The relationship between physical exercise and cognition in children with typical development and neurodevelopmental disorders

This research project sought to investigate the relationship between physical exercise and cognition in children with and without a neurodevelopmental condition. To achieve this aim, three approaches were undertaken to explore the exercise and cognition relationship. The first approach sought to understand the efficacy of exercise interventions on cognition in individuals with a neurodevelopmental disorder. The second approach was to understand the effectiveness of an exercise activity when compared to a cognitively-engaging tablet game activity on measures of implicit learning and attention in children with and without a neurodevelopmental condition. The third approach was to investigate if psychophysiological measures could account for the cognitive effect observed after exercising in children with and without a neurodevelopmental condition. Taking the approaches together, this research project focused on investigating the efficacy, effect, and mechanism of the exercise-cognition relationship. To investigate the efficacy of the exercise interventions, a meta-analytic review was conducted on 22 studies from the neurodevelopmental literature. The main findings from this meta-analysis revealed an overall small-to-medium effect size of exercise on cognition, supporting the efficacy of applying exercise interventions to young individuals with a neurodevelopmental disorder. Similar to the general population, physical exercise has been demonstrated to improve some but not all cognitive functions, with some individuals demonstrating no change in cognitive function after exercising. In terms of the effects of physical exercise, this project conducted an experimental study comparing a moderate-intensity exercise activity with a tablet game activity for a period of 12 minutes in 35 children aged 6-11 years. Overall, the study found that the effect of exercise was comparable to the tablet activity across the reaction time measures, but not on the accuracy performance of the implicit learning and attention tasks. Overall, exercise activity led to a better accuracy performance on implicit learning and executive attention compared to the tablet activity, particularly in children with a neurodevelopmental condition. The last part of this project was an extension of the experimental study whereby psychophysiological measures were investigated based on a proposed detrended fluctuation analysis (DFA). This investigation found that galvanic skin response (GSR), as indexed by its scaling exponent, was related to whether children revealed a change in cognitive function after receiving the exercise activity, particularly on executive attention. Importantly, this relationship was also able to account for children who did not demonstrate a cognitive effect of exercise. This result was not evident in the electroencephalogram (EEG) measures. This investigation concluded that the effect of exercise on executive attention was dependent on the interplay between an individual’s arousal system, cognitive task demand, and the novelty of the exercise activity. Taking the findings together, this project highlights the importance of individual differences to the exercise and cognition relationship. Specifically, this project demonstrated the feasibility of investigating the scaling exponent, via fractal analysis (e.g., DFA), as an index of individual differences. Additionally, fractal analysis is a valuable tool to assist in further understanding the mechanism underlying the exercise-cognition relationship, particularly on the influence of individual difference

Exploring the combined use of electrical and hemodynamic brain activity to investigate brain function

This thesis explored the relationship between electrical and metabolic aspects of brain functioning in health and disease, measured with QEEG and NIRS, in order to evaluate its clinical potential. First the limitations of NIRS were investigated, depicting its susceptibility to different types of motion artefacts and the inability of the CBSI-method to remove them from resting state data. Furthermore, the quality of the NIRS signals was poor in a significant portion of the investigated sample, reducing clinical potential. Different analysis methods were used to explore both EEG and NIRS, and their coupling in an eyes open eyes closed paradigm in healthy participants. It could be reproduced that during eyes closed blocks less HbO2 (p = 0.000), more Hbb (p = 0.008), and more alpha activity (p = 0.000) was present compared to eyes open blocks. Furthermore, dynamic cross correlation analysis reproduced a positive correlation between alpha and Hbb (r: 0.457 and 0.337) and a negative correlation between alpha and HbO2 (r: -0.380 and -0.366) with a delayed hemodynamic response (7 to 8s). This was only possible when removing all questionable and physiological illogical data, suggesting that an 8s hemodynamic delay might not be the golden standard. Also the inability of the cross correlation to take non-linear relationships into account may distort outcomes. Therefore, In chapter 5 non-linear aspects of the relationship were evaluated by introducing the measure of relative cross mutual information. A newly suggested approach and the most valuable contribution of the thesis since it broadens knowledge in the fields of EEG, NIRS and general time series analysis. Data of two stroke patients then showed differences from the healthy group between the coupling of EEG and NIRS. The differences in long range temporal correlations (p= 0.000 for both cases), entropy (p< 0.040 and p =0.000), and relative cross mutual information (p < 0.003 and p < 0.013) provide the proof of principle that these measures may have clinical utility. Even though more research is necessary before widespread clinical use becomes possible

