ADHD

Neurophysiological studies in ADHD have shown a relatively uniform picture with regards to EEG – QEEG data (based on group data). Most studies find excess slow brain activity (theta) (Hermens et al., 2004; Mann et al., 1992; Chabot and Serfontein, 1996; Clarke et al., 1998, 2001; Lazzaro et al., 1998, 1999) and a decreased fast brain activity (beta) (Hermens et al., 2004; Clarke et al., 1998; Mann et al., 1992; Lazzaro et al., 1998, 1999). Theta EEG activity is often associated with an “inattentive” or a dreamy state, and beta activity is often seen when the brain is very busy with for instance solving a cognitive task. Figure 1 shows an example of this based on the data of the Brain Resource International Brain Database of 275 patients with ADHD. In this example the increased theta and decreased beta can be clearly seen, with a frontal localization.

THETA                                                                            BETA                                                                      RELATIVE BETA

Figure 1: This figure shows the average brain activity (quantitative EEG – QEEG) of 275 children with ADHD, compared to a control group. On the left the increased theta EEG activity (p<.0001) can be seen, in the middle the absolute beta EEG activity (p<.0001) and on the left the decreased relative beta EEG activity (p<.0001). This deviant brain activity has a fronto-central localization. This pattern is found in almost all ADHD studies

If one takes a look at the individual data, however, (see figure 2) a completely different picture emerges. In figure 2 the individual data of 36 random ADHD patients is represented drawn from this same Brain Resource International Brain Database. In the table below the following is represented Theta – Red; Alpha – Yellow  and Beta – light blue. The quantitative EEG data of these children – or QEEGs – are compared to a normative database of more than 5000 healthy controls enabling an individual comparison. It can clearly be seen that indeed 47% of the ADHD patients have an increased theta activity. However, 5,6% of the patients show a decreased beta activity and 22% show an increased beta activity. The increased beta can be explained by the presence of beta spindles which occur in 20% of the cases of the ADHD children and which demand a different treatment strategy. The inter-individual variability within a behaviorally homogenous group such as ADHD patients thus is quite considerable.

Figure 2: This figure shows the EEG data of 36 random children (4-digit ID codes) with ADHD from the same dataset as in figure 1. This time, however, the individual data are represented. Indeed some children show an increased theta EEG activity (47%), but only 5,6% of the children show a decreased beta EEG activity and 22% show an increased beta EEG activity. Note the contrast between the individual and group data.

Considering the fact that Ritalin does not have a clinically meaningful effect in 20-40% of the ADHD patients (Swanson et al., 1993; Gordon, 2007) is seems plausible that the cause of it is to be found in the interindividual variability of the brain functioning, as shown.

The above mentioned group of ADHD children is part of a large scale clinical investigation, and therefore all of these children were treated with a stimulant such as Ritalin. Consequently we tested the prior mentioned hypothesis. A group of 50 of those children were divided into different groups according to their individual EEG phenotype, as seen in figure 3. It turned out that only the group with frontal slow activity (frontal theta) responded well to treatment with stimulant medication (Methylphenidate: Ritalin), as measured by the improvement on a continuous performance test (CPT), whereas the other groups did not show any improvement on the CPT as a result of medication (Arns et al. submitted).

Comparable studies of ADHD have shown that patients who responded well to stimulant medication such as Ritalin indeed showed excess slow brain activity frontally (Delta en Theta: Clarke et al., 2002; Satterfield et al., 1972; Suffin & Emory, 1995). This is clearly a well identifiable ADHD sub-type that responds well to medication. This knowledge can very well be applied to personalizing ADHD treatment not only with respect to pharmacotherapy but also for EEG biofeedback or Neurofeedback treatment.

Figure 3: In the figure above the prevalence of the occurrence of the different EEG phenotypes is shown for a group of ADHD children and a matched control group. It can clearly be seen that ADHD and control group differ particularly on op Frontal Slow, Slow Alpha Peak Frequency, Low Voltage en Frontal Alpha. This demonstrates that there is a great diversity of EEG patterns observed within a group of patients, but also within a group of ‘healthy’ controls. According to the literature these ADHD patients will all respond favourably to different medications, the Frontal Slows will respond best to Ritalin (Arns et al., submitted) and the Frontal Alpha will respond better to an SSRI (Suffin & Emory, 1995).

For more information on QEEG and neuropsychological methods which are used by Brainquiry see the section “professional” on QEEG.