Imaging of epileptic activity using EEG-correlated functional MRI.

This thesis describes the method of EEG-correlated fMRI and its application to patients with epilepsy. First, an introduction on MRI and functional imaging methods in the field of epilepsy is provided. Then, the present and future role of EEG-correlated fMRI in the investigation of the epilepsies is discussed. The fourth chapter reviews the important practicalities of EEG-correlated fMRI that were addressed in this project. These included patient safety, EEG quality and MRI artifacts during EEG-correlated fMRI. Technical solutions to enable safe, good quality EEG recordings inside the MR scanner are presented, including optimisation of the EEG recording techniques and algorithms for the on-line subtraction of pulse and image artifact. In chapter five, a study applying spike-triggered fMRI to patients with focal epilepsy (n = 24) is presented. Using statistical parametric mapping (SPM), cortical Blood Oxygen Level-Dependent (BOLD) activations corresponding to the presumed generators of the interictal epileptiform discharges (IED) were identified in twelve patients. The results were reproducible in repeated experiments in eight patients. In the remaining patients no significant activation (n = 10) was present or the activation did not correspond to the presumed epileptic focus (n = 2). The clinical implications of this finding are discussed. In a second study it was demonstrated that in selected patients, individual (as opposed to averaged) IED could also be associated with hemodynamic changes detectable with fMRI. Chapter six gives examples of combination of EEG-correlated fMRI with other modalities to obtain complementary information on interictal epileptiform activity and epileptic foci. One study compared spike-triggered fMRI activation maps with EEG source analysis based on 64-channel scalp EEG recordings of interictal spikes using co-registration of both modalities. In all but one patient, source analysis solutions were anatomically concordant with the BOLD activation. Further, the combination of spike- triggered fMRI with diffusion tensor and chemical shift imaging is demonstrated in a patient with localisation-related epilepsy. In chapter seven, applications of EEG-correlated fMRI in different areas of neuroscience are discussed. Finally, the initial imaging findings with the novel technique for the simultaneous and continuous acquisition of fMRI and EEG data are presented as an outlook to future applications of EEG-correlated fMRI. In conclusion, the technical problems of both EEG-triggered fMRI and simultaneous EEG-correlated fMRI are now largely solved. The method has proved useful to provide new insights into the generation of epileptiform activity and other pathological and physiological brain activity. Currently, its utility in clinical epileptology remains unknown

Methods for cleaning the BOLD fMRI signal

Available online 9 December 2016 http://www.sciencedirect.com/science/article/pii/S1053811916307418?via%3Dihubhttp://www.sciencedirect.com/science/article/pii/S1053811916307418?via%3DihubBlood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.This work was supported by the Spanish Ministry of Economy and Competitiveness [Grant PSI 2013–42343 Neuroimagen Multimodal], the Severo Ochoa Programme for Centres/Units of Excellence in R & D [SEV-2015-490], and the research and writing of the paper were supported by the NIMH and NINDS Intramural Research Programs (ZICMH002888) of the NIH/HHS

Análise de desempenho de métricas de grafos para reconhecimento de tarefas de imaginação motora das mãos a partir de dados de eletroencefalografia