Dynamic correlations in ongoing neuronal oscillations in humans - perspectives on brain function and its disorders

This Thesis is involved with neuronal oscillations in the human brain and their coordination across time, space and frequency. The aim of the Thesis was to quantify correlations in neuronal oscillations over these dimensions, and to elucidate their significance in cognitive processing and brain disorders. Magnetoencephalographic (MEG) recordings of major depression patients revealed that long-range temporal correlations (LRTC) were decreased, compared to control subjects, in the 5 Hz oscillations in a manner that was dependent on the degree of the disorder. While studying epileptic patients, on the other hand, it was found that the LRTC in neuronal oscillations recorded intracranially with electroencephalography (EEG) were strengthened in the seizure initiation region. A novel approach to map spatial correlations between cortical regions was developed. The method is based on parcellating the cortex to patches and estimating phase synchrony between all patches. Mapping synchrony from inverse-modelled MEG / EEG data revealed wide-spread phase synchronization during a visual working memory task. Furthermore, the network architectures of task-related synchrony were found to be segregated over frequency. Cross-frequency interactions were investigated with analyses of nested brain activity in data recorded with full-bandwidth EEG during a somatosensory detection task. According to these data, the phase of ongoing infra-slow fluctuations (ISF), which were discovered in the frequency band of 0.01-0.1 Hz, was correlated with the amplitude of faster > 1 Hz neuronal oscillations. Strikingly, the behavioral detection performance displayed similar dependency on the ISFs as the > 1 Hz neuronal oscillations. The studies composing this Thesis showed that correlations in neuronal oscillations are functionally related to brain disorders and cognitive processing. Such correlations are suggested to reveal the coordination of neuronal oscillations across time, space and frequency. The results contribute to system-level understanding of brain function

Underlying Mechanisms of Epilepsy

This book is a very provocative and interesting addition to the literature on Epilepsy. It offers a lot of appealing and stimulating work to offer food of thought to the readers from different disciplines. Around 5% of the total world population have seizures but only 0.9% is diagnosed with epilepsy, so it is very important to understand the differences between seizures and epilepsy, and also to identify the factors responsible for its etiology so as to have more effective therapeutic regime. In this book we have twenty chapters ranging from causes and underlying mechanisms to the treatment and side effects of epilepsy. This book contains a variety of chapters which will stimulate the readers to think about the complex interplay of epigenetics and epilepsy

Biochemical and electrophysiological markers predictive of return of spontaneous circulation and post-resuscitation outcome

The majority of patients resuscitated from cardiac arrest (CA) subsequently die due to post-cardiac arrest syndrome (PCAS), whose mechanisms are only partially understood. We adopted an approach of untargeted/targeted plasma metabolomics in rats to identify metabolites involved in the mechanisms of PCAS to be tested as predictors of outcome. Activation of the kynurenine pathway (KP) for tryptophan (TRP) degradation was demonstrated in rats, pigs and in a small cohort of patients. Decreases in TRP occurred during the post-CA period and were accompanied by significant increases in KP metabolites, 3-hydroxyanthranilic acid (3 -HAA) and kynurenic acid in each species, that persisted up to 3-5 days post-CA (p<0.01). KP metabolites changes were significantly related to the severity of myocardial and cerebral injuries and survival. Finally, when tested in 155 patients resuscitated from CA, KP metabolites were significantly higher in patients with poor outcomes. The quality of chest compression (CC) is another major issue for cardiopulmonary resuscitation (CPR) success and survival. The decision whether to interrupt CC to deliver a defibrillation (DF) is difficult. The potential benefit of a DF guided by a real time ventricular fibrillation (YF) waveform analysis would maximize DF success, minimize CC interruptions and myocardial damage by repetitive and unnecessary DFs. We evaluated amplitude spectrum area (AMSA) as predictor of DF outcome in two large databases of out-of-hospital VFs, from US (609 patients) and Italy (1.617 patients). AMSA was significantly higher prior to a successful DF than prior to an unsuccessful one (p<0.0001). Thresholds for prediction of successful and unsuccessful DFs were 16-17 mV-Hz for success and <7 mV-Hz for failure, with a positive predictive value of 80% and a negative predictive value of 97%. AMSA was a better predictor of DF outcome (AUC 0.86, p<0.0001) compared to other VF parameters, i.e. amplitude and frequencies. In conclusion, AMSA would be a useful tool for guiding CPR