Brain ictal state characterisation through multimodal information integration

This Thesis addresses the problem of automated false-positive free detection of epileptic events by the fusion of information extracted from simultaneously recorded electro-encephalographic (EEG) and the electrocardiographic (ECG) time-series. The approach relies on a biomedical case for the coupling of the Brain and Heart systems through the central autonomic network during temporal lobe epileptic events: neurovegetative manifestations associated with temporal lobe epileptic events consist of alterations to the cardiac rhythm. From a neurophysiological perspective, epileptic episodes are characterised by a loss of complexity of the state of the brain. The description of arrhythmias, from a probabilistic perspective, observed during temporal lobe epileptic events and the description of the complexity of the state of the brain, from an information theory perspective, are integrated in a fusion-of-information framework towards temporal lobe epileptic seizure detection. The main contributions of the Thesis include the introduction of a biomedical case for the coupling of the Brain and Heart systems during temporal lobe epileptic seizures, partially reported in the clinical literature; the investigation of measures for the characterisation of ictal events from the EEG time series towards their integration in a fusion-of-knowledge framework; the probabilistic description of arrhythmias observed during temporal lobe epileptic events towards their integration in a fusion-of-knowledge framework; and the investigation of the different levels of the fusion-of-information architecture at which to perform the combination of information extracted from the EEG and ECG time-series. The performance of the method designed in the Thesis for the false-positive free automated detection of epileptic events achieved a false-positives rate of zero on the dataset of long-term recordings used in the Thesis.

Which physiological components are more suitable for visual ERP based brain-computer interface?:A preliminary MEG/EEG study

We investigated which evoked response component occurring in the first 800 ms after stimulus presentation was most suitable to be used in a classical P300-based brain-computer interface speller protocol. Data was acquired from 275 Magnetoencephalographic sensors in two subjects and from 61 Electroencephalographic sensors in four. To better characterize the evoked physiological responses and minimize the effect of response overlap, a 1000 ms Inter Stimulus Interval was preferred to the short (

Disordered connectivity in the autistic brain:challenges for the 'new psychophysiology'

In 2002, we published a paper [Brock, J., Brown, C., Boucher, J., Rippon, G., 2002. The temporal binding deficit hypothesis of autism. Development and Psychopathology 142, 209-224] highlighting the parallels between the psychological model of 'central coherence' in information processing [Frith, U., 1989. Autism: Explaining the Enigma. Blackwell, Oxford] and the neuroscience model of neural integration or 'temporal binding'. We proposed that autism is associated with abnormalities of information integration that is caused by a reduction in the connectivity between specialised local neural networks in the brain and possible overconnectivity within the isolated individual neural assemblies. The current paper updates this model, providing a summary of theoretical and empirical advances in research implicating disordered connectivity in autism. This is in the context of changes in the approach to the core psychological deficits in autism, of greater emphasis on 'interactive specialisation' and the resultant stress on early and/or low-level deficits and their cascading effects on the developing brain [Johnson, M.H., Halit, H., Grice, S.J., Karmiloff-Smith, A., 2002. Neuroimaging of typical and atypical development: a perspective from multiple levels of analysis. Development and Psychopathology 14, 521-536].We also highlight recent developments in the measurement and modelling of connectivity, particularly in the emerging ability to track the temporal dynamics of the brain using electroencephalography (EEG) and magnetoencephalography (MEG) and to investigate the signal characteristics of this activity. This advance could be particularly pertinent in testing an emerging model of effective connectivity based on the balance between excitatory and inhibitory cortical activity [Rubenstein, J.L., Merzenich M.M., 2003. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes, Brain and Behavior 2, 255-267; Brown, C., Gruber, T., Rippon, G., Brock, J., Boucher, J., 2005. Gamma abnormalities during perception of illusory figures in autism. Cortex 41, 364-376]. Finally, we note that the consequence of this convergence of research developments not only enables a greater understanding of autism but also has implications for prevention and remediation. © 2006.

Preterm infants with video-EEG confirmed seizures:outcome at 30 months of age

Our aim was to identify early predictors of poor neurodevelopmental outcome and of subsequent epilepsy in very early preterm and late preterm newborns with neonatal seizures.

Hand somatosensory subcortical and cortical sources assessed by functional source separation:an EEG study

We propose a novel electroencephalographic application of a recently developed cerebral source extraction method (Functional Source Separation, FSS), which starts from extracranial signals and adds a functional constraint to the cost function of a basic independent component analysis model without requiring solutions to be independent. Five ad-hoc functional constraints were used to extract the activity reflecting the temporal sequence of sensory information processing along the somatosensory pathway in response to the separate left and right median nerve galvanic stimulation. Constraints required only the maximization of the responsiveness at specific latencies following sensory stimulation, without taking into account that any frequency or spatial information. After source extraction, the reliability of identified FS was assessed based on the position of single dipoles fitted on its retroprojected signals and on a discrepancy measure. The FS positions were consistent with previously reported data (two early subcortical sources localized in the brain stem and thalamus, the three later sources in cortical areas), leaving negligible residual activity at the corresponding latencies. The high-frequency component of the oscillatory activity (HFO) of the extracted component was analyzed. The integrity of the low amplitude HFOs was preserved for each FS. On the basis of our data, we suggest that FSS can be an effective tool to investigate the HFO behavior of the different neuronal pools, recruited at successive times after median nerve galvanic stimulation. As FSs are reconstructed along the entire experimental session, directional and dynamic HFO synchronization phenomena can be studied.

