事件相关脑电位与人类行为活动

事件相关脑电位(Event Related potential,缩写为ERp)不同于自发脑电位(EEG),前者代表与刺激和反应的出现有一定关系的神经活动。由于在头皮外记录到的ERP信号一般不高于10微伏,所以在一般情况下它很容易被自发的脑电活动噪音(其电位可达50微伏以上)所掩蔽。六十年代以来采用了改进信噪比的技术,使ERP的研究有了长足的进步。     

6-12岁儿童额叶自发脑电频谱相干的特点

EEG频谱相干分析发现额叶发育在童年中期存在可能的加速期。针对这一问题,本研究通过记录75名6至12岁正常儿童静坐和闭目状态下的自发脑电,分析δ、θ、α和β基本脑电频段下31对电极相干的变化情况,系统探索了该年龄段儿童额叶自发脑电频谱相干的变化特点,结果发现:θ波活动普遍强于α和β波活动;6至12岁儿童额叶内、额叶与其他脑叶间相干在整体上表现为随年龄增长而增加的趋势;额叶内、额叶与其他脑叶间相干在各频段均表现为7岁、11岁突增,10岁、12岁表现为高峰。上述结果支持6至12岁儿童额叶发育存在加速变化的结论。     

自我信息的反应抑制优势：来自神经振荡的证据

为探明个体对自我信息的反应抑制神经机制,记录了被试在完成面孔识别的停止信号任务时的脑电信号。神经振荡结果显示,反应任务中,加工自我面孔引发了更大的同步化δ节律和去同步化β节律;停止任务中,自我面孔引发了更大的去同步化β节律,特别在大脑前额区和中线上。表明,自我信息的反应抑制优势发生在抑制控制阶段,在于增强的β节律的去同步化促进了运动准备,提高了后续的动作抑制的速度。     

脑机增强：公平问题及其反思

脑机接口增强性应用引起了人们的广泛热议。相比以治疗为目的的应用,当脑机接口用于增强健全人的身体和心理等功能时,所带来的问题可能更多、更复杂,容易带来公平上的问题和挑战。面对这些问题和挑战,需要辩证地分析,客观、理性地看待。从根本上讲,导致这些不公平不在技术本身。因此,需要深刻反思脑机增强公平问题产生根源的同时,也需要从两方面予以应对,一是重视脑机增强的公平风险,二是明确脑机增强的使用范围,避免滥用。     

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。     

ERP的神经机制：诱发模型还是相位重排模型?

ERP的神经机制问题一直存在争议。诱发模型认为, ERP产生于触发事件诱发的确定性响应电位, 该诱发电位与背景脑电振荡相互独立。相位重排模型认为, 触发事件并不会诱发出一个独立于脑电信号的诱发电位, ERP产生于背景脑电节律振荡的部分相位重排。已有研究提供了各种实验证据以支持诱发模型或/和相位重排模型, 同时也引发了相关学者的诸多质疑。实验记录方式、数据处理及分析方法等方面的提高有利于进一步澄清ERP的神经机制。     

事件相关振荡与振荡脑网络

事件相关振荡是伴随认知、情感和行为过程的脑电磁振荡活动,观察到其各类调频、调幅和调相现象,这种介观和宏观尺度上大量神经元的集体活动与微观尺度上神经元平均发放率和发放定时相互影响,共同参与神经信息的编码、表征、通讯和调控。动态细胞集群假说认为大脑认知功能是神经网络通过同步振荡相互作用的结果,在基于振荡的大脑理论指引下,多尺度、跨脑区和跨频率事件相关振荡研究为揭开振荡脑网络的工作原理带来了希望     

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。     

脑电神经反馈：一种前景广阔的注意力训练方法

脑电神经反馈(EEG-NF)是一种注意力训练中的热门方法因其安全无创、无副作用、易于联合应用等优点,受到越来越广泛的关注,在注意缺陷障碍(ADHD)的治疗等方面表现优异。然而,目前这种方法在注意力训练中的应用还比较局限。抱着对脑电神经反馈广阔前景的预期,本文对脑电神经反馈训练中出现的重点问题进行了总结,描绘了这种方法未来的前景和改进方向,以期在未来更好的应用这种技术。     

触觉-视觉交叉模式工作记忆的研究

目的:探讨触觉-视觉交叉模式工作记忆的大脑神经活动机理.方法:训练11个正常受试者学习交叉模式工作记忆任务,利用Neuroscan EEG系统记录脑电活动,对脑电数据求源分析后,着重考察事件相关脑电成分所处的大脑空间位置.结果发现:在延时过程中的3个主要的脑电成分N40,LPC和LNC的神经活动源分别处于大脑的右侧顶叶,中间后顶叶和前额叶.这提示了交叉模式工作记忆中相继的三个神经认知功能:感知,触觉一视觉模式阃的信息交互,和工作记忆的维持.     

