Neural synchrony during response production and inhibition

Inhibition of irrelevant information (conflict monitoring) and/or of prepotent actions is an essential component of adaptive self-organized behavior. Neural dynamics underlying these functions has been studied in humans using event-related brain potentials (ERPs) elicited in Go/NoGo tasks that require a speeded motor response to the Go stimuli and withholding a prepotent response when a NoGo stimulus is presented. However, averaged ERP waveforms provide only limited information about the neuronal mechanisms underlying stimulus processing, motor preparation, and response production or inhibition. In this study, we examine the cortical representation of conflict monitoring and response inhibition using time-frequency analysis of electroencephalographic (EEG) recordings during continuous performance Go/NoGo task in 50 young adult females. We hypothesized that response inhibition would be associated with a transient boost in both temporal and spatial synchronization of prefrontal cortical activity, consistent with the role of the anterior cingulate and lateral prefrontal cortices in cognitive control. Overall, phase synchronization across trials measured by Phase Locking Index and phase synchronization between electrode sites measured by Phase Coherence were the highest in the Go and NoGo conditions, intermediate in the Warning condition, and the lowest under Neutral condition. The NoGo condition was characterized by significantly higher fronto-central synchronization in the 300-600 ms window, whereas in the Go condition, delta- and theta-band synchronization was higher in centro-parietal regions in the first 300 ms after the stimulus onset. The present findings suggest that response production and inhibition is supported by dynamic functional networks characterized by distinct patterns of temporal and spatial synchronization of brain oscillations.     

建立猕猴Go/NoGo视觉分辨任务的方法

在认知神经科学研究中,Go/NoGo模型是一种非常有效的研究方法。在本试验中,以两只猕猴为研究对象,采用Go/NoGo模型,以不同的视觉线索作为刺激来研究相关认知行为。结果表明猕猴能够很快学会Go/NoGo视觉分辨任务,而且对NoGo任务的完成要优于对Go任务的完成。本实验建立了一种有效的猕猴Go/NoGo视觉分辨实验的方法及计算机控制系统,为进一步记录神经元活动建立了良好的基础。     

A review of EEG and MEG for brainnetome research

The majority of brain activities are performed by functionally integrating separate regions of the brain. Therefore, the synchronous operation of the brain’s multiple regions or neuronal assemblies can be represented as a network with nodes that are interconnected by links. Because of the complexity of brain interactions and their varying effects at different levels of complexity, one of the corresponding authors of this paper recently proposed the brainnetome as a new –ome to explore and integrate the brain network at different scales. Because electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive and have outstanding temporal resolution and because they are the primary clinical techniques used to capture the dynamics of neuronal connections, they lend themselves to the analysis of the neural networks comprising the brainnetome. Because of EEG/MEG’s applicability to brainnetome analyses, the aim of this review is to identify the procedures that can be used to form a network using EEG/MEG data in sensor or source space and to promote EEG/MEG network analysis for either neuroscience or clinical applications. To accomplish this aim, we show the relationship of the brainnetome to brain networks at the macroscale and provide a systematic review of network construction using EEG and MEG. Some potential applications of the EEG/MEG brainnetome are to use newly developed methods to associate the properties of a brainnetome with indices of cognition or disease conditions. Associations based on EEG/MEG brainnetome analysis may improve the comprehension of the functioning of the brain in neuroscience research or the recognition of abnormal patterns in neurological disease.     

Weakening of the Top-Down Inhibitory Influences from the Prefrontal Cortex under the Loading of the Working Memory in Students with Learning Difficulties

Two groups of students (with and without learning difficulties) were studied. In the experimental technique used in experiments, an increased load on the working memory by lengthening the interstimulus interval between the conditioning positive (Go) or inhibitory (NoGo) signals and the triggering stimulus was combined with EEG recording. In students with learning difficulties, the evoked synchronization/desynchronization of low-frequency α-oscillations (8–10 Hz) in individual intersimulation intervals was significantly weakened. The hypothesis of the disturbed coordinating mechanism of selective implicit attention with the involvement of the prefrontal cortex in the organization of cognitive activity in students with learning difficulties is discussed and substantiated.     

