Relation of connectome topology to brain volume across 103 mammalian species.

The brain connectome is an embedded network of anatomically interconnected brain regions, and the study of its topological organization in mammals has become of paramount importance due to its role in scaffolding brain function and behavior. Unlike many other observable networks, brain connections incur material and energetic cost, and their length and density are volumetrically constrained by the skull. Thus, an open question is how differences in brain volume impact connectome topology. We address this issue using the MaMI database, a diverse set of mammalian connectomes reconstructed from 201 animals, covering 103 species and 12 taxonomy orders, whose brain size varies over more than 4 orders of magnitude. Our analyses focus on relationships between volume and modular organization. After having identified modules through a multiresolution approach, we observed how connectivity features relate to the modular structure and how these relations vary across brain volume. We found that as the brain volume increases, modules become more spatially compact and dense, comprising more costly connections. Furthermore, we investigated how spatial embedding shapes network communication, finding that as brain volume increases, nodes' distance progressively impacts communication efficiency. We identified modes of variation in network communication policies, as smaller and bigger brains show higher efficiency in routing- and diffusion-based signaling, respectively. Finally, bridging network modularity and communication, we found that in larger brains, modular structure imposes stronger constraints on network signaling. Altogether, our results show that brain volume is systematically related to mammalian connectome topology and that spatial embedding imposes tighter restrictions on larger brains.

Inner Hemispheric and Interhemispheric Connectivity Balance in the Human Brain.

The connectome of the brain has a great impact on the function of the brain as the structure of the connectome affects the speed and efficiency of information transfer. As a highly energy-consuming organ, an efficient network structure is essential. A previous study has shown consistent overall brain connectivity across a large variety of species. This connectivity conservation was explained by a balance between interhemispheric and intrahemispheric connections; that is, spices with highly connected hemispheres appear to have weaker interhemisphere connections. This study examines this connectivity trade-off in the human brain using diffusion-based tractography and network analysis in the Human Connectome Project (970 subjects, 527 female). We explore the biological origins of this phenomenon, heritability, and the effect on cognitive measures.The proportion of commissural fibers in the brain had a negative correlation to hemispheric efficiency, pointing to a trade-off between inner hemispheric and interhemispheric connectivity. Network hubs including anterior and middle cingulate cortex, superior frontal areas, medial occipital areas, the parahippocampal gyrus, post- and precentral gyri, and the precuneus had the strongest contribution to this phenomenon. Other results show a high heritability as well as a strong connection to crystalized intelligence. This work presents cohort-based network analysis research, spanning a large variety of samples and exploring the overall architecture of the human connectome. Our results show a connectivity conservation phenomenon at the base of the overall brain network architecture. This network structure may explain much of the functional, behavioral, and cognitive variability among different brains.SIGNIFICANCE STATEMENT The network structure of the brain is at the basis of every brain function as it dictates the characteristics of information transfer. Understanding the patterns and mechanisms that guide the connectome structure is crucial to understanding the brain itself. Here we unravel the mechanism at the base of the connectivity conservation phenomenon by exploring the interaction between hemispheric and commissural connectivity in a large-scale cohort-based connectivity study. We describe the trade-off between the two components and examine the origins of the trade-off and observe the effect on cognitive abilities and behavior.

In vivo measurements of lamination patterns in the human cortex.

The laminar composition of the cerebral cortex is tightly connected to the development and connectivity of the brain, as well as to function and pathology. Although most of the research on the cortical layers is done with the aid of ex vivo histology, there have been recent attempts to use magnetic resonance imaging (MRI) with potential in vivo applications. However, the high-resolution MRI technology and protocols required for such studies are neither common nor practical. In this article, we present a clinically feasible method for assessing the laminar properties of the human cortex using standard pulse sequence available on any common MRI scanner. Using a series of low-resolution inversion recovery (IR) MRI scans allows us to calculate multiple T1 relaxation time constants for each voxel. Based on the whole-brain T1 -distribution, we identify six different gray matter T1 populations and their variation across the cortex. Based on this, we show age-related differences in these population and demonstrate that this method is able to capture the difference in laminar composition across varying brain areas. We also provide comparison to ex vivo high-resolution MRI scans. We show that this method is feasible for the estimation of layer variability across large population cohorts, which can lead to research into the links between the cortical layers and function, behavior and pathologies that was heretofore unexplorable.

