Utilizing anatomical information for signal detection in functional magnetic resonance imaging

We are considering the statistical analysis of functional magnetic resonance imaging (fMRI) data. As demonstrated in previous work, grouping voxels into regions (of interest) and carrying out a multiple test for signal detection on the basis of these regions typically leads to a higher sensitivity when compared with voxel-wise multiple testing approaches. In the case of a multi-subject study, we propose to define the regions for each subject separately based on their individual brain anatomy, represented, e.g., by so-called Aparc labels. The aggregation of the subject-specific evidence for the presence of signals in the different regions is then performed by means of a combination function for p-values. We apply the proposed methodology to real fMRI data and demonstrate that our approach can perform comparably to a two-stage approach for which two independent experiments are needed, one for defining the regions and one for actual signal detection

Apport de nouvelles techniques dans l’évaluation de patients candidats à une chirurgie d’épilepsie : résonance magnétique à haut champ, spectroscopie proche infrarouge et magnétoencéphalographie

L'épilepsie constitue le désordre neurologique le plus fréquent après les maladies cérébrovasculaires. Bien que le contrôle des crises se fasse généralement au moyen d'anticonvulsivants, environ 30 % des patients y sont réfractaires. Pour ceux-ci, la chirurgie de l'épilepsie s'avère une option intéressante, surtout si l’imagerie par résonance magnétique (IRM) cérébrale révèle une lésion épileptogène bien délimitée. Malheureusement, près du quart des épilepsies partielles réfractaires sont dites « non lésionnelles ». Chez ces patients avec une IRM négative, la délimitation de la zone épileptogène doit alors reposer sur la mise en commun des données cliniques, électrophysiologiques (EEG de surface ou intracrânien) et fonctionnelles (tomographie à émission monophotonique ou de positrons). La faible résolution spatiale et/ou temporelle de ces outils de localisation se traduit par un taux de succès chirurgical décevant. Dans le cadre de cette thèse, nous avons exploré le potentiel de trois nouvelles techniques pouvant améliorer la localisation du foyer épileptique chez les patients avec épilepsie focale réfractaire considérés candidats potentiels à une chirurgie d’épilepsie : l’IRM à haut champ, la spectroscopie proche infrarouge (SPIR) et la magnétoencéphalographie (MEG). Dans une première étude, nous avons évalué si l’IRM de haut champ à 3 Tesla (T), présentant théoriquement un rapport signal sur bruit plus élevé que l’IRM conventionnelle à 1,5 T, pouvait permettre la détection des lésions épileptogènes subtiles qui auraient été manquées par cette dernière. Malheureusement, l’IRM 3 T n’a permis de détecter qu’un faible nombre de lésions épileptogènes supplémentaires (5,6 %) d’où la nécessité d’explorer d’autres techniques. Dans les seconde et troisième études, nous avons examiné le potentiel de la SPIR pour localiser le foyer épileptique en analysant le comportement hémodynamique au cours de crises temporales et frontales. Ces études ont montré que les crises sont associées à une augmentation significative de l’hémoglobine oxygénée (HbO) et l’hémoglobine totale au niveau de la région épileptique. Bien qu’une activation contralatérale en image miroir puisse être observée sur la majorité des crises, la latéralisation du foyer était possible dans la plupart des cas. Une augmentation surprenante de l’hémoglobine désoxygénée a parfois pu être observée suggérant qu’une hypoxie puisse survenir même lors de courtes crises focales. Dans la quatrième et dernière étude, nous avons évalué l’apport de la MEG dans l’évaluation des patients avec épilepsie focale réfractaire considérés candidats potentiels à une chirurgie. Il s’est avéré que les localisations de sources des pointes épileptiques interictales par la MEG ont eu un impact majeur sur le plan de traitement chez plus des deux tiers des sujets ainsi que sur le devenir postchirurgical au niveau du contrôle des crises.Epilepsy is the most common chronic neurological disorder after stroke. The major form of treatment is long-term drug therapy to which approximately 30% of patients are unfortunately refractory to. Brain surgery is recommended when medication fails, especially if magnetic resonance imaging (MRI) can identify a well-defined epileptogenic lesion. Unfortunately, close to a quarter of patients have nonlesional refractory focal epilepsy. For these MRI-negative cases, identification of the epileptogenic zone rely heavily on remaining tools: clinical history, video-electroencephalography (EEG) monitoring, ictal single-photon emission computed tomography (SPECT), and a positron emission tomography (PET). Unfortunately, the limited spatial and/or temporal resolution of these localization techniques translates into poor surgical outcome rates. In this thesis, we explore three relatively novel techniques to improve the localization of the epileptic focus for patients with drug-resistant focal epilepsy who are potential candidates for epilepsy surgery: high-field 3 Tesla (T) MRI, near-infrared spectroscopy (NIRS) and magnetoencephalography (MEG). In the first study, we evaluated if high-field 3T MRI, providing a higher signal to noise ratio, could help detect subtle epileptogenic lesions missed by conventional 1.5T MRIs. Unfortunately, we show that the former was able to detect an epileptogenic lesion in only 5.6% of cases of 1.5T MRI-negative epileptic patients, emphasizing the need for additional techniques. In the second and third studies, we evaluated the potential of NIRS in localizing the epileptic focus by analyzing the hemodynamic behavior of temporal and frontal lobe seizures respectively. We show that focal seizures are associated with significant increases in oxygenated haemoglobin (HbO) and total haemoglobin (HbT) over the epileptic area. While a contralateral mirror-like activation was seen in the majority of seizures, lateralization of the epileptic focus was possible most of the time. In addition, an unexpected increase in deoxygenated haemoglobin (HbR) was noted in some seizures, suggesting possible hypoxia even during relatively brief focal seizures. In the fourth and last study, the utility of MEG in the evaluation of nonlesional drug-refractory focal epileptic patients was studied. It was found that MEG source localization of interictal epileptic spikes had an impact both on patient management for over two thirds of patients and their surgical outcome

