This study explored longitudinal change in executive function (EF) and episodic memory (EM) related to multimorbidity, number of chronic conditions, change in chronic conditions overtime in a nationally representative sample of young, middle-aged,and older adults. Participants were from the second (2004-2006) and third (2013-2015) waves of the Survey of Midlife Development in the United States (MIDUS; N=2,532). Participants completed telephone interviews and questionnaires providing information on demographics and chronic conditions. The Brief Test of Adult Cognition by Telephone (BTACT) assessedcognitive function. The BTACT includes measures of EM (ex. word list recall) and EF (ex. digits backward, category fluency, etc.).Overall, only change in chronic conditions was associated with EF decline in the whole sample. In young adults multimorbidity and number of chronic conditions was significantly associated with both EF and EM decline, whereas only change in number of chronic conditions was significantly associated with EF decline in middle aged adults.Future research is needed to assess a broader range of chronic conditions to determine their overall burden on EF and EM over time.

Cerebral malaria is characterised by an accumulation of infected erythrocytes in the microvasculature of the brain. Plasmodium falciparum infected erythrocytes have been shown to bind to a Human Brain Endothelial Cell line (HBEC-5i) in vitro. This provides a model for the investigation of interactions between P. falcuparum and human brain endothelium. Currently neither the parasite adhesion ligands on infected erythrocytes, nor the host endothelial cell receptors necessary for this interaction have been identified. In this work, the identity of the host receptor on brain endothelial cells was addressed by binding assays of selected and unselected parasites on a wide range of malaria-associated host molecules. The identity of the parasite ligand was investigated by microarray analysis of parasites after selection for cytoadherence to HBEC-5i. The hypothesis being tested was that the gene encoding the parasite cytoadherence ligand would show significant upregulation in selected compared to unselected paarasites. The P. falciparum laboratory strains 3D7, HB3 and IT/FCR3 were selected for binding to HBEC-5i using a panning assay. Compared to unselected parasites, HBEC-5i selected parasites showed a distinct phenotype with reduced platelet-mediated clumping. There was no significant increase in binding of parasites to any of the known endothelial cytoadherence receptors for P. falciparum after selection on HBEC-5i. Binding inhibition assays with various antibodies and soluble receptors did not greatly block the adhesion of parasites to HBEC-5i except for heparin. Altogether, the receptor(s) mediating the interation with HBEC-5i remains unknown. In order to carry out transcriptional analysis of selected and unselected paarasites form all three parasite strains, it was necessary to update the existing microarray chip which is based on the 3D7 genome. This is because each parasite train has a unique repertoire of variant surface antigens (VSAs) including var, rif and stevor genes. Therefore, to fully analysis HB3 and IT genomes. Unique oligonnucleotide probes were then designed for each new sequence and the 3D7-based microarray chip was updated. Transcriptional analysis was then carried out on selected and unselected parasites of all strains. Microarray data clearly indicated that the most highly upregulated genes after selection were group A or group A-like var genes (HB3var3, 3D7_PFDOO2Oc, ITvar7 and ITvar19), showing 11 to over 100 fold upregulation in selected parasites. The rif gene adjacent to the upregulated var gene was also highly expressed. To a lesser extent some exported proteins like RESA-1, PfEMP3 or PHIST family members also showed increased transcription in HBEC-selected parasites (2-3 fold upregulation). Reverse transcriptase-PCR confirmed the upregulation of group A var genes in selected parasites, suggessted that the group A PfEMP1 variants are major candidate ligands for parasite binding to HBEC-5i. These findings are consistent with previous work showing an association between Group A var genes and cerebral malaria.

