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Electroencephalography signatures of attention-deficit/hyperactivity disorder: clinical utility

Authors Alba G, Pereda E, Mañas S, Méndez L, González A, González J

Received 8 May 2015

Accepted for publication 11 September 2015

Published 22 October 2015 Volume 2015:11 Pages 2755—2769


Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Ryouhei Ishii

Peer reviewer comments 2

Editor who approved publication: Dr Roger Pinder

Guzmán Alba,1 Ernesto Pereda,2 Soledad Mañas,3 Leopoldo D Méndez,3 Almudena González,1 Julián J González1

1Physiology Unit, Health Sciences Faculty (S Medicine), 2Department of Industrial Engineering, School of Engineering and Technology, University of La Laguna, 3Clinical Neurophysiology Unit, University Hospital La Candelaria, Tenerife, Spain

Abstract: The techniques and the most important results on the use of electroencephalography (EEG) to extract different measures are reviewed in this work, which can be clinically useful to study subjects with attention-deficit/hyperactivity disorder (ADHD). First, we discuss briefly and in simple terms the EEG analysis and processing techniques most used in the context of ADHD. We review techniques that both analyze individual EEG channels (univariate measures) and study the statistical interdependence between different EEG channels (multivariate measures), the so-called functional brain connectivity. Among the former ones, we review the classical indices of absolute and relative spectral power and estimations of the complexity of the channels, such as the approximate entropy and the Lempel-Ziv complexity. Among the latter ones, we focus on the magnitude square coherence and on different measures based on the concept of generalized synchronization and its estimation in the state space. Second, from a historical point of view, we present the most important results achieved with these techniques and their clinical utility (sensitivity, specificity, and accuracy) to diagnose ADHD. Finally, we propose future research lines based on these results.

Keywords: EEG, ADHD, power spectrum, functional connectivity, clinical assessment

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