Direct brain communication: neuroelectric and metabolic approaches at Tübingen

The brain–computer interface (BCI) provides users with the possibility of sending messages and commands to the external world without using their muscles, thus enabling communication to occur independent of movement. Such a possibility is of utmost importance for paralyzed patients who may otherwise lose their ability to communicate. Enhanced methodology and the development of faster computers have substantially improved applications and offer new possibilities in this field. To date, there have been over 20 BCI research groups working on different approaches. In this paper, we review our studies of BCI based on electric and metabolic activity of the brain.     

Brain-computer interface research comes of age: traditional assumptions meet emerging realities

Brain-computer interfaces (BCIs) could provide important new communication and control options for people with severe motor disabilities. Most BCI research to date has been based on 4 assumptions that: (a) intended actions are fully represented in the cerebral cortex; (b) neuronal action potentials can provide the best picture of an intended action; (c) the best BCI is one that records action potentials and decodes them; and (d) ongoing mutual adaptation by the BCI user and the BCI system is not very important. In reality, none of these assumptions is presently defensible. Intended actions are the products of many areas, from the cortex to the spinal cord, and the contributions of each area change continually as the CNS adapts to optimize performance. BCIs must track and guide these adaptations if they are to achieve and maintain good performance. Furthermore, it is not yet clear which category of brain signals will prove most effective for BCI applications. In human studies to date, low-resolution electroencephalography-based BCIs perform as well as high-resolution cortical neuron-based BCIs. In sum, BCIs allow their users to develop new skills in which the users control brain signals rather than muscles. Thus, the central task of BCI research is to determine which brain signals users can best control, to maximize that control, and to translate it accurately and reliably into actions that accomplish the users' intentions.     

Informed Consent in Implantable BCI Research: Identifying Risks and Exploring Meaning

Implantable brain–computer interface (BCI) technology is an expanding area of engineering research now moving into clinical application. Ensuring meaningful informed consent in implantable BCI research is an ethical imperative. The emerging and rapidly evolving nature of implantable BCI research makes identification of risks, a critical component of informed consent, a challenge. In this paper, 6 core risk domains relevant to implantable BCI research are identified—short and long term safety, cognitive and communicative impairment, inappropriate expectations, involuntariness, affective impairment, and privacy and security. Work in deep brain stimulation provides a useful starting point for understanding this core set of risks in implantable BCI. Three further risk domains—risks pertaining to identity, agency, and stigma—are identified. These risks are not typically part of formalized consent processes. It is important as informed consent practices are further developed for implantable BCI research that attention be paid not just to disclosing core research risks but exploring the meaning of BCI research with potential participants.     

Design and operation of an EEG-based brain-computer interface with digital signal processing technology

We are developing an electroencephalographic (EEG)-based brain-computer interface (BCI) system that could provide an alternative communication channel for those who are totally paralyzed or have other severe motor impairments. The essential features of this system are as follows: (1) EEG analysis in real time, (2) real-time conversion of that analysis into device control, and (3) appropriate adaptation to the EEG of each user. Digital signal processing technology provides the speed and flexibility needed to satisfy these requirements. It also supports evaluation of alternative analysis and control algorithms, and thereby facilitates further BCI development.     

Embodiment and Estrangement: Results from a First-in-Human “Intelligent BCI” Trial

While new generations of implantable brain computer interface (BCI) devices are being developed, evidence in the literature about their impact on the patient experience is lagging. In this article, we address this knowledge gap by analysing data from the first-in-human clinical trial to study patients with implanted BCI advisory devices. We explored perceptions of self-change across six patients who volunteered to be implanted with artificially intelligent BCI devices. We used qualitative methodological tools grounded in phenomenology to conduct in-depth, semi-structured interviews. Results show that, on the one hand, BCIs can positively increase a sense of the self and control; on the other hand, they can induce radical distress, feelings of loss of control, and a rupture of patient identity. We conclude by offering suggestions for the proactive creation of preparedness protocols specific to intelligent—predictive and advisory—BCI technologies essential to prevent potential iatrogenic harms.

