Comparison of magneto-and electroencephalographic techniques in event-related response research—a brief survey

Event-related brain potentials are widely used in psychophysiological and neurophysiological research. Recently it has become possible to record weak magnetic fields associated with the electric events of the human brain. In this short survey the magnetoencephalo-graphic (MEG) techniques are compared with the conventional electric measures. MEG and EEG are sensitive to current sources of different orientation. Extracerebral tissues smear and damp the electric potentials but they do not have any significant effect on the magnetic fields. EEG measures potential differences whereas the actual current paths determine the magnetic fields measured outside the skull. In general MEG provides better spatial resolution than the electric recordings, as far as the cortical sources are concerned. It is concluded that EEG and MEG are complementary noninvasive techniques in brain research. As an example slow EEG and MEG shifts preceding voluntary foot movements are compared.     

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。     

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.     

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.     

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.     

A decade of infant neuroimaging research: What have we learned and where are we going?

The past decade has seen the emergence of neuroimaging studies of infant populations. Incorporating imaging has resulted in invaluable insights about neurodevelopment at the start of life. However, little has been enquired of the experimental specifications and study characteristics of typical findings. This review systematically screened empirical studies that used electroencephalography (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) on infants (max. age of 24 months). From more than 21,000 publications, a total of 710 records were included for analyses. With the exception of EEG studies, infant studies with MEG, fNIRS, and fMRI were most often conducted around birth and at 12 months. The vast majority of infant studies came from North America, with very few studies conducted in Africa, certain parts of South America, and Southeast Asia. Finally, longitudinal neuroimaging studies were inclined to adopt EEG, followed by fMRI, fNIRS, and MEG. These results show that there is compelling need for studies with larger sample sizes, studies investigating a broader range of infant developmental periods, and studies from under- and less-developed regions in the world. Addressing these shortcomings in the future will provide a more representative and accurate understanding of neurodevelopment in infancy.     

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。     

Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD

Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group’s data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca’s area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4–8 Hz) during encoding and in the alpha band (9–12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.     

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.     

Different Brain Wave Patterns and Cortical Control Abilities in Relation to Different Creative Potentials

Contemporary understanding of brain functions provides a way to probe into the mystery of creativity. However, the prior evidence regarding the relationship between creativity and brain wave patterns reveals inconsistent conclusions. One possible reason might be that the means of selecting creative individuals in the past has varied in each study. By distinguishing creative potential as open-ended versus closed-ended based on theoretical views, this study examined different brain wave patterns and cortical control abilities in relation to different creative potentials by using electroencephalogram (EEG) biofeedback equipment. The results demonstrated that participants’ performance on the open-ended creative problem was positively related to EEG alpha frequencies, whereas performance on the closed-ended creative problem was related to larger variability in EEG dynamics between alpha and beta waves when performing either open-ended or closed-ended creativity tasks. Further, better control in changing states of brain wave activities according to the EEG biofeedback signals could predict closed-ended creativity performance. Open-ended creativity was related only to the enhancement of alpha signals. These results help clarify previous inconsistent findings, reveal different natures of distinct creativities, and further suggest ways to improve different aspects of creativity with modified biofeedback procedures.     

Reduced electroencephalographic coherence asymmetry in the Chernobyl accident survivors

An electroencephalograph (EEG) study was carried out from 1990 to 2006, using power spectra, averaged coherence, and integral EEG coherence asymmetry coefficients to compare 189 clean-up workers of the Chernobyl accident with 63 age-matched healthy controls. Most of the Chernobyl workers showed three abnormal EEG patterns, as indicated by EEG power mapping. The higher power, most prominent in slow alpha and theta bands, or in fast alpha frequencies, were observed in persons 3-5 years after the clean-up works (the early stage). The lower EEG power in alpha band was found in Chernobyl workers 10 or more years after the accident (the late stage). EEG coherence analysis revealed the existence of two stages in EEG alterations following the Chernobyl clean-up. In the early stage, an increase of EEG coherence in the central brain areas was observed, whereas at the later stage, a decrease of EEG coherence, most prominent in the frontal brain areas, and reduced brain asymmetry prevailed. These results allow us to propose that the described EEG signs may be a reflection of radiation-induced brain dysfunction at the late period after the Chernobyl clean-up and were similar to the EEG markers of brain ageing. The results, in comparison to data of the literature, provide additional support to the premature brain ageing hypothesis in Chernobyl survivors as a result of the radiation brain damage after-effect.     

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.     