The blood-brain barrier, formed by brain microvessel endothelial cells, is the restrictive barrier between the brain parenchyma and the circulating blood. It was previously demonstrated in our laboratory that knock down of fatty acid transport proteins FATP-1 and CD36 attenuated apical to basolateral monounsaturated fatty acid transport across human brain microvessel endothelial cells (HBMEC). Arachidonic acid (AA; 5,8,11,14 - cis-eicosatetraenoic acid) is a conditionally essential, polyunsaturated fatty acid [20:4(n-6)] and a major constituent of brain lipids. We examined transport of AA across confluent monolayers of HBMEC. Control cells or HBMEC with knock down of FATP-1 or CD36 were cultured on Transwell® plates and incubated apically with [3H]AA and incorporation of [3H]AA into the basolateral medium was determined temporally. [3H]AA was rapidly incorporated into the basolateral medium with time in control cells. Surprisingly, knock down of FATP-1 or CD36 did not alter [3H]AA movement into the basolateral medium. The increased permeability mediated by AA was likely caused by a metabolite of AA produced de novo and was confirmed by an increased movement of fluorescent dextran from apical to basolateral medium. HBMECs expressed PGE2 synthase, cyclooxygenase-1 and -2, PGE2 receptors, tight junction proteins and prostaglandin transporters. The AA-mediated increase in membrane permeability was not attenuated by cyclooxygenase inhibitor drugs (NSAIDs). Incubation of the HBMEC monolayers with exogenous PGE2 resulted in attenuation of the AA-mediated permeability increases. The results indicate that AA increases the permeability of the HBMEC monolayer likely via increased production of metabolites or by-products of the lipoxygenase or epoxygenase pathways. These observations may explain the rapid influx of AA into the brain previously observed upon plasma infusion with AA.

The blood-brain barrier, formed by brain microvessel endothelial cells, is the restrictive barrier between the brain parenchyma and the circulating blood. It was previously demonstrated in our laboratory that knock down of fatty acid transport proteins FATP-1 and CD36 attenuated apical to basolateral monounsaturated fatty acid transport across human brain microvessel endothelial cells (HBMEC). Arachidonic acid (AA; 5,8,11,14 - cis-eicosatetraenoic acid) is a conditionally essential, polyunsaturated fatty acid [20:4(n-6)] and a major constituent of brain lipids. We examined transport of AA across confluent monolayers of HBMEC. Control cells or HBMEC with knock down of FATP-1 or CD36 were cultured on Transwell® plates and incubated apically with [3H]AA and incorporation of [3H]AA into the basolateral medium was determined temporally. [3H]AA was rapidly incorporated into the basolateral medium with time in control cells. Surprisingly, knock down of FATP-1 or CD36 did not alter [3H]AA movement into the basolateral medium. The increased permeability mediated by AA was likely caused by a metabolite of AA produced de novo and was confirmed by an increased movement of fluorescent dextran from apical to basolateral medium. HBMECs expressed PGE2 synthase, cyclooxygenase-1 and -2, PGE2 receptors, tight junction proteins and prostaglandin transporters. The AA-mediated increase in membrane permeability was not attenuated by cyclooxygenase inhibitor drugs (NSAIDs). Incubation of the HBMEC monolayers with exogenous PGE2 resulted in attenuation of the AA-mediated permeability increases. The results indicate that AA increases the permeability of the HBMEC monolayer likely via increased production of metabolites or by-products of the lipoxygenase or epoxygenase pathways. These observations may explain the rapid influx of AA into the brain previously observed upon plasma infusion with AA.

Orientador: Fernando Cendes / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Ciencias Medicas / Made available in DSpace on 2018-08-11T18:31:26Z (GMT). No. of bitstreams: 1 Rondina_JaneMaryam_D.pdf: 1600669 bytes, checksum: 1ea760868c65fb9012161a1d5b9c3efa (MD5) Previous issue date: 2008 / Resumo: Este trabalho teve como objetivo a aquisição, processamento e análise de imagens funcionais por ressonância magnética através da aplicação de estímulos para o estudo de processos relacionados à memória verbal e visual em controles e em pacientes com epilepsia do lobo temporal medial associada a atrofia hipocampal. As imagens foram adquiridas pela sequência EPI (Echo-planar Imaging) e o sinal BOLD (Blood-oxygenation-level-dependent) obtido foi analisado de forma multivariada. O contraste entre as condições definidas no desenho do experimento foi analisado estatisticamente através da utilização do teste t-student. Foram realizadas comparações entre diferentes abordagens de processamento das imagens. Foi realizada uma análise de regiões de interesse (ROIs) com o objetivo de explorar as condições definidas no projeto do experimento e avaliar o envolvimento de estruturas anatômicas temporais e frontais no processo de codificação de memória. Foram discutidas questões sobre a utilização de diferentes abordagens de análise individual e de grupo, sobre o planejamento do paradigma e desenho do experimento, sobre o padrão de ativação das estruturas anatômicas consideradas sob diferentes condições e sobre diferenças observadas entre os grupos de pacientes e o grupo de controles / Abstract: The purpose of this work was the acquisition, processing and analysis of functional