Editorial Perspective: How to optimise frequency band neurofeedback for ADHD

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1 Journal of Child Psychology and Psychiatry 57:4 (2016), pp doi: /jcpp Editorial Perspective: How to optimise frequency band neurofeedback for ADHD Annet Bluschke, Veit Roessner, and Christian Beste Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany Attention deficit/hyperactivity disorder (ADHD) is one of the most prevalent paediatric neuropsychiatric disorders and is characterised by hyperactivity, inattention and increased impulsivity. Children with ADHD are often also characterised by deficits in a variety of cognitive domains. These can include problems in working memory, a generally slower and more variable style of information processing and deficits in temporal processing, inhibitory functions and delay processing (Sonuga-Barke, Bitsakou, & Thompson, 2010). Also, overarching executive functions (Diamond, 2013) like information updating, response inhibition and mental set shifting are impaired in many, but not all, children with ADHD, demonstrating the neuropsychological heterogeneity characterising this disorder (Walshaw, Alloy, & Sabb, 2010). Deficits in executive functions persist into adulthood and can have a substantial negative impact on everyday life. A variety of approaches are commonly considered for the treatment of ADHD, including pharmacological interventions, patient-centred cognitive-behavioural therapy approaches and specific teacher/parent training programmes (Hinshaw & Arnold, 2015). Adding to this multimodal treatment approach, in the past 15 years, neurofeedback has grown in popularity as an intervention option for patients with ADHD. During neurofeedback, cortical activation is recorded from the participant s head using EEG electrodes. The recordings are then presented to the participant in the form of sounds, animations or simple computer games (e.g. car on race course), which the participant is required to control by regulating specific parameters of the EEG recordings. This training is usually supplemented by elements of cognitive-behavioural therapy, including the development of regulation strategies, psychoeducation, a token system and therapeutic homework to encourage practice and transfer of acquired skills to everyday requirements. Two forms of neurofeedback training are usually conducted in ADHD: (a) slow cortical potential (SCP) training, and (b) theta/beta training. In SCP training, cortical excitability, as a measure of anticipation and arousal, is supposed to be regulated by the participant. Specific emphasis is put on the patients ability to readily shift between contrasting states of cortical excitability (i.e. high arousal vs. low arousal) and to thus increasingly differentiate between them and their behavioural correlates. Concerning executive functions, SCP training has been shown to be beneficial in regard to temporal processing deficits (Holtmann, 2013). In contrast, the theta/beta training aims at regulating two different frequencies of neuronal oscillations; i.e. the slower theta band (4 8 Hz) and the faster beta band (13 21 Hz), commonly measured at electrode position Cz. The aim of the theta/beta training is to decrease the strength of central theta band power and to increase beta oscillations. The rationale for this is that children with ADHD have been observed to have increased theta power accompanied by reduced beta power, which has been interpreted as a sign of cortical hypoarousal (Hammond, 2011; Heinrich et al., 2014). A large number of studies, including some randomised controlled trials, have so far demonstrated the beneficial effects of neurofeedback for ADHD symptomatology and academic performance, with effects lasting up to 2 years after training (Holtmann, Sonuga-Barke, Cortese, & Brandeis, 2014; Sonuga- Barke et al., 2013). However, meta-analyses suggest that psychological treatment (including neurofeedback) only produces significant effects when ADHD assessments are made by raters close to the therapeutic setting, but not when an independent blinded assessment is employed (Holtmann et al., 2014; Sonuga-Barke et al., 2013). Aiming to allow a more balanced assessment of neurofeedback effects, efforts are being made to rectify this issue (Micoulaud-Franchi et al., 2014). The mixed effects of neurofeedback training in ADHD become even more apparent when executive control processes are used as outcome measures. Currently, there are only few studies on the effects of theta/beta neurofeedback training on executive functions in ADHD (for overview see Enriquez-Geppert, Huster, & Herrmann, 2013; Perreau-Linck, Lessard, Levesque, & Beauregard, 2010; Steiner, Frenette, Rene, Brennan, & Perrin, 2014). However, this is important for a number of reasons: It has been suggested that goal-directed task performance in ADHD is dysfunctional because ADHD patients are prone to interferences from default mode network activity which disrupts executive control (Sonuga-Barke & Castellanos, 2007). A high level of executive control Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden, MA 02148, USA