Single Cortical Microinfarcts Lead to Widespread Microglia/Macrophage Migration Along the White Matter.

Loss of cognitive function with aging is a complex and poorly understood process. Recently, clinical research has linked the occurrence of cortical microinfarcts to cognitive decline. Cortical microinfarcts form following the occlusion of penetrating vessels and are considered to be restricted to the proximity of the occluded vessel. Whether and how such local events propagate and affect remote brain regions remain unknown. To this end, we combined histological analysis and longitudinal diffusion tensor imaging (DTI), following the targeted-photothrombotic occlusion of single cortical penetrating vessels. Occlusions resulted in distant tissue reorganization across the mouse brain. This remodeling co-occurred with the formation of a microglia/macrophage migratory path along subcortical white matter tracts, reaching the contralateral hemisphere through the corpus callosum and leaving a microstructural signature detected by DTI-tractography. CX3CR1-deficient mice exhibited shorter trail lengths, differential remodeling, and only ipsilateral white matter tract changes. We concluded that microinfarcts lead to brain-wide remodeling in a microglial CX3CR1-dependent manner.

Brain volumetric changes in the general population following the COVID-19 outbreak and lockdown.

The coronavirus disease 2019 (COVID-19) outbreak introduced unprecedented health-risks, as well as pressure on the economy, society, and psychological well-being due to the response to the outbreak. In a preregistered study, we hypothesized that the intense experience of the outbreak potentially induced stress-related brain modifications in the healthy population, not infected with the virus. We examined volumetric changes in 50 participants who underwent MRI scans before and after the COVID-19 outbreak and lockdown in Israel. Their scans were compared with those of 50 control participants who were scanned twice prior to the pandemic. Following COVID-19 outbreak and lockdown, the test group participants uniquely showed volumetric increases in bilateral amygdalae, putamen, and the anterior temporal cortices. Changes in the amygdalae diminished as time elapsed from lockdown relief, suggesting that the intense experience associated with the pandemic induced transient volumetric changes in brain regions commonly associated with stress and anxiety. The current work utilizes a rare opportunity for real-life natural experiment, showing evidence for brain plasticity following the COVID-19 global pandemic. These findings have broad implications, relevant both for the scientific community as well as the general public.

Widespread cortical dyslamination in epilepsy patients with malformations of cortical development.

PURPOSE: Recent research in epilepsy patients confirms our understanding of epilepsy as a network disorder with widespread cortical compromise. Here, we aimed to investigate the neocortical laminar architecture in patients with focal cortical dysplasia (FCD) and periventricular nodular heterotopia (PNH) using clinically feasible 3 T MRI. METHODS: Eighteen epilepsy patients (FCD and PNH groups; n = 9 each) and age-matched healthy controls (n = 9) underwent T1 relaxation 3 T MRI, from which component probability T1 maps were utilized to extract sub-voxel composition of 6 T1 cortical layers. Seventy-eight cortical areas of the automated anatomical labeling atlas were divided into 1000 equal-volume sub-areas for better detection of cortical abnormalities, and logistic regressions were performed to compare FCD/PNH patients with healthy controls with the T1 layers composing each sub-area as regressors. Statistical significance (p < 0.05) was determined by a likelihood-ratio test with correction for false discovery rate using Benjamini-Hochberg method. RESULTS: Widespread cortical abnormalities were observed in the patient groups. Out of 1000 sub-areas, 291 and 256 bilateral hemispheric cortical sub-areas were found to predict FCD and PNH, respectively. For each of these sub-areas, we were able to identify the T1 layer, which contributed the most to the prediction. CONCLUSION: Our results reveal widespread cortical abnormalities in epilepsy patients with FCD and PNH, which may have a role in epileptogenesis, and likely related to recent studies showing widespread structural (e.g., cortical thinning) and diffusion abnormalities in various human epilepsy populations. Our study provides quantitative information of cortical laminar architecture in epilepsy patients that can be further targeted for study in functional and neuropathological studies.