magnetic resonance images through the application of stimuli for the study of processes related to both verbal and visual memory in both controls and patients with medial temporal lobe epilepsy associated to hippocampal atrophy. The images were acquired using the EPI (Echo-planar Imaging) protocol and the BOLD (Blood-oxygenation-level-dependent) signal was analyzed using a multivariate approach. The contrast between the conditions defined in the design was statistically analyzed using t-test. Voxelwise analysis was performed for comparison among different approaches and ROI (Region of interest) analysis was performed aiming both to explore the conditions defined in the design and to study the involvement of anatomical structures considered (both temporal and frontal) in the memorizing process. Conclusions were obtained about: the use of different analysis approaches; the planning of paradigm and design definition; the activation patterns observed in the anatomical structures considered during the different conditions; and differences observed among the patients and control groups / Doutorado / Ciencias Biomedicas / Doutor em Ciências Médicas

La presente investigación tiene como objetivo diseñar una colección de indumentaria a partir del estudio teórico y visual de la actividad neuronal en el cerebro humano. El cerebro es el órgano principal que rige el organismo del cuerpo humano y está compuesto por dos subsistemas principales, el Sistema Nervioso Central y el Sistema Nervioso Periférico. La neurona, conocida como la unidad básica del Sistema Nervioso, es aquella que contiene toda la carga eléctrica y se encarga de almacenar y transmitir información; dando como resultado los movimientos voluntarios e involuntarios del cuerpo. Por ello, para este estudio, se realizó un riguroso análisis visual de la neurona, de la forma de sus partes principales: cuerpo, axón y dendritas; de su comportamiento en el cerebro y de su proceso de comunicación: la sinapsis. Se buscó interpretar la complejidad estructural y conductual de la neurona para lograr obtener una base creativa y sustentada para el desarrollo de la colección. En este proyecto, para el ámbito teórico, se recopiló información de artículos científicos, libros de ciencia y medicina, revistas académicas y; para el visual, de trabajos de laboratorio, videos, estudios oficiales y libros digitales relacionados al Sistema Nervioso, la neurona y la sinapsis neuronal. Asimismo, se realizó una entrevista a la neurocirujana Astrid Wicht, quien aportó significativamente y otorgó un punto de vista profesional y académico a la investigación. / The following research has the objective of creating a fashion collection, that comes from the theoretical and visual investigation of neural activity in the human brain. The brain is the main organ that controls the body. It is built upon two mayor main systems, the Central Nervous System, and the Peripheral Nervous System. The neuron is known as the basic unit of th nervous system, it oversees controlling electrical impulses, store energy and transmit information, as a result they control of voluntary and involuntary impulses. For this study, an intensive visual analysis of the neuron and its parts was made. The body, the axon, and the dendrite, how they behave in the brain and their process of communication: the synapsis. The structural and behavioral complexity of the neuron were our main goal as a creative base for the development of the collection. In this research regarding the theory, information from scientific articles, science and medicine books, academic magazines were gathered. For the visual; laboratories research, videos, official studies and digital books about the Nervous System, the neuron, and the synapsis. In addition, an interview to neurosurgeon Astrid Wicht was performed, who gave a professional and academic point of view to the investigation. / Trabajo de investigación

The analysis of signals stemming from a physical system is crucial for the experimental investigation of the underlying dynamics that drives the system itself. The field of time series analysis comprises a wide variety of techniques developed with the purpose of characterizing signals and, ultimately, of providing insights on the phenomena that govern the temporal evolution of the generating system. A renowned example in this field is given by spectral analysis: the use of Fourier or Laplace transforms to bring time-domain signals into the more convenient frequency space allows to disclose the key features of linear systems. A more complex scenario turns up when nonlinearity intervenes within a system's dynamics. Nonlinear coupling between a system's degrees of freedom brings about interesting dynamical regimes, such as self-sustained periodic (though anharmonic) oscillations ("limit cycles"), or quasi-periodic evolutions that exhibit sharp spectral lines while lacking strict periodicity ("limit tori"). Among the consequences of nonlinearity, the onset of chaos is definitely the most fascinating one. Chaos is a dynamical regime characterized by unpredictability and lack of periodicity, despite being generated by deterministic laws. Signals generated by chaotic dynamical systems appear as irregular: the corresponding spectra are broad and flat, prediction of future values is challenging, and evolutions within the systems' state spaces converge to strange attractor sets with noninteger dimensionality. Because of these properties, chaotic