Orientadores: Gabriela Castellano, Romis Ribeiro de Faissol AttuxDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb WataghinResumo: Interfaces cérebro-computador (BCIs, brain-computer interfaces) são sistemas cuja finalidade é fornecer um canal de comunicação direto entre o cérebro e um dispositivo externo, como um computador, uma prótese ou uma cadeira de rodas. Por não utilizarem as vias fisiológicas convencionais, BCIs podem constituir importantes tecnologias assistivas para pessoas que sofreram algum tipo de lesão e, por isso, tiveram sua interação com o ambiente externo comprometida. Os sinais cerebrais a serem extraídos para utilização nestes sistemas devem ser gerados mediante estratégias específicas. Nesta dissertação, trabalhamos com a estratégia de imaginação motora (MI, motor imagery), e extraímos a resposta cerebral correspondente a partir de dados de eletroencefalografia (EEG). Os objetivos do trabalho foram caracterizar as redes cerebrais funcionais oriundas das tarefas de MI das mãos e explorar a viabilidade de utilizar métricas da teoria de grafos para a classificação dos padrões mentais, gerados por esta estratégia, de usuários de um sistema BCI. Para isto, fez-se a hipótese de que as alterações no espectro de frequências dos sinais de eletroencefalografia devidas à MI das mãos deveria, de alguma forma, se refletir nos grafos construídos para representar as interações cerebrais corticais durante estas tarefas. Em termos de classificação, diferentes conjuntos de pares de eletrodos foram testados, assim como diferentes classificadores (análise de discriminantes lineares ¿ LDA, máquina de vetores de suporte ¿ SVM ¿ linear e polinomial). Os três classificadores testados tiveram desempenho similar na maioria dos casos. A taxa média de classificação para todos os voluntários considerando a melhor combinação de eletrodos e classificador foi de 78%, sendo que alguns voluntários tiveram taxas de acerto individuais de até 92%. Ainda assim, a metodologia empregada até o momento possui várias limitações, sendo a principal como encontrar os pares ótimos de eletrodos, que variam entre voluntários e aquisições; além do problema da realização online da análiseAbstract: Brain-computer interfaces (BCIs) are systems that aim to provide a direct communication channel between the brain and an external device, such as a computer, a prosthesis or a wheelchair. Since BCIs do not use the conventional physiological pathways, they can constitute important assistive technologies for people with lesions that compromised their interaction with the external environment. Brain signals to be extracted for these systems must be generated according to specific strategies. In this dissertation, we worked with the motor imagery (MI) strategy, and we extracted the corresponding cerebral response from electroencephalography (EEG) data. Our goals were to characterize the functional brain networks originating from hands¿ MI and investigate the feasibility of using metrics from graph theory for the classification of mental patterns, generated by this strategy, of BCI users. We hypothesized that frequency alterations in the EEG spectra due to MI should reflect themselves, in some manner, in the graphs representing cortical interactions during these tasks. For data classification, different sets of electrode pairs were tested, as well as different classifiers (linear discriminant analysis ¿ LDA, and both linear and polynomial support vector machines ¿ SVMs). All three classifiers tested performed similarly in most cases. The mean classification rate over subjects, considering the best electrode set and classifier, was 78%, while some subjects achieved individual hit rates of up to 92%. Still, the employed methodology has yet some limitations, being the main one how to find the optimum electrode pairs¿ sets, which vary among subjects and among acquisitions; in addition to the problem of performing an online analysisMestradoFísicaMestre em Física165742/2014-31423625/2014CNPQCAPE

Lagged and instantaneous dynamical influences related to brain structural connectivity

Contemporary neuroimaging methods can shed light on the basis of human neural and cognitive specializations, with important implications for neuroscience and medicine. Different MRI acquisitions provide different brain networks at the macroscale; whilst diffusion-weighted MRI (dMRI) provides a structural connectivity (SC) coincident with the bundles of parallel fibers between brain areas, functional MRI (fMRI) accounts for the variations in the blood-oxygenation-level-dependent T2* signal, providing functional connectivity (FC).Understanding the precise relation between FC and SC, that is, between brain dynamics and structure, is still a challenge for neuroscience. To investigate this problem, we acquired data at rest and built the corresponding SC (with matrix elements corresponding to the fiber number between brain areas) to be compared with FC connectivity matrices obtained by 3 different methods: directed dependencies by an exploratory version of structural equation modeling (eSEM), linear correlations (C) and partial correlations (PC). We also considered the possibility of using lagged correlations in time series; so, we compared a lagged version of eSEM and Granger causality (GC). Our results were two-fold: firstly, eSEM performance in correlating with SC was comparable to those obtained from C and PC, but eSEM (not C nor PC) provides information about directionality of the functional interactions. Second, interactions on a time scale much smaller than the sampling time, captured by instantaneous connectivity methods, are much more related to SC than slow directed influences captured by the lagged analysis. Indeed the performance in correlating with SC was much worse for GC and for the lagged version of eSEM. We expect these results to supply further insights to the interplay between SC and functional patterns, an important issue in the study of brain physiology and function.Comment: Accepted and published in Frontiers in Psychology in its current form. 27 pages, 1 table, 5 figures, 2 suppl. figure

fNIRS Measurement of Cortical Activity in Younger and Older Adults During Gait and Dual-Task Assignment

Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive brain imaging technique which measures brain activity via local changes in blood hemoglobin concentration. Since brain activity decreases as a function of age, it is expected that aging adults will demonstrate less hemodynamic changes and therefore, indicate less cortical activation compared to younger adults. To test the stated relationships, this study involves using the Near Infra-Red Optimal Tomography (NIROT) workflow with Maximum Entropy on the Mean (MEM), using personalized fNIRS and local 3D reconstruction to assess the hemodynamic response elicited during simultaneous walking and arithmetic tasks in healthy young and older adults. Personalized fNIRS consisted of following the Optimal Montage algorithm, which maximizes the positions of fNIRS sensors to increase sensitivity to two targeted brain regions: the Inferior Frontal Gyrus (IFG) and Middle Frontal Gyrus (MFG) which are both involved in performing mental arithmetic and shown to demonstrate compensatory behaviors in single task (mental arithmetic only) when compared to dual task (walking while performing mental arithmetic). Single and dual tasks were considered for five younger adults and two older adults. Subject-specific optimal montages were calculated to ensure maximum light sensitivity to the target ROI and sufficient spatial overlap between sensors, allowing local 3D reconstruction of [HbO] and [HbR] response along the underlying cortical surface. Single task consisted of a block design arithmetic task (Serial-Sevens: sequential subtraction. For dual task, the same arithmetic task was performed, while participants were walking on a treadmill. NIRSTORM software package was used for channel space analysis of fNIRS signal, motion correction, modified Beer Lambert Law and block averaging. Reconstruction in 3D using Maximum Entropy on the Mean (MEM) was calculated using the same number of trials for each subject. In addition to answering questions encompassing brain activity as a function of age and balancing a cognitive task during gait, the study provided data for investigating trends around motion artifacts and testing the effectiveness of an accelerometer during simultaneous gait and fNIRS acquisitions. Due to restrictions during the Covid-19 pandemic, this study serves as a proof of concept and methods in improving the quality of data

Analysis of electroencephalography signals collected in a magnetic resonance environment: characterisation of the ballistocardiographic artefact

L’acquisizione simultanea di segnali elettroencefalografici (EEG) e immagini di risonanza magnetica funzionale (fMRI) permette di investigare attivazioni cerebrali in modo non invasivo. La presenza del campo magnetico altera però in modo non trascurabile la qualità dei segnali EEG acquisiti. In particolare due artefatti sono stati individuati: l’artefatto da gradiente e l’artefatto da ballistocardiogramma (BCG). L’artefatto da BCG è legato all’attività cardiaca del soggetto, ed è caratterizzato da elevata variabilità tra un’occorrenza e l’altra in termini di ampiezza, forma d’onda e durata dell’artefatto. Differenti algoritmi sono stati implementati al fine di rimuoverlo, ma la rimozione completa rimane ancora un difficile obiettivo da raggiungere a causa della sua complessa natura. L’argomento della tesi riguarda l’analisi di segnali EEG acquisiti in ambiente di risonanza magnetica e la caratterizzazione dell’artefatto BCG. L’obiettivo è individuare ulteriori caratteristiche dell’artefatto che possano condurre al miglioramento dei precedenti metodi, o all’implementazione di nuovi. Con questa tesi abbiamo mostrato quali sono i motivi che causano la presenza di residui artefattuali nei segnali EEG processati con i metodi presenti in letteratura. Attraverso analisi statistica abbiamo riscontrato che occorrenze dell’artefatto BCG sono caratterizzate da un ritardo variabile rispetto al picco R sull’ECG, che nella nostra analisi rappresenta l’evento di riferimento nell’attività cardiaca. Abbiamo inoltre trovato che il ritardo R-BCG varia con la frequenza cardiaca. Le successive valutazioni riguardano i maggiori contributi all’artefatto BCG. Attraverso l’analisi alle componenti principali, sono stati individuati due contributi legati al fluire del sangue dal cuore verso il cervello e alla sua pulsatilità nei vasi principali dello scalpo

