study the relationship between these two processes in the same experimental session. In this study, we isolated brain activity associated with response anticipation (after a cue to prepare vs relax) and with response conflict (responding to a target with incongruent vs congruent flankers) and examined the independence and interaction of brain networks supporting these processes using event-related potentials (ERPs) and functional magnetic resonance imaging. Response anticipation generated a contingent negative variation ERP that correlated with shorter reaction times, and was associated with activation of a thalamo-cortico-striatal network, as well as increased gamma band power in frontal and parietal regions, and decreased spectral power in theta, alpha, and beta bands in most regions. Response conflict was associated with increased activation in the anterior cingulate cortex (ACC) and prefrontal cortex of the executive control network, with an overlap in activation with response anticipation in regions including the middle frontal gyrus, ACC, and superior parietal lobule. Although the executive control network showed increased activation in response to unanticipated versus anticipated targets, the response conflict effect was not altered by response anticipation. These results suggest that common regions of a dorsal frontoparietal network and the ACC are engaged in the flexible control of a wide range of executive processes, and that response anticipation modulates overall activity in the executive control network but does not interact with response conflict processing.