signals can be mistakenly classified as noise if linear techniques such as spectral analysis are used. The identification of chaos and its characterization require the assessment of dynamical invariants that quantify the complex features of a chaotic system's evolution. For example, Lyapunov exponents provide a marker of unpredictability; the estimation of attractor dimensions, on the other hand, highlights the unconventional geometry of a chaotic system's state space. Nonlinear time series analysis techniques act directly within the state space of the system under investigation. However, experimentally, full access to a system's state space is not always available. Often, only a scalar signal stemming from the dynamical system can be recorded, thus providing, upon sampling, a scalar sequence. Nevertheless, by virtue of a fundamental theorem by Takens, it is possible to reconstruct a proxy of the original state space evolution out of a single, scalar sequence. This reconstruction is carried out by means of the so-called embedding procedure: m-dimensional vectors are built by picking successive elements of the scalar sequence delayed by a lag L. On the other hand, besides posing some necessary conditions on the integer embedding parameters m and L, Takens' theorem does not provide any clue on how to choose them correctly. Although many optimal embedding criteria were proposed, a general answer to the problem is still lacking. As a matter of fact, conventional methods for optimal embedding are flawed by several drawbacks, the most relevant being the need for a subjective evaluation of the outcomes of applied algorithms. Tackling the issue of optimally selecting embedding parameters makes up the core topic of this thesis work. In particular, I will discuss a novel approach that was pursued by our research group and that led to the development of a new method for the identification of suitable embedding parameters. Rather than most conventional approaches, which seek a single optimal value for m and L to embed an input sequence, our approach provides a set of embedding choices that are equivalently suitable to reconstruct the dynamics. The suitability of each embedding choice m, L is assessed by relying on statistical testing, thus providing a criterion that does not require a subjective evaluation of outcomes. The starting point of our method are embedding-dependent correlation integrals, i.e. cumulative distributions of embedding vector distances, built out of an input scalar sequence. In the case of Gaussian white noise, an analytical expression for correlation integrals is available, and, by exploiting this expression, a gauge transformation of distances is introduced to provide a more convenient representation of correlation integrals. Under this new gauge, it is possible to test—in a computationally undemanding way—whether an input sequence is compatible with Gaussian white noise and, subsequently, whether the sequence is compatible with the hypothesis of an underlying chaotic system. These two statistical tests allow ruling out embedding choices that are unsuitable to reconstruct the dynamics. The estimation of correlation dimension, carried out by means of a newly devised estimator, makes up the third stage of the method: sets of embedding choices that provide uniform estimates of this dynamical invariant are deemed to be suitable to embed the sequence.The method was successfully applied to synthetic and experimental sequences, providing new insight into the longstanding issue of optimal embedding. For example, the relevance of the embedding window (m-1)L, i.e. the time span covered by each embedding vector, is naturally highlighted by our approach. In addition, our method provides some information on the adequacy of the sampling period used to record the input sequence.The method correctly distinguishes a chaotic sequence from surrogate ones generated out of it and having the same power spectrum. The technique of surrogate generation, which I also addressed during my Ph. D. work to develop new dedicated algorithms and to analyze brain signals, allows to estimate significance levels in situations where standard analytical algorithms are unapplicable. The novel embedding approach being able to tell apart an original sequence from surrogate ones shows its capability to distinguish signals beyond their spectral—or autocorrelation—similarities.One of the possible applications of the new approach concerns another longstanding issue, namely that of distinguishing noise from chaos. To this purpose, complementary information is provided by analyzing the asymptotic (long-time) behaviour of the so-called time-dependent divergence exponent. This embedding-dependent metric is commonly used to estimate—by processing its short-time linearly growing region—the maximum Lyapunov exponent out of a scalar sequence. However, insights on the kind of source generating the sequence can be extracted from the—usually overlooked—asymptotic behaviour of the divergence exponent. Moreover, in the case of chaotic sources, this analysis also provides a precise estimate of the system's correlation dimension. Besides describing the results concerning the discrimination of chaotic systems from noise sources, I will also discuss the possibility of using the related correlation dimension estimates to improve the third stage of the method introduced above for the identification of suitable embedding parameters. The discovery