Mammillothalamic Disconnection Alters Hippocampocortical Oscillatory Activity and Microstructure: Implications for Diencephalic Amnesia.

Diencephalic amnesia can be as debilitating as the more commonly known temporal lobe amnesia, yet the precise contribution of diencephalic structures to memory processes remains elusive. Across four cohorts of male rats, we used discrete lesions of the mammillothalamic tract to model aspects of diencephalic amnesia and assessed the impact of these lesions on multiple measures of activity and plasticity within the hippocampus and retrosplenial cortex. Lesions of the mammillothalamic tract had widespread indirect effects on hippocampocortical oscillatory activity within both theta and gamma bands. Both within-region oscillatory activity and cross-regional synchrony were altered. The network changes were state-dependent, displaying different profiles during locomotion and paradoxical sleep. Consistent with the associations between oscillatory activity and plasticity, complementary analyses using several convergent approaches revealed microstructural changes, which appeared to reflect a suppression of learning-induced plasticity in lesioned animals. Together, these combined findings suggest a mechanism by which damage to the medial diencephalon can impact upon learning and memory processes, highlighting an important role for the mammillary bodies in the coordination of hippocampocortical activity.SIGNIFICANCE STATEMENT Information flow within the Papez circuit is critical to memory. Damage to ascending mammillothalamic projections has consistently been linked to amnesia in humans and spatial memory deficits in animal models. Here we report on the changes in hippocampocortical oscillatory dynamics that result from chronic lesions of the mammillothalamic tract and demonstrate, for the first time, that the mammillary bodies, independently of the supramammillary region, contribute to frequency modulation of hippocampocortical theta oscillations. Consistent with the associations between oscillatory activity and plasticity, the lesions also result in a suppression of learning-induced plasticity. Together, these data support new functional models whereby mammillary bodies are important for coordinating hippocampocortical activity rather than simply being a relay of hippocampal information as previously assumed.

Short-term plasticity following motor sequence learning revealed by diffusion magnetic resonance imaging.

Current noninvasive methods to detect structural plasticity in humans are mainly used to study long-term changes. Diffusion magnetic resonance imaging (MRI) was recently proposed as a novel approach to reveal gray matter changes following spatial navigation learning and object-location memory tasks. In the present work, we used diffusion MRI to investigate the short-term neuroplasticity that accompanies motor sequence learning. Following a 45-min training session in which participants learned to accurately play a short sequence on a piano keyboard, changes in diffusion properties were revealed mainly in motor system regions such as the premotor cortex and cerebellum. In a second learning session taking place immediately afterward, feedback was given on the timing of key pressing instead of accuracy, while participants continued to learn. This second session induced a different plasticity pattern, demonstrating the dynamic nature of learning-induced plasticity, formerly thought to require months of training in order to be detectable. These results provide us with an important reminder that the brain is an extremely dynamic structure. Furthermore, diffusion MRI offers a novel measure to follow tissue plasticity particularly over short timescales, allowing new insights into the dynamics of structural brain plasticity.

Tremor Relief and Structural Integrity after MRI-guided Focused US Thalamotomy in Tremor Disorders.