Brain connectivity in positive and negative syndrome schizophrenia

If, as is widely believed, schizophrenia is characterized by abnormalities of brain functional connectivity, then it seems reasonable to expect that different subtypes of schizophrenia could be discriminated in the same way. However, evidence for differences in functional connectivity between the subtypes of schizophrenia is largely lacking and, where it exists, it could be accounted for by clinical differences between the patients (e.g. medication) or by the limitations of the measures used. In this study, we measured EEG functional connectivity in unmedicated male patients diagnosed with either positive or negative syndrome schizophrenia and compared them with age and sex matched healthy controls. Using new methodology (Medkour et al., 2009) based on partial coherence, brain connectivity plots were constructed for positive and negative syndrome patients and controls. Reliable differences in the pattern of functional connectivity were found with both syndromes showing not only an absence of some of the connections that were seen in controls but also the presence of connections that the controls did not show. Comparing connectivity graphs using the Hamming distance, the negative-syndrome patients were found to be more distant from the controls than were the positive syndrome patients. Bootstrap distributions of these distances were created which showed a significant difference in the mean distances that was consistent with the observation that negative-syndrome diagnosis is associated with a more severe form of schizophrenia. We conclude that schizophrenia is characterized by widespread changes in functional connectivity with negative syndrome patients showing a more extreme pattern of abnormality than positive syndrome patients.

Contradictory reasoning network:an EEG and FMRI study

Contradiction is a cornerstone of human rationality, essential for everyday life and communication. We investigated electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) in separate recording sessions during contradictory judgments, using a logical structure based on categorical propositions of the Aristotelian Square of Opposition (ASoO). The use of ASoO propositions, while controlling for potential linguistic or semantic confounds, enabled us to observe the spatial temporal unfolding of this contradictory reasoning. The processing started with the inversion of the logical operators corresponding to right middle frontal gyrus (rMFG-BA11) activation, followed by identification of contradictory statement associated with in the right inferior frontal gyrus (rIFG-BA47) activation. Right medial frontal gyrus (rMeFG, BA10) and anterior cingulate cortex (ACC, BA32) contributed to the later stages of process. We observed a correlation between the delayed latency of rBA11 response and the reaction time delay during inductive vs. deductive reasoning. This supports the notion that rBA11 is crucial for manipulating the logical operators. Slower processing time and stronger brain responses for inductive logic suggested that examples are easier to process than general principles and are more likely to simplify communication. © 2014 Porcaro et al.

Hypnotic induction is followed by state-like changes in the organization of EEG functional connectivity in the theta and beta frequency bands in high-hypnotically susceptible individuals

Altered state theories of hypnosis posit that a qualitatively distinct state of mental processing, which emerges in those with high hypnotic susceptibility following a hypnotic induction, enables the generation of anomalous experiences in response to specific hypnotic suggestions. If so then such a state should be observable as a discrete pattern of changes to functional connectivity (shared information) between brain regions following a hypnotic induction in high but not low hypnotically susceptible participants. Twenty-eight channel EEG was recorded from 12 high susceptible (highs) and 11 low susceptible (lows) participants with their eyes closed prior to and following a standard hypnotic induction. The EEG was used to provide a measure of functional connectivity using both coherence (COH) and the imaginary component of coherence (iCOH), which is insensitive to the effects of volume conduction. COH and iCOH were calculated between all electrode pairs for the frequency bands: delta (0.1-3.9 Hz), theta (4-7.9 Hz) alpha (8-12.9 Hz), beta1 (13-19.9 Hz), beta2 (20-29.9 Hz) and gamma (30-45 Hz). The results showed that there was an increase in theta iCOH from the pre-hypnosis to hypnosis condition in highs but not lows with a large proportion of significant links being focused on a central-parietal hub. There was also a decrease in beta1 iCOH from the pre-hypnosis to hypnosis condition with a focus on a fronto-central and an occipital hub that was greater in high compared to low susceptibles. There were no significant differences for COH or for spectral band amplitude in any frequency band. The results are interpreted as indicating that the hypnotic induction elicited a qualitative change in the organization of specific control systems within the brain for high as compared to low susceptible participants. This change in the functional organization of neural networks is a plausible indicator of the much theorized "hypnotic-state". © 2014 Jamieson and Burgess.

