The brain is a complex dynamic and self-organizing system. Normal brain function emerges from synchronized neuronal firing between local neurons which are integrated into large scale networks via white matter tracts. Normal brain function and consciousness arise from the continual integration and dissolution of neuronal networks, and this fluctuation in synchronization is termed variability. Brain electrical activity is recorded as local field potentials using electroencephalography (EEG). The phase synchrony and variability of EEG waveforms can be quantified. The healthy brain exhibits a relatively low degree of phase synchrony and a high degree of variability. Clinicians are interested in using a complex system approach to brain function to provide dynamic information on neuronal physiology and pathology not available by other evaluation methods. A common challenge in paediatric critical care is evaluation of the comatose child post brain injury. Coma and medical interventions confound the clinical examination making monitoring and prognostication of outcome difficult. Brain cells and white matter tracts are disrupted post injury altering the phase synchrony between neuronal networks. It is proposed in this thesis that the estimation of the variability in EEG phase synchrony can evaluate paediatric brain function. The EEG recordings of normal children and patients in coma post brain injury are used, in a series of studies, to test the main hypothesis that slow EEG wave brain states associated with brain injury have higher magnitudes of EEG phase synchrony and lower variability values than those of EEG waves associated with consciousness. Further, the effects of age, brain development brain and the effect of a conscious slow wave EEG state (hyperventilation) on phase synchrony and variability are evaluated. Results of the studies showed that EEG phase synchrony is increased in all slow wave states and is highest in comatose children with poor neurological outcome. Younger children’s brains have higher phase synchrony than older children. The variability of the EEG phase synchrony differentiates between the awake (higher values) and unconscious states (lower values). Physiologic models underlying EEG phase synchrony are discussed. The EEG phase synchrony and variability measures provide new insight into paediatric brain function.

The brain is a complex dynamic and self-organizing system. Normal brain function emerges from synchronized neuronal firing between local neurons which are integrated into large scale networks via white matter tracts. Normal brain function and consciousness arise from the continual integration and dissolution of neuronal networks, and this fluctuation in synchronization is termed variability. Brain electrical activity is recorded as local field potentials using electroencephalography (EEG). The phase synchrony and variability of EEG waveforms can be quantified. The healthy brain exhibits a relatively low degree of phase synchrony and a high degree of variability. Clinicians are interested in using a complex system approach to brain function to provide dynamic information on neuronal physiology and pathology not available by other evaluation methods. A common challenge in paediatric critical care is evaluation of the comatose child post brain injury. Coma and medical interventions confound the clinical examination making monitoring and prognostication of outcome difficult. Brain cells and white matter tracts are disrupted post injury altering the phase synchrony between neuronal networks. It is proposed in this thesis that the estimation of the variability in EEG phase synchrony can evaluate paediatric brain function. The EEG recordings of normal children and patients in coma post brain injury are used, in a series of studies, to test the main hypothesis that slow EEG wave brain states associated with brain injury have higher magnitudes of EEG phase synchrony and lower variability values than those of EEG waves associated with consciousness. Further, the effects of age, brain development brain and the effect of a conscious slow wave EEG state (hyperventilation) on phase synchrony and variability are evaluated. Results of the studies showed that EEG phase synchrony is increased in all slow wave states and is highest in comatose children with poor neurological outcome. Younger children’s brains have higher phase synchrony than older children. The variability of the EEG phase synchrony differentiates between the awake (higher values) and unconscious states (lower values). Physiologic models underlying EEG phase synchrony are discussed. The EEG phase synchrony and variability measures provide new insight into paediatric brain function.

Children and adolescents with autism spectrum disorder (ASD) were compared to age-matched typically developing controls in the context of phase synchrony statistics acquired through magnetoencephalography. Subjects performed a “low-attention” task, pressing a button to a single, repeated auditory tone, and this was contrasted to an “oddball” task where they were required to button press only to deviant tones. The differences in task outcomes were primarily thought to relate to differences in sensory and executive attention. Regardless of task condition, ASD subjects showed greater magnitudes of synchrony between the parietal hemispheres which variably extended across frequencies. Additionally, for ASD subjects, increases in synchrony from the “low-attention” task to the “oddball” task were observed; whereas an opposite tendency occurred for controls. Furthermore, rates of fluctuation of phase differences showed more stable parietal synchrony within ASD across the hemispheric midline. Implications including the possibility of coordination as an indicator of ASD are discussed.