of chaos as a possible dynamical regime for nonlinear systems led to the search of chaotic behaviour in experimental recordings. In some fields, this search gave plenty of positive results: for example, chaotic dynamics was successfully identified and tamed in electronic circuits and laser-based optical setups. These two families of experimental chaotic systems eventually became versatile tools to study chaos and its possible applications. On the other hand, chaotic behaviour is also looked for in climate science, biology, neuroscience, and even economics. In these fields, nonlinearity is widespread: many smaller units interact nonlinearly, yielding a collective motion that can be described by means of few, nonlinearly coupled effective degrees of freedom. The corresponding recorded signals exhibit, in many cases, an irregular and complex evolution. A possible underlying chaotic evolution—as opposed to a stochastic one—would be of interest both to reveal the presence of determinism and to predict the system's future states. While some claims concerning the existence of chaos in these fields have been made, most results are debated or inconclusive. Nonstationarity, low signal-to-noise ratio, external perturbations and poor reproducibility are just few among the issues that hinder the search of chaos in natural systems. In the final part of this work, I will briefly discuss the problem of chasing chaos in experimental recordings by considering two example sequences, the first one generated by an electronic circuit and the second one corresponding to recordings of brain activity. The present thesis is organized as follows. The core concepts of time series analysis, including the key features of chaotic dynamics, are presented in Chapter 1. A brief review of the search for chaos in experimental systems is also provided; the difficulties concerning this quest in some research fields are also highlighted. Chapter 2 describes the embedding procedure and the issue of optimally choosing the related parameters. Thereupon, existing methods to carry out the embedding choice are reviewed and their limitations are pointed out. In addition, two embedding-dependent nonlinear techniques that are ordinarily used to characterize chaos, namely the estimation of correlation dimension by means of correlation integrals and the assessment of maximum Lyapunov exponent, are presented. The new approach for the identification of suitable embedding parameters, which makes up the core topic of the present thesis work, is the subject of Chapter 3 and 4. While Chapter 3 contains the theoretical outline of the approach, as well as its implementation details, Chapter 4 discusses the application of the approach to benchmark synthetic and experimental sequences, thus illustrating its perks and its limitations. The study of the asymptotic behaviour of the time-dependent divergent exponent is presented in Chapter 5. The alternative estimator of correlation dimension, which relies on this asymptotic metric, is discussed as a possible improvement to the approach described in Chapters 3, 4. The search for chaos out of experimental data is discussed in Chapter 6 by means of two examples of real-world recordings. Concluding remarks are finally drawn in Chapter 7.

In einem RT-PCR Ansatz aus neuronalen post mortem Gewebe des Menschen konnten EPB41 (Erythrozytäres Protein Bande 4.1) Spleißformen in verschiedenen Hirnregionen nachgewiesen werden. In einem weiteren RT-PCR Ansatz wurden höhermolekulare p4.1R-Spleißormen generiert, kloniert und zwei der erhaltenen Spleißformen (Klon 9 und Klon 13) charakterisiert. In einer In-situ-Hybridisierungsstudie an humanen Temporalkortex und Hippocampus konnten EPB41-Isoformen in fast allen Neuronen nachgewiesen werden. In immunhistochemischen Untersuchungen mit selbstgenerierten p4.1R spezifischen Antikörper wurden ebenfalls ausschließlich Neurone markiert. In proteinbiochemischen Untersuchungen konnte in verschiedenen humanen Hirnareale mit den p4.1R spezifischen Antikörpern eine 110 kDa und 120 kDa immunreaktive Bande nachgewiesen werden. In Experimenten an Primärkulturen von Rattenneuronen konnte eine Herunterregulation der p4.1R Proteine sowie der mRNA von p4.1R durch Verarmung des funktionellen Pools an G-Proteinen der Rho-Familie in der Zelle gezeigt werden. Die GTPasen der Rho-Familie regulieren unter anderem die Plastizität des Dendritenbaumes von Neuronen. / In a RT-PCR approach using human postmortem cerebral tissue from different brain regions several EPB41 (erythrocyte protein band 4.1) spliceforms could be generated. The amplificates were cloned and two of the highmolecular EPB41 spliceforms Klon 9 and Klon 13 were characterized. Klon 9 is a new spliceform, Klon13 is identical with EPB41 (accesion number AF156225). In an in situ hybridization study the EPB41 spliceforms were detected in almost all neurons of the temporal cortex and the hippocampus. Immunhistochemical localization of the p4.1R immunreactive proteins in human temporal cortex using p4.1R specific peptide antibodies, confirmed these results. The stning pattern of soma and dendrites of the neurones was punctuated. In Western Blot experiments a 110 kDa and 120 kDa p4.1R immunreactive proteinband was detected. A regulation of the protein 4.1R immunreactive proteins as well as the mRNA of protein 4.1 was found in experiments in which the functional pool of Rho GTPases in hippocampal primary neurones of the rat was manipulated.

