A review of the efficacy of neurofeedback for Attention Deficit Disorder 

Introduction

Attention Deficit Hyperactivity Disorder (ADHD) is a heterogeneous psychiatric disorder, characterised by age inappropriate symptoms of inattention, hyperactivity and impulsivity. However, the main difficulty appears to be the volitional control of attention and impulses, especially during monotonous or effortful tasks that lack reward or inherent gratification (Barkley, 2001). The disorder is thought to affect around 3-5% of school age children (APA, 1994), with boys outnumbering girls by a ratio of three to one (Baumeister and Hawkins, 2001). In adolescence and young adulthood more girls are affected (Logan, et al., 2000), although whether this reflects a different time course for the disorder between the sexes, or an earlier referral bias for boys due to more disruptive behaviours (Baydala and Wikman, 2001) is unclear. Although research on sex differences in ADHD is limited (Nigg, 2001), there is a suggestion of a different pattern of severity of impairment in girls, evidenced by functional brain differences (Ernst, 1994).

Over the years, the taxonomy and classification of ADHD has undergone considerable revision. The DSM-IV (APA, 1994) categorises ADHD children according to 3 main subtypes; Inattentive (ADHD-in), Hyperactive (ADHDhyp), and Combined (ADHD-com). Each subtype has different developmental patterns, outcomes, and associated co-morbidities (Johansen et al., 2002). As the hyperactive subtype is less common after the early years, it has been suggested it may be a precursor to the combined “classic ADHD profile” (Nigg, 2001, p. 572), whose symptoms include inattention, impulsiveness, low frustration tolerance, poor organisation of behaviour, distractibility and hyperactivity. However, the cognitive and behavioural symptoms of Inattentives differ from those of the Hyperactive and Combined types in more dimensions than hyperactivity alone. Inattentives present cognitive problems that are more non-specific, with generally less accurate information processing and poorer focusing and selective attention.

Although ADHD is a disorder defined by behavioural symptoms, differences in  neurochemistry, brain physiology and genetics suggest a biological basis to the disorder. This evidence provides the rationale for the most common treatment of the disorder; stimulant medication (Conners et al., 2001). However, a number of problems remain. Firstly, not all individuals are good candidates for medication due to numerous associated side-effects, such as anxiety, irritability, insomnia and suppressed appetite (Braswell et al., 1997). Secondly, stimulant medication is most effective on motor function and behaviour, but has little effect on the ability to attend (Logan et al., 2000). Indeed, data on the effectiveness of the medication for Inattentives is sparse (Johansen et al., 2002). Thirdly, there is a rapid return of symptoms once the medication has been eliminated from the body (Brown et al., 1986). Finally, although the use of stimulant medication is generally considered safe, concerns about its long-term usage have been raised, particularly with respect to recent reports suggesting an increased risk of cytogenetic effects (El-Zein, 2005).

While some researchers suggest the cognitive and behavioural manifestations of ADHD may be the result of a single deficit or dysfunction (e.g., Barkley,1997), others reject the search for a ‘grand theory’ of ADHD and attempt to account for the heterogeneous aspects of the disorder, with multi-factor models reflecting multiple sources of disruption in cortical and sub-cortical function (e.g., Goldberg, 2001; Sonuga-Barke, 2002). Although children with ADHD present with symptoms of disrupted executive function, it is unclear whether the fundamental problem resides at the executive level or is the result of a cascade of difficulties at lower levels of processing (Logan et al., 2000). At the cognitive level, the deficits are either low level, such as orienting (van Leeuwen et al., 1998) or higher level executive dysfunction (Pennington, 1996). The latter include deficits in inhibition, either response inhibition, that is, withholding a pre-potent response (Aron et al., 2003) or processing inhibition - the inability to inhibit cognitive processing of distracting, irrelevant information (Carter et al., 1995).