Children and adolescents with autism spectrum disorder (ASD) were compared to age-matched typically developing controls in the context of phase synchrony statistics acquired through magnetoencephalography. Subjects performed a “low-attention” task, pressing a button to a single, repeated auditory tone, and this was contrasted to an “oddball” task where they were required to button press only to deviant tones. The differences in task outcomes were primarily thought to relate to differences in sensory and executive attention. Regardless of task condition, ASD subjects showed greater magnitudes of synchrony between the parietal hemispheres which variably extended across frequencies. Additionally, for ASD subjects, increases in synchrony from the “low-attention” task to the “oddball” task were observed; whereas an opposite tendency occurred for controls. Furthermore, rates of fluctuation of phase differences showed more stable parietal synchrony within ASD across the hemispheric midline. Implications including the possibility of coordination as an indicator of ASD are discussed.

SUMMARY Introduction: There has recently been a great deal of interest in the role of synchronous high-frequency gamma oscillations in brain function. This interest has been motivated by an increasing body of evidence, that oscillations which are synchronous in phase across separated neuronal populations, may represent an important mechanism by which the brain binds or integrates spatially distributed processing activity which is related to the same object. Many models of schizophrenia suggest an impairment in the integration of brain processing, such as a loosening of associations, disconnection, defective multiple constraint organization, or cognitive dysmetria. This has led to recent speculation that abnormalities of high-frequency gamma synchronization may reflect a core dimension of the disturbance underlying this disorder. However, examination of the phase synchronization of gamma oscillations in patients with schizophrenia has never been previously undertaken. Method: In this thesis a new method of analysis of gamma synchrony was introduced, which enables the phase relationships of oscillations in a specific frequency band to be examined across multiple scalp sites as a function of time. This enabled, for the first time, the phase synchronization of gamma oscillations across widespread regions, to be studied in electrical brain activity measured at the scalp in humans. Gamma synchrony responses were studied in electroencephalographic (EEG) data acquired during a commonly employed conventional auditory oddball paradigm. The research consisted of two sets of experiments. In the first set of experiments, data from 100 normal subjects, consisting of 10 males and 10 females in each age decade from 20 to 70, was examined. These experiments were designed to characterize the gamma synchonizations that occurred in response to target and background stimuli and their functional significance in normal brain activity, and to exclude the possibility of these findings being due to electromyogram (EMG) or volume conduction artifact. The examination of functional significance involved the development of an additional new analysis technique. In the second set of experiments, data acquired from 35 patients with schizophrenia and 35 matched normal controls was analyzed. The purpose of these experiments was to determine whether patients showed disturbances of gamma synchrony compared to controls, and to establish the relationship of any such disturbances to medication levels, symptom profiles, duration of illness, and a range of psychophysiological variables. Results: In the 100 normals, responses to target stimuli were characterized by two bursts of synchronous gamma oscillations, an early (evoked) and a late (induced) synchronization, with different topographic distributions. Only the early gamma synchronization was seen in response to background stimuli. The main variable modulating the magnitude of these gamma synchronizations from epoch to epoch was pre-stimulus EEG theta (3-7 Hz) and delta (1-3 Hz) power. Early and late gamma synchrony were also associated with N1 and P3 ERP component amplitude across epochs. Across subjects, the early gamma synchronization was associated with shorter latency of the ERP components P2, N2 and P3, smaller amplitude of N1 and P2, and smaller pre-stimulus beta power. The control analyses showed that these gamma responses were specific to a narrow frequency range (37 to 41 Hz), and were not present in adjacent frequency bands. The responses were not generated by EMG contamination or volume conduction. In the 35 patients with schizophrenia, significant abnormalities of both the early and late synchronizations were observed compared to the 35 normal controls, with distinctive topographic characteristics. In general, early gamma synchrony was increased in patients compared to controls, and late gamma synchrony was decreased. These gamma synchrony disturbances were not related to medication level or the four summed symptom profile scores (positive, negative, general and total). They were, however, associated with duration of illness, becoming less severe the longer the patient had suffered from the disorder. The disordered gamma synchrony in patients was not secondary to abnormalities in other psychophysiological variables, but appeared to represent a primary disturbance. Discussion: The early synchronization may relate to the binding of object representations in early sensory processing, or, given that a constant inter-stimulus interval was employed, may be anticipatory and related to active memory. The late response is probably involved in binding in relation to activation of the internal contextual model involved in late expectancy/contextual processing (context updating or context closure) for target stimuli. The across epochs effects may relate to whether the focus of attention immediately prior to stimulus presentation is internal or is directed at the task. The across subjects effects suggest that a larger magnitude of the early gamma synchronization might indicate that the subject maintains a more stable and less ambiguous internal representation of the environment, that reduces the complexity of input and facilitates target/background discrimination and subsequent processing. The early gamma synchronization findings in patients with schizophrenia suggest that anticipatory processing involving active memory and forward-prediction of the environment is subject to over-binding or the formation of inappropriate associations. The late synchronization disturbances may reflect a fragmentation of contextual processing, and an inability to maintain contextual models of the environment intact over time. Conclusion: This research demonstrates the potential importance of integrative network activity as indexed by gamma phase synchrony in relation to normal cognition, and the possible broad relevance of such activity in psychiatric disorders. In particular, the application in this study to patients with schizophrenia showed that an impairment of brain integrative activity (missing links) might be a key feature of this illness.