Background MRI-guided focused US thalamotomy of ventral intermediate nucleus of the thalamus is a treatment for tremor disorders. Purpose To evaluate white matter integrity before and after thalamotomy and its correlation with clinical outcome. Materials and Methods Participants with essential tremor (ET) or Parkinson disease (PD) undergoing thalamotomy were prospectively recruited between March 2016 and October 2018. Tremor and quality of life were assessed before, 1 month after, and 6 months after thalamotomy. Participants underwent T1-weighted, T2-weighted fluid-attenuated image recovery, and diffusion-tensor MRI before and 1 day, 7-10 days, 1-3 months, and 6 months or longer after treatment. Diffusivity and fiber tractography measures were calculated. Repeated measures analysis of variance with post hoc paired t test and Skillings-Mack test with post hoc Wilcoxon signed-rank test were used for normally and nonnormally distributed data, respectively, and Bonferroni method corrected for multiple comparisons. Results Twenty-two study participants with ET (mean age, 72 years ± 6 [standard deviation]; 14 men), 17 participants with PD (mean age, 65 years ± 8; 13 men), and a replication set of 17 participants with ET (mean age, 73 years ± 6; 10 men) were evaluated. Long-term damage was found in the ablated core (mean fractional anisotropy [FA] at baseline, 0.41 ± 0.10, and at ≥6 months, 0.23 ± 0.09; P < .001) and thalamus to red nucleus tract (mean number of tracts at baseline, 1663, and at ≥6 months, 1070; P = .003). Negative correlation was observed between motor thalamus FA 1 day after ablation and tremor improvement (ET: R = -0.52 [P = .03]; PD: R = -0.61 [P = .003]). Better tremor relief in ET was associated with lower fractional anisotropy before treatment (R = -0.5; P = .02). Conclusion MRI-guided focused US thalamotomy resulted in short- and long-term white-matter changes. Diffusion-tensor imaging provided evidence for long-term damage in the ablation core and in the thalamus and red nucleus tract, and a correlation between preablation fractional anisotropy in the motor thalamus and clinical outcome. © RSNA, 2020 Online supplemental material is available for this article.

Imaging laminar structures in the gray matter with diffusion MRI.

The cortical layers define the architecture of the gray matter and its neuroanatomical regions and are essential for brain function. Abnormalities in cortical layer development, growth patterns, organization, or size can affect brain physiology and cognition. Unfortunately, while large population studies are underway that will greatly increase our knowledge about these processes, current non-invasive techniques for characterizing the cortical layers remain inadequate. For decades, high-resolution T1 and T2 Weighted Magnetic Resonance Imaging (MRI) have been the method-of-choice for gray matter and layer characterization. In the past few years, however, diffusion MRI has shown increasing promise for its unique insights into the fine structure of the cortex. Several different methods, including surface analysis, connectivity exploration, and sub-voxel component modeling, are now capable of exploring the diffusion characteristics of the cortex. In this review, we will discuss current advances in the application of diffusion imaging for cortical characterization and its unique features, with a particular emphasis on its spatial resolution, arguably its greatest limitation. In addition, we will explore the relationship between the diffusion MRI signal and the cellular components of the cortex, as visualized by histology. While the obstacles facing the widespread application of cortical diffusion imaging remain daunting, the information it can reveal may prove invaluable. Within the next few years, we predict a surge in the application of this technique and a concomitant expansion of our knowledge of cortical layers.

The role of diffusion MRI in neuroscience.

Diffusion-weighted imaging has pushed the boundaries of neuroscience by allowing us to examine the white matter microstructure of the living human brain. By doing so, it has provided answers to fundamental neuroscientific questions, launching a new field of research that had been largely inaccessible. We briefly summarize key questions that have historically been raised in neuroscience concerning the brain's white matter. We then expand on the benefits of diffusion-weighted imaging and its contribution to the fields of brain anatomy, functional models and plasticity. In doing so, this review highlights the invaluable contribution of diffusion-weighted imaging in neuroscience, presents its limitations and proposes new challenges for future generations who may wish to exploit this powerful technology to gain novel insights.

Resolution considerations in imaging of the cortical layers.

The cortical layers are a finger print of brain development, function, connectivity and pathology. Obviously, the formation of the layers and their composition is essential to cognition and behavior. The layers were traditionally measured by histological means but recent studies utilizing MRI suggested that T1 relaxation imaging consist of enough contrast to separate the layers. Indeed extreme resolution, post mortem, studies demonstrated this phenomenon. Yet, one of the limiting factors of using T1 MRI to visualize the layers in neuroimaging research is partial volume effect. This happen when the image resolution is not high enough and two or more layers resides within the same voxel. In this paper we demonstrate that due to the physical small thickness of the layers it is highly unlikely that high resolution imaging could resolve the layers. By contrast, we suggest that low resolution multi T1 mapping conjugate with composition analysis could provide practical means for measuring the T1 layers. We suggest an acquisition platform that is clinically feasible and could quantify measures of the layers. The key feature of the suggested platform is that separation of the layers is better achieved in the T1 relaxation domain rather than in the spatial image domain.

