Toward a quantitative description of large-scale neocortical dynamic function and EEG

A general conceptual framework for large-scale neocortical dynamics based on data from many laboratories is applied to a variety of experimental designs, spatial scales, and brain states. Partly distinct, but interacting local processes (e.g., neural networks) arise from functional segregation. Global processes arise from functional integration and can facilitate (top down) synchronous activity in remote cell groups that function simultaneously at several different spatial scales. Simultaneous local processes may help drive (bottom up) macroscopic global dynamics observed with electroencephalography (EEG) or magnetoencephalography (MEG). A local/global dynamic theory that is consistent with EEG data and the proposed conceptual framework is outlined. This theory is neutral about properties of neural networks embedded in macroscopic fields, but its global component makes several qualitative and semiquantitative predictions about EEG measures of traveling and standing wave phenomena. A more general "metatheory" suggests what large-scale quantitative theories of neocortical dynamics may be like when more accurate treatment of local and nonlinear effects is achieved. The theory describes the dynamics of excitatory and inhibitory synaptic action fields. EEG and MEG provide large-scale estimates of modulation of these synaptic fields around background levels. Brain states are determined by neuromodulatory control parameters. Purely local states are dominated by local feedback gains and rise and decay times of postsynaptic potentials. Dominant local frequencies vary with brain region. Other states are purely global, with moderate to high coherence over large distances. Multiple global mode frequencies arise from a combination of delays in corticocortical axons and neocortical boundary conditions. Global frequencies are identical in all cortical regions, but most states involve dynamic interactions between local networks and the global system. EEG frequencies may involve a "matching" of local resonant frequencies with one or more of the many, closely spaced global frequencies.     

Dealing with artifacts: The EOG contamination of the event-related brain potential

Eye movements and blinks represent a major source of artifacts in the electroencephalogram (EEG) and event-related brain potentials (ERPs). The origin of this artifact is the large difference in potential that exists between the cornea and the retina. Eye movements and blinks produce shifts of the electric fields that propagate across the whole head and that can be several times larger than the activity generated by the brain. Ocular activity can be monitored by electrodes located near the eyes (electrooculogram, or EOG). The electric fields associated with eye movements and blinks are somewhat different. The simplest procedure for dealing with ocular artifacts is to eliminate trials on which EOG activity is detected (rejection). However, this technique may result in data loss and biased data samples, especially when one is comparing clinical populations or tasks involving large amounts of eye movements. Another approach involves estimation and correction of the ocular artifact on the EEG and ERP traces. Several techniques have been proposed. Some of them are reviewed in the present paper. Issues related to the accuracy of the various techniques, as well as other advantages and limitations, are also discussed. Finally, general guidelines for how to deal with ocular artifacts are proposed.     

认知心理生理学与无创性脑功能成像技术

无创性脑功能成像技术是认知心理生理学研究的重要手段。脑电图、事件相关电位、脑磁图、正电子发射断层摄影术、单光子发射计算机断层摄影术、功能磁共振成像和功能红外线成像等技术通过对人脑的电磁、新陈代谢、血流量、氧消耗、神经元活动等的测量来研究如视觉、注意、记忆、语言等认知活动及其与相关脑机制的相互关系。它们各有优缺点。     

Brain Development During the Preschool Years

The preschool years represent a time of expansive mental growth, with the initial expression of many psychological abilities that will continue to be refined into young adulthood. Likewise, brain development during this age is characterized by its ??blossoming?? nature, showing some of its most dynamic and elaborative anatomical and physiological changes. In this article, we review human brain development during the preschool years, sampling scientific evidence from a variety of sources. First, we cover neurobiological foundations of early postnatal development, explaining some of the primary mechanisms seen at a larger scale within neuroimaging studies. Next, we review evidence from both structural and functional imaging studies, which now accounts for a large portion of our current understanding of typical brain development. Within anatomical imaging, we focus on studies of developing brain morphology and tissue properties, including diffusivity of white matter fiber tracts. We also present new data on changes during the preschool years in cortical area, thickness, and volume. Physiological brain development is then reviewed, touching on influential results from several different functional imaging and recording modalities in the preschool and early school-age years, including positron emission tomography (PET), electroencephalography (EEG) and event-related potentials (ERP), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS). Here, more space is devoted to explaining some of the key methodological factors that are required for interpretation. We end with a section on multimodal and multidimensional imaging approaches, which we believe will be critical for increasing our understanding of brain development and its relationship to cognitive and behavioral growth in the preschool years and beyond.     