Novel strategies for mouse cardiac MRI : better, faster, stronger

Mouse models of cardiac disease are an important tool to gain understanding of the pathophysiological processes related to the heart, as well as for the development of new treatment strategies. In this respect, Magnetic Resonance Imaging (MRI) has become the gold standard imaging modality, because it combines high spatial resolution imaging with a large variety of soft tissue contrast weightings that can be related to the presence of diseased tissue. In addition, (targeted) MRI contrast agents can be employed to visualize different processes on the molecular level, for example in relation to myocardial infarction and the subsequent cardiac remodeling process. The specificity to discriminate healthy from diseased tissue as well as the sensitivity for detection of MR contrast agents is strongly affected by the specific MRI protocol design. Moreover, the challenging physiology of the mouse heart, especially with respect to its small size and high heart rate, often limits the direct translation of imaging protocols already available from clinical studies. Finally, the growing knowledge on cardiac pathology continuously pushes the development of sophisticated mouse cardiac MRI protocols that allow more detailed measurements of a variety of physiologically relevant cardiac parameters. The overall goal of this thesis was therefore to design and investigate novel imaging strategies in the field of mouse cardiac MRI and their application in models of cardiac disease. Chapter 2 of this thesis contains an extensive overview of currently available protocols for mouse cardiac MRI and more specifically those related to contrast enhanced imaging of myocardial infarction. The remainder of the thesis contains the experimental chapters describing all details on our newly developed mouse cardiac MRI techniques. This chapter shortly summarizes the aims and results with respect to each of these techniques, categorized based on the parameter of interest for which each measurement was specifically designed. Diastolic function Measurement of murine diastolic function requires Cine imaging with an extremely high frame rate ¿ more than 60 frames within a cardiac cycle of 100-120 ms ¿ to be able to discriminate between the two separate filling phases of the heart. In chapter 3, it was shown that using a retrospectively triggered MRI sequence, reconstruction of 80 Cine images was feasible, corresponding to a temporal resolution of around 1.5 ms. This was achieved without using any form of data interpolation. With retrospective triggering, the MRI measurements are not synchronized with the ECG, thereby in theory sampling an infinite number of time points during the cardiac cycle. Correct assignment of each k-line to a specific cardiac frame could be done retrospectively by measuring an additional navigator signal prior to image acquisition, whose signal amplitude varies with cardiac as well as respiratory movements. Because in this case, filling of k-space for each cardiac frame is a stochastic process, simulations were performed to investigate the efficiency of the method with respect to signal averaging, which was found to be almost equal compared to regular prospective triggering. Diabetic cardiomyopathy has a high prevalence in type 2 diabetes patients and is characterized by diastolic dysfunction. With the current technique, we were indeed able to measure a subtle reduction is several diastolic function parameters, which are the E/A-ratio and the E-contribution to total left ventricular filling. Therefore, this technique is a promising tool in experimental studies of diabetic cardiomyopathy and for evaluation of emerging treatment strategies for diastolic dysfunction. Myocardial perfusion Chapter 4 describes the application of first-pass perfusion measurements in a mouse model of myocardial infarction to allow the assessment of the myocardial perfusion status. A first-pass perfusion measurement is performed by venous injection of an MRI contrast agent and monitoring its passage through the left ventricle and myocardial wall. From the signal intensity changes upon passage of the contrast agent, myocardial perfusion values can be determined. The application of this technique in mice requires ultra-fast MRI sequences that can sample the signal intensity-time curves with sufficient temporal resolution. Because this concerns imaging of non-periodic signal changes this is a much different problem compared to the diastolic function experiments described in chapter 3. We showed that using a saturation recovery MRI sequence with segmented k-space read-out in combination with parallel imaging acceleration techniques, a time-series of images could be acquired with a temporal resolution of 1 image for each 3 heart beats. The use of parallel imaging was crucial, since this requires less k-lines for image reconstruction compared to conventional imaging. Furthermore, the use of saturation pulses enhanced the contrast between contrast-enhanced and non-enhanced blood and myocardium. Using this technique, semi-quantitative perfusion values could be determined based on the upslope of the signal intensity-time curves. Experiments in mice with permanent occlusion of the LAD showed a significant decrease of perfusion values in the infarcted myocardium as compared to remote myocardium. In future experiments, this technique will be extended to provide quantitative perfusion values (in mg/l/min), requiring determination of the true arterial input function from a pre-bolus measurement with a smaller contrast agent bolus volume. T1 and T2 relaxation times Pathology is often accompanied by a change in the magnetic properties of the tissue, in particular the T1 and T2 relaxation times. This directly affects the signal intensity on the MR image. Diseased and healthy tissue can therefore be discriminated on MR images, which is one of the main applications of MRI in clinical diagnostics. However, there is much interest in quantitative assesment of T1 and T2 relaxation times, as this improves repeatibility of results in longitudinal studies and reproducibility between research groups. In this thesis, we aimed at developing protocols for both T1 and T2 mapping of the complete mouse heart for application in mouse models of myocardial infarction. Whole-heart coverage is important considering that a priori, the extent of the infarct is unknown. Currently available protocols for T1 mapping are relatvively time-consuming. In chapter 5, a 3D T1 mapping sequence is presented which allows myocardial T1 quantification of the mouse heart within 20 minutes. The retrospective triggering sequence used in chapter 3 proved also useful in this study, because it allows steady-state acqusition with very short repetition times, enabling whole heart coverage. T1 values were derived from measuring a variable flip angle data set and using available MRI signal models. Variable flip angle data showed excellent agreement in cardiac anatomy, allowing pixel-wise determination of T1. In healthy mice, no substantial differences in T1 were found for different heart regions in the 3D volume. Coefficents of repeatibility were determined from measurements at different days, which varied as function of the number of flip angles used in data analysis. In contrast to T1, T2 values could not be acquired using 3D acquisitons or retrospective triggering. Alternatively, chapter 6 describes a multi-slice T2 mapping protocol for the mouse heart based on a ECG-triggered T2 magnetization preparation module with variable TE. Because the preparation module consisted of many consecutive RF pulses, the effect of these pulses on T2 relxation had to be taken into account. Additionally, simulations were used to calculate the effect of T1 relaxation on T2 estimation, which was small as long as the repetition time was kept sufficiently long. Homogeneous T2 maps of healthy mouse heart were obtained, with no substantial differences between different heart regions or slices. In a ischemia/reperfusion model, elevated T2 values were found in the infarcted area, probably as result of edema formation. The extent of the infarction was also measured using late gadolinium enhanced imaging. The degree of correlation of T2 and LGE enhanced regions strongly depended on the signal intensity thresholds derived from remote tissue. Contrast agent accumulation Another application of quantitative T1 and T2¬ mapping is the assessment of the concentration of a contrast agent, which has been targeted to a specific disease site. This is especially valuable in molecular imaging applications where contrast agents report on the presence of specific disease markers related to various cardiac remodeling processes after myocardial infarction. Chapter 7 describes the application of the T1 mapping protocol from chapter 5 to quantify the accumulation of a Gd-based liposomal contrast agent in a model of myocardial infarction. Functional imaging and assessment of wall thickening values were used to determine which regions could be identified as being infarcted. Statistical analysis showed that before contrast agent administration, T¬1¬ values were already elevated in the infarcted regions as compared to remote myocardium, however, a more pronounced change in T1 values was found 24h post-contrast, with significantly lower T1 values in the infarcted areas. Pre-contrast T1 values in control mice were very similar to the study described in chapter 5, proving good reproducibility of T1 quantification using our methods. After the MRI measurement, the hearts were cut into slices, from which the Gd-content was determined in different sections of the heart using inductively coupled plasma mass spectrometry. T1 changes measured using in vivo MRI correlated well with ex vivo measurements of Gd concentration. These are promising results for quantification of contrast agent concentrations in contrast-enhanced MRI of mouse models of cardiac disease. More research has to be performed with regard to changes in contrast agent efficiency as a result of different cellular environments. Our results already indicate that the relaxivity values of liposomal contrast agents are significantly lower in vivo as compared to values obtained from measurements in phantom solutions. Conclusion This thesis has shown that mouse cardiac MRI is capable of assessing a large variety of parameters related to cardiac physiology in the in vivo mouse heart in a non-invasive way. This makes this technique an attractive platform for experimental studies on cardiac disease, as well as developing new treatment strategies

