Subtypes of ADHD distinguished by Quantitative EEG and ERPs

Beverley Steffert, Tony Steffert, Biao Zeng

Research output: Contribution to conferencePosterpeer-review

Abstract

Abnormalities in quantitative Electroencephlogram (QEEG) and Event Related potentials (ERPs) in Attention Deficit Hyperactivity Disorder (ADHD) patients have been reported for decades. This talk will focus on the typologies of ADHD (and symptoms that can mimic ADHD) that can be distinguished using a quantitative EEG and ERP analysis. Some subtypes indicate a pathology, while others suggest a maturation delay and each will respond differently to treatments.

The major pattern associated with the classic DSM criteria of ADHD (around 60% of the ADHD population) is an excessive amplitude of low frequency (4-8 Hz) above norms in frontal cortex. In some this can be in combination with a deficit of high frequency (18-21 Hz) EEG activity, known as the Theta/Beta ratio.
A smaller proportion (around 5 to 7 %) of patients are ‘hyperaroused’, with a raised amplitude of high frequency activity (above 21 Hz). This underlies the irritability and aggressiveness of some clients and for which stimulant medication would be contraindicated. A qEEG/ERP test-retest is able to predict the efficacy of stimulant medication.

The opposite pattern, the “inattentive only” subtype is characterised by excessive Alpha frequencies (8-12 Hertz).

Other unbalanced rhythms can predict unstable emotional, cognitive and physical states that leave individuals unable to draw on normal inhibitory and excitatory mechanisms. This affects impulsivity, alertness and attention, and will be described, with their relevant treatment options or medications. One of these is undiagnosed Epilepsy.

ERPs represent the neuronal responses associated with specific sensory, cognitive and motor events. Comparison studies between ADHD and control groups have revealed a wide range of altered ERP components. Such clinical ERP studies mainly lie in four aspects: error detection, attentional processing, memory and emotion. Firstly, error detection is most extensively investigated by the typical Go/NoGo task and the ADHD group shows reduced error related negativity (ERN), a sharp negative wave that is present selectively on error trials. Secondly, the contingent negative variation (CNV) is indicative of attentional expectancy and anticipation and use to test attentional processing. The ADHD group shows larger early CNV decrements over time. Additionally, many memory tasks indicate altered ERP components in ADHD. For example, the visual short-term memory task shows that the contralateral delay activity (CDA) amplitude emerges in an early time window for ADHD patients compared to control participants. As well, CDA amplitude was negatively correlated with severity of ADHD symptom and, anomalies are also found in several late EPR components involved in emotional processing, e.g. P1 and P3.

Simulant drugs have been the normal treatment for most ADHD sufferers. However the efficacy has been equivocal in terms of reduction of symptoms over time and occurrence of side-effects thus therapists have been looking for effective non-drug therapies. One that has some evidence of efficacy is Neurofeedback training. By reflecting their aberrant brainwaves to the patient in real-time, it is possible by operant conditioning to normalise brain activity. Neurofeedback training has been shown to; increase the CNV, reduce the theta/beta ratio, lower the excess high frequency amplitude and thereby improve attentional status.
Original languageEnglish
Publication statusPublished - Nov 2017
EventThe 2017 International Conference on Brain Informatics : Informatics Perspective of Investigation on the Brain and Mind - Beijing Advanced Innovation Center for Future Internet Technology/BJUT and Institute of Automation/Chinese Academy of Sciences, Beijing, China
Duration: 16 Nov 201718 Nov 2017

Conference

ConferenceThe 2017 International Conference on Brain Informatics
Abbreviated titleBI 2017
Country/TerritoryChina
CityBeijing
Period16/11/1718/11/17

Keywords

  • qEEG
  • ERP
  • ADHD
  • subtype

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