Application of EEG,ERP and intracranial recordings to the investigation of cognitive functions in children

Neurophysiological measures can provide important information about the substrate of cognitive function in children, and most importantly, can give precise temporal information about ‘on‐line’ brain function. These measures can be readily used in infants and children, and we present some examples of their application to understanding cognitive development. The most widely used of these techniques for developmental research is the method of event‐related potentials (ERPs). In addition, the electroencephalogram (EEG) and the more rarely used invasive, intracranial investigations are also important to furthering our knowledge of how the brain–behaviour relations develop. The paper summarizes practical issues and presents some selected examples of experimental and clinical research.     

Electric source localization adds evidence for task-specific CNVs

This study was an attempt to replicate recent magnetoencephalographic (MEG) findings on human task-specific CNV sources (Basile et al., Electroencephalography and Clinical Neurophysiology 90, 1994, 157-165) by means of a spatio-temporal electric source localization method (Scherg and von Cramon, Electroencephalography and Clinical Neurophysiology 62, 1985, 32-44; Scherg and von Cramon, Electroencephalography and Clinical Neurophysiology 65, 1986, 344-360; Scherg and Berg, Brain Electric Source Analysis Handbook, Version 2). The previous MEG results showed CNV sources in the prefrontal cortex of the two hemispheres for two tasks used, namely visual pattern recognition and visual spatial recognition tasks. In the right hemisphere, the sources were more anterior and inferior for the spatial recognition task than for the pattern recognition task. In the present study we obtained CNVs in five subjects during two tasks identical to the MEG study. The elicited electric potentials were modeled with four spatio-temporal dipoles for each task, three of which accounted for the visual evoked response and one that accounted for the CNV. For all subjects the dipole explaining the CNV was always localized in the frontal region of the head, however, the dipole obtained during the visual spatial recognition task was more anterior than the one obtained during the pattern recognition task. Thus, task-specific CNV sources were again observed, although the stable model consisted of only one dipole located close to the midline instead of one dipole in each hemisphere. This was a major difference in the CNV sources between the previous MEG and the present electric source analysis results. We discuss the possible basis for the difference between the two methods used to study slow brain activity that is believed to originate from extended cortical patches.     

Magnetoencephalography in pediatric neuroimaging

Neural currents give rise to electroencephalogram (EEG) and magnetoencephalogram (MEG). MEG has selective sensitivity to tangential currents (from fissural cortex), and less distorted signals compared with EEG. A major goal of MEG is to determine the location and timing of cortical generators for event‐related responses, spontaneous brain oscillations or epileptiform activity. MEG provides a spatial accuracy of a few mm under optimal conditions, combined with an excellent submillisecond temporal resolution, which together enable spatiotemporal tracking of distributed neural activities, e.g. during cognitive tasks or epileptic discharges. While the present focus of pediatric MEG is on tailored epilepsy surgery, the complete noninvasiveness of MEG also provides unlimited possibilities to study the brain functions of healthy and developmentally deviant children.     

