Where Does EEG Come From and What Does It Mean?

脑电图 神经科学 心理学 认知心理学
作者
Michael X Cohen
出处
期刊:Trends in Neurosciences [Elsevier BV]
卷期号:40 (4): 208-218 被引量:555
标识
DOI:10.1016/j.tins.2017.02.004
摘要

EEG is one of the most important non-invasive brain imaging tools in neuroscience and in the clinic, but surprisingly little is known about how activity in neural circuits produces the various EEG features linked to cognition. The ‘standard model’ of EEG states that simultaneous postsynaptic potentials of neural populations produces EEG, but this explains only the existence of EEG, not the meaning of the content of the EEG signal. No ‘grand unified theories’ are presented, because there is unlikely to be a single ‘neural correlate of EEG’. More experiments, analyses, and models that span multiple spatial scales are necessary. Recent advances in neuroscience knowledge and technologies make this an ideal time for new discoveries about the origins and significances of EEG. This research will benefit fundamental neuroscience, cognitive neuroscience, clinical diagnoses, and data analysis development. Electroencephalography (EEG) has been instrumental in making discoveries about cognition, brain function, and dysfunction. However, where do EEG signals come from and what do they mean? The purpose of this paper is to argue that we know shockingly little about the answer to this question, to highlight what we do know, how important the answers are, and how modern neuroscience technologies that allow us to measure and manipulate neural circuits with high spatiotemporal accuracy might finally bring us some answers. Neural oscillations are perhaps the best feature of EEG to use as anchors because oscillations are observed and are studied at multiple spatiotemporal scales of the brain, in multiple species, and are widely implicated in cognition and in neural computations. Electroencephalography (EEG) has been instrumental in making discoveries about cognition, brain function, and dysfunction. However, where do EEG signals come from and what do they mean? The purpose of this paper is to argue that we know shockingly little about the answer to this question, to highlight what we do know, how important the answers are, and how modern neuroscience technologies that allow us to measure and manipulate neural circuits with high spatiotemporal accuracy might finally bring us some answers. Neural oscillations are perhaps the best feature of EEG to use as anchors because oscillations are observed and are studied at multiple spatiotemporal scales of the brain, in multiple species, and are widely implicated in cognition and in neural computations. the measurement of brain electrical fields via electrodes (which act as small antennas) placed on the head. The electrical fields are the result of electrochemical signals passing from one neuron to the next. When billions of these tiny signals are passed simultaneously in spatially extended and geometrically aligned neural populations, the electrical fields sum and become powerful enough to be measured from outside the head. EEG is often attributed to Hans Berger, who was trying to discover a ‘mechanism’ for extra-sensory phenomena. It was known since the late 19th century that the brain produces electrical fields, and that these fields exhibit oscillations; Berger’s great contributions included demonstrating that these fields could be measured in humans from outside the brain, and demonstrating that neural oscillations were related to cognitive phenomena such as sensory processing and solving mathematical equations. this term is used here as shorthand for an idiosyncratic spatial/temporal/spectral pattern that is associated with a particular sensory or cognitive process, similar to a ‘fingerprint’ [17]. Examples include midfrontal theta and response conflict monitoring, and posterior alpha power and spatial attention. brain function can be measured at many spatial scales, ranging from individual synapses (∼10 nm) to whole-brain networks (∼10 cm). Although neuroscience research in general spans all these spatial scales, there is little understanding of how the dynamics are related across spatial scales. Is understanding multiscale dynamics important for understanding brain function? No-one really knows, but multiscale dynamics are hypothesized to be necessary for the complexity required for higher cognitive functioning including consciousness [93]. Studying multiscale interactions presents conceptual, mathematical, and technological challenges, and scientists tend to like challenges. a microcircuit refers to a spatial scale of brain anatomical/functional organization that is larger than a single neuron but smaller than an fMRI voxel. Microcircuits can take several forms; the term ‘microcircuit’ often connotes a bundling of dozens or hundreds of cells of various classes that are more densely interconnected than they are connected to neighboring microcircuits, and that work together towards a common function [57]. Orientation-tuned columns in primate V1 is an example of a microcircuit. the EEG activity of a living brain is not flat, nor is it random. Instead, EEG is dominated by rhythms that are grouped into a small number of characteristic frequencies. These rhythms are driven by fluctuations in excitability of populations of neurons, and have complex spatiotemporal patterns that vary in amplitude, timing, and frequency. These variations are known as nonstationarities, and the general goal of cognitive electrophysiology is to understand how and why these nonstationarities are related to various cognitive and perceptual processes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研2121完成签到,获得积分10
刚刚
城南花已开完成签到,获得积分20
1秒前
我是老大应助周em12_采纳,获得10
2秒前
terence完成签到,获得积分0
2秒前
suger完成签到,获得积分10
3秒前
科研2121发布了新的文献求助10
4秒前
Stardust发布了新的文献求助10
4秒前
浮浮世世完成签到,获得积分10
4秒前
5秒前
完美世界应助非一采纳,获得10
5秒前
果果完成签到,获得积分10
9秒前
万能图书馆应助好滴捏采纳,获得10
9秒前
9秒前
9秒前
科目三应助拼搏一曲采纳,获得10
9秒前
量子星尘发布了新的文献求助10
11秒前
12秒前
852应助lemonkane采纳,获得20
12秒前
思源应助linn采纳,获得10
13秒前
lilila666发布了新的文献求助10
13秒前
16秒前
张钦奎发布了新的文献求助10
16秒前
Jem完成签到,获得积分10
16秒前
悦悦应助天真的冬瓜采纳,获得10
17秒前
猪猪侠完成签到,获得积分10
19秒前
20秒前
zyj完成签到,获得积分10
21秒前
21秒前
啦啦啦发布了新的文献求助10
22秒前
23秒前
23秒前
天真的冬瓜完成签到,获得积分10
24秒前
26秒前
27秒前
啦啦啦完成签到,获得积分10
27秒前
CodeCraft应助一方通行采纳,获得10
27秒前
Stardust发布了新的文献求助10
27秒前
传奇3应助summer采纳,获得30
28秒前
机灵的忆梅完成签到 ,获得积分10
29秒前
上官若男应助科研2121采纳,获得10
30秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989378
求助须知:如何正确求助?哪些是违规求助? 3531442
关于积分的说明 11254002
捐赠科研通 3270126
什么是DOI,文献DOI怎么找? 1804887
邀请新用户注册赠送积分活动 882087
科研通“疑难数据库(出版商)”最低求助积分说明 809173