2 458 Annet Bluschke, Veit Roessner, and Christian Beste J Child Psychol Psychiatr 2016; 57(4): functions has been shown to be central for several aspects of life including school readiness as well as success and quality of life (Diamond, 2013). Certain components of executive functions (including inhibitory processes) may be of particular relevance to the day-to-day functioning of a significant proportion of children with ADHD (Biederman et al., 2004; Walshaw et al., 2010). It was found that children receiving theta/beta neurofeedback targeting medial central oscillations showed significant improvements in executive functioning compared to cognitive training interventions, but effect sizes of the neurofeedback intervention were in fact quite small (~0.31) (Steiner et al., 2014), especially when compared against pharmacological interventions. It therefore seems to be the case that the effects of neurofeedback on the executive abilities of children with ADHD are rather small and it appears necessary to improve neurofeedback protocols to achieve better therapy outcomes in different cognitive domains including executive functions. Returning to the underlying research findings, it has recently been questioned whether theta power is actually consistently increased in children with ADHD (Liechti et al., 2013; Loo et al., 2013). Along similar lines, the theoretical underpinnings of theta/ beta neurofeedback have recently been critically discussed (Heinrich et al., 2014; Holtmann et al., 2014; Saad & Kohn, 2015). From our point of view it appears that the mixed reports concerning theta/ beta neurofeedback training currently apparent in the literature could be based on fundamental, though historically routed misconceptions about the role of theta oscillations for cognitive brain function. Theta frequency oscillations are commonly interpreted as signifying a daydream-like, inattentive state and mental inefficiency (Hammond, 2011). Activity in the faster beta band (13 21 Hz), in contrast, is thought to reflect focused attention and mental arousal (Hammond, 2011). The larger proportion of theta power along with reduced beta oscillations in the resting EEG observed in ADHD is therefore interpreted as a more idle, unprepared and inefficient cortical state compared to healthy controls. Unlike the view that theta frequency oscillations are suggestive of a relaxed state, several more recent lines of evidence suggest that theta band activity rather plays a critical role in executive control processes (Cavanagh & Frank, 2014). In particular, it has been suggested that frontal midline theta band oscillations may reflect the central mechanisms by which top-down control across distributed networks is achieved (Cavanagh & Frank, 2014) and by which task-irrelevant networks are suppressed in children (Michels, L uchinger, Koenig, Martin, & Brandeis, 2012). Evidence for this concept comes from a number of neurophysiological studies on conflict processing and cognitive flexibility, working memory and response inhibition (Enriquez-Geppert, Huster, Scharfenort, et al., 2014). All of these processes are known to be core executive functions which are also often altered in ADHD (Walshaw et al., 2010). It has been shown that increases in medial frontal cortical theta oscillatory power are related to cognitive control and therefore represent the opposite of an idle, unprepared and inefficient cortical state. There are several reasons for this (Cavanagh & Frank, 2014): (a) the medial frontal cortex is closely connected to various cortical and subcortical regions and can therefore modulate processing in a broad functional network. (b) Especially high-amplitude, low-frequency oscillations seem to be ideal for organising processing across long-distance networks in the brain. (c) Moreover, theta band oscillations reflect a generic process similar to the effects of neuromodulators. All these properties make it possible that theta band activity contributes to the integration of multiple inputs (e.g. from context and memory) to regulate executive functions and cognitive control, including the tuning of selective attention. Thus, theta band oscillations (and particularly those measured over frontal midline regions as opposed to central regions) should play a crucial role for ADHD symptomatology (Loo et al., 2013) and the executive dysfunctions commonly associated with it and it would be useful to address them in neurofeedback training. There thus seems to be a mismatch