Although 30-50% of children with ADHD outgrow their symptoms, approximately one third still meet the criteria for ADHD into adulthood (Rubia, 2002). As the symptoms of hyperactivity decrease with age (Bresnahan et al., 1999), it has been suggested that ADHD may indicate a maturational lag in development (Kinsbourne, 1973). Evidence in support of this hypothesis was provided by a study by Satterfield (1973) in which the Event Related Potentials (ERPs) of children with ADHD had significantly longer latencies and lower amplitudes, typical of younger children. In addition, Electroencephalography (EEG) studies have suggested that children with ADHD have increased slow wave activity relative to normal controls (Mann et al., 1992), suggestive of a maturational lag. However, the evidence for this is equivocal, with findings from Bresnahan et al (1999) showing that while slow waves decrease with age for both ADHD and normal participants, the differences between the groups persists into adulthood. As such, the elevation in slow wave activity in children with ADHD cannot be interpreted as a sign of maturational lag, but might rather reflect neurotransmitter dysfunction resulting in cortical hypoarousal.

Although the aetiology of ADHD remains disputed, relatively consistent findings in the electrophysiology of the brain have emerged over the past thirty years. Spectral analysis of the EEGs of children with ADHD has frequently shown increased levels of slow waves (predominantly theta) and decreased levels of relative alpha and beta activity when compared to the EEGs of normal controls (Barry et al., 2003a). In general, the abnormalities seem to be more pronounced in the Combined compared to the Inattentive subtype. Both the theta/beta and theta/alpha ratios reliably distinguish between the groups, with the Inattentives’ ratios between those of the Combined type and normal controls (Clarke et al., 1998). In a maturational study, theta remained elevated in an ADHD group across the age levels, while relative beta activity increased with age toward levels seen in the normal control group (Bresnahan et al., 1999). Since symptoms of hyperactivity decrease with age, while impulsivity remains, it has been suggested that these results link beta with the former and theta to the latter.

Cluster analyses of spectral EEG measures have provided well-replicated evidence of distinct neurophysiological subtypes within the ADHD population (Clarke et al., 2001a, b, c; 2003a). Barry et al (2003a) suggest that one of these subtypes (relative theta, theta/beta ratio and total power all increased; relative delta and beta decreased across all regions) represents a cortical arousal dysregulation, while the other (deficiencies of fast wave and increased slow wave activity) indicates a maturational lag. Significantly, these subtypes are independent of the diagnostic subtypes of the DSM-IV, suggesting that various behavioural manifestations of ADHD may result from a similar mix of pathophysiologies and mechanisms, although the abnormalities may be more severe in one behavioural subtype than the other (Chabot and Serfontein, 1996). This heterogeneity in the disorder may account for some of the inconsistencies found between studies of different ADHD populations.

Regardless of these inconsistencies, ADHD is, nonetheless, typically characterised by a preponderance of slow wave (theta) activity in frontal areas, and a deficit of fast (beta) wave activity around central and parietal regions. Against this backdrop came the discovery by Sterman (Sterman, 1969; Wywricka and Sterman, 1968) that following training, cats rewarded for decreasing motor output were able to learn operant control of their EEG. This discovery was soon extended to findings that epileptic patients could be taught to decrease epileptiform activity if given feedback about sensorimotor (SMR; 12-15Hz) activity from electrodes placed over motor cortex. Continuing this theme of learned self-regulation of the electroencephalogram, Lubar and Shouse (1976) reasoned that inhibiting theta/enhancing SMR and/or inhibiting theta/enhancing beta1 might redress some of the core symptoms of ADHD, with early reports indicating positive outcome. Over the years, increasing evidence has amassed indicating that EEG biofeedback (also known as neurofeedback or neurotherapy) may be a viable alternative to pharmacological treatments for ADHD. If participants can learn self-regulation of their EEG, this should be accompanied by concomitant improvements in cognitive and behavioural functioning, which can be objectively evaluated by behavioural and psychophysiological assessment.

