237 research outputs found

    Medically Relevant Criteria used in EEG Compression for Improved Post-Compression Seizure Detection

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    Biomedical signals aid in the diagnosis of different disorders and abnormalities. When targeting lossy compression of such signals, the medically relevant information that lies within the data should maintain its accuracy and thus its reliability. In fact, signal models that are inspired by the bio-physical properties of the signals at hand allow for a compression that preserves more naturally the clinically significant features of these signals. In this paper, we illustrate this through the example of EEG signals; more specifically, we analyze three specific lossy EEG compression schemes. These schemes are based on signal models that have different degrees of reliance on signal production and physiological characteristics of EEG. The resilience of these schemes is illustrated through the performance of seizure detection post compression.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

    EEG/MEG Sparse Source Imaging and Its Application in Epilepsy

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    This dissertation is a summary of my Ph.D. work on the development of sparse source imaging technologies based on electroencephalography (EEG) and magneto-encephalography (MEG) and their application to noninvasively reconstruct brain activation from external surface measurements. Conventional sparse source imaging (SSI) methods using the ℓ1-norm regularization to enforce sparseness in the original source domain leads to over-focused solutions and causes bias in estimating spatially extended brain sources. I address the over-focused issue in the ℓ1-norm regularization technique framework by exploring sparseness in the transform domains. First, I apply a SSI method that uses the variation transform, i.e. V-SSI, on clinical MEG interictal recordings from partial epilepsy patients. Estimated epileptic sources by V-SSI are validated using clinical pre-surgical evaluation data and surgical outcomes. Second, I implement a novel face-based wavelet transform, which can efficiently compress brain activation signals into sparse representations on a multi-resolution cortical source model, into the SSI technology framework. The proposed wavelet-based SSI (W-SSI) demonstrates a significantly improved ability in inferring both brain source locations and extents as compared with conventional ℓ2-norm regularizations in obtaining EEG/MEG inverse solutions and other SSI technologies. Furthermore, the face-based wavelet also indicates better performance than a previously reported vertex-based wavelet in W-SSI. I evaluate the W-SSI method and conduct the comparison studies using both simulations and real data collected from partial epilepsy patients. Lastly, I further propose the concept of using multiple transforms in the SSI technology framework and investigated a new SSI method by enforcing sparseness in both variation and face-based wavelet domains, termed as VW-SSI. I conduct simulation studies, which demonstrate that VW-SSI has significantly better detection accuracies in both source locations and extents than conventional ℓ2-norm regularizations and other SSI methods, including SSI, V-SSI, and W-SSI. I further validate the VW-SSI method using clinical MEG data from both language and motor experiments collected from epilepsy patients again to localize their important functional brain areas. The results indicate that VW-SSI provides a performance advantage in detecting neural phenomena that have been extremely difficult to recognize by other EEG/MEG inverse solutions. It thus suggests that the sparse source imaging technique is promising to serve as a non-invasive tool in assisting pre-surgical planning for partial epilepsy patients

    Acquisition of subcortical auditory potentials with around-the-Ear cEEGrid technology in normal and hearing impaired listeners

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    Even though the principles of recording brain electrical activity remain unchanged since their discovery, their acquisition has seen major improvements. The cEEGrid, a recently developed flex-printed multi-channel sensory array, can be placed around the ear and successfully record well-known cortical electrophysiological potentials such as late auditory evoked potentials (AEPs) or the P300. Due to its fast and easy application as well as its long-lasting signal recording window, the cEEGrid technology offers great potential as a flexible and 'wearable' solution for the acquisition of neural correlates of hearing. Early potentials of auditory processing such as the auditory brainstem response (ABR) are already used in clinical assessment of sensorineural hearing disorders and envelope following responses (EFR) have shown promising results in the diagnosis of suprathreshold hearing deficits. This study evaluates the suitability of the cEEGrid electrode configuration to capture these AEPs. cEEGrid potentials were recorded and compared to cap-EEG potentials for young normal-hearing listeners and older listeners with high-frequency sloping audiograms to assess whether the recordings are adequately sensitive for hearing diagnostics. ABRs were elicited by presenting clicks (70 and 100-dB peSPL) and stimulation for the EFRs consisted of 120 Hz amplitudemodulated white noise carriers presented at 70-dB SPL. Data from nine bipolar cEEGrid channels and one classical cap-EEG montage (earlobes to vertex) were analysed and outcome measures were compared. Results show that the cEEGrid is able to record ABRs and EFRs with comparable shape to those recorded using a conventional capEEG recording montage and the same amplifier. Signal strength is lower but can still produce responses above the individual neural electrophysiological noise floor. This study shows that the application of the cEEGrid can be extended to the acquisition of early auditory evoked potentials

    Modeling auditory evoked potentials to complex stimuli

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    Causal evidence that intrinsic beta frequency is relevant for enhanced signal propagation in the motor system as shown through rhythmic TMS

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    Correlative evidence provides support for the idea that brain oscillations underpin neural computations. Recent work using rhythmic stimulation techniques in humans provide causal evidence but the interactions of these external signals with intrinsic rhythmicity remain unclear. Here, we show that sensorimotor cortex precisely follows externally applied rhythmic TMS (rTMS) stimulation in the beta-band but that the elicited responses are strongest at the intrinsic individual beta-peak-frequency. While these entrainment effects are of short duration, even subthreshold rTMS pulses propagate through the network and elicit significant cortico-spinal coupling, particularly when stimulated at the individual beta-frequency. Our results show that externally enforced rhythmicity interacts with intrinsic brain rhythms such that the individual peak frequency determines the effect of rTMS. The observed downstream spinal effect at the resonance frequency provides evidence for the causal role of brain rhythms for signal propagation

    Fast and Efficient Formulations for Electroencephalography-Based Neuroimaging Strategies

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)

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    Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG. (C) 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V.Peer reviewe
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