Flexible multivariate hemodynamics fMRI data analyses and simulations with PyHRF

International audienceAs part of fMRI data analysis, the pyhrf package provides a set of tools for addressing the two 3 main issues involved in intra-subject fMRI data analysis: (i) the localization of cerebral regions 4 that elicit evoked activity and (ii) the estimation of the activation dynamics also referenced to 5 as the recovery of the Hemodynamic Response Function (HRF). To tackle these two problems, 6 pyhrf implements the Joint Detection-Estimation framework (JDE) which recovers parcel-level 7 HRFs and embeds an adaptive spatio-temporal regularization scheme of activation maps. With 8 respect to the sole detection issue (i), the classical voxelwise GLM procedure is also available 9 through nipy, whereas Finite Impulse Response (FIR) and temporally regularized FIR models 10 are implemented to deal with HRF estimation concerns (ii). Several parcellation tools are also 11 integrated such as spatial and functional clustering. Parcellations may be used for spatial 12 averaging prior to FIR/RFIR analysis or to specify the spatial support of the HRF estimates 13 in the JDE approach. These analysis procedures can be applied either to volumic data sets or 14 to data projected onto the cortical surface. For validation purpose, this package is shipped with 15 artificial and real fMRI data sets, which are used in this paper to compare the outcome of the 16 different available approaches. The artificial fMRI data generator is also described to illustrate 17 how to simulate different activation configurations, HRF shapes or nuisance components. To 18 cope with the high computational needs for inference, pyhrf handles distributing computing 19 by exploiting cluster units as well as multiple cores computers. Finally, a dedicated viewer is 20 presented, which handles n-dimensional images and provides suitable features to explore whole 21 brain hemodynamics (time series, maps, ROI mask overlay)

Étude de la réponse hémodynamique dans un modèle réussi de vieillissement chez le rat par imagerie optique intrinsèque