between the way theta/beta neurofeedback is practised in ADHD on the one hand, and studies as well as novel conceptions stressing the importance of phasic frontal midline theta for cognitive control and executive functions on the other hand. We suggest that this mismatch may lead to inefficiencies in modulating cognitive control dysfunctions in patients with ADHD through neurofeedback. It is possible that the comparatively low effects of theta/beta neurofeedback training on executive functions in ADHD emerge because protocols are based on historically biased views on theta oscillations and somewhat disregard its topographical and functional distinctions (i.e. focussing on central instead of frontal midline theta oscillations). It could be the case that components of theta/beta neurofeedback protocols are conceptualised in a way in which they may not produce the best possible therapeutic effects as far as executive control functions are concerned. It is therefore questionable, whether the currently pursued strategy of theta/beta neurofeedback is the most optimal one when trying to increase cognitive control and executive functions in ADHD. In fact, recent results suggest that neurofeedback training focusing on increasing (rather than reducing) theta power measured over central and frontal electrodes (i.e. reflecting frontal midline theta oscillations) enhances cognitive control processes in healthy controls (Enriquez-Geppert, Huster, Scharfenort, et al., 2014). It may therefore be the case that the direction of theta modulation in neurofeedback

3 doi: /jcpp Optimising neurofeedback in ADHD 459 training is not optimal in order to maximise therapeutic effects in the domain of executive functions in ADHD. It cannot be excluded that the positive effects neurofeedback has for patients with ADHD may solely rest on the incorporated aspect of beta band up-regulation (Engel & Fries, 2010). Converging evidence from different lines of studies suggests that beta frequency oscillations are important for the stabilisation and continuation of processes protecting cognitive operations against the effect of potentially novel, or unexpected, external events (Engel & Fries, 2010). Beta band oscillations therefore subserve important functional roles for executive control processes and top-down attentional selection (Engel & Fries, 2010). It is therefore possible that the beneficial effects of current neurofeedback theta/ beta ratio protocols are mainly due to the regulation of only one component, namely the increase in beta band activity. This issue may also explain recent critical views on theta/beta neurofeedback training (Heinrich et al., 2014). In other words, current theta/beta neurofeedback training protocols possibly only use a small part of their therapeutic potential to treat executive control dysfunctions in ADHD. Apart from discussions of statistical confounders and sensitivity/specificity issues, the main point here concerns the measurement and interpretation of the theta/beta ratio. Importantly, it has been shown that the differentiation between controls and ADHD patient is more reliable when theta/beta ratio is measured in active task conditions rather than at rest (Heinrich et al., 2014). This may suggest that the reported heightened theta power reflects compensatory mechanisms taking place in patients with ADHD, as more executive control may be required for those patients when initiating cognitive activity or engaging in challenging mental tasks. Together, these observations suggest that a change in the strategy to treat executive control dysfunctions in ADHD using theta/beta neurofeedback should be considered and empirically tested. Overall, we thus propose the idea that a protocol modification aiming to increase beta and theta oscillatory power at the same time may have stronger therapeutic effects on executive functions in ADHD. This protocol may then also focus on frontal midline theta oscillations, opposed to currently used strategies to modulate central theta oscillations. Specifically, we suggest that a one-size-fits-all use of the theta/beta ratio may not be the optimal parameter to be used in frequency band neurofeedback training and that training the ability to successfully and flexibly self-regulate the theta/beta ratio (rather than simply reducing it) may be a more meaningful Figure 1 Neurofeedback treatment for ADHD. (A) In the theta/beta neurofeedback training used currently, participants are required to down-regulate theta power (top) while up-regulating beta power (bottom). Based on recent findings regarding the functions of theta oscillations, we suggest that, in this set-up, the connections between various cortical and subcortical regions are not used to the best possible extent. (B) In the proposed adaption of the current theta/beta training, an intermittent block design is used. Each block lasts for around 10 s and participants can either (I) be required to down-regulate theta and up-regulate beta, or (II) be asked to up-regulate the power of both frequency bands. By this, participants should learn to flexibly control and adapt their theta band. This would then lead to a strengthening of (sub)cortical connections and a better use of available cognitive resources. (pmfc = posterior medial frontal cortex, amfc = anterior medial frontal cortex; BG = basal ganglia, PFC = prefrontal cortex)