Timing of human cortical functions during cognition: role of MEG

Understanding of sensory and cognitive brain processes requires information about activation timing within and between different brain sites. Such data can be obtained by magnetoencephalography (MEG) that tracks cortical activation sequences with a millisecond temporal accuracy. MEG is gaining a well-established role in human neuroscience, complementing with its excellent temporal resolution the spatially more focused brain imaging methods. As examples of MEG's role in cognitive neuroscience, we discuss time windows related to cortical processing of sensory and multisensory stimuli, effects of the subject's own voice on the activity of their auditory cortex, timing of brain activation in reading, and cortical dynamics of the human mirror-neuron system activated when the subject views another person's movements.     

Neuroplastic Changes Following Social Cognition Training in Schizophrenia: A Systematic Review

Social cognitive impairment is a key feature of schizophrenia and social cognition training (SCT) is a promising tool to address these deficits. Neurobiological dysfunction in schizophrenia has been widely researched, but neuronal changes induced by SCT have been scarcely explored. This review aims to assess the neuroplastic effects of SCT in patients with schizophrenia spectrum disorders. PubMed and Web of Science databases were searched for clinical trials testing the effects of SCT in functional and structural brain measurements of adult patients with schizophrenia or schizoaffective disorders. A total of 11 studies were included: five used fMRI, two used EEG and ERP, one used ERP only, two used MEG and one study used MRI. Data extracting and processing regarding sociodemographic and clinical variables, intervention characteristics, neuroimaging procedures, neuroplastic findings, effect sizes and study quality criteria was completed by two raters. Results indicate a wide range of structural and functional changes in numerous regions and circuits of the social brain, including early perceptual areas, the limbic system and prefrontal regions. Despite the small number of trials currently available, evidence suggests that SCT is associated with neuroplastic changes in the social brain and concomitant improvements in social cognitive performance. There is a lack of extensive knowledge about the neural mechanisms that underlie social cognitive enhancement after treatment, but the reported findings may shed light on the neural substrates of social cognitive impairment in schizophrenia and how improved treatment procedures can be developed and applied.     

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.     

Neurofeedback and the Brain

Neurofeedback is an emerging neuroscience-based clinical application, and understanding the underlying principles of neurofeedback allows the therapist to provide referrals or treatment, and provides clients with a framework for understanding the process. The brain's electrical patterns are a form of behavior, modifiable through “operant conditioning,” with the excessive brain frequencies reduced, and those with a deficit are increased. The learning curve for EEG has been described (Hardt, 1975).     

An inexpensive circuit for beta,alpha, theta,or delta EEG biofeedback

An inexpensive circuit is described for EEG biofeedback or measurement. The circuit is designed to interface easily with most basic EEG machines. It taps the output from a single recording channel of the basic EEG instrument and provides the following for each EEG band (beta, alpha, theta, and delta): (a) very selective bandpass discrimination, (b) variable center frequency, (c) variable threshold at which feedback will be provided, or the measurement made, and (d) use with any biofeedback stimulus or measurement device that one wishes to switch contingent with S’s EEG rhythms.     

Composition of brain oscillations and their functions in the maintenance of auditory,visual and audio–visual speech percepts: an exploratory study

In the present exploratory study based on 7 subjects, we examined the composition of magnetoencephalographic (MEG) brain oscillations induced by the presentation of an auditory, visual, and audio-visual stimulus (a talking face) using an oddball paradigm. The composition of brain oscillations were assessed here by analyzing the probability-classification of short-term MEG spectral patterns. The probability index for particular brain oscillations being elicited was dependent on the type and the modality of the sensory percept. The maintenance of the integrated audio-visual percept was accompanied by the unique composition of distributed brain oscillations typical of auditory and visual modality, and the contribution of brain oscillations characteristic for visual modality was dominant. Oscillations around 20 Hz were characteristic for the maintenance of integrated audio-visual percept. Identifying the actual composition of brain oscillations allowed us (1) to distinguish two subjectively/consciously identical mental percepts, and (2) to characterize the types of brain functions involved in the maintenance of the multi-sensory percept.     

Effects of unilateral hippocampus-amygdala-partial temporal lobe resection on auditory EEG/MEG responses: a case study

Auditory orienting and discrimination were studied with combined multi-channel EEG and MEG recordings in a patient with unilateral amygdala-hippocampus-partial temporal lobe resection of the right hemisphere. The results revealed abnormalities of habituation in alerting- and orienting-related responses, and discrimination-related responses, elicited by auditory stimulation contralateral to the resected cerebral hemisphere. These results give support to the notions about the role of the amygdala and hippocampus in alerting and orienting, respectively, and of the temporal cortex in auditory discrimination.