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Use of EEG to Diagnose ADHD

  • Attention-Deficit Disorder (A Rostain, Section Editor)
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Abstract

Electroencephalography (EEG) has, historically, played a focal role in the assessment of neural function in children with attention deficit hyperactivity disorder (ADHD). We review here the most recent developments in the utility of EEG in the diagnosis of ADHD, with emphasis on the most commonly used and emerging EEG metrics and their reliability in diagnostic classification. Considering the clinical heterogeneity of ADHD and the complexity of information available from the EEG signals, we suggest that considerable benefits are to be gained from multivariate analyses and a focus towards understanding of the neural generators of EEG. We conclude that while EEG cannot currently be used as a diagnostic tool, vast developments in analytical and technological tools in its domain anticipate future progress in its utility in the clinical setting.

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Conflict of Interest

Agatha Lenartowicz declares that she has no conflict of interest.

Sandra K. Loo has received a grant from the National Institutes of Health.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

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Authors and Affiliations

  1. Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, 760 Westwood Pl. Suite 17-369, Los Angeles, CA, 90095, USA

    Agatha Lenartowicz

  2. Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, 760 Westwood Pl. Suite 47-406, Los Angeles, CA, 90095, USA

    Sandra K. Loo

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  1. Agatha Lenartowicz
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Correspondence to Agatha Lenartowicz.

Additional information

This article is part of the Topical Collection on Attention-Deficit Disorder

Glossary

Alpha band

Referring to oscillations in the range of 8-15 Hz

Beta band

Referring to oscillations in the range of 16-30 Hz

Delta band

Referring to oscillations <4 Hz

Event-related desynchronization (ERD)

Decrease in power of a frequency following a stimulus in event-related spectral analysis relative to pre-event; thought to arise from decreased synchronization of neural activity in that frequency

Event-related potential (ERP)

The average EEG signal in a time window following an event of interest (e.g., beep), computed over many repetitions of that event; typically associated with transient cortical dynamics in response to a stimulus or response

Event-related spectral analysis

The average power in a time window following an event of interest (e.g., beep), computed over many repetitions of that event; computed separately across many frequencies; typically associated with transient changes in brain state

Event-related synchronization (ERS)

Increase in power of a frequency following a stimulus in event-related spectral analysis relative to pre-event; thought to arise from increased synchronization of neural activity in that frequency

Feature

A descriptor or metric of EEG data; can be categorized into subclasses (see below) such as spectral, temporal, spatial or fractal

Fractal

Referring to characterization of jaggedness or serratedness of an EEG time series

Frequency

Number of cycles of an oscillation occurring per unit time; units of Hertz (Hz) or cycles/sec; distinguishes between “fast” and “slow” oscillations

Gamma band

Referring to oscillations above 30 Hz

Independent components analysis

Statistical technique that attempts to parse multivariate data (e.g., signal across many electrodes in EEG) into latent components that describe patterns of variables that covary across some other variable (e.g., time); these components are selected to be maximally statistically independent

Machine learning

The study and design of computer-based statistical algorithms that can learn from the data; typically designed to predict categorical outcome variables such as diagnosis; logistic regression is a univariate example of Machine Learning

Multidimensional

Simultaneous observation and analysis of more than one domain of data (e.g., ERP and performance measures)

Multivariate

Simultaneous observation and analysis of more than one outcome variable

Power

A measure of the amplitude of oscillations of a particular frequency in an EEG time course; typically associated with brain state

Spatial

Referring to characterization of electrode or cortical source of EEG time series

Spectral

Referring to characterization of frequency content of EEG time series

Spectral analysis

Quantification of time series in terms of power across frequencies, producing a power “spectrum”

Synchronization

The degree to which two or more neural units (cells or populations) show oscillations of a particular frequency that are the same across time (i.e., have the same phase and amplitude); the metric of “coherence” is sometimes used in analog to the “correlation” coefficient, to quantify this co-variation

Temporal

Referring to characterization of time content of EEG time series

Theta band

Referring to oscillations in the range of 4-7 Hz

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Lenartowicz, A., Loo, S.K. Use of EEG to Diagnose ADHD. Curr Psychiatry Rep 16, 498 (2014). https://doi.org/10.1007/s11920-014-0498-0

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