The brain timewise: how timing shapes and supports brain function

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.     

Proactive Control Strategies for Overt and Covert Go/NoGo Tasks: An Electrical Neuroimaging Study

Proactive and reactive inhibition are generally intended as mechanisms allowing the withholding or suppression of overt movements. Nonetheless, inhibition could also play a pivotal role during covert actions (i.e., potential motor acts not overtly performed, despite the activation of the motor system), such as Motor Imagery (MI). In a previous EEG study, we analyzed cerebral activities reactively triggered during two cued Go/NoGo tasks, requiring execution or withholding of overt or covert imagined actions, respectively. This study revealed activation of pre-supplementary motor area (pre-SMA) and right inferior frontal gyrus (rIFG), key nodes of the network underpinning reactive inhibition of overt responses in NoGo trials, also during MI enactment, enabling the covert nature of the imagined motor response. Taking into account possible proactive engagement of inhibitory mechanisms by cue signals, for an exhaustive interpretation of these previous findings in the present study we analyzed EEG activities elicited during the preparatory phase of our cued overt and covert Go/NoGo tasks. Our results demonstrate a substantial overlap of cerebral areas activated during proactive recruitment and subsequent reactive implementation of motor inhibition in both overt and covert actions; also, different involvement of pre-SMA and rIFG emerged, in accord with the intended type (covert or overt) of incoming motor responses. During preparation of the overt Go/NoGo task, the cue is encoded in a pragmatic mode, as it primes the possible overt motor response programs in motor and premotor cortex and, through preactivation of a pre-SMA-related decisional mechanism, it triggers a parallel preparation for successful response selection and/or inhibition during the response phase. Conversely, the preparatory strategy for the covert Go/NoGo task is centered on priming of an inhibitory mechanism in rIFG, tuned to the instructed covert modality of motor performance and instantiated during subsequent MI, which allows the imagined response to remain a potential motor act.     

A cognitive hypothesis of the development of differentiative cortical inhibition in humans

Positive and inhibitory conditioning stimuli (Go/NoGo) were presented to healthy adults (n = 35) in an experimental setting for angry face recognition with short intervals between the setting (face), conditioning, and triggering stimuli. A modification of the previously used experimental conditions that consisted in a reduction of the duration of the interstimulus intervals promoted an increase in attitude flexibility (expansion of the group of subjects that made no identification errors at the stage of set testing). The improvement of cognitive performance was accompanied by expansion of the zone of α-oscillation synchronization induced by the NoGo inhibitory conditioning stimulus. Synchronization of α-oscillations was less pronounced in subjects with a rigid cognitive set. Thus, the cognitive hypothesis of cortical inhibition (termed “internal inhibition” by I.P. Pavlov) has been confirmed. The concept of the emergence of top-down inhibitory effects in the prefrontal cortex, implicit internal representation, and selective modulation of attention is discussed.     

Spatiotemporal mapping of brain activity by integration of multiple imaging modalities

Functional magnetic resonance imaging (fMRI) and positron emission tomography measure local changes in brain hemodynamics induced by cognitive or perceptual tasks. These measures have a uniformly high spatial resolution of millimeters or less, but poor temporal resolution (about 1s). Conversely, electroencephalography (EEG) and magnetoencephalography (MEG) measure instantaneously the current flows induced by synaptic activity, but the accurate localization of these current flows based on EEG and MEG data alone remains an unsolved problem. Recently, techniques have been developed that, in the context of brain anatomy visualized with structural MRI, use both hemodynamic and electromagnetic measures to arrive at estimates of brain activation with high spatial and temporal resolution. These methods range from simple juxtaposition to simultaneous integrated techniques. Their application has already led to advances in our understanding of the neural bases of perception, attention, memory and language. Further advances in multi-modality integration will require an improved understanding of the coupling between the physiological phenomena underlying the different signal modalities.     

