Tilburg University the Application of Alpha EEG Training in Healthy Participants Dekker, M.K.J
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Tilburg University The application of alpha EEG training in healthy participants Dekker, M.K.J. Publication date: 2014 Document Version Publisher's PDF, also known as Version of record Link to publication in Tilburg University Research Portal Citation for published version (APA): Dekker, M. K. J. (2014). The application of alpha EEG training in healthy participants. Prismaprint. 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Dekker, Eindhoven Research described in this thesis was commissioned by the Cognitive Neuropsychology department of the Tilburg University (Tilburg, the Netherlands), and the Behaviour, Cognition, and Perception group of Philips Research (Eindhoven, the Netherlands). Layout: Marian Dekker, Eindhoven, the Netherlands Philips Translation Services, Eindhoven, the Netherlands Cover design: Bregtje Viegers, Utrecht, the Netherlands Cover copyright: Age fotostock / Barry Downard Reproduction: PrismaPrint Tilburg University, Tilburg, the Netherlands ISBN 978-94-6167-212-4 The application of alpha EEG training in healthy participants PROEFSCHRIFT ter verkrijging van de graad van doctor aan Tilburg University op gezag van de rector magnificus, prof.dr. Ph.Eijlander, in het openbaar te verdedigen ten overstaan van een door het college voor promoties aangewezen commissie in de aula van de Universiteit op donderdag 18 december 2014 om 14.15 uur door Marian Karin Joke Dekker geboren op 22 april 1983 te Deurne Promotor: Prof. dr. M.M. Sitskoorn Copromotor: Dr. G.J.M. van Boxtel Promotiecommissie: Prof. dr. J.H. Gruzelier Prof. dr. R. van Ee Prof. dr. J.L. Kenemans Dr. R. Breteler Prof. dr. J.H.M. Vroomen Contents 1. General introduction 1 1.1. Introducing EEG training 2 1.2. Research objectives 5 1.3. Outline 9 2. Theoretical background: EEG alpha brain activity 13 2.1. Alpha EEG properties 14 2.2. The underlying neurophysiological origins of alpha activity 15 2.2.1. A gating mechanism 18 2.3. Functional significance 19 2.3.1. Mental state 19 2.3.2. Memory processes 20 2.3.3. Attention processes 21 2.3.4. Regulation of incoming information 24 2.3.5. Interim summary 26 2.4. Current alpha neurofeedback applications 26 2.4.1. Enhancing cognitive performance through stimulation 27 2.4.2. Enhancing cognitive, artistic and sports performance through neurofeedback 28 2.4.3. Enhancing well-being through neurofeedback 30 2.5. Future applications and conclusions 31 3. A novel self-guided approach to alpha activity training 33 3.1. Introduction 34 3.1.1. Alpha activity 34 3.1.2. Double-blind, placebo-controlled study design 36 3.1.3. Alpha activity training system 37 3.2. Study Method 39 3.2.1. Participants 39 3.2.2. Design and procedure 40 3.2.3. Data analysis 47 3.3. Results 49 3.3.1. Alpha power recorded with qEEG and with the novel system 49 3.3.2. Guided interviews 50 3.3.3. Behavioural data (questionnaires) 51 3.3.4. qEEG measurements 54 3.3.5. Heart rate variability 58 3.4. Discussion 59 4. The time-course of alpha neurofeedback training effects in healthy participants 67 4.1. Introduction 68 4.2. Study method 69 4.2.1. Participants 69 4.2.2. Design and procedure 69 4.2.3. Data analysis 70 4.2.4. Statistical analysis 70 4.3. Results 71 4.3.1. Alpha power between training sessions 71 4.3.2. Alpha power within training sessions 73 4.4. Discussion 76 5. Alpha neurofeedback and mental fitness in soldiers returning from deployment 79 5.1. Introduction 80 5.1.1. Background 80 5.1.2. Objectives 82 5.2. Study method 84 5.2.1. Participants 84 5.2.2. Design and procedure 84 5.2.3. Data analysis 89 5.2.4. Statistical analysis 91 5.3. Results 91 5.3.1. Demographics 91 5.3.2. Stress level of the participants at entry 91 5.3.3. Training experience 93 5.3.4. Training effects 94 5.4. Discussion 101 6. Feasibility of eyes open alpha power training for mental enhancement in elite gymnasts 107 6.1. Introduction 108 6.1.1. The alpha power training method 110 6.1.2. Aims of the present investigation 111 6.2. Study method 111 6.2.1. Participants 111 6.2.2. Design and procedure 112 6.2.3. Data analysis 116 6.2.4. Statistical analysis 116 6.3. Results 117 6.3.1. Alpha power 117 6.3.2. Training experiences 117 6.3.3. Questionnaires 120 6.3.4. Mental and physical shape during the training s. 121 6.3.5. Mood during the training sessions and simulated