Functional and structural substrates of increased dosage of Grik4 gene elucidated using multi-modal MRI

Grik4 is the gene responsible for encoding the high-affinity GluK4 subunit of the kainate receptors. Increased dosage of this subunit in the forebrain was linked to an increased level of anxiety, lack of social communication, and depression. On the synaptic level, abnormal synaptic transmission was also reported. The manifestations of this abnormal expression have not been investigated at the circuit level, nor the correlations between those circuits and the abnormal patterns of the behavior previously reported. In this line of work, we aspired to use different non-invasive magnetic resonance imaging (MRI) modalities to elucidate any disturbance that might stem from the increased dosage of Grik4 and how those changes might explain the abnormal behaviors. MRI offers a noninvasive way to look into the intact brain in vivo. Resting-state functional MRI casts light on how the brain function at rest on the network level and has the capability to detect any anomalies that might occur within or between those networks. On the microstructural level, the diffusion MRI is concerned with the underlying features of the tissues, using the diffusion of water molecules as a proxy for that end. Moving more macroscopically, using structural scans, voxel-based morphometry can detect subtle differences in the morphology of the different brain structures. We recorded videos of our animals performing two tasks that have long been linked to anxiety, the open field and the plus-maze tests before acquiring structural and functional scans. Lastly, we recorded blood-oxygenationlevel dependent (BOLD) signals in a different set of animals during electrical stimulation of specific white matter tracts in order to investigate how neuronal activity propagates. Our analysis showed a vast spectrum of changes in the transgenic group relative to the animals in the control group. On the resting-state networks level, we observed an increase in the within-network strength spanning different structures such as the hippocampus, some regions of the cortex, and the hypothalamus. The increased internal coherence or strength in the networks contrasted with a significant reduction in between-networks connectivity for some regions such as parts of the cortex and the hypothalamus, suggesting long-range network decorrelation. Supporting this idea, major white matter (WM) tracts, such as the corpus callosum and the hippocampal commissure, suffered from substantial changes compatible with an important reduction in myelination and/or a decrease in the mean axonal diameter. Macrostructurally speaking, the overexpression of GluK4 subunit had a bimodal effect, with expansion in some cortical areas in the transgenic animals accompanied by a shrinkage in the subcortical regions. Upon stimulating the brain with an electrical current, we noticed a difference in activity propagation between the two hemispheres. In transgenic animals, the evoked activity remained more confined to the stimulated hemisphere, again consistent with an impaired long-range connectivity. The structural changes both, at the micro and macro level, were in tight correlation with different aspects of the behavior including markers of anxiety such as the time spent in the open arms vs the closed arms in the plus-maze test and the time spent in the center vs the corners in the open field test. Our findings reveal how the disruption of kainate receptors, or more globally the glutamate receptors, and the abnormal synaptic transmission can translate into brain-wide changes in connectivity and alter the functional equilibrium between macro-and mesoscopic networks. The postsynaptic enhancement previously reported in the transgenic animals was here reflected in the BOLD signal and measured as an increase in the within-network strength. Importantly, the correlations between the structural changes and the behavior help to put the developmental changes and their behavioral ramifications into context. RESUMEN Grik4 es el gen responsable de codificar la subunidad GluK4 de alta afinidad de los receptores de kainato. El aumento de la dosis de esta subunidad en el prosencéfalo se relacionó con un mayor nivel de ansiedad, falta de comunicación social y depresión. A nivel sináptico, también se informó una transmisión sináptica anormal. Las manifestaciones de esta expresión anormal no se han investigado a nivel de circuito, ni las correlaciones entre esos circuitos y los patrones anormales de la conducta previamente informada. En esta línea de trabajo, aspiramos a utilizar diferentes modalidades de imágenes por resonancia magnética (MRI) no invasivas para dilucidar cualquier alteración que pudiera derivarse del aumento de la dosis de Grik4 y cómo esos cambios podrían explicar los comportamientos anormales. La resonancia magnética ofrece una forma no invasiva de observar el cerebro intacto in vivo. La resonancia magnética funcional en estado de reposo arroja luz sobre cómo funciona el cerebro en reposo en el nivel de la red y tiene la capacidad de detectar cualquier anomalía que pueda ocurrir dentro o entre esas redes. En el nivel microestructural, la resonancia magnética de difusión se ocupa de las características subyacentes de los tejidos utilizando la difusión de moléculas de agua como un proxy para ese fin. Moviéndose más macroscópicamente, utilizando escaneos estructurales, la morfometría basada en vóxeles puede detectar diferencias sutiles en la morfología de las diferentes estructuras cerebrales. Grabamos videos de nuestros animales realizando dos tareas que durante mucho tiempo se han relacionado con la ansiedad, el campo abierto y las pruebas de laberinto positivo antes de adquirir escaneos estructurales y funcionales. Por último, registramos señales dependientes del nivel de oxigenación de la sangre (BOLD) en un grupo diferente de animales durante la estimulación eléctrica de tractos específicos de materia blanca para investigar cómo se propaga la actividad neuronal. Nuestro análisis mostró un amplio espectro de cambios en el grupo transgénico en relación con los animales en el grupo de control. En el nivel de las redes de estado de reposo, observamos un aumento en la fuerza dentro de la red que abarca diferentes estructuras como el hipocampo, algunas regiones de la corteza y el hipotálamo. La mayor coherencia interna o fuerza en las redes contrastó con una reducción significativa en la conectividad entre redes para algunas regiones como partes de la corteza y el hipotálamo, lo que sugiere una descorrelación de redes de largo alcance. Apoyando esta idea, los grandes tractos de materia blanca (WM), como el cuerpo calloso y la comisura del hipocampo, sufrieron cambios sustanciales compatibles con una importante reducción de la mielinización y / o una disminución del diámetro axonal medio. Macroestructuralmente hablando, la sobreexpresión de la subunidad GluK4 tuvo un efecto bimodal, con expansión en algunas áreas corticales en los animales transgénicos acompañada de una contracción en las regiones subcorticales. Al estimular el cerebro con una corriente eléctrica, notamos una diferencia en la propagación de la actividad entre las dos hemiesferas. En los animales transgénicos, la actividad evocada permaneció más confinada al hemisferio estimulado, de nuevo consistente con una conectividad de largo alcance deteriorada. Los cambios estructurales, tanto a nivel micro como macro, estaban en estrecha correlación con diferentes aspectos de la conducta, incluidos marcadores de ansiedad como el tiempo pasado con los brazos abiertos frente a los brazos cerrados en la prueba del laberinto positivo y el tiempo pasado en el centro vs las esquinas en la prueba de campo abierto. Nuestros hallazgos revelan cómo la interrupción de los receptores de kainato, o más globalmente los receptores de glutamato, y la transmisión sináptica anormal pueden traducirse en cambios de conectividad en todo el cerebro y alterar el equilibrio funcional entre las redes macro y mesoscópicas. La mejora postsináptica informada anteriormente en los animales transgénicos se reflejó aquí en la señal BOLD y se midió como un aumento en la fuerza dentro de la red. Es importante destacar que las correlaciones entre los cambios estructurales y elcomportamiento ayudan a contextualizar los cambios en el desarrollo y sus ramificaciones conductuales

Super-resolution in brain Diffusion Weighted Imaging (DWI)

Abstract. Diffusion Weighted (DW) imaging has proven to be useful at analysing brain architecture as well as at establishing brain tract organization and neuronal connectivity. However, an actual clinical use of DW images is currently limited by a series of acquisition artifacts, among them the partial volume effect (PVE) that may completely alter the spatial resolution and therefore the visualization of microanatomical details. In this work, a new superresolution method will be presented, taking advantage of the redundant structural patterns that shape the brain. The proposed method couples low-high resolution information and explores different directional spaces that might exploit the spectral content of the DW images. A comparison of this proposal with a classical image interpolation method demostrates an improvement of about 3 dB when using the typical PSNR.Las imágenes de Difusión Ponderada (DWI por sus siglas en inglés) han probado ser de gran utilidad en proceso de análisis de la arquitectura del cerebro y en investigaciones acerca de la organización de tractos y la conectividad neuronal. Sin embargo, el uso clínico de la imágenes DW está limitado actualmente por algunos artefactos propios de la adquisición, tales como el efecto de volumen parcial (PVE), que afecta la resolución espacial y por ende la visualización de detalles microanatómicos. En este trabajo de tesis se presenta un nuevo método de super-resolución que aprovecha lo redundante de los patrones estructurales que dan forma al cerebro el cerebro. El método propuesto acopla información de alta /baja resolución y explora diferentes espacios de representación para las características direccionales y el contenido espectral de las DWI. Una comparación con métodos clásicos de interpolación demuestra una mejora de cerca de 3dB usando como métrica el PSNR.Maestrí

Super-resolution in brain Diffusion Weighted Imaging (DWI)

Abstract. Diffusion Weighted (DW) imaging has proven to be useful at analysing brain architecture as well as at establishing brain tract organization and neuronal connectivity. However, an actual clinical use of DW images is currently limited by a series of acquisition artifacts, among them the partial volume effect (PVE) that may completely alter the spatial resolution and therefore the visualization of microanatomical details. In this work, a new superresolution method will be presented, taking advantage of the redundant structural patterns that shape the brain. The proposed method couples low-high resolution information and explores different directional spaces that might exploit the spectral content of the DW images. A comparison of this proposal with a classical image interpolation method demostrates an improvement of about 3 dB when using the typical PSNR.Las imágenes de Difusión Ponderada (DWI por sus siglas en inglés) han probado ser de gran utilidad en proceso de análisis de la arquitectura del cerebro y en investigaciones acerca de la organización de tractos y la conectividad neuronal. Sin embargo, el uso clínico de la imágenes DW está limitado actualmente por algunos artefactos propios de la adquisición, tales como el efecto de volumen parcial (PVE), que afecta la resolución espacial y por ende la visualización de detalles microanatómicos. En este trabajo de tesis se presenta un nuevo método de super-resolución que aprovecha lo redundante de los patrones estructurales que dan forma al cerebro el cerebro. El método propuesto acopla información de alta /baja resolución y explora diferentes espacios de representación para las características direccionales y el contenido espectral de las DWI. Una comparación con métodos clásicos de interpolación demuestra una mejora de cerca de 3dB usando como métrica el PSNR.Maestrí

A novel mechanism of contrast in MRI: pseudo super-diffusion of water molecules unveils microstructural details in biological tissues

The goal of this work is to investigate the properties of the contrast provided by Anomalous Diffusion (AD) γ-imaging technique and to test its potential in detecting tissue microstructure. The collateral purpose is to implement this technique by optimizing data acquisition and data processing, with the long term perspective of adoption in massive in vitro, in vivo and clinical studies. The AD γ-imaging technique is a particular kind of Diffusion Weighted- Magnetic Resonance Imaging (DW-MRI). It represents a refinement of conventionally used DW-MRI methods, sharing with them the advantage of being non invasive, since it uses water as an endogenous contrast agent. Besides, it is more suitable to the study of complex tissues, because it is based on a theoretical model that overcomes the simplistic Gaussian assumption. While the Gaussian assumption predicates the linearity between the average molecular displacement of water and the diffusing time, as in case of diffusion in isotropic, homogeneous and infinite environments, a number of experiments performed in vitro and in vivo on both animals and humans showed an anomalous behavior of water molecules, with a non linear relation between the distance travelled and the elapsed time. In particular, the γ-parameter quantifies water pseudo super-diffusion, a peculiarity due to the fact that water diffusion occurs in multi-compartments and it is probed by means of MRI. In fact, a restricted diffusion is rather predicted for water diffusing in biological tissues. Recently, the trick that allows to make the traditional DW-MRI acquisition sequence suitable for pseudo super-diffusion quantification has been unveiled, and in short it consists in performing DW experiments varying the diffusion gradient strengths, at a constant diffusive time. The γ-parameter is extracted by fitting DW-data to a stretched-exponential function. Finally, probing water diffusion in different directions allows to reconstruct a γ-tensor, with scalar invariants that quantify the entity of AD and its anisotropy in a given volume element. In vitro results on inert materials revealed that γ correlates with internal gradients arising from magnetic susceptibility differences (Δ) between neighboring compartments, and that it reflects the multi-compartmentalization of the space explored by diffusing molecules. Furthermore, values of γ compatible with a description of super-diffusive motion were found. This anomaly can be explained considering that the presence of Δ induce an additional attenuation to the signal, simulating a pseudo super-diffusion. Finally, In vivo results on human brain showed that γ is more effective in discriminating among different brain regions compared to conventional DWMRI parameters. These studies suggest that the contrast provided by AD γ-imaging is influenced by an interplay of two factors, Δ -effects on one hand, multicompartmentalization on the other hand, through which γ could reflect tissue microstructure. With the aim to shed some light on this issue I performed AD γ-imaging in excised mouse spinal cord (MSC) at 9.4 T and healthy human brain at 3.0 T. The adoption of MSC was motivated by its current use in studies of demyelination due to an induced pathology that mimics Multiple Sclerosis alterations, and by its simplified geometry. I acquired DW-data with parameters optimized for the particular system chosen: the MSC was scanned along 3 orthogonal directions, thus an apparent γ was derived; for the in vivo studies I used more directions and I extracted a γ-tensor. I found that γ and its anisotropy reflected the microstructure of spinal cord tracts (such as the axon diameters and the axonal density). I investigated both in MSC and human brain the relation between γ and the rate of relaxation (R2*), a parameter well-known to reflect Δ, and found significant linear correlations. Because of this γ was able to differentiate white matter regions on the basis of their spatial orientation, and gray matter regions on the basis of their intrinsic iron content in human brain imaged at 3.0 T. These results suggest that AD γ-imaging could be an alternative or complementary technique to DW-MRI in the field of neuroscience. Indeed it could be useful for the assessment of the bulk susceptibility inhomogeneity, which reflects iron deposition, the hallmark of several neurodegenerative diseases. The part of this thesis work concerning the in vivo experiment in human brain gave rise to a paper published on NeuroImage, a relevant scientific journal in the field of MRI applied to brain investigation

Assessing Optic Neuritis in a Mouse Model of Multiple Sclerosis with Diffusion MR Imaging

Optic neuritis (ON) is an early manifestation in patients of multiple sclerosis (MS), typically resulting in visual dysfunction. The inflammatory demyelination of the optic nerve in ON closely resembles pathologies of the rest of central nervous system (CNS) white matter in MS. Since accumulated axonal degeneration in MS was considered as the potential cause leading to permanent disability, correlating optic nerve pathology and visual function in ON could be a model system to investigate the relationship between functional outcome and neuropathology. It may also present a new way to reflect the disease progression in MS. Various MR techniques have been used to assess inflammation (inflammatory cell infiltration and vasogenic edema) of ON, but rarely demonstrated the ability to image cellularity changes non-invasively. Diffusion MRI measures the Brownian motion of water molecules in the microstructure of biological tissues. Diffusion tensor imaging (DTI) holds the promise to provide a specific biomarker of axonal injury and demyelination in CNS white matter by axial diffusivity (the diffusion parallel to white matter fibers) and radial diffusivity (the diffusion perpendicular to white matter fibers), respectively. However, DTI assumes a single diffusion tensor model and thus takes an average of varied diffusion components. In contrast, our recently developed diffusion basis spectrum imaging (DBSI) resolves the complex diffusion components and provides relatively accurate directional diffusivities and diffusion component fractions, relating to the detail and accurate pathological picture of the disease or injury. In the current work, in vivo 25-direction DBSI was applied to the optic nerve of mice with experimental autoimmune encephalomyelitis (EAE), an animal model of MS, with visual impairment at onset of ON. Our results demonstrate that inflammation correlated well with visual impairment in acute ON. DBSI successfully detected inflammatory cell infiltration and optic nerve white matter pathology in EAE that was consistent with histology, supporting the capability of DBSI to quantify increased cellularity, axonal injury and myelin damage in the optic nerve of EAE mice

Development of novel magnetic resonance methods for advanced parametric mapping of the right ventricle

The detection of diffuse fibrosis is of particular interest in congenital heart disease patients, including repaired Tetralogy of Fallot (rTOF), as clinical outcome is linked to the accurate identification of diffuse fibrosis. In the Left Ventricular (LV) myocardium native T1 mapping and Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) are promising approaches for detection of diffuse fibrosis. In the Right Ventricle (RV) current techniques are limited due to the thinner, mobile and complex shaped compact myocardium. This thesis describes technical development of RV tissue characterisation methods. An interleaved variable density spiral DT-CMR method was implemented on a clinical 3T scanner allowing both ex and in vivo imaging. A range of artefact corrections were implemented and tested (gradient timing delays, off-resonance and T2* corrections). The off- resonance and T2* corrections were evaluated using computational simulation demonstrating that for in vivo acquisitions, off-resonance correction is essential. For the first-time high-resolution Stimulated Echo Acquisition Mode (STEAM) DT-CMR data was acquired in both healthy and rTOF ex-vivo hearts using an interleaved spiral trajectory and was shown to outperform single-shot EPI methods. In vivo the first DT-CMR data was shown from the RV using both an EPI and an interleaved spiral sequence. Both sequences provided were reproducible in healthy volunteers. Results suggest that the RV conformation of cardiomyocytes differs from the known structure in the LV. A novel STEAM-SAturation-recovery Single-sHot Acquisition (SASHA) sequence allowed the acquisition of native T1 data in the RV. The excellent blood and fat suppression provided by STEAM is leveraged to eliminate partial fat and blood signal more effectively than Modified Look-Locker Imaging (MOLLI) sequences. STEAM-SASHA T1 was validated in a phantom showing more accurate results in the native myocardial T1 range than MOLLI. STEAM-SASHA demonstrated good reproducibility in healthy volunteers and initial promising results in a single rTOF patient.Open Acces

The impact of aerobic exercise on brain's white matter integrity in the Alzheimer's disease and the aging population

The brain is the most complex organ in the body. Currently, its complicated functionality has not been fully understood. However, in the last decades an exponential growth on research publications emerged thanks to the use of in-vivo brain imaging techniques. One of these techniques pioneered for medical use in the early 1970s was known as nuclear magnetic resonance imaging based (now called magnetic resonance imaging [MRI]). Nowadays, the advances of MRI technology not only allowed us to characterize volumetric changes in specific brain structures but now we could identify different patterns of activation (e.g. functional MRI) or changes in structural brain connectivity (e.g. diffusion MRI). One of the benefits of using these techniques is that we could investigate changes that occur in disease-specific cohorts such as in the case of Alzheimer’s disease (AD), a neurodegenerative disease that affects mainly older populations. This disease has been known for over a century and even though great advances in technology and pharmacology have occurred, currently there is no cure for the disease. Hence, in this work I decided to investigate whether aerobic exercise, an emerging alternative method to pharmacological treatments, might provide neuroprotective effects to slow down the evident brain deterioration of AD using novel in-vivo diffusion imaging techniques. Previous reports in animal and human studies have supported these exercise-related neuro-protective mechanisms. Concurrently in AD participants, increased brain volumes have been positively associated with higher cardiorespiratory fitness levels, a direct marker of sustained physical activity and increased exercise. Thus, the goal of this work is to investigate further whether exercise influences the brain using structural connectivity analyses and novel diffusion imaging techniques that go beyond volumetric characterization. The approach I chose to present this work combined two important aspects of the investigation. First, I introduced important concepts based on the neuro-scientific work in relation to Alzheimer’s diseases, in-vivo imaging, and exercise physiology (Chapter 1). Secondly, I tried to describe in simple mathematics the physics of this novel diffusion imaging technique (Chapter 2) and supported a tract-specific diffusion imaging processing methodology (Chapter 3 and 4). Consequently, the later chapters combined both aspects of this investigation in a manuscript format (Chapter 5-8). Finally, I summarized my findings, include recommendations for similar studies, described future work, and stated a final conclusion of this work (Chapter 9)

Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference

AbstractCharacterizing a particular neurodegenerative condition against others possible diseases remains a challenge along clinical, biomarker, and neuroscientific levels. This is the particular case of frontotemporal dementia (FTD) variants, where their specific characterization requires high levels of expertise and multidisciplinary teams to subtly distinguish among similar physiopathological processes. Here, we used a computational approach of multimodal brain networks to address simultaneous multiclass classification of 298 subjects (one group against all others), including five FTD variants: behavioral variant FTD, corticobasal syndrome, nonfluent variant primary progressive aphasia, progressive supranuclear palsy, and semantic variant primary progressive aphasia, with healthy controls. Fourteen machine learning classifiers were trained with functional and structural connectivity metrics calculated through different methods. Due to the large number of variables, dimensionality was reduced, employing statistical comparisons and progressive elimination to assess feature stability under nested cross-validation. The machine learning performance was measured through the area under the receiver operating characteristic curves, reaching 0.81 on average, with a standard deviation of 0.09. Furthermore, the contributions of demographic and cognitive data were also assessed via multifeatured classifiers. An accurate simultaneous multiclass classification of each FTD variant against other variants and controls was obtained based on the selection of an optimum set of features. The classifiers incorporating the brain’s network and cognitive assessment increased performance metrics. Multimodal classifiers evidenced specific variants’ compromise, across modalities and methods through feature importance analysis. If replicated and validated, this approach may help to support clinical decision tools aimed to detect specific affectations in the context of overlapping diseases