SUMMARY Introduction: There has recently been a great deal of interest in the role of synchronous high-frequency gamma oscillations in brain function. This interest has been motivated by an increasing body of evidence, that oscillations which are synchronous in phase across separated neuronal populations, may represent an important mechanism by which the brain binds or integrates spatially distributed processing activity which is related to the same object. Many models of schizophrenia suggest an impairment in the integration of brain processing, such as a loosening of associations, disconnection, defective multiple constraint organization, or cognitive dysmetria. This has led to recent speculation that abnormalities of high-frequency gamma synchronization may reflect a core dimension of the disturbance underlying this disorder. However, examination of the phase synchronization of gamma oscillations in patients with schizophrenia has never been previously undertaken. Method: In this thesis a new method of analysis of gamma synchrony was introduced, which enables the phase relationships of oscillations in a specific frequency band to be examined across multiple scalp sites as a function of time. This enabled, for the first time, the phase synchronization of gamma oscillations across widespread regions, to be studied in electrical brain activity measured at the scalp in humans. Gamma synchrony responses were studied in electroencephalographic (EEG) data acquired during a commonly employed conventional auditory oddball paradigm. The research consisted of two sets of experiments. In the first set of experiments, data from 100 normal subjects, consisting of 10 males and 10 females in each age decade from 20 to 70, was examined. These experiments were designed to characterize the gamma synchonizations that occurred in response to target and background stimuli and their functional significance in normal brain activity, and to exclude the possibility of these findings being due to electromyogram (EMG) or volume conduction artifact. The examination of functional significance involved the development of an additional new analysis technique. In the second set of experiments, data acquired from 35 patients with schizophrenia and 35 matched normal controls was analyzed. The purpose of these experiments was to determine whether patients showed disturbances of gamma synchrony compared to controls, and to establish the relationship of any such disturbances to medication levels, symptom profiles, duration of illness, and a range of psychophysiological variables. Results: In the 100 normals, responses to target stimuli were characterized by two bursts of synchronous gamma oscillations, an early (evoked) and a late (induced) synchronization, with different topographic distributions. Only the early gamma synchronization was seen in response to background stimuli. The main variable modulating the magnitude of these gamma synchronizations from epoch to epoch was pre-stimulus EEG theta (3-7 Hz) and delta (1-3 Hz) power. Early and late gamma synchrony were also associated with N1 and P3 ERP component amplitude across epochs. Across subjects, the early gamma synchronization was associated with shorter latency of the ERP components P2, N2 and P3, smaller amplitude of N1 and P2, and smaller pre-stimulus beta power. The control analyses showed that these gamma responses were specific to a narrow frequency range (37 to 41 Hz), and were not present in adjacent frequency bands. The responses were not generated by EMG contamination or volume conduction. In the 35 patients with schizophrenia, significant abnormalities of both the early and late synchronizations were observed compared to the 35 normal controls, with distinctive topographic characteristics. In general, early gamma synchrony was increased in patients compared to controls, and late gamma synchrony was decreased. These gamma synchrony disturbances were not related to medication level or the four summed symptom profile scores (positive, negative, general and total). They were, however, associated with duration of illness, becoming less severe the longer the patient had suffered from the disorder. The disordered gamma synchrony in patients was not secondary to abnormalities in other psychophysiological variables, but appeared to represent a primary disturbance. Discussion: The early synchronization may relate to the binding of object representations in early sensory processing, or, given that a constant inter-stimulus interval was employed, may be anticipatory and related to active memory. The late response is probably involved in binding in relation to activation of the internal contextual model involved in late expectancy/contextual processing (context updating or context closure) for target stimuli. The across epochs effects may relate to whether the focus of attention immediately prior to stimulus presentation is internal or is directed at the task. The across subjects effects suggest that a larger magnitude of the early gamma synchronization might indicate that the subject maintains a more stable and less ambiguous internal representation of the environment, that reduces the complexity of input and facilitates target/background discrimination and subsequent processing. The early gamma synchronization findings in patients with schizophrenia suggest that anticipatory processing involving active memory and forward-prediction of the environment is subject to over-binding or the formation of inappropriate associations. The late synchronization disturbances may reflect a fragmentation of contextual processing, and an inability to maintain contextual models of the environment intact over time. Conclusion: This research demonstrates the potential importance of integrative network activity as indexed by gamma phase synchrony in relation to normal cognition, and the possible broad relevance of such activity in psychiatric disorders. In particular, the application in this study to patients with schizophrenia showed that an impairment of brain integrative activity (missing links) might be a key feature of this illness.

