Opinion
Where Does EEG Come From and What Does It Mean?

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Trends

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.

Section snippets

What Is the Answer to the Title Question?

When the question in the title of this paper is posed to colleagues, textbooks, or the Internet, the answers often involve some combination of a description of Maxwell’s equations regarding volume conduction of electrical potentials and mathematical descriptions of anatomical localization algorithms 1, 2. The assumption behind this answer is that understanding the significance of EEG requires solving the ill-posed inverse problem: given an observed topographical distribution of voltage values,

The Ultimate but Ultimately Unattainable Goal: One-to-One Mapping between EEG Feature and Microcircuit Configuration

EEG could be a much more powerful and insightful brain measurement tool if only we could identify one-to-one mappings between EEG feature and neural microcircuit configuration, as in Figure 1C. In truth, the relationship between EEG feature and microcircuit configuration is likely to be at best ‘few-to-some’, meaning that a small number of EEG features may correspond to a larger (but hopefully not very large) number of microcircuit configurations. In part, this is necessarily true because EEG

EEG Oscillations Are an Excellent Link to Neurophysiology

Neural oscillations are the most prominent feature of EEG data, and countless studies over many decades have demonstrated that perceptual, cognitive, motor, and emotional processes are tightly linked with specific patterns of oscillations [17]. Oscillations are observed throughout the nervous system and at multiple spatial and temporal scales [18], and they seem to be ubiquitous across species [19]. Taken together, this suggests that oscillations have important functions that have been

What Then Do We Know about Where EEG Comes From?

From a biophysics perspective, much is known about the origins of the local field potential (LFP) and EEG [23]. The (here termed) ‘standard model’ states that LFP and EEG are the extracellular currents reflecting summed dendritic postsynaptic potentials (the exchange of electrochemical signaling across the synapse) in thousands to millions of pyramidal cells in parallel alignment 2, 24, 25. Although postsynaptic potentials make the largest contributions, other neural processes including calcium

Now Is the Time To Start Answering the Title Question

We are at the convergence of three developments that together provide the opportunity for new and important discoveries about the origins and significances of EEG features. The first development is the bulging of the literature that characterizes EEG features accompanying memory, perception, emotion, language, action, and other cognitive processes. One can criticize such investigations as being correlational, too macroscopic, or unable to determine whether oscillations are part of the

What Types of Data Are Needed?

To discover what EEG means, insightful experiments are likely to include empirical measurements of neural data across multiple spatial scales recorded simultaneously. The ideal dataset includes several sets of laminar probes comprising hundreds of microelectrodes that span multiple layers of the cortex and multiple cortical regions, in combination with EEG on the skull or scalp. The EEG should have sufficient density (ideally >30 electrodes) to create topographical maps and implement spatial

What Types of Analyses Are Needed?

Properly analyzing the types of datasets described above may require novel, or at least different, analyses compared to the standard corpus of EEG analysis techniques (Figure 2). For one thing, the majority of time–frequency methods assume sinusoidal activity at the timescale of hundreds of milliseconds [80]. Clearly, neural oscillations are (by definition) rhythmic, but are they sinusoidal? That is less clear. There are noteworthy cases of nonsinusoidal neural oscillations, including up–down

Anticipated Challenges

Although it is not fashionable in neuroscience to highlight inter-species differences, there may be significant difficulties when trying to generalize findings across, for example, rodents and humans. Some of these difficulties may be relatively tractable. For example, differences in skull thickness and electrode size mean that a scalp electrode in humans measures activity from a larger neural population than does a screw drilled into a mouse skull. Other species differences may be more

Why This Research Is Important

Despite (or perhaps because of) these difficulties, this type of research is important and must be done. The benefits to fundamental neuroscientific knowledge, ideas about the roles of multiscale integration in cognition 18, 93, and clinical diagnosis are myriad, including the categories listed below.

Concluding Remarks

The literature linking human EEG oscillations to cognition is large and growing rapidly. It is imperative to work towards an understanding of the neurophysiological phenomena that drive those oscillations, and of the implications these oscillations have for how cognitive computations are implemented at the neural level. Linking brain dynamics across spatial and measurement scales is one of the great challenges in 21st century neuroscience.

How many configurations can produce a single EEG

Acknowledgments

Work in the laboratory of M.X.C. is funded by a grant from the European Research Council (ERC-StG 638589).

Glossary

Electroencephalography (EEG)
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,

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