RESUME L'enjeu de cette these de doctorat est de mesurer les changements de parametres neurovasculaires et les modications de la reponse hemodynamique au cours du vieillissement chez le rat. La reponse hemodynamique est le processus par lequel, suite a une augmentation de l'activite neuronale, il se produit une augmentation locale du debit sanguin pour suivre les changements de l'activite metabolique venant de l'activite neuronale. La mesure de la reponse hemodynamique est a la base de l'imagerie fonctionnelle et permet de suivre de facon indirecte les changements d'activite neuronale a travers le couplage neurovasculaire. Toutefois, de nombreuses proprietes physiologiques du cerveau (debit, volume sanguin, compliance des vaisseaux, densite vasculaire, etc.) peuvent ^etre modiees au cours du vieillissement et aecter le couplage neurovasculaire. Cette these vise donc a mieux comprendre les changements de couplage neurovasculaire au cours du vieillissement et leur eet sur les mesures obtenues en imagerie fonctionnelle. Dans le cadre de cette these, les changements de reponse hemodynamique ont ete mesur es a l'aide d'un systeme d'imagerie optique intrinseque(IOI) developpe au laboratoire. Cette technique recente d'imagerie cerebrale se base sur les proprietes d'absorption de la lumiere visible dans le cortex. La technique a une tres bonne resolution spatiale et une faible profondeur de penetration ce qui en fait une technique tres bien adaptee a l'etude chez le rat. En IOI, la lumiere visible illumine le cortex et voyage dans la couche supercielle du cerveau avant d'^etre re echie a la surface du cortex et mesuree a l'aide d'une camera CCD. Lors de sa propagation a travers le cortex, une partie de la lumiere est absorbee par les deux principaux chromophores presents (l'hemoglobine et la deoxyhemoglobine). Ainsi, les changements de concentration d'un chromophore peuvent ^etre determines a travers des changements d'intensit e lumineuse. Ce qui permet ensuite d'etudier les concentrations de sang oxygene et desoxygene. En plus des mesures d'IOI, le systeme mesure simultanement les changements de debit sanguin a travers une mesure par granularite laser. La premiere partie des resultats mesure les changements de la reponse hemodynamique au cours du vieillissement. Les principales observations consistent en une diminution de l'amplitude de la reponse hemodynamique et une augmentation du temps d'activation de la reponse hemodynamique en fonction de l'^age. On observa aussi des changements spatiaux de la reponse hemodynamique. Ainsi, l'amplitude de la reponse hemodynamique diminue plus lentement en fonction----------ABSTRACT The aim of this thesis is to measure changes in neurovascular parameters and in hemodynamic response in aging rats. The hemodynamic response is the process by which, following an increase of neuronal activity, the blood ow increase locally to follow the changes in metabolic activity from neural activity. Measuring the hemodynamic response is the key process of functional imaging and allows to monitor indirectly changes of neuronal activity through the neurovascular coupling. However, many physiological properties in the brain ( ow, blood volume, vessel compliance, vascular density, etc.) may be modied during aging and aect neurovascular coupling. The thesis aims to better understand the changes in neurovascular coupling during aging and their eect measurements obtained in functional imaging. In this work, changes in hemodynamic response were measured using an intrinsic optical imaging system (IOI) developed in the laboratory. This recent imaging technique is based on the absorption properties of the visible light in the cortex. The technique has a very good spatial resolution and low depth of penetration which makes it well suited to study brain activity in rats. In IOI, visible light illuminates the cortex and travels in the surface layer of the brain before being re ected at the surface of the cortex and measured using a CCD camera. In the journey through the cortex, a part of the light is absorbed by the two main chromophores present (hemoglobin and deoxyhemoglobin). Thus, changes in chromophore concentration can be determined through changes in light intensity. This allows to study the concentrations of oxygenated blood and deoxygenated. In addition to measures of IOI, the system simultaneously measures changes in blood ow through a laser speckle measurement technique. The rst part of the results then shows the changes in the hemodynamic response during aging. The main observations is that during aging we observe a decrease in the amplitude of the hemodynamic response and an increase in the activation time of the hemodynamic response. Age also produce changes of the hemodynamic response. Thus, the amplitude of the hemodynamic response decreases more slowly as a function of aging on the side ipsilateral to stimulation from the contralateral side. The second part of the work studies neurovascular coupling using three dierent biophysical models. The three biophysical models can reproduce the dierent types of hemodynamic response found in our rats population. A comparison of models by log evidence did not foound signicative dierence between the performance of the three models. However, the model-Boas Huppert that we developed has an advantage of nding neurovascular restin

EEG-fMRI in the presurgical evaluation of temporal lobe epilepsy.