Temporal Constraints of Behavioral Inhibition: Relevance of Inter-stimulus Interval in a Go-Nogo Task

The capacity to inhibit prepotent and automatic responses is crucial for proper cognitive and social development, and inhibitory impairments have been considered to be key for some neuropsychiatric conditions. One of the most used paradigms to analyze inhibitory processes is the Go-Nogo task (GNG). This task has been widely used in psychophysical and cognitive EEG studies, and more recently in paradigms using fMRI. However, a technical limitation is that the time resolution of fMRI is poorer than that of the EEG technique. In order to compensate for these temporal constraints, it has become common practice in the fMRI field to use longer inter-stimulus intervals (ISI) than those used in EEG protocols. Despite the noticeable temporal differences between these two techniques, it is currently assumed that both approaches assess similar inhibitory processes. We performed an EEG study using a GNG task with both short ISI (fast-condition, FC, as in EEG protocols) and long ISI (slow-condition, SC, as in fMRI protocols). We found that in the FC there was a stronger Nogo-N2 effect than in the SC. Moreover, in the FC, but not in the SC, the number of preceding Go trials correlated positively with the Nogo-P3 amplitude and with the Go trial reaction time; and negatively with commission errors. In addition, we found significant topographical differences for the Go-P3 elicited in FC and SC, which is interpreted in terms of different neurotransmitter dynamics. Taken together, our results provide evidence that frequency of stimulus presentation in the GNG task strongly modulates the behavioral response and the evoked EEG activity. Therefore, it is likely that short-ISI EEG protocols and long-ISI fMRI protocols do not assess equivalent inhibitory processes.     

Three-dimensional tomography of event-related potentials during response inhibition: evidence for phasic frontal lobe activation

Objectives: Spatial analysis of the evoked brain electrical fields during a cued revealed an extremely robust anteriorization of the positivity of a P300 microstate in the NoGo compared to the Go condition (NoGo-anteriorization in a prevailing study). To allow a neuroanatomical interpretation the NoGo-anteriorization was investigated with a new three-dimensional source tomography method (LORETA) was applied.Methods: The test contains subsets of stimuli requiring the execution (Go) or the inhibition (NoGo) of a cued motor response which can be considered as mutual control conditions for the study of inhibitory brain functions. 21-channel ERPs were obtained from 10 healthy subjects during a cued CPT, And analyzed with LORETA.Results: Topographic analyses revealed significantly different scalp distributions between the Go and the NoGo conditions in both P100 and P300 microstates, indicating that already at an early stage different neural assemblies are activated. LORETA disclosed a significant hyperactivity located in the right frontal lobe during the NoGo condition in the P300 microstate.Conclusions: The results indicate that right frontal sources are responsible for the NoGo-anteriorization of the scalp P300 which is consistent with animal and human lesion studies of inhibitory brain functions. Furthermore, it demonstrates that frontal activation is confined to a brief microstate and time-locked to phasic inhibitory motor control. This adds important functional and chronometric specificity to findings of frontal activation obtained with PET and Near-Infrared-Spectroscopy studies during the cued CPT, and suggests that these metabolic results are not due to general task demands.     

ERP Correlates of Proactive and Reactive Cognitive Control in Treatment-Na?ve Adult ADHD

This study investigated whether treatment naïve adults with Attention Deficit Hyperactivity Disorder (ADHD; n = 33; 19 female) differed from healthy controls (n = 31; 17 female) in behavioral performance, event-related potential (ERP) indices of preparatory attention (CueP3 and late CNV), and reactive response control (Go P3, NoGo N2, and NoGo P3) derived from a visual cued Go/NoGo task. On several critical measures, Cue P3, late CNV, and NoGo N2, there were no significant differences between the groups. This indicated normal preparatory processes and conflict monitoring in ADHD patients. However, the patients had attenuated Go P3 and NoGoP3 amplitudes relative to controls, suggesting reduced allocation of attentional resources to processes involved in response control. The patients also had a higher rate of Go signal omission errors, but no other performance decrements compared with controls. Reduced Go P3 and NoGo P3 amplitudes were associated with poorer task performance, particularly in the ADHD group. Notably, the ERPs were not associated with self-reported mood or anxiety. The results provide electrophysiological evidence for reduced effortful engagement of attentional resources to both Go and NoGo signals when reactive response control is needed. The absence of group differences in ERP components indexing proactive control points to impairments in specific aspects of cognitive processes in an untreated adult ADHD cohort. The associations between ERPs and task performance provided additional support for the altered electrophysiological responses.     

