TY - JOUR
T1 - EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD
AU - Kiiski, Hanni
AU - Bennett, Marc
AU - Rueda-Delgado, Laura M.
AU - Farina, Francesca R.
AU - Knight, Rachel
AU - Boyle, Rory
AU - Roddy, Darren
AU - Grogan, Katie
AU - Bramham, Jessica
AU - Kelly, Clare
AU - Whelan, Robert
N1 - Funding Information:
Dr. Kiiski reports having research funding from Irish Research Council's Government of Ireland Postdoctoral Fellowship and no potential conflicts of interest. Dr. Kiiski is now employed by neuraltrain GmbH. Dr. Bennett disclosed research funding from Irish Research Council's Government of Ireland Postdoctoral Fellowship and from the Wellcome Trust (107496/Z/15/Z) and no potential conflicts of interest. Dr. Rueda‐Delgado reported no research funding and no conflicts of interest. Dr. Rueda‐Delgado is now employed by BrainWaveBank Ltd. Dr. Farina disclosed research funding from Irish Research Council's Postdoctoral Enterprise Partnership Scheme and no potential conflicts of interest. Ms. Knight reported no research funding and conflicts of interest. Mr. Boyle disclosed research funding from Irish Research Council's Postgraduate Enterprise Partnership Scheme and no potential conflicts of interest. Dr. Roddy reported research funding from the Irish Health Research Board grant to the REDEEM group at Trinity College Institute of Neuroscience and Department of Psychiatry (of which D. Roddy is a member) and no conflicts of interest. Dr. Grogan disclosed research funding from Irish Research Council's Government of Ireland Postgraduate Scholarship and no potential conflicts of interest. Dr. Bramham reported no research funding and conflicts of interest. Prof. Kelly disclosed research funding from Pathfinder seed grant from Trinity College Dublin and no conflicts of interest. Prof. Whelan reported research funding from Brain & Behavior Research Foundation's NARSAD Young Investigator grant and a Science Foundation Ireland grant and no conflicts of interest.
Funding Information:
We would like to express our gratitude to Mr. Andrea Aleni, Ms. Aoife Sweeney, Ms. Laura Rai and Mr. Ernest Mihelj for their assistance in participant recruitment, and in data collection and management. We would also like to thank HADD Ireland for their valuable support with participant recruitment. The address of the corresponding author Prof. Robert Whelan is Lloyd Building, Trinity College Dublin, Dublin 2, Ireland (email: robert.whelan@tcd.ie ). This work was supported by Irish Research Council's Government of Ireland Postdoctoral Fellowship grant to H. Kiiski (grant number GOIPD/2015/777), and M. Bennett's contribution was supported by the Irish Research Council's Government of Ireland Postdoctoral Fellowship grant (grant number GOIPD/2016/617) and the Wellcome Trust (107496/Z/15/Z). This work was also supported by Irish Research Council's Postdoctoral Enterprise Partnership Scholarship (grant number 207401) to F. Farina, Irish Research Council's Postgraduate Enterprise Partnership Scholarship (grant number EPSPG/2017/277) to R. Boyle, Irish Research Council's Government of Ireland Postgraduate Scholarship to K. Grogan (GOIPG/2014/294), the Irish Health Research Board grant to the REDEEM group at Trinity College Institute of Neuroscience and Department of Psychiatry of which D. Roddy is a member (grant number 201651.12553), Pathfinder seed grant from Trinity College Dublin to C. Kelly, and Brain & Behavior Research Foundation's NARSAD Young Investigator grant (grant number 23599) and a Science Foundation Ireland grant (grant number 16/ERCD/3797) to R. Whelan. The other authors did not have funding to disclose. The study sponsors had no involvement in the collection, analysis and interpretation of data and in the writing of the manuscript.
Publisher Copyright:
© 2019 Federation of European Neuroscience Societies and John Wiley & Sons Ltd
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1–45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71–0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68–0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.
AB - Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1–45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71–0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68–0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.
KW - adults
KW - attention-deficit
KW - endophenotype
KW - hyperactivity disorder
KW - machine learning
KW - resting-state EEG
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U2 - 10.1111/ejn.14645
DO - 10.1111/ejn.14645
M3 - Article
C2 - 31834950
AN - SCOPUS:85078681354
SN - 0953-816X
VL - 51
SP - 2095
EP - 2109
JO - European Journal of Neuroscience
JF - European Journal of Neuroscience
IS - 10
ER -