Complexity lies halfway between stochasticity and determinism, suggesting that brain activity is neither fully random nor fully predictable but lives by the rules of nonlinear high- and low-complexity dynamics. One important aspect of brain function is noise-like activity (NLA), defined as background, electrical potential fluctuations in the nervous system distinct from spiking rhythms in the foreground. The objective of this thesis was to investigate the neurodynamical complexity of NLA recorded at the cellular and local network scales in in vitro preparations of mouse and human hippocampal tissue, under healthy and epileptiform conditions. In particular, it was found that neuronal NLA arises out of the physiological contributions of gap junctions and chemical synaptic channels and is characterized by a spectrum of complexity, ranging from high- to low-complexity, that was measured using methods from nonlinear dynamical systems theory. Importantly, the complexity of background, neuronal NLA was shown to depend on the degree of cellular interconnectivity to the surrounding local network. In addition, the complexity and multifractality of NLA was further studied at the cellular and local network scales in epileptiform transitions to seizure-like events, identifying emergent low-complexity and reduced multifractality (bordering on monofractal-type dynamics) in the pathological ictal state. Finally, dual intracellular recordings of hippocampal epileptiform activity were analyzed to measure NLA synchronicity, showing evidence for increased same- and cross-frequency correlations and increased phase synchronization in the pathological ictal state. Convergence towards increased phase synchrony manifested in lower frequency regions including theta (4-10 Hz) and beta (12-30 Hz), but also in higher frequency bands (gamma, 30-80 Hz). In summary, there is evidence to suggest that background NLA captures important neurodynamical information pertinent to the classification and identification of brain state transitions in healthy and epileptiform hippocampal dynamics, using sophisticated neuroengineering analyses of these physiological signals.

Complexity lies halfway between stochasticity and determinism, suggesting that brain activity is neither fully random nor fully predictable but lives by the rules of nonlinear high- and low-complexity dynamics. One important aspect of brain function is noise-like activity (NLA), defined as background, electrical potential fluctuations in the nervous system distinct from spiking rhythms in the foreground. The objective of this thesis was to investigate the neurodynamical complexity of NLA recorded at the cellular and local network scales in in vitro preparations of mouse and human hippocampal tissue, under healthy and epileptiform conditions. In particular, it was found that neuronal NLA arises out of the physiological contributions of gap junctions and chemical synaptic channels and is characterized by a spectrum of complexity, ranging from high- to low-complexity, that was measured using methods from nonlinear dynamical systems theory. Importantly, the complexity of background, neuronal NLA was shown to depend on the degree of cellular interconnectivity to the surrounding local network. In addition, the complexity and multifractality of NLA was further studied at the cellular and local network scales in epileptiform transitions to seizure-like events, identifying emergent low-complexity and reduced multifractality (bordering on monofractal-type dynamics) in the pathological ictal state. Finally, dual intracellular recordings of hippocampal epileptiform activity were analyzed to measure NLA synchronicity, showing evidence for increased same- and cross-frequency correlations and increased phase synchronization in the pathological ictal state. Convergence towards increased phase synchrony manifested in lower frequency regions including theta (4-10 Hz) and beta (12-30 Hz), but also in higher frequency bands (gamma, 30-80 Hz). In summary, there is evidence to suggest that background NLA captures important neurodynamical information pertinent to the classification and identification of brain state transitions in healthy and epileptiform hippocampal dynamics, using sophisticated neuroengineering analyses of these physiological signals.