Sex beyond the genitalia: The human brain mosaic.

Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains ("female brain" or "male brain"). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only "male" or only "female" features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the "maleness-femaleness" continuum are rare. Rather, most brains are comprised of unique "mosaics" of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain.

The rapid development of structural plasticity through short water maze training: A DTI study.

Diffusion MRI is sensitive to the microstructure of tissue and allows the study of structural plasticity over short time scales of only hours. The initial temporal and spatial progression of this process, however, has yet to be elucidated. With the aim of examining early temporal progression of structural plasticity, we subjected rats to short training periods on a task in the Morris water maze (MWM), a paradigm previously shown to induce rapid changes in diffusion tensor imaging (DTI) indices. Two groups of rats were each divided into subgroups that consecutively completed 1, 2 or 3 sets of short trials (up to 60s) in the MWM. Each set comprised 4 trials (1 from each quadrant of the WMW), with a specific time interval between sets. To assess the effect of the duration of the task on the evolving changes in DTI indices, we allowed a rest of 45min between sets in one group of rats and a 2-h rest in the other. All rats were scanned with a DTI protocol before and 45min after their last trial. We found that a few minutes of training in a new task sufficed to generate changes in diffusion indices. The earliest changes in DTI (measured after one set of trials) progressed with further training (measured after two sets), but within a few more minutes (after three sets) they reached a plateau. Lengthening the duration of the overall task by prolonging the time interval between sessions did not alter this pattern of change, suggesting that at least within this short time scale such changes are task-dependent, but not time dependent. Our results demonstrate the progression of structural neuroplasticity at different stages of exposure to a novel experience, and show that DTI can be used to trace, in vivo, the localization of structural plasticity induced by training.

T1 relaxometry of crossing fibres in the human brain.

A comprehensive tract-based characterisation of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organisation within the voxel. Recently, a new experimental framework that combines inversion recovery and diffusion MRI, called inversion recovery diffusion tensor imaging (IR-DTI), was introduced and applied in an animal study. IR-DTI provides the ability to assign to each unique fibre population within a voxel a specific value of the longitudinal relaxation time, T1, which is a proxy for myelin content. Here, we apply the IR-DTI approach to the human brain in vivo on 7 healthy subjects for the first time. We demonstrate that the approach is able to measure differential tract properties in crossing fibre areas, reflecting the different myelination of tracts. We also show that tract-specific T1 has less inter-subject variability compared to conventional T1 in areas of crossing fibres, suggesting increased specificity to distinct fibre populations. Finally we show in simulations that changes in myelination selectively affecting one fibre bundle in crossing fibre areas can potentially be detected earlier using IR-DTI.

Resolving relaxometry and diffusion properties within the same voxel in the presence of crossing fibres by combining inversion recovery and diffusion-weighted acquisitions.

PURPOSE: A comprehensive image-based characterization of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organization within the voxel. While progress has been made with diffusion MRI-based approaches to measure axonal morphology, to date available myelin metrics simply assign a single scalar value to the voxel, reflecting some form of average of its constituent fibres. Here, a new experimental framework that combines diffusion MRI and relaxometry is introduced. It provides, for the first time, the ability to assign to each unique fibre system within a voxel, a unique value of the longitudinal relaxation time, T1, which is largely influenced by the myelin content. METHODS: We demonstrate the method through simulations, in a crossing fibres phantom, in fixed brains and in vivo. RESULTS: The method is capable of recovering unique values of T1 for each fibre population. CONCLUSION: The ability to extract fibre-specific relaxometry properties will provide enhanced specificity and, therefore, sensitivity to differences in white matter architecture, which will be invaluable in many neuroimaging studies. Further the enhanced specificity should ultimately lead to earlier diagnosis and access to treatment in a range of white matter diseases where axons are affected.