Method

The basic tenant of neurofeedback training is that over time (generally between 20-40 sessions), participants learn to inhibit frequencies associated with under performance (in the case of ADHD, excessive levels of theta, associated with drowsy, inattentive states), while simultaneously increasing the frequencies in which they are deficient (e.g., SMR/Beta, associated with focused attention). Any change in the EEG, such as a decreased theta/beta ratio, should be accompanied by a concomitant remediation of symptoms. Feedback is normally provided via audio-visual representation and is accompanied by points, which provide the reward. Assuming the individual is able to gain operant control of the EEG, it is thought that they will maintain this state by utilising their newly increased knowledge of their physiological processes (Loo and Barkley, 2005). Although there is evidence to suggest that these changes are stable and long lasting, possibly as a result of long-term potentiation (LTP), further studies are required to test the long-term efficacy of neurofeedback.

Results and discussion

Although a substantial number of investigations, ranging from single case reports to group studies have been conducted, the value of neurofeedback remains disputed by the general scientific community. A number of critiques (e.g., Barkley, 1990, 2003; Baydala and Wikman, 2001; Kline, Brann and Loney, 2002; Loo, 2003; Loo and Barkley, 2005) have suggested that positive outcome is attributable to non-specific effects, rather than neurofeedback per se, with criticism levelled at the lack of randomisation to treatment groups, small subject numbers, failure to control for therapist interaction, practice effects, poor/inappropriate use of statistics and inappropriate/missing control groups.

Although a study by Linden, Habib and Radojevic (1996) redressed this first criticism, by randomly assigning participants to groups, only 18 participants were tested. Half the participants received neurofeedback, with the remainder assigned to a no treatment condition. While those in the neurofeedback group improved from pre to post test on IQ and parent rating scales, the study although promising, lacked statistical power, random assignment and equivalent levels of experimenter contact between groups. More promising was experimental data from a study by Monastra, Monastra and George (2002) in which a battery of dependent variables, including cognitive, behavioural and neurophysiological indices were measured. Importantly, participants receiving neurofeedback showed significant improvements in cognitive functioning post test on the Test of Variables of Attention (TOVA), a continuous performance test, as well as on electrophysiological measures (evidenced by a decreased theta/beta ratio post test). The control group (who received a ‘Comprehensive Clinical Care’ (CCC) package) did not evidence improvements compared to the neurofeedback and CCC condition. However, again the study lacked random assignment and equivalent levels of therapist contact.

Although these studies are not impervious to criticism, they do nonetheless suggest that neurofeedback may be efficacious in the treatment of ADHD. However, the clinical utility of neurofeedback can only be realised once studies can demonstrate effects equivalent to stimulant medication without confounds in their design. In support of this, Fuchs et al (2003) directly compared the efficacy of 22 participants assigned neurofeedback training against 12 participants taking stimulant medication. Participants in the neurofeedback group were trained to suppress theta and high beta activity, while enhancing SMR and low (15-18 Hz) beta. Performance was measured on two tests of attention, the d2 Attention Test and the TOVA. Further behavioural measures included IQ assessment and parent and teacher ratings on the Conners Behaviour Rating Scale. Both groups showed improvements on all measures, suggesting that neurofeedback is of equivalent efficacy to stimulant medication. However, once again the study lacked randomisation, groups were small and contained uneven subject numbers, and the amount of therapist contact between groups differed markedly. In addition, as EEG data was omitted, it is impossible to determine whether the positive effects evidenced in this study were attributable to neurofeedback or other non-specific effects.

In order to address some of these issues, the present study used a single blind randomised design, with equivalent levels of experimenter contact in each condition. Participants were randomly assigned to either a programme of computerised attention training or neurofeedback, with medication stratified across groups. A follow-up assessment was conducted six months post-training to determine the stability of any effects. The results of this follow-up are not included in this preliminary report as several participants have only recently completed training. In addition, as analysis of EEG data is still in progress, only behavioural data are considered. A more extensive report detailing EEG findings and follow-up analysis will be undertaken in due course.

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Page last updated: 21/12/2011 16:03 
 
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