探究事件相关脑电/脑磁信号中的神经表征模式：基于分类解码和表征相似性分析的方法

探究不同心智活动下的神经表征差异, 是认知神经科学关注的核心问题之一。早期的脑电/脑磁分析方法主要关注组平均后的神经响应水平, 这要求在关注的时间进程上, 各个被试在相同刺激条件下事件相关电位/事件相关磁场的振幅大小和方向、以及地形图分布和极性均要有较高的一致性。近些年来, 研究者们将功能性磁共振成像研究中常用到的两种技术——机器学习中的分类算法(即基于分类的解码)和表征相似性分析——引入到了脑电/脑磁数据分析中。这两种新技术可以克服传统脑电/脑磁数据基于具体电压/磁感应强度波形平均分析的缺点, 具有在个体水平上探究神经表征编码的特点, 为人们探究大脑在不同时间进程上如何对特定的神经表征信息进行动态编码提供了新的思路。两种技术基于不同的方法学原理来抽提个体间一致的脑认知加工机制, 还为脑电/脑磁研究开展跨时域、跨任务、跨模态、跨群体比较不同认知过程中的表征差异提供了更多新颖的途径。我们首先通过与传统的脑电/脑磁分析方法进行比较, 系统性介绍了基于分类的解码和表征相似性分析的原理和操作流程, 之后对两种方法的应用场景进行了梳理, 并在最后对未来可供研究的方向提出了我们的见解。     

Magnetoencephalography and magnetic source imaging: technology overview and applications in psychiatric neuroimaging

Magnetoencephalography (MEG) is an electrophysiologic brain imaging technology that has been applied to the study of mental illness, particularly schizophrenia. Like electroencephalography, it provides excellent temporal resolution, and in combination with magnetic resonance imaging, can also provide good spatial resolution. Studies of the auditory system in schizophrenia using MEG have demonstrated an abnormality in functional cerebral asymmetry, in which persons with schizophrenia typically show reduced, or reversed, cerebral asymmetry compared with normal subjects. This abnormality is sex-specific; it is more pronounced in males with schizophrenia. These findings have not been demonstrated using other neuroimaging strategies. Thus, MEG appears to offer a unique and valuable contribution to psychiatric neuroimaging. Current research and clinical applications of MEG are limited, however, by the high cost of instrumentation. The cost of MEG systems should improve as more applications are developed, in schizophrenia as well as other neuropsychiatric conditions, and hospitals begin to invest in the technology.     

Mining event-related brain dynamics

This article provides a new, more comprehensive view of event-related brain dynamics founded on an information-based approach to modeling electroencephalographic (EEG) dynamics. Most EEG research focuses either on peaks 'evoked' in average event-related potentials (ERPs) or on changes 'induced' in the EEG power spectrum by experimental events. Although these measures are nearly complementary, they do not fully model the event-related dynamics in the data, and cannot isolate the signals of the contributing cortical areas. We propose that many ERPs and other EEG features are better viewed as time/frequency perturbations of underlying field potential processes. The new approach combines independent component analysis (ICA), time/frequency analysis, and trial-by-trial visualization that measures EEG source dynamics without requiring an explicit head model.     

Changes of chaoticness in spontaneous EEG/MEG

Depending on the task being investigated in EEG/MEG experiments, the corresponding signal is more or less ordered. The question still open is how can one detect the changes of this order while the tasks performed by the brain vary continuously. By applying a static measurement of the fractal dimension or Lyapunov exponent, different brain states could be characterized. However, transitions between different states may not be detected, especially if the moments of transitions are not strictly defined. Here we show how the dynamical measure based on the largest local Lyapunov exponent can be applied for the detection of the changes of the chaoticity of the brain processes measured in EEG and MEG experiments. In this article, we demonstrate an algorithm for computation of chaoticity that is especially useful for nonstationary signals. Moreover, we introduce the idea that chaoticity is able to detect, locally in time, critical jumps (phase-transition-like phenomena) in the human brain, as well as the information flow through the cortex.     

Perspectives on health effects of electric and magnetic fields

Some epidemiological studies have fostered concern about cancers caused by electric and magnetic fields associated with distribution and use of electric power. At present, there is no scientific consensus as to which factors, the electric field and/or magnetic field, are biologically important. Similarly, there is no clear indication whether higher field levels are of greater risk than lower level fields. The complex scientific issues attending health effects of power-frequency electric and magnetic fields would be most effectively resolved through interdisciplinary research involving investigators from biological, medical and engineering research communities. A critical need, at present, is a significant increase in federal funding for research on interaction mechanisms and animal studies, while maintaining efforts in epidemiology but with greater emphasis on confounding factors and known cancer-causing agents.     