La parcellisation du cerveau humain en aires fonctionnelles est un problème complexe mais majeur pour la compréhension du fonctionnement du cerveau et pourrait avoir des applications médicales importantes en neurochirurgie par exemple pour mieux identifier les zones fonctionnelles à sauvegarder. Cet objectif va de pair avec l’idée de construire le connectome cérébral humain, qui n’est autre que le réseau de ses connexions.Pour définir un tel réseau, il faut en effet définir les éléments de ce réseau de connexions : c’est-à-dire avoir un découpage du cerveau en régions. Il existe de multiples manières et critères pour identifier ces régions et à ce jour il n’y a pas de parcellisation universelle du cortex. Dans cette thèse nous étudierons la possibilité d’effectuer cette parcellisation en fonction des données de connectivité anatomique, issues de l’imagerie par résonance magnétique de diffusion, qui est une technique d’acquisition permettant de reconstruire les faisceaux de neurones cérébraux de manière non invasive. Nous nous placerons dans un cadre surfacique en étudiant seulement la surface corticale et les connexions anatomiques sous-jacentes. Dans ce contexte nous présenterons un ensemble de nouveaux outils pour construire, visualiser et simuler le connectome cérébral humain, dans un cadre surfacique et à partir des données de connectivité anatomique reconstruites par IRM, et ceci pour un groupe de sujets. A partir de ces outils nous présenterons des méthodes de réduction de dimension des données de connectivité, que nous appliquerons pour parcelliser le cortex entier de quelques sujets. Nous proposons aussi une nouvelle manière de décomposer les données de connectivité au niveau d’un groupe de sujets en tenant compte de la variabilité inter-individuelle. Cette méthode sera testée et comparée à d’autres méthodes sur des données simulées et des données réelles. Les enjeux de ce travail sont multiples, tant au niveau méthodologique (comparaison de différents algorithmes de tractographie par exemple) que clinique (étude du lien entre altérations des connexions et pathologie). / In-vivo parcellation of the human cortex into functional brain areas is a major goal to better understand how the brain works and could have a lot of medical applications and give useful information to guide neurosurgery for example. This objective is related to the buildong of the human brain connectome, which is the networks of brain connections.Indeed, it is necessary to define the basic element of this connectome, and for doing this to have a subdivision of the cortex into brain regions. Actually, there is no such gold standard parcellation : there are a lot of techniques and methods to achieve this goal. During this PhD., anatomical connectivité based on diffusion-weighted imaging hase been used to address this problem, with a surfacic approach. In this context, we will present a set of new tools to create, visualize and simulate the human brain connectome for a group of subjects. We will introduce dimension reduction methods to compile the cortical connectivity profiles taking into account the interindividual variability. These methods will be apply to parcellate the cortex, for one subject or for a group of subjects simultaneously.There are many applications of this work, in methodology, to compare tractography algorithms for example or in clinical, to look at the relations between connections damages and pathology.

