Literature DB >> 31875684

The Theta/Beta Ratio as an Index of Cognitive Processing in Adults With the Combined Type of Attention Deficit Hyperactivity Disorder.

Christie Picken1, Adam R Clarke1, Robert J Barry1, Rory McCarthy2, Mark Selikowitz3.   

Abstract

An elevated theta/beta ratio in the EEG has long been observed among individuals with Attention Deficit Hyperactivity Disorder (ADHD). The theta/beta ratio was previously hypothesised to be an index of arousal, but a number of studies failed to find any association between the ratio and indices of arousal, instead proposing that the theta/beta ratio may actually be indicative of cognitive processing. This hypothesis was tested by Clarke et al using a sample of healthy adults, with results indicating that the theta/beta ratio correlated with a marker of cognitive processing (P300 latency in an auditory oddball task), while P300 amplitude correlated with an arousal marker (alpha power). The aim of this study was to test whether similar results could be found in a sample of 41 adults with the combined type of ADHD. EEGs were recorded during an eyes-closed resting condition and an auditory oddball task. Results demonstrated that the theta/beta ratio correlated significantly with P300 latency. Absolute alpha power did not correlate significantly with P300 amplitude or P300 latency. These results support the hypotheses that the theta/beta ratio is a marker of cognitive processing capacity in both the general population and in participants with ADHD, and that the alpha/arousal linkage is anomalous in ADHD.

Entities:  

Keywords:  EEG; alpha; attention deficit hyperactivity disorder (ADHD); processing; theta/beta ratio

Mesh:

Year:  2019        PMID: 31875684     DOI: 10.1177/1550059419895142

Source DB:  PubMed          Journal:  Clin EEG Neurosci        ISSN: 1550-0594            Impact factor:   1.843


  2 in total

1.  Neurological Mechanisms of Diagnosis and Therapy in School Children with ADHD in Poland.

Authors:  Małgorzata Nermend; Kinga Flaga-Gieruszyńska; Zdzisław Kroplewski; Kesra Nermend
Journal:  Int J Environ Res Public Health       Date:  2022-06-22       Impact factor: 4.614

2.  Electrophysiological Features to Aid in the Construction of Predictive Models of Human-Agent Collaboration in Smart Environments.

Authors:  Dor Mizrahi; Inon Zuckerman; Ilan Laufer
Journal:  Sensors (Basel)       Date:  2022-08-30       Impact factor: 3.847

  2 in total

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