     

A validation and short form of the Basic Character Inventory

The Basic Character Inventory (BCI) contains 136 items, 17 lower-order personality factors and three higher-order personality factors derived from psychoanalytic theory: Oral, Obsessive Compulsion, and Hysteria. Previous research that investigated the BCI's psychometric properties examined small, special populations and did not use modern statistical methods to validate the BCI. The present study validates the BCI via confirmatory factor analyses using a large sample of 6,285 Norwegian nursing and teaching students. Reliability, convergent validity, and divergent validity of the BCI were also assessed. Results indicated general support for the original BCI factor structure in a reduced form of the BCI that possesses strong reliability and validity, and is suitable for use in time-limited measurement settings.     

Changing the P300 brain computer interface.

Brain-computer interfaces (BCIs) are now feasible for use as an alternative control option for those with severe motor impairments. The P300 component of the evoked potential has proven useful as a control signal. Individuals do not need to be trained to produce the signal, and it is fairly stable and has a large evoked potential. Even with recent signal classification advances, on-line experiments with P300-based BCIs remain far from perfect. We present two potential methods for improving control accuracy. Experimental results in an evoked potential BCI, used to control items in a virtual apartment, show a reduced response exists when items are accidentally controlled. The presence of a P300-like signal in response to goal items means that it can be used for automatic error correction. Preliminary results from an interface experiment using three different button configurations for a yes/no BCI task show that the configuration of buttons may affect on-line signal classification. These results will be discussed in light of the special considerations needed when working with an amyotrophic lateral sclerosis (ALS) patient.     

Alcohol Counseling in Hospital Trauma: Examining Two Brief Interventions

Hospital trauma centers intervene with patients who incur alcohol‐related injuries. This prospective study, using professional counselors and trainees, investigated brief counseling interventions (BCIs). Participants were randomized to either a conventional BCI examining quantity and frequency of drinks or a personalized BCI exploring overintoxication. No statistically significant difference between risky drinkers randomized to either intervention in a hospital trauma center was observed. Findings indicate that a personalized BCI may be an alternative to a quantitative BCI in reducing risky alcohol consumption.     

A re-evaluation of the psychometric properties of the Basic Character Inventory

The aim of this study was to re-evaluate the psychometric properties of the Basic Character Inventory (BCI). In a rather large sample of 503 subjects (323 women and 180 men, 88 non-psychotic psychiatric inpatients and 415 non-patients) factor analysis resulted in three factors with personality traits almost identical with the BCI Oral, Obsessive and Hysterical scales. BCI seems to be a fruitful and reliable assessment instrument for personality traits and character types as outlined in psychoanalytic theory. However, some of the trait subscales ought to be scrutinized in future psychometric re-evaluative studies of BCI on new, large samples. Another factor analysis showed that the BCI Oral scale, together with all the ten subscales of the psychiatric Symptom Check-list 90 (SCL-90), loaded on the first factor, and the BCI Obsessive and Hysterical scales loaded on the second factor, but with different signs. Orality seems to be related to psychopathology.     

Psychological variables in the control of brain-computer interfaces

BCI (Brain-Computer Interface) is a system that allows interaction between the human brain and a computer. It is based on analyzing electroencephalographic signals (EEG) and processing them to generate control commands. The study analyzed the possible influence of psychological variables, such as the imaginative kinesthetic capacity and anxiety, in relation to performance in a BCI. All participants (4 male and 19 female students) completed the questionnaires and carried out a session of BCI to control their EEG signals in a virtual setting of a car along a straight road. The group was divided into two subgroups according to their EEG signals or differential responses obtained in the left-right discrimination. Study results showed no significant differences in cognitive variables of imagination or in anxiety. By comparing the degree of participants' BCI control, a new quantitative parameter for comparing performances and making decisions in signal processing was found. The findings, the ongoing research process to refine the control of a BCI, and the interaction of psychological and computer procedures are discussed.