L'objectif de cette thèse était d'explorer le potentiel de l’imagerie du cerveau humain par ultrasons. L'anatomie, le flux sanguin et la rigidité des tissus mous ont déjà été étudiés avec l'imagerie ultrasonore ultrarapide chez l'homme et validés sur plusieurs organes, tels que le sein et le foie, mais pas encore sur le cerveau adulte. La principale limitation de l'imagerie échographique transcrânienne est aujourd'hui le très fort artefact d'aberration induit par le crâne. En effet, l’os, de par sa composition ne permet pas la propagation des ultrasons comme ailleurs dans le corps humain. Dans cette thèse, nous avons utilisé l'imagerie ultrasonore ultrarapide pour l'évaluation de la rigidité des tissus mous et l'imagerie neurofonctionnelle dans le cerveau humain adulte, lors de chirurgies du cerveau afin de contourner dans un premier temps le problème des aberrations induites par le crâne. La dernière partie de cette thèse était axée sur la correction d’aberration pour l’échographie quantitative et l’imagerie ultrasonore transcrânienne. Nous avons tout d’abord fourni plusieurs preuves de l'intérêt d'utiliser l’élastographie par onde de cisaillement pendant la chirurgie du cerveau. Nous avons également présenté notre nouvelle technique d’élastographie par onde de cisaillement en 3D à l'aide d'une sonde matricielle dans le but de pouvoir dépasser les limitations du 2D et notamment être moins dépendant de l’opérateur.Dans un second volet, nous avons démontré la capacité des ultrasons ultrarapides à identifier, cartographier et différencier en profondeur les régions d'activation corticales en réponse à un stimulus, à la fois chez les patients éveillés et chez les patients anesthésiés. Nous avons démontré que l'imagerie neurofonctionnelle par ultrasons a le potentiel de devenir une modalité complète de neuroimagerie avec des avantages majeurs pour une utilisation peropératoire.Dans un troisième volet, nous avons utilisé une technique en trois étapes pour calculer précisément la vitesse du son (SSE) dans un milieu. Cette technique a été testée dans des fantômes ultrasonores et in vivo dans les foies de patients. Dans les deux cas, notre méthode a été capable de trouver la vitesse du son correspondant au milieu. Nous avons démontré que la SSE était liée à la fraction de graisse. Cette analyse a permis de conclure que la SSE était en mesure de distinguer un foie sain et d’un foie malade aussi bien avec la biopsie qu’avec l’IRM comme méthode de référence. Combiné à l'utilisation de la formule de Wood, nous avons même pu avoir accès à une fraction de graisse mesurée par ultrasons de manière non invasive. Puis nous avons combiné la correction d’aberration de phase, d'amplitude et de vitesse du son pour faire de l’imagerie transcrânienne en simulation numérique. Nous avons atteint notre objectif en obtenant des images représentant fidèlement le milieu (position latérale et profondeur) et caractérisées par une résolution et un contraste similaires à ceux obtenus avec une source ponctuelle dans le milieu / The objective of this thesis was to explore the potential of human brain ultrasound imaging. Anatomy, blood flow and soft tissue stiffness have already been studied with ultrafast ultrasound imaging in humans and validated in several organs, such as, the breast and liver but not yet on the adult brain. The main limitation of transcranial ultrasound imaging is today the very strong skull-induced aberration artefact. Indeed, the bone, due to its composition, does not allow for ultrasound propagation as elsewhere in the human body. Therefore, this thesis was focused on the development of ultrafast ultrasound imaging for the evaluation of soft tissue stiffness and neurofunctional imaging in the adult human brain, during brain surgery to bypass the problem of skull aberration, and on an aberration correction technique for transcranial ultrasound imaging.We first provided several evidence of the benefit of using shear wave elastography during brain surgery. We also presented our new technique for 3D shear wave elastography using a matrix array in order to be able to overcome the limitations of 2D imaging and in particular to reduce the operator dependence.In a second phase, we demonstrated the capability of ultrasound to identify, map and differentiate in depth cortical regions of activation in response to a stimulus, both in awake patients and in anaesthetized patients. We have demonstrated that ultrasound neurofunctional imaging has the potential to become a comprehensive modality of neuroimaging with major benefits for intraoperative use. In a third part, we developed a new sound speed estimation (SSE) technique, based on a three-step technique that estimates the sound speed accurately corresponding to the illuminated medium. This technique was tested in ultrasound phantoms and in vivo in patient’s liver. In both cases, our method was able to find the sound speed corresponding to the medium. We demonstrated that SSE was related to the fat fraction. This analysis led to the conclusion that SSE was able to distinguish a healthy liver from a diseased liver with both biopsy and MRI as gold standard. Combined with the use of the Wood’s formula, we were even able to access a fat fraction measured by non-invasive ultrasound. Finally, by combining the phase, the amplitude and the sound speed estimation, we have developed a new aberration correction algorithm to perform transcranial ultrasound imaging. By performing numerical simulations, we obtained images that faithfully represented the medium (lateral position and depth) and characterized by one resolution and one contrast similar to those obtained with a punctual source in the medium