Short-term learning induces white matter plasticity in the fornix.

Magnetic resonance imaging (MRI) has greatly extended the exploration of neuroplasticity in behaving animals and humans. Imaging studies recently uncovered structural changes that occur in gray and white matter, mainly after long-term training. A recent diffusion tensor imaging (DTI) study showed that training in a car racing game for 2 h induces changes in the hippocampus and parahippocampal gyri. However, the effect of short-term training on the white matter microstructure is unknown. Here we investigated the influence of short learning tasks on structural plasticity in the white matter, and specifically in the fornix, in humans and rats. Human subjects performed a 2 h spatial learning task, and rats underwent training for 1 d in a Morris water maze. Between tasks, subjects were scanned with DTI, a diffusion MRI framework sensitive to tissue microstructure. Using tract-based spatial statistics, we found changes in diffusivity indices in both humans and rats. In both species, changes in diffusion in the fornix were correlated with diffusion changes in the hippocampus, as well as with behavioral measures of improvement in the learning tasks. These results, which provide the first indication of short-term white matter plasticity in the human brain, suggest that the adult brain white matter preserves dynamic characteristics and can be modified by short-term learning experiences. The extent of change in white matter was correlated with their extent in gray matter, suggesting that all components of the neural network are capable of rapid remodeling in response to cognitive experiences.

Why diffusion tensor MRI does well only some of the time: variance and covariance of white matter tissue microstructure attributes in the living human brain.

Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter (e.g., local fibre architecture, axon morphology, and myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametric data for a comprehensive assessment of white matter properties. The present work exploits that framework to characterise the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, with the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterising the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, showing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts.

Separate parts of occipito-temporal white matter fibers are associated with recognition of faces and places.

A central finding of functional MRI studies is the highly selective response of distinct brain areas in the occipital temporal cortex to faces and places. However, little is known about the association of white matter fibers with the processing of these object categories. In the current study we used DTI-based tractography to reconstruct two main fibers that connect the occipital lobe with the anterior temporal lobe (inferior longitudinal fasciculus-ILF) and with the frontal lobe (inferior fronto-occipital fasciculus-IFOF) in normal individuals. In addition to MRI scans subjects performed face, scene and body recognition tasks outside the scanner. Results show that recognition of faces and scenes were selectively associated with separate parts of the ILF. In particular, face recognition was highly associated with the fractional anisotropy (FA) of the anterior part of the ILF in the right hemisphere. In contrast, scene recognition was strongly correlated with the FA of the posterior and middle but not the anterior part of the ILF bilaterally. Our findings provide the first demonstration that faces and places are not only associated with distinct brain areas but also with separate parts of white matter fibers.

Assessing white matter microstructure of the newborn with multi-shell diffusion MRI and biophysical compartment models.

Brain white matter connections have become a focus of major interest with important maturational processes occurring in newborns. To study the complex microstructural developmental changes in-vivo, it is imperative that non-invasive neuroimaging approaches are developed for this age-group. Multi-b-value diffusion weighted imaging data were acquired in 13 newborns, and the biophysical compartment diffusion models CHARMED-light and NODDI, providing new microstructural parameters such as intra-neurite volume fraction (νin) and neurite orientation dispersion index (ODI), were developed for newborn data. Comparative analysis was performed and twenty ROIs in the white matter were investigated. Diffusion tensor imaging and both biophysical compartment models highlighted the compact and oriented structure of the corpus-callosum with the highest FA and νin values and the smallest ODI values. We could clearly differentiate, using the FA, νin and ODI, the posterior and anterior internal capsule representing similar cellular structure but with different maturation (i.e. partially myelinated and absence of myelin, respectively). Late maturing regions (external capsule and periventricular crossroads of pathways) had lower νin values, but displayed significant differences in ODI. The compartmented models CHARMED-light and NODDI bring new indices corroborating the cellular architectures, with the lowest νin, reflecting the late maturation of areas with thin non-myelinated fibers, and with highest ODI indicating the presence of fiber crossings and fanning. The application of biophysical compartment diffusion models adds new insights to the brain white matter development in vivo.