Altered resting-state EEG source functional connectivity in schizophrenia:the effect of illness duration

Despite the increasing body of evidence supporting the hypothesis of schizophrenia as a disconnection syndrome, studies of resting-state EEG Source Functional Connectivity (EEG-SFC) in people affected by schizophrenia are sparse. The aim of the present study was to investigate resting-state EEG-SFC in 77 stable, medicated patients with schizophrenia (SCZ) compared to 78 healthy volunteers (HV). In order to study the effect of illness duration, SCZ were divided in those with a short duration of disease (SDD; n = 25) and those with a long duration of disease (LDD; n = 52). Resting-state EEG recordings in eyes closed condition were analyzed and lagged phase synchronization (LPS) indices were calculated for each ROI pair in the source-space EEG data. In delta and theta bands, SCZ had greater EEG-SFC than HV; a higher theta band connectivity in frontal regions was observed in LDD compared with SDD. In the alpha band, SCZ showed lower frontal EEG-SFC compared with HV whereas no differences were found between LDD and SDD. In the beta1 band, SCZ had greater EEG-SFC compared with HVs and in the beta2 band, LDD presented lower frontal and parieto-temporal EEG-SFC compared with HV. In the gamma band, SDD had greater connectivity values compared with LDD and HV. This study suggests that resting state brain network connectivity is abnormally organized in schizophrenia, with different patterns for the different EEG frequency components and that EEG can be a powerful tool to further elucidate the complexity of such disordered connectivity.

Comparing interaction techniques for serious games through brain-computer interfaces:a user perception evaluation study

This paper examines the application of commercial and non-invasive electroencephalography (EEG)-based brain-computer (BCIs) interfaces with serious games. Two different EEG-based BCI devices were used to fully control the same serious game. The first device (NeuroSky MindSet) uses only a single dry electrode and requires no calibration. The second device (Emotiv EPOC) uses 14 wet sensors requiring additional training of a classifier. User testing was performed on both devices with sixty-two participants measuring the player experience as well as key aspects of serious games, primarily learnability, satisfaction, performance and effort. Recorded feedback indicates that the current state of BCIs can be used in the future as alternative game interfaces after familiarisation and in some cases calibration. Comparative analysis showed significant differences between the two devices. The first device provides more satisfaction to the players whereas the second device is more effective in terms of adaptation and interaction with the serious game.

Case study: auditory brain responses in a minimally verbal child with autism and cerebral palsy

An estimated 30% of individuals with autism spectrum disorders (ASD) remain minimally verbal into late childhood, but research on cognition and brain function in ASD focuses almost exclusively on those with good or only moderately impaired language. Here we present a case study investigating auditory processing of GM, a nonverbal child with ASD and cerebral palsy. At the age of 8 years, GM was tested using magnetoencephalography (MEG) whilst passively listening to speech sounds and complex tones. Where typically developing children and verbal autistic children all demonstrated similar brain responses to speech and nonspeech sounds, GM produced much stronger responses to nonspeech than speech, particularly in the 65–165 ms (M50/M100) time window post-stimulus onset. GM was retested aged 10 years using electroencephalography (EEG) whilst passively listening to pure tone stimuli. Consistent with her MEG response to complex tones, GM showed an unusually early and strong response to pure tones in her EEG responses. The consistency of the MEG and EEG data in this single case study demonstrate both the potential and the feasibility of these methods in the study of minimally verbal children with ASD. Further research is required to determine whether GM's atypical auditory responses are characteristic of other minimally verbal children with ASD or of other individuals with cerebral palsy.

Brain activity modifications following spinal cord stimulation for chronic neuropathic pain:a systematic review

Background and objective: Spinal cord stimulation (SCS) is believed to exert supraspinal effects; however, these mechanisms are still far from fully elucidated. This systematic review aims to assess existing neurophysiological and functional neuroimaging literature to reveal current knowledge regarding the effects of SCS for chronic neuropathic pain on brain activity, to identify gaps in knowledge, and to suggest directions for future research. Databases and data treatment: Electronic databases and hand-search of reference lists were employed to identify publications investigating brain activity associated with SCS in patients with chronic neuropathic pain, using neurophysiological and functional neuroimaging techniques (fMRI, PET, MEG, EEG). Studies investigating patients with SCS for chronic neuropathic pain and studying brain activity related to SCS were included. Demographic data (age, gender), study factors (imaging modality, patient diagnoses, pain area, duration of SCS at recording, stimulus used) and brain areas activated were extracted from the included studies. Results: Twenty-four studies were included. Thirteen studies used neuroelectrical imaging techniques, eight studies used haemodynamic imaging techniques, two studies employed both neuroelectrical and haemodynamic techniques separately, and one study investigated cerebral neurobiology. Conclusions: The limited available evidence regarding supraspinal mechanisms of SCS does not allow us to develop any conclusive theories. However, the studies included appear to show an inhibitory effect of SCS on somatosensory evoked potentials, as well as identifying the thalamus and anterior cingulate cortex as potential mediators of the pain experience. The lack of substantial evidence in this area highlights the need for large-scale controlled studies of this kind.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.