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources.Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e., perform group-level analysis) based on a common cortical coordinate space.     

Motor Inhibition during Overt and Covert Actions: An Electrical Neuroimaging Study

Given ample evidence for shared cortical structures involved in encoding actions, whether or not subsequently executed, a still unsolved problem is the identification of neural mechanisms of motor inhibition, preventing “covert actions” as motor imagery from being performed, in spite of the activation of the motor system. The principal aims of the present study were the evaluation of: 1) the presence in covert actions as motor imagery of putative motor inhibitory mechanisms; 2) their underlying cerebral sources; 3) their differences or similarities with respect to cerebral networks underpinning the inhibition of overt actions during a Go/NoGo task. For these purposes, we performed a high density EEG study evaluating the cerebral microstates and their related sources elicited during two types of Go/NoGo tasks, requiring the execution or withholding of an overt or a covert imagined action, respectively. Our results show for the first time the engagement during motor imagery of key nodes of a putative inhibitory network (including pre-supplementary motor area and right inferior frontal gyrus) partially overlapping with those activated for the inhibition of an overt action during the overt NoGo condition. At the same time, different patterns of temporal recruitment in these shared neural inhibitory substrates are shown, in accord with the intended overt or covert modality of action performance. The evidence that apparently divergent mechanisms such as controlled inhibition of overt actions and contingent automatic inhibition of covert actions do indeed share partially overlapping neural substrates, further challenges the rigid dichotomy between conscious, explicit, flexible and unconscious, implicit, inflexible forms of motor behavioral control.     

Methylphenidate and if-then plans are comparable in modulating the P300 and increasing response inhibition in children with ADHD

A disturbed functioning of the prefrontal cortex, the anterior cingulate cortex, and an accordingly reduced P300 presumably underlies executive function deficits of children with attention deficit hyperactivity disorder (ADHD). Using a combined classification and Go/NoGo task paradigm, the present study investigated whether medication with methylphenidate (MPH) modulates the P300 as measured by a high-density electroencephalogram (EEG) and facilitates response inhibition in children with ADHD. Further, effects of MPH were compared with effects of self-regulation by if-then plans (Gollwitzer in Am Psychol 54: 493-503, 1999). MPH as well as if-then plans modulated the P300 and improved inhibition of an unwanted response on a Go/NoGo task to the same level observed in children without ADHD. Importantly, self-regulation strategies might be a valuable alternative to medication with MPH in children with ADHD.     

Behavior and Approximate Entropy of Right-eye Lateralization During Predation in the Music Frog

Brain asymmetry for processing visual information is widespread in animals. However, it is still unknown how the complexity of the underlying neural network activities represents this asymmetrical pattern in the brain. In the present study, we investigated this complexity using the approximate entropy(ApEn)protocol for electroencephalogram(EEG) recordings from the forebrain and midbrain while the music frogs(Nidirana daunchina) attacked prey stimulus. The results showed that(1) more significant prey responses were evoked by the prey stimulus presented in the right visual field than that in the left visual field,consistent with the idea that right-eye preferences for predatory behaviors exist in animals including anurans;(2) in general, the ApEn value of the left hemisphere(especially the left mesencephalon) was greatest under various stimulus conditions, suggesting that visual lateralization could be reflected by the dynamics of underlying neural network activities and that the stable left-hemisphere dominance of EEG ApEn may play an important role in maintaining this brain asymmetry.     