4 460 Annet Bluschke, Veit Roessner, and Christian Beste J Child Psychol Psychiatr 2016; 57(4): approach (Liechti et al., 2013). This is the case especially when considering findings suggesting that the ratio is not per se connected to arousal, but rather to its activation (i.e. the adaptation of arousal from rest to task conditions) (Heinrich et al., 2014). Instead of instructing ADHD patients to generally increase their frontal midline theta and beta power, it could thus be more important to require patients to regulate them based on task demands (see Figure 1). Here, the idea of measuring and using the concept of event-related oscillations could thus constitute a novel neurofeedback approach: ADHD patients could be trained to up- or down-regulate their theta power based on the value of a cue presented to them, similarly to the way it is currently done within SCP training (see Figure 1). Training the ability to readily and flexibly change cortical activation depending on a presented stimulus would thus address executive control on a neurophysiological as well as behavioural level. Along these lines, an adaptation of the training requirements (e.g. frequency of requiring a switch between theta up- and down-regulation) according to the patients neuropsychological/executive function abilities could also be considered. This could take place in a fashion similar to z-score neurofeedback training, for which beneficial effects for executive functions in ADHD have been reported in an uncontrolled pilot study (Arns, Drinkenburg, & Kenemans, 2012). Overall, evidence concerning the functional meaning of theta oscillations seems to suggest that it may not be useful to uniformly train patients with ADHD to decrease central theta power. Instead, for patients with ADHD and deficits in executive functions it may rather be necessary to adapt neurofeedback training so that patients are required to increase their frontal midline theta power. Furthermore, patients with issues in cognitive flexibility may benefit from a neurofeedback approach requiring them to intermittently switch between theta up- and down-regulation, as this may strengthen their ability to control their cognitive control. All these suggestions are yet to be tested empirically, starting with healthy controls or those with subclinical ADHD symptomatology. This is necessary as the effects of frequency band neurofeedback in healthy adult controls are still not clearly defined (compare Enriquez-Geppert, Huster, Figge, & Herrmann, 2014 with Studer et al., 2014) and meta-analytical evidence is lacking. From this perspective it would first be important to contrast the differential functional mechanisms and effects of the traditional and an adapted neurofeedback protocol in an unaffected adult sample. After the functional mechanisms of neurofeedback requiring theta up-regulation have been established in typically functioning individuals, the derived conclusions could be applied to nontypically functioning individuals. Focusing on the most relevant issue of treatment implications, a randomised controlled study could then reveal the differential effects of the two approaches in a full (paediatric) ADHD sample. Acknowledgements The work reported here was supported by a grant by Deutsche Forschungsgemeinschaft (BE4045/10-2) to C.B. A.B. declares no competing or potential conflicts of interest. V.R. has received payment for consulting and writing activities from Lilly, Novartis, and Shire Pharmaceuticals, lecture honoraria from Lilly, Novartis, Shire Pharmaceuticals, and Medice Pharma, and support for research from Shire and Novartis; he has carried out (and is currently carrying out) clinical trials in cooperation with the Novartis, Shire, and Otsuka companies. C.B. has received payment for consulting from GlaxoSmithKline, and Teva. The authors thank Mr. Benjamin Teufert for his assistance in creating the Figure. Correspondence Annet Bluschke, Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Schubertstrasse 42, D Dresden, Germany; annet.bluschke@uniklinikum-dresden.de References Arns, M., Drinkenburg, W., & Kenemans, J.L. (2012). The effects of QEEG-informed neurofeedback in ADHD: An open-label pilot study. 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