Designing EEG Neurofeedback Procedures to Enhance Open-ended versus Closed-ended Creative Potentials

Recent empirical evidence demonstrated that open-ended creativity (which refers to creativity measures that require various and numerous responses, such as divergent thinking) correlated with alpha brain wave activation, whereas closed-ended creativity (which refers to creativity measures that ask for one final correct answer, such as insight problem solving) was related to larger variability in electroencephalogram (EEG) differences between alpha and beta waves. This study designed two EEG neurofeedback procedures to examine their training effects on open- versus closed-ended creative potentials. In the alpha-enhancement condition, participants were reinforced to elevate only their alpha frequencies by auditory feedback for 10 sessions. In the alpha-transformation condition, enhancement and suppression of the signal tone (and hence, the appearance and disappearance of alpha waves) were both practiced. Pre- and posttest comparisons indicated that, compared to the active contrast condition, the alpha-enhancement practice improved only open-ended creativity performance. The alpha-transformation training enhanced closed-ended creativity performance, which was first demonstrated in the literature, and simultaneously facilitated open-ended creativity performances. In addition, changes in brain wave patterns by training positively correlated with change in predicted creativity performances. All of these results were of medium to large effect sizes. The effectiveness of these EEG neurofeedback procedures for creativity training was implied and discussed.     

工作记忆的神经振荡调控：基于神经振荡夹带现象

工作记忆的神经振荡机制研究是当前记忆领域的研究热点之一。那么, 神经振荡仅仅是工作记忆过程的伴随现象, 还是直接参与并调控了工作记忆的加工过程?已有研究发现, 大脑内部的神经振荡活动在外界节律性刺激的驱动下, 逐步与外界刺激节律相位同步化, 这一现象被称为“神经振荡夹带”。重复经颅磁刺激(repetitive Transcranial Magnetic Stimulation, rTMS)和经颅交流电刺激(transcranial Alternating Current Stimulation, tACS)干预研究基于此现象, 对大脑局部脑区施加节律性磁、电刺激, 进而调控工作记忆过程中特定频段的神经振荡活动、跨频段的神经振荡耦合或跨脑区的神经振荡相位同步, 为神经振荡参与工作记忆加工提供较为直接的因果证据。未来研究需考虑从脑网络的角度出发, 调控多个脑区之间的神经振荡活动, 进一步考察神经振荡对工作记忆的影响。此外, 还需注意探索和优化rTMS/tACS调控工作记忆的刺激方案, 并辅以客观的脑电记录, 提高该类研究的有效性和可重复性, 最终达到提高工作记忆能力的目的。     

A neurocognitive approach to the study of private speech

The paper presents the current state of the art of research identifying the neurophysiological and neuroanatomical substrates of private speech, both in typical and clinical (or atypical) populations. First, it briefly describes the evolution of private speech research, which goes from classic traditions as the naturalistic and referential paradigms to the neurocognitive approach. An overview of the neurophysiological (e.g., event-related potentials or ERPs) and neuroimaging techniques (e.g., functional magnetic resonance imaging or fMRI) is also presented. The next three sections review empirical works about the neurocognitive basis of private speech, across three groups of techniques: ERPs; fMRI/MRI; and other neuroimaging techniques (positron emission tomography [PET], magnetoencephalogram [MEG], and repetitive transcranial magnetic stimulation [rTMS]). Such neurocognitive research analyzes the neural activity of individuals during a variety of task settings, including spontaneous and instructed overt and inner private speech use, subvocal verbalizations, and silent and overt reading. The fifth section focuses on electrophysiological and neuroimaging studies of private speech in atypical populations, for example: schizophrenia, pure alexia, hearing impairment, blindness, social phobia, alexithymia, Parkinson, and multiple sclerosis. The neurocognitive study of the various forms of private speech appears to be very promising in the understanding of these pathologies. Lastly, the advances and new challenges in the field are discussed.     