Drug-resistant temporal lobe epilepsy (TLE) often requires thorough investigation to define the epileptogenic zone for surgical treatment. We used simultaneous interictal scalp EEG-fMRI to evaluate its value for predicting long-term postsurgical outcome

Bounded Influence Approaches to Constrained Mixed Vector Autoregressive Models

The proliferation of many clinical studies obtaining multiple biophysical signals from several individuals repeatedly in time is increasingly recognized, a recognition generating growth in statistical models that analyze cross-sectional time series data. In general, these statistical models try to answer two questions: (i) intra-individual dynamics of the response and its relation to some covariates; and, (ii) how this dynamics can be aggregated consistently in a group. In response to the first question, we propose a covariate-adjusted constrained Vector Autoregressive model, a technique similar to the STARMAX model (Stoffer, JASA 81, 762-772), to describe serial dependence of observations. In this way, the number of parameters to be estimated is kept minimal while offering flexibility for the model to explore higher order dependence. In response to (ii), we use mixed effects analysis that accommodates modelling of heterogeneity among cross-sections arising from covariate effects that vary from one cross-section to another. Although estimation of the model can proceed using standard maximum likelihood techniques, we believed it is advantageous to use bounded influence procedures in the modelling (such as choosing constraints) and parameter estimation so that the effects of outliers can be controlled. In particular, we use M-estimation with a redescending bounding function because its influence function is always bounded. Furthermore, assuming consistency, this influence function is useful to obtain the limiting distribution of the estimates. However, this distribution may not necessarily yield accurate inference in the presence of contamination as the actual asymptotic distribution might have wider tails. This led us to investigate bootstrap approximation techniques. A sampling scheme based on IID innovations is modified to accommodate the cross-sectional structure of the data. Then the M-estimation is applied to each bootstrap sample naively to obtain the asymptotic distribution of the estimates.We apply these strategies to the extracted BOLD activation from several regions of the brain from a group of individuals to describe joint dynamic behavior between these locations. We used simulated data with both innovation and additive outliers to test whether the estimation procedure is accurate despite contamination

Synchrony, metastability, dynamic integration, and competition in the spontaneous functional connectivity of the human brain

Available online 3 June 2019.The human brain is functionally organized into large-scale neural networks that are dynamically interconnected. Multiple short-lived states of resting-state functional connectivity (rsFC) identified transiently synchronized networks and cross-network integration. However, little is known about the way brain couplings covary as rsFC states wax and wane. In this magnetoencephalography study, we explore the synchronization structure among the spontaneous interactions of well-known resting-state networks (RSNs). To do so, we extracted modes of dynamic coupling that reflect rsFC synchrony and analyzed their spatio-temporal features. These modes identified transient, sporadic rsFC changes characterized by the widespread integration of RSNs across the brain, most prominently in the β band. This is in line with the metastable rsFC state model of resting-state dynamics, wherein our modes fit as state transition processes. Furthermore, the default-mode network (DMN) stood out as being structured into competitive cross-network couplings with widespread DMN-RSN interactions, especially among the β-band modes. These results substantiate the theory that the DMN is a core network enabling dynamic global brain integration in the β band.This work was supported by the Action de Recherche Concert ee (ARC Consolidation 2015–2019, “Characterization of the electrophysiological bases, the temporal dynamics and the functional relevance of resting state network” attributed to X.D.T.) and by the research convention “Les Voies du Savoir” (Fonds Erasme, Brussels, Belgium). M.B. benefited from the program Attract of Innoviris (grant 2015-BB2B-10), the Spanish Ministry of Economy and Competitiveness (grant PSI2016-77175-P), and theMarie Skłodowska-Curie Action of the European Commission (grant 743562). M.V.G. and G.N.were supported by the Fonds Erasme. N.C. benefited from a research grant from the ARC Consolidation (2014–2017, “Characterization of the electrophysiological bases, the temporal dynamics and the functional relevance of resting state network” attributed to X.D.T.) and from the Fonds Erasme (research convention “Les Voies du Savoir”). X.D.T. is Post-doctorate Clinical Master Specialist at the Fonds de la Recherche Scientifique (F.R.S.-FNRS, Brussels, Belgium). The MEG project at the CUB – H^opital Erasme is financially supported by the Fonds Erasme (research convention “Les Voies du Savoir”)

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