Identification of brain epileptiform discharges from electroencephalograms

Brain interictal epileptiform discharges (IEDs), as the fundamental indicators of seizure, are transient events occurring between two or before seizure onsets, captured using electroencephalogram (EEG). For epilepsy diagnosis and localization of seizure sources, both interictal and ictal recordings are extremely informative. Accurate detection of IEDs from over the scalp helps faster diagnosis of epilepsy. The scalp EEG (sEEG) suffers from a low signal-to-noise ratio and high attenuation of IEDs due to the high skull electrical impedance. On the other hand, the intracranial EEG (iEEG) recorded using implanted electrodes enjoys high temporal-spatial resolution and enables capturing most IEDs. Therefore, in this thesis, the focus is on the identification of IEDs from the concurrent scalp and intracranial EEGs. Multi-way analysis provides an opportunity to jointly analyse the data in different domains. IEDs may share some features within and between the segments. We have developed methods based on multi-way analysis and tensor factorization to detect the IEDs from the concurrent sEEG in both segmented and real-time approaches. The diversities in IED morphology, strength, and source location within the brain cause a great deal of uncertainty in their labeling by clinicians. We have exploited and incorporated this uncertainty (the probability of the waveform being an IED) in an IED detection system. Furthermore, IEDs are naturally sparse. We have benefited from the sparsity of IED waveforms in developing an algorithm to exploit sparse common features among the IED segments, referred to as sparse common feature analysis. By mapping sEEG to iEEG, the sEEG quality is improved. In this thesis, the proposed tensor factorization maps the time-frequency features of sEEG to those of iEEG to detect the IEDs from over the scalp with high sensitivity. We have concatenated time, frequency, and channel modes of iEEG recordings into a tensor. After decomposing the tensor into temporal, spectral, and spatial components, the EEG time-frequency features have been extracted and projected onto the temporal components. Furthermore, we have developed two novel algorithms based on generative adversarial networks to map the raw sEEG to iEEG. As a result of this work, the visibility of IEDs from sEEG has over 4-fold improvement. Additionally, the outcome paves the path for future research in epilepsy prediction, seizure source localisation, and modeling the brain seizure pathways

Epilepsy

With the vision of including authors from different parts of the world, different educational backgrounds, and offering open-access to their published work, InTech proudly presents the latest edited book in epilepsy research, Epilepsy: Histological, electroencephalographic, and psychological aspects. Here are twelve interesting and inspiring chapters dealing with basic molecular and cellular mechanisms underlying epileptic seizures, electroencephalographic findings, and neuropsychological, psychological, and psychiatric aspects of epileptic seizures, but non-epileptic as well

Functional Imaging Studies of Speech and Verbal Memory in Healthy Adults and Patients with Alzheimer’s Disease

Alzheimer’s disease (AD) results in a diffuse, but characteristic impairment of cognitive function, with early involvement of verbal episodic memory. A prodromal phase of amnestic mild cognitive impairment (MCI) consists of patients with a mild, isolated impairment of episodic memory. In this thesis, I have described experiments performed on these patients and healthy volunteers using functional magnetic resonance imaging (fMRI). I aimed to investigate changes in neural activity associated with the breakdown in verbal episodic memory. Initially, I established the feasibility of using fMRI to investigate spoken responses in a study of speech production in healthy volunteers. This was important for investigating spoken retrieval of episodic memory. I also demonstrated integration of perceptual feedback and motor feedforward responses during propositional speech production within the medial planum temporale, associated with suppression of activity in secondary somatosensory cortex within the parietal operculum. In the verbal memory study, I demonstrated that successful encoding of heard sentences was associated with greater activity in cortical regions associated with semantic processing, but lower activity within early auditory cortex; implying a “top-down” effect on early perceptual cortex, related to sustained auditory attention. Patients with AD did not show this top-down effect. In addition, less activity was observed during encoding in AD patients, compared to MCI patients or controls, in regions associated with motivation. In the medial temporal lobes, there was less activity in AD compared to controls, but higher activity in MCI, consistent with previous reports. During retrieval, there was less activity in frontal executive control systems in AD compared to controls. This was seen in both performance-matched comparisons and in the neural response to a reduction in retrieval performance. MCI patients showed early changes in parietal lobe retrieval performance-related activity. Overall, the reduced verbal encoding performance in AD was related to impairments in the function of both MTL memory-related systems and sustained auditory attention, and was associated with reduced motivation. During free recall, lower performance in AD was associated with impairment of frontal cognitive control. Therefore, I have shown that verbal episodic memory impairment in AD is the consequence of altered activity in multiple cognitive networks, in addition to the well-recognised impairments in the MTL-memory network. These results have implications for future therapeutic interventions to improve memory function in this patient group, highlighting the potential use of drugs that enhance attention, motivation and frontal executive function

Paradigm free mapping: detection and characterization of single trial fMRI BOLD responses without prior stimulus information