A Fourier Description of Covariance, and Separation of Simultaneously Encoded Slices with In-Plane Acceleration in fMRI

Functional magnetic resonance imaging (fMRI) studies aim to identify localized neural regions associated with a cognitive task performed by the subject. An indirect measure of the brain activity is the blood oxygenation level dependent (BOLD) signal fluctuations observed within the complex-valued spatial frequencies measured over time. The standard practice in fMRI is to discard the phase information after image reconstruction, even with evidence of biological task-related change in the phase time-series. In the first aim of this dissertation, a complex-valued time-series covariance is derived as a linear combination of second order temporal Fourier frequency coefficients. As opposed to magnitude-only analysis, the complex-valued covariance increases the sensitivity and specificity in fMRI correlation analysis, which is particularly advantageous for low contrast-to-noise ratio (CNR) fMRI time-series. In the remaining aims, increased statistical significance is achieved through a higher sampling rate of the fMRI time-course, by simultaneously magnetizing multiple slice images. With multi-frequency band excitations, a single k-space readout reconstructs to an image of composite aliased slice images. To disentangle the signal, or aliased voxels, phase and coil encoding techniques are incorporated into the data acquisition and image reconstruction. Inter-slice signal leakage, which also manifests as improper placement of the BOLD signal, presents in the separated slice images from induced correlations as a result of suboptimal simultaneous multi-slice (SMS) reconstruction methods. In the second aim of this dissertation, the Multi-coil Separation of Parallel Encoded Complex-valued Slices (mSPECS) reconstruction method is proposed as a solution to preserve the activation statistics in the separated slice images through a Bayesian approach of sampling calibration images. In the third aim of this dissertation, the mSPECS reconstruction is extended to include In-Plane Acceleration (mSPECS-IPA), to reconstruct aliased slice images with additional in-plane subsampling using a two-dimensional orthogonal phase encoding derivation of Hadamard encoding. Mitigating induced correlations with mSPECS(-IPA), results in accurately placed functional activation in the previously aliased complex-valued slice images. The development of novel complex-valued analysis and reconstruction methods in fMRI strengthens the significance of the activation statistics and precludes inter-slice signal leakage, so the true underlying neural dynamics are modeled in complex-valued fMRI data analysis