competition day 124 6.4. Discussion 126 7. General discussion 131 7.1. Study findings and applicability in healthy participants 132 7.1.1. Training effects in the (Q)EEG 132 7.1.2. Training effects in cognition, behaviour and well-being 136 7.2. Study limitations and recommendations 138 7.3. Conclusions and future applications 143 References 147 Supplementary information 177 Summary 193 Dutch summary (Nederlandse samenvatting) 197 Acknowledgements (Dankwoord) 201 Curriculum vitae 105 Chapter 1 General Introduction 1 1.1. Introducing EEG training In 1924, the German psychiatrist and neuroscientist Hans Berger discovered that the electrical activity of the human brain can be measured with electroencephalography (EEG) (Berger, 1929; Gloor, 1969). His findings followed previous attempts made with animals (such as dogs and frogs; Shaw, 2003). EEG is an imaging technique which records electrical neuron activity (i.e., synchronous postsynaptic potentials) using multiple electrodes on the surface of the head (Angelakis et al., 2007; Teplan, 2002). Although many neurons can produce local current flows (the human brain has around 1011 neurons in total), only large populations of active neurons can generate enough electrical activity to be recordable on the scalp (Teplan, 2002). Electrical brain activity can be measured for a specific time-window and then transformed (by Fast Fourier Transform) into a power spectrum (by presenting the power by frequency of the recorded signal), which was first performed and reported by Dietsch (1932). The EEG power spectrum can be used for analyses and interpretation; a method which is now known as quantitative (Q)EEG. Since the 1950s, the different frequency bands of the QEEG have been associated with a continuous scale of arousal (Lindsley, 1952). This scale, with deep sleep followed by coma at one end, and alertness at the other end of the scale, was associated with the human sleep-wake cycle (Steriade & Llinas, 1988). The ‘classical’ alpha rhythm (frequency band 8-12 Hz) was the first of these to be discovered during Berger’s early EEG measurements (1929) and appeared to be dominant in the human EEG. This rhythm, being roughly in the middle of the arousal scale, was found to be most prevalent in adults who were relaxed and awake with their eyes closed but was blocked by mental effort (Gloor, 1969). When a person starts to fall asleep the alpha rhythm diminishes, and theta waves (4-7 Hz) start appearing 2 (Ogilvie, 2001). The alpha rhythm is replaced by the beta rhythm (13-35 Hz) when a person is in a state of ‘alert attentiveness’ (Lindsley, 1960). Further to his discovery, Berger developed an interest in relating brain activity to mental processes (Shaw, 2003). Before using EEG, he had already made several attempts at measuring cerebral blood flow and metabolism (which is the fundamental basis of Positron Emission Tomography as it is known today; Shaw, 2003). Since then, many researchers have put effort into understanding the (Q)EEG and relating electrical brain activity to physiological and psychological processes, such as intelligence, personality, and attention (Lindsley, 1952). However, due to the great excitement surrounding new discoveries, many attempts were not taken seriously or experiments were not conducted on a sound enough basis (Lindsley, 1952). A few years after the discovery of the EEG, in the 1930s, it was discovered that rather than being static, the human brain has a self-organising character, now known as brain plasticity or neuroplasticity (already described by Konorski in 1948 (Livingston, 1966) and Hebb (Hebb, 1949)). That is, the human brain was found to respond to learning principles, such as classical conditioning, in which an unconditioned stimulus, giving a specific response, is replaced by a conditioned stimulus, giving a similar response. More specifically, an ‘alpha blocking response’ in the EEG was shown to be classically conditioned (e.g., Durup & Fessard, 1935). In the 1960s, the human brain was shown to respond to operant conditioning learning principles as well (Kamiya, 1962). Through operant or instrumental conditioning, the behaviour of an individual is modified by means of reward and punishment. Neurofeedback training (NFT) or EEG biofeedback is also a behaviour training technique in which individuals become aware of and learn to self-regulate their own electrical brain activity through operant conditioning.