The increased contrast to noise ratio available at Ultrahigh (7T) Magnetic Resonance Imaging (MRI) allows mapping in space and time the brain's response to single trial events with functional MRI (fMRI) based on the Blood Oxygenation Level Dependent (BOLD) contrast. This thesis primarily concerns with the development of techniques to detect and characterize single trial event-related BOLD responses without prior paradigm information, Paradigm Free Mapping, and assess variations in BOLD sensitivity across brain regions at high field fMRI. Based on a linear haemodynamic response model, Paradigm Free Mapping (PFM) techniques rely on the deconvolution of the neuronal-related signal driving the BOLD effect using regularized least squares estimators. The first approach, named PFM, builds on the ridge regression estimator and spatio-temporal t-statistics to detect statistically significant changes in the deconvolved fMRI signal. The second method, Sparse PFM, benefits from subset selection features of the LASSO and Dantzig Selector estimators that automatically detect the single trial BOLD responses by promoting a sparse deconvolution of the signal. The third technique, Multicomponent PFM, exploits further the benefits of sparse estimation to decompose the fMRI signal into a haemodynamical component and a baseline component using the morphological component analysis algorithm. These techniques were evaluated in simulations and experimental fMRI datasets, and the results were compared with well-established fMRI analysis methods. In particular, the methods developed here enabled the detection of single trial BOLD responses to visually-cued and self-paced finger tapping responses without prior information of the events. The potential application of Sparse PFM to identify interictal discharges in idiopathic generalized epilepsy was also investigated. Furthermore, Multicomponent PFM allowed us to extract cardiac and respiratory fluctuations of the signal without the need of physiological monitoring. To sum up, this work demonstrates the feasibility to do single trial fMRI analysis without prior stimulus or physiological information using PFM techniques

Paradigm free mapping: detection and characterization of single trial fMRI BOLD responses without prior stimulus information

The increased contrast to noise ratio available at Ultrahigh (7T) Magnetic Resonance Imaging (MRI) allows mapping in space and time the brain's response to single trial events with functional MRI (fMRI) based on the Blood Oxygenation Level Dependent (BOLD) contrast. This thesis primarily concerns with the development of techniques to detect and characterize single trial event-related BOLD responses without prior paradigm information, Paradigm Free Mapping, and assess variations in BOLD sensitivity across brain regions at high field fMRI. Based on a linear haemodynamic response model, Paradigm Free Mapping (PFM) techniques rely on the deconvolution of the neuronal-related signal driving the BOLD effect using regularized least squares estimators. The first approach, named PFM, builds on the ridge regression estimator and spatio-temporal t-statistics to detect statistically significant changes in the deconvolved fMRI signal. The second method, Sparse PFM, benefits from subset selection features of the LASSO and Dantzig Selector estimators that automatically detect the single trial BOLD responses by promoting a sparse deconvolution of the signal. The third technique, Multicomponent PFM, exploits further the benefits of sparse estimation to decompose the fMRI signal into a haemodynamical component and a baseline component using the morphological component analysis algorithm. These techniques were evaluated in simulations and experimental fMRI datasets, and the results were compared with well-established fMRI analysis methods. In particular, the methods developed here enabled the detection of single trial BOLD responses to visually-cued and self-paced finger tapping responses without prior information of the events. The potential application of Sparse PFM to identify interictal discharges in idiopathic generalized epilepsy was also investigated. Furthermore, Multicomponent PFM allowed us to extract cardiac and respiratory fluctuations of the signal without the need of physiological monitoring. To sum up, this work demonstrates the feasibility to do single trial fMRI analysis without prior stimulus or physiological information using PFM techniques

Functional imaging studies of visual-auditory integration in man.

This thesis investigates the central nervous system's ability to integrate visual and auditory information from the sensory environment into unified conscious perception. It develops the possibility that the principle of functional specialisation may be applicable in the multisensory domain. The first aim was to establish the neuroanatomical location at which visual and auditory stimuli are integrated in sensory perception. The second was to investigate the neural correlates of visual-auditory synchronicity, which would be expected to play a vital role in establishing which visual and auditory stimuli should be perceptually integrated. Four functional Magnetic Resonance Imaging studies identified brain areas specialised for: the integration of dynamic visual and auditory cues derived from the same everyday environmental events (Experiment 1), discriminating relative synchronicity between dynamic, cyclic, abstract visual and auditory stimuli (Experiment 2 & 3) and the aesthetic evaluation of visually and acoustically perceived art (Experiment 4). Experiment 1 provided evidence to suggest that the posterior temporo-parietal junction may be an important site of crossmodal integration. Experiment 2 revealed for the first time significant activation of the right anterior frontal operculum (aFO) when visual and auditory stimuli cycled asynchronously. Experiment 3 confirmed and developed this observation as the right aFO was activated only during crossmodal (visual-auditory), but not intramodal (visual-visual, auditory-auditory) asynchrony. Experiment 3 also demonstrated activation of the amygdala bilaterally during crossmodal synchrony. Experiment 4 revealed the neural correlates of supramodal, contemplative, aesthetic evaluation within the medial fronto-polar cortex. Activity at this locus varied parametrically according to the degree of subjective aesthetic beauty, for both visual art and musical extracts. The most robust finding of this thesis is that activity in the right aFO increases when concurrently perceived visual and auditory sensory stimuli deviate from crossmodal synchrony, which may veto the crossmodal integration of unrelated stimuli into unified conscious perception

Vividness, Consciousness, and Mental Imagery

Today in many studies, mental images are still either treated as conscious by definition, or as empirical operations implicit to completing some type of task, such as the measurement of reaction time in mental rotation, an underlying mental image is assumed, but there is no direct determination of whether it is conscious or not. The vividness of mental images is a potentially helpful construct which may be suitable, as it may correspond to consciousness or aspects of the consciousness of images. In this context, a complicating factor seems to be the surprising variety in what is meant by the term vividness or how it is used or theorized. To fill some of the gaps, the goal of the present Special Issue is to create a publication outlet where authors can fully explore through sound research the missing theoretical and empirical links between vividness, consciousness and mental imagery across disciplines, neuroscience, psychology, philosophy, cognitive science, to mention the most obvious ones, as well as transdisciplinary methodological (single, combined, or multiple) approaches