Functional Brain Connectivity Using fMRI in Aging and Alzheimer’s Disease

Normal aging and Alzheimer’s disease (AD) cause profound changes in the brain’s structure and function. AD in particular is accompanied by widespread cortical neuronal loss, and loss of connections between brain systems. This degeneration of neural pathways disrupts the functional coherence of brain activation. Recent innovations in brain imaging have detected characteristic disruptions in functional networks. Here we review studies examining changes in functional connectivity, measured through fMRI (functional magnetic resonance imaging), starting with healthy aging and then Alzheimer’s disease. We cover studies that employ the three primary methods to analyze functional connectivity—seed-based, ICA (independent components analysis), and graph theory. At the end we include a brief discussion of other methodologies, such as EEG (electroencephalography), MEG (magnetoencephalography), and PET (positron emission tomography). We also describe multi-modal studies that combine rsfMRI (resting state fMRI) with PET imaging, as well as studies examining the effects of medications. Overall, connectivity and network integrity appear to decrease in healthy aging, but this decrease is accelerated in AD, with specific systems hit hardest, such as the default mode network (DMN). Functional connectivity is a relatively new topic of research, but it holds great promise in revealing how brain network dynamics change across the lifespan and in disease.     

Magnetic stimulation studies of visual cognition

The panoply of non-invasive techniques for brain imaging is responsible for much of the current excitement in cognitive neuroscience; sensory, perceptual and cognitive behaviour can now be correlated with cerebral blood flow as assessed by functional imaging, the electrical fields generated by populations of neurons or changes in magnetic fields created by electrical activity. Correlations between localized brain activity and behaviour, however, do not of themselves establish that any brain area is necessary for a particular task; necessity is the domain of the lesion technique. Transcranial magnetic stimulation (TMS) is a technique that can be used non-invasively to produce reversible functional disruption and has already been used to investigate visual detection, discrimination, attention and plasticity. The power of TMS as a `lesion' technique lies in the opportunity to combine reversible disruption with high degrees of spatial and temporal resolution. In this review we trace some of the major developments in the use of TMS as a technique for the investigation of visual cognition.     

Event‐related oscillations (EROs) and event‐related potentials (ERPs) comparison in facial expression recognition

The study aims to explore the significance of event‐related potentials (ERPs) and event‐related brain oscillations (EROs) (delta, theta, alpha, beta, gamma power) in response to emotional (fear, happiness, sadness) when compared with neutral faces during 180–250 post‐stimulus time interval. The ERP results demonstrated that the emotional face elicited a negative peak at approximately 230 ms (N2). Moreover, EEG measures showed that motivational significance of face (emotional vs. neutral) could modulate the amplitude of EROs, but only for some frequency bands (i.e. theta and gamma bands). In a second phase, we considered the resemblance of the two EEG measures by a regression analysis. It revealed that theta and gamma oscillations mainly effect as oscillation activity at the N2 latency. Finally, a posterior increased power of theta was found for emotional faces.     

Frontal cortex electrophysiology in reward- and punishment-related feedback processing during advice-guided decision making: An interleaved EEG-DC stimulation study

During decision making, individuals are prone to rely on external cues such as expert advice when the outcome is not known. However, the electrophysiological correlates associated with outcome uncertainty and the use of expert advice are not completely understood. The feedback-related negativity (FRN), P3a, and P3b are event-related brain potentials (ERPs) linked to dissociable stages of feedback and attentional processing during decision making. Even though these ERPs are influenced by both reward- and punishment-related feedback, it remains unclear how extrinsic information during uncertainty modulates these brain potentials. In this study, the effects of advice cues on decision making were investigated in two separate experiments. In the first experiment, electroencephalography (EEG) was recorded in healthy volunteers during a decision-making task in which the participants received reward or punishment feedback preceded by novice, amateur, or expert advice. The results showed that the P3a component was significantly influenced by the subjective predictive value of an advice cue, whereas the FRN and P3b were unaffected by the advice cues. In the second, sham-controlled experiment, cathodal transcranial direct current stimulation (ctDCS) was administered in conjunction with EEG in order to explore the direct contributions of the frontal cortex to these brain potentials. Results showed no significant change in either advice-following behavior or decision times. However, ctDCS did decrease FRN amplitudes as compared to sham, with no effect on the P3a or P3b. Together, these findings suggest that advice information may act primarily on attention allocation during feedback processing, whereas the electrophysiological correlates of the detection and updating of internal prediction models are not affected.