Comparative power spectral analysis of simultaneous elecroencephalographic and magnetoencephalographic recordings in humans suggests non-resistive extracellular media

The resistive or non-resistive nature of the extracellular space in the brain is still debated, and is an important issue for correctly modeling extracellular potentials. Here, we first show theoretically that if the medium is resistive, the frequency scaling should be the same for electroencephalogram (EEG) and magnetoencephalogram (MEG) signals at low frequencies (<10 Hz). To test this prediction, we analyzed the spectrum of simultaneous EEG and MEG measurements in four human subjects. The frequency scaling of EEG displays coherent variations across the brain, in general between 1/f and 1/f ², and tends to be smaller in parietal/temporal regions. In a given region, although the variability of the frequency scaling exponent was higher for MEG compared to EEG, both signals consistently scale with a different exponent. In some cases, the scaling was similar, but only when the signal-to-noise ratio of the MEG was low. Several methods of noise correction for environmental and instrumental noise were tested, and they all increased the difference between EEG and MEG scaling. In conclusion, there is a significant difference in frequency scaling between EEG and MEG, which can be explained if the extracellular medium (including other layers such as dura matter and skull) is globally non-resistive.     

Method for single-trial recordings of somatosensory evoked potentials

Evoked potentials (EPs) in response to stimuli are recorded from a human scalp contaminated with noise. To improve the signal-to-noise ratio, averaging methods have been widely used for the recorded data. However, when the waveforms of EP for each stimulus are not identical, the average waveform of the EP deteriorates. Variation of the EP waveform to each stimulus itself is important information for the EP. In this paper, a recording method for single somatosensory evoked potential (SEP) waveform is proposed, in which three kinds of band-pass filters were selectively used during three specific time sectors for each interstimulus interval. For the late section of the interval, an EEG waveform prediction method was applied to eliminate contaminated alpha rhythm components. By using the proposed method, we were successful in detecting the single SEP waveform.     

Large-Scale Functional Networks Identified from Resting-State EEG Using Spatial ICA

Several methods have been applied to EEG or MEG signals to detect functional networks. In recent works using MEG/EEG and fMRI data, temporal ICA analysis has been used to extract spatial maps of resting-state networks with or without an atlas-based parcellation of the cortex. Since the links between the fMRI signal and the electromagnetic signals are not fully established, and to avoid any bias, we examined whether EEG alone was able to derive the spatial distribution and temporal characteristics of functional networks. To do so, we propose a two-step original method: 1) An individual multi-frequency data analysis including EEG-based source localisation and spatial independent component analysis, which allowed us to characterize the resting-state networks. 2) A group-level analysis involving a hierarchical clustering procedure to identify reproducible large-scale networks across the population. Compared with large-scale resting-state networks obtained with fMRI, the proposed EEG-based analysis revealed smaller independent networks thanks to the high temporal resolution of EEG, hence hierarchical organization of networks. The comparison showed a substantial overlap between EEG and fMRI networks in motor, premotor, sensory, frontal, and parietal areas. However, there were mismatches between EEG-based and fMRI-based networks in temporal areas, presumably resulting from a poor sensitivity of fMRI in these regions or artefacts in the EEG signals. The proposed method opens the way for studying the high temporal dynamics of networks at the source level thanks to the high temporal resolution of EEG. It would then become possible to study detailed measures of the dynamics of connectivity.     

脑磁源的定位研究

在脑电脑磁研究中,常将大脑视为一电磁系统,利用准静态近似下的麦克斯韦方程,可以发现代表脑神经元活动的原在电流密度与脑外磁场之间呈线性关系。在高斯哭喊杨存在的情况下,采用极大似然估计理论,讨论了一种基于脑磁场时域－罕注解磁源定位问题的一般方法。球对称导体模型下的模拟计算表明,这一方法是有效的。对于考虑真实头模型下的磁源定位问题求解磁源定位,提出了一种联合使用脑磁脑电数据的近似方法。     

EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful.