Characterizing functional and structural brain alterations driven by chronic alcohol drinking: a resting-state fMRI connectivity and voxel-based morphometry analysis

El balance del cerebro se altera a nivel estructural y funcional por el consumo de alcohol y puede causar trastornos por consumo de alcohol (TCA). El objetivo de esta Tesis Doctoral fue investigar los efectos del consumo crónico y excesivo de alcohol en el cerebro desde una perspectiva funcional y estructural, mediante análisis de imágenes multimodales de resonancia magnética (RM). Realizamos tres estudios con objetivos específicos: i) Para entender cómo las neuroadaptaciones desencadenadas por el consumo de alcohol se ven reflejadas en la conectividad cerebral funcional entre redes cerebrales, así como en la actividad cerebral, realizamos estudios en ratas msP en condiciones de control y tras un mes con acceso a alcohol. Para cada sujeto se obtuvieron las señales específicas de sus redes cerebrales tras aplicar análisis probabilístico de componentes independientes y regresión espacial a las imágenes funcionales de RM en estado de reposo (RMf-er). Después, estimamos la conectividad cerebral en estado de reposo mediante correlación parcial regularizada. Para una lectura de la actividad neuronal realizamos un experimento con imágenes de RM realzadas con manganeso. En la condición de alcohol encontramos hipoconectividades entre la red visual y las redes estriatal y sensorial; todas con incrementos en actividad. Por el contrario, hubo hiperconectividades entre tres pares de redes cerebrales: 1) red prefrontal cingulada media y red estriatal, 2) red sensorial y red parietal de asociación y 3) red motora-retroesplenial y red sensorial, siendo la red parietal de asociación la única red sin incremento de actividad. Estos resultados indican que las redes cerebrales ya se alteran desde una fase temprana de consumo continuo y prolongado de alcohol, disminuyendo el control ejecutivo y la flexibilidad comportamental. ii) Para comparar el volumen de materia gris (MG) cortical entre 34 controles sanos y 35 pacientes con dependencia al alcohol, desintoxicados y en abstinencia de 1 a 5 semanas, realizamos un análisis de morfometría basado en vóxel. Las principales estructuras cuyo volumen de MG disminuyó en los sujetos en abstinencia fueron el giro precentral (GPreC), el giro postcentral (GPostC), la corteza motora suplementaria (CMS), el giro frontal medio (GFM), el precúneo (PCUN) y el lóbulo parietal superior (LPS). Disminuciones de MG en el volumen de esas áreas pueden dar lugar a cambios en el control de los movimientos (GPreC y CMS), en el procesamiento de información táctil y propioceptiva (GPostC), personalidad, previsión (GFM), reconocimiento sensorial, entendimiento del lenguaje, orientación (PCUN) y reconocimiento de objetos a través de su forma (LPS). iii) Caracterizar estados cerebrales dinámicos en señales de RMf mediante una metodología basada en un modelo oculto de Markov (HMM en inglés)-Gaussiano en un paradigma con diseño de bloques, junto con distintas señales temporales de múltiples redes: componentes independientes y modos funcionales probabilísticos (PFMs en inglés) en 14 sujetos sanos. Cuatro condiciones experimentales formaron el paradigma de bloques: reposo, visual, motora y visual-motora. Mediante la aplicación de HMM-Gaussiano a los PFMs pudimos caracterizar cuatro estados cerebrales a partir de la actividad media de cada PFM. Los cuatro mapas espaciales obtenidos fueron llamados HMM-reposo, HMM-visual, HMM-motor y HMM-RND (red neuronal por defecto). HMM-RND apareció una vez el estado de tarea se había estabilizado. En un futuro cercano se espera obtener estados cerebrales en nuestros datos de RMf-er en ratas, para comparar dinámicamente el comportamiento de las redes cerebrales como un biomarcador de TCA. En conclusión, las técnicas de neuroimagen aplicadas en imagen de RM multimodal para estimar la conectividad cerebral en estado de reposo, la actividad cerebral y el volumen de materia gris han permitido avanzar en el entendimiento de los mecanismos homeostáticoLa ingesta d'alcohol altera el balanç del cervell a nivell estructural i funcional i pot causar trastorns per consum d' alcohol (TCA). L'objectiu d'aquesta Tesi Doctoral fou estudiar els efectes en el cervell del consum crònic i excessiu d'alcohol, des d'un punt de vista funcional i estructural i per mitjà d'anàlisi d'imatges de ressonància magnètica (RM). Vam realitzar tres anàlisis amb objectius específics: i) Per a entendre com les neuroadaptacions desencadenades pel consum d'alcohol es veuen reflectides en la connectivitat cerebral funcional entre xarxes cerebrals, així com en l'activitat cerebral, vam realitzar estudis en rates msP en les condicions de control i després d'un mes amb accés a alcohol. Per a cada subjecte vam obtindre els senyals de les xarxes cerebrals tras aplicar a les imatges funcionals de RM en estat de repòs una anàlisi probabilística de components independents i regressió espacial. Després, estimàrem la connectivitat cerebral en estat de repòs per mitjà de correlació parcial regularitzada. Per a una lectura de l'activitat cerebral vam adquirir imatges de RM realçades amb manganés. En la condició d'alcohol vam trobar hipoconnectivitats entre la xarxa visual i les xarxes estriatal i sensorial, totes amb increments en activitat. Al contrari, va haver-hi hiperconnectivitats entre tres parells de xarxes cerebrals: 1) xarxa prefrontal cingulada mitja i xarxa estriatal, 2) xarxa sensorial i xarxa parietal d'associació i 3) xarxa motora-retroesplenial i xarxa sensorial, sent la xarxa parietal d'associació l'única xarxa sense increment d'activitat. Aquests resultats indiquen que les xarxes cerebrals ja s'alteren des d'una fase primerenca caracteritzada per consum continu i prolongat d'alcohol, disminuint el control executiu i la flexibilitat comportamental. ii) Per a comparar el volum de MG cortical entre 34 controls sans i 35 pacients amb dependència a l'alcohol, desintoxicats i en abstinència de 1 a 5 setmanes vam emprar anàlisi de morfometria basada en vòxel. Les principals estructures on el volum de MG va disminuir en els subjectes en abstinència van ser el gir precentral (GPreC), el gir postcentral (GPostC), la corteça motora suplementària (CMS), el gir frontal mig (GFM), el precuni (PCUN) i el lòbul parietal superior (LPS). Les disminucions de MG en eixes àrees poden donar lloc a canvis en el control dels moviments (GPreC i CMS), en el processament d'informació tàctil i propioceptiva (GPostC), personalitat, previsió (GFM), reconeixement sensorial, enteniment del llenguatge, orientació (PCUN) i reconeixement d'objectes a través de la seua forma (LPS). iii) Caracterització de les dinàmiques temporals del cervell com a diferents estats cerebrals, en senyals de RMf mitjançant una metodologia basada en un model ocult de Markov (HMM en anglès)-Gaussià en imatges de RMf, junt amb dos tipus de senyals temporals de múltiples xarxes cerebrals: components independents i modes funcionals probabilístics (PFMs en anglès) en 14 subjectes sans. Quatre condicions experimentals van formar el paradigma de blocs: repòs, visual, motora i visual-motora. HMM-Gaussià aplicat als PFMs (senyals de RM funcional de xarxes cerebrals) va permetre la millor caracterització dels quatre estats cerebrals a partir de l'activitat mitjana de cada PFM. Els quatre mapes espacials obtinguts van ser anomenats HMM-repòs, HMM-visual, HMM-motor i HMM-XND (xarxa neuronal per defecte). HMM-XND va aparèixer una vegada una tasca estava estabilitzada. En un futur pròxim s'espera obtindre estats cerebrals en les nostres dades de RMf-er en rates, per a comparar dinàmicament el comportament de les xarxes cerebrals com a biomarcador de TCA. En conclusió, s'han aplicat tècniques de neuroimatge per a estimar la connectivitat cerebral en estat de repòs, l'activitat cerebral i el volum de MG, aplicades a imatges multimodals de RM i s'han obtés resultats que han permés avançar en l'enteniment dels mAlcohol intake alters brain balance, affecting its structure and function, and it may cause Alcohol Use Disorders (AUDs). We aimed to study the effects of chronic, excessive alcohol consumption on the brain from a functional and structural point of view, via analysis of multimodal magnetic resonance (MR) images. We conducted three studies with specific aims: i) To understand how the neuroadaptations triggered by alcohol intake are reflected in between-network resting-state functional connectivity (rs-FC) and brain activity in the onset of alcohol dependence, we performed studies in msP rats in control and alcohol conditions. Group probabilistic independent component analysis (group-PICA) and spatial regression were applied to resting-state functional magnetic resonance imaging (rs-fMRI) images to obtain subject-specific time courses of seven resting-state networks (RSNs). Then, we estimated rs-FC via L2-regularized partial correlation. We performed a manganese-enhanced (MEMRI) experiment as a readout of neuronal activity. In alcohol condition, we found hypoconnectivities between the visual network (VN), and striatal (StrN) and sensory-cortex (SCN) networks, all with increased brain activity. On the contrary, hyperconnectivities were found between three pairs of RSNs: 1) medial prefrontal-cingulate (mPRN) and StrN, 2) SCN and parietal association (PAN) and 3) motor-retrosplenial (MRN) and SCN networks, being PAN the only network without brain activity rise. Interestingly, the hypoconnectivities could be explained as control to alcohol transitions from direct to indirect connectivity, whereas the hyperconnectivities reflected an indirect to an even more indirect connection. These findings indicate that RSNs are early altered by prolonged and moderate alcohol exposure, diminishing the executive control and behavioral flexibility. ii) To compare cortical gray matter (GM) volume between 34 healthy controls and 35 alcohol-dependent patients who were detoxified and remained abstinent for 1-5 weeks before MRI acquisition, we performed a voxel-based morphometry analysis. The main structures whose GM volume decreased in abstinent subjects compared to controls were precentral gyrus (PreCG), postcentral gyrus (PostCG), supplementary motor cortex (SMC), middle frontal gyrus (MFG), precuneus (PCUN) and superior parietal lobule (SPL). Decreases in GM volume in these areas may lead to changes in control of movement (PreCG and SMC), in processing tactile and proprioceptive information (PostCG), personality, insight, prevision (MFG), sensory appreciation, language understanding, orientation (PCUN) and the recognition of objects by touch and shapes (SPL). iii) To characterize dynamic brain states in functional MRI (fMRI) signals by means of an approach based on the Hidden Markov model (HMM). Several parameter configurations of HMM-Gaussian in a block-design paradigm were considered, together with different time series: independent components (ICs) and probabilistic functional modes (PFMs) on 14 healthy subjects. The block-design fMRI paradigm consisted of four experimental conditions: rest, visual, motor and visual-motor. Characterizing brain states' dynamics in fMRI data was possible applying the HMM-Gaussian approach to PFMs, with mean activity driving the states. The four spatial maps obtained were named HMM-rest, HMM-visual, HMM-motor and HMM-DMN (default mode network). HMM-DMN appeared once a task state had stabilized. The ultimate goal will be to obtain brain states in our rs-fMRI rat data, to dynamically compare the behavior of brain RSNs as a biomarker of AUD. In conclusion, neuroimaging techniques to estimate rs-FC, brain activity and GM volume can be successfully applied to multimodal MRI in the advance of the understanding of brain homeostasis in AUDs. These functional and structural alterations are a biomarker of chronic alcoholism to explain impairments in executive control, reward evaluation and visuospatial processing.Pérez Ramírez, MÚ. (2018). Characterizing functional and structural brain alterations driven by chronic alcohol drinking: a resting-state fMRI connectivity and voxel-based morphometry analysis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11316

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience

Approaches For Capturing Time-Varying Functional Network Connectivity With Application to Normative Development and Mental Illness

Since the beginning of medical science, the human brain has remained an unsolved puzzle; an illusive organ that controls everything- from breathing to heartbeats, from emotion to anger, and more. With the power of advanced neuroimaging techniques, scientists have now started to solve this nearly impossible puzzle, piece by piece. Over the past decade, various in vivo techniques, including functional magnetic resonance imaging (fMRI), have been increasingly used to understand brain functions. fMRI is extensively being used to facilitate the identification of various neuropsychological disorders such as schizophrenia (SZ), bipolar disorder (BP) and autism spectrum disorder (ASD). These disorders are currently diagnosed based on patients’ self-reported experiences, and observed symptoms and behaviors over the course of the illnesses. Therefore, efficient identification of biological-based markers (biomarkers) can lead to early diagnosis of these mental disorders, and provide a trajectory for disease progression. By applying advanced machine learning techniques on fMRI data, significant differences in brain function among patients with mental disorders and healthy controls can be identified. Moreover, by jointly estimating information from multiple modalities, such as, functional brain data and genetic factors, we can now investigate the relationship between brain function and genes. Functional connectivity (FC) has become a very common measure to characterize brain functions, where FC is defined as the temporal covariance of neural signals between multiple spatially distinct brain regions. Recently, researchers are studying the FC among functionally specialized brain networks which can be defined as a higher level of FC, and is termed as functional network connectivity (FNC, defined as the correlation value that summarizes the overall connection between brain ‘networks’ over time). Most functional connectivity studies have made the limiting assumption that connectivity is stationary over multiple minutes, and ignore to identify the time-varying and reoccurring patterns of FNC among brain regions (known as time-varying FNC). In this dissertation, we demonstrate the use of time-varying FNC features as potential biomarkers to differentiate between patients with mental disorders and healthy subjects. The developmental characteristics of time-varying FNC in children with typically developing brain and ASD have been extensively studies in a cross-sectional framework, and age-, sex- and disease-related FNC profiles have been proposed. Also, time-varying FNC is characterized in healthy adults and patients with severe mental disorders (SZ and BP). Moreover, an efficient classification algorithm is designed to identify patients and controls at individual level. Finally, a new framework is proposed to jointly utilize information from brain’s functional network connectivity and genetic features to find the associations between them. The frameworks that we presented here can help us understand the important role played by time-varying FNC to identify potential biomarkers for the diagnosis of severe mental disorders

Mapping connections in the neonatal brain with magnetic resonance imaging

The neonatal brain undergoes rapid development after birth, including the growth and maturation of the white matter fibre bundles that connect brain regions. Diffusion MRI (dMRI) is a unique tool for mapping these bundles in vivo, providing insight into factors that impact the development of white matter and how its maturation influences other developmental processes. However, most studies of neonatal white matter do not use specialised analysis tools, instead using tools that have been developed for the adult brain. However, the neonatal brain is not simply a small adult brain, as differences in geometry and tissue decomposition cause considerable differences in dMRI contrast. In this thesis, methods are developed to map white matter connections during this early stage of neurodevelopment. First, two contrasting approaches are explored: ROI-constrained protocols for mapping individual tracts, and the generation of whole-brain connectomes that capture the developing brain's full connectivity profile. The impact of the gyral bias, a methodological confound of tractography, is quantified and compared with the equivalent measurements for adult data. These connectomes form the basis for a novel, data-driven framework, in which they are decomposed into white matter bundles and their corresponding grey matter terminations. Independent component analysis and non-negative matrix factorisation are compared for the decomposition, and are evaluated against in-silico simulations. Data-driven components of dMRI tractography data are compared with manual tractography, and networks obtained from resting-state functional MRI. The framework is further developed to provide corresponding components between groups and individuals. The data-driven components are used to generate cortical parcellations, which are stable across subjects. Finally, some future applications are outlined that extend the use of these methods beyond the context of neonatal imaging, in order to bridge the gap between functional and structural analysis paradigms, and to chart the development of white matter throughout the lifespan and across species

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

Mapping connections in the neonatal brain with magnetic resonance imaging

The neonatal brain undergoes rapid development after birth, including the growth and maturation of the white matter fibre bundles that connect brain regions. Diffusion MRI (dMRI) is a unique tool for mapping these bundles in vivo, providing insight into factors that impact the development of white matter and how its maturation influences other developmental processes. However, most studies of neonatal white matter do not use specialised analysis tools, instead using tools that have been developed for the adult brain. However, the neonatal brain is not simply a small adult brain, as differences in geometry and tissue decomposition cause considerable differences in dMRI contrast. In this thesis, methods are developed to map white matter connections during this early stage of neurodevelopment. First, two contrasting approaches are explored: ROI-constrained protocols for mapping individual tracts, and the generation of whole-brain connectomes that capture the developing brain's full connectivity profile. The impact of the gyral bias, a methodological confound of tractography, is quantified and compared with the equivalent measurements for adult data. These connectomes form the basis for a novel, data-driven framework, in which they are decomposed into white matter bundles and their corresponding grey matter terminations. Independent component analysis and non-negative matrix factorisation are compared for the decomposition, and are evaluated against in-silico simulations. Data-driven components of dMRI tractography data are compared with manual tractography, and networks obtained from resting-state functional MRI. The framework is further developed to provide corresponding components between groups and individuals. The data-driven components are used to generate cortical parcellations, which are stable across subjects. Finally, some future applications are outlined that extend the use of these methods beyond the context of neonatal imaging, in order to bridge the gap between functional and structural analysis paradigms, and to chart the development of white matter throughout the lifespan and across species