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1.
Nat Commun ; 13(1): 997, 2022 02 22.
Artículo en Inglés | MEDLINE | ID: mdl-35194018

RESUMEN

Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant's brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.


Asunto(s)
Sustancia Blanca , Encéfalo/diagnóstico por imagen , Imagen de Difusión por Resonancia Magnética , Humanos , Lactante , Recién Nacido , Imagen por Resonancia Magnética/métodos , Vaina de Mielina , Sustancia Blanca/diagnóstico por imagen
2.
Commun Biol ; 4(1): 1191, 2021 10 14.
Artículo en Inglés | MEDLINE | ID: mdl-34650227

RESUMEN

Development of cortical tissue during infancy is critical for the emergence of typical brain functions in cortex. However, how cortical microstructure develops during infancy remains unknown. We measured the longitudinal development of cortex from birth  to six months of age  using multimodal quantitative imaging of cortical microstructure. Here we show that infants' cortex undergoes profound microstructural tissue growth during the first six months of human life. Comparison of postnatal to prenatal transcriptomic gene expression data demonstrates that myelination and synaptic processes are dominant contributors to this postnatal microstructural tissue growth. Using visual cortex as a model system, we find hierarchical microstructural growth: higher-level visual areas have less mature tissue at birth than earlier visual areas but grow at faster rates. This overturns the prominent view that visual areas that are most mature at birth develop fastest. Together, in vivo, longitudinal, and quantitative measurements, which we validated with ex vivo transcriptomic data, shed light on the rate, sequence, and biological mechanisms of developing cortical systems during early infancy. Importantly, our findings propose a hypothesis that cortical myelination is a key factor in cortical development during early infancy, which has important implications for diagnosis of neurodevelopmental disorders and delays in infants.


Asunto(s)
Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética , Corteza Visual/crecimiento & desarrollo , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Corteza Visual/fisiología
3.
Cereb Cortex ; 31(1): 603-619, 2021 01 01.
Artículo en Inglés | MEDLINE | ID: mdl-32968767

RESUMEN

Human visual cortex contains many retinotopic and category-specific regions. These brain regions have been the focus of a large body of functional magnetic resonance imaging research, significantly expanding our understanding of visual processing. As studying these regions requires accurate localization of their cortical location, researchers perform functional localizer scans to identify these regions in each individual. However, it is not always possible to conduct these localizer scans. Here, we developed and validated a functional region of interest (ROI) atlas of early visual and category-selective regions in human ventral and lateral occipito-temporal cortex. Results show that for the majority of functionally defined ROIs, cortex-based alignment results in lower between-subject variability compared to nonlinear volumetric alignment. Furthermore, we demonstrate that 1) the atlas accurately predicts the location of an independent dataset of ventral temporal cortex ROIs and other atlases of place selectivity, motion selectivity, and retinotopy. Next, 2) we show that the majority of voxel within our atlas is responding mostly to the labeled category in a left-out subject cross-validation, demonstrating the utility of this atlas. The functional atlas is publicly available (download.brainvoyager.com/data/visfAtlas.zip) and can help identify the location of these regions in healthy subjects as well as populations (e.g., blind people, infants) in which functional localizers cannot be run.


Asunto(s)
Reconocimiento Visual de Modelos/fisiología , Lóbulo Temporal/fisiología , Corteza Visual/fisiología , Vías Visuales/fisiología , Adulto , Mapeo Encefálico/métodos , Femenino , Humanos , Imagen por Resonancia Magnética/métodos , Masculino , Lóbulo Occipital/fisiología , Percepción Visual/fisiología
4.
Cereb Cortex ; 30(9): 4882-4898, 2020 07 30.
Artículo en Inglés | MEDLINE | ID: mdl-32372098

RESUMEN

We have an amazing ability to categorize objects in the world around us. Nevertheless, how cortical regions in human ventral temporal cortex (VTC), which is critical for categorization, support this behavioral ability, is largely unknown. Here, we examined the relationship between neural responses and behavioral performance during the categorization of morphed silhouettes of faces and hands, which are animate categories processed in cortically adjacent regions in VTC. Our results reveal that the combination of neural responses from VTC face- and body-selective regions more accurately explains behavioral categorization than neural responses from either region alone. Furthermore, we built a model that predicts a person's behavioral performance using estimated parameters of brain-behavior relationships from a different group of people. Moreover, we show that this brain-behavior model generalizes to adjacent face- and body-selective regions in lateral occipitotemporal cortex. Thus, while face- and body-selective regions are located within functionally distinct domain-specific networks, cortically adjacent regions from both networks likely integrate neural responses to resolve competing and perceptually ambiguous information from both categories.


Asunto(s)
Reconocimiento Visual de Modelos/fisiología , Lóbulo Temporal/fisiología , Adulto , Mapeo Encefálico/métodos , Femenino , Humanos , Masculino
5.
Neuroimage ; 170: 257-270, 2018 04 15.
Artículo en Inglés | MEDLINE | ID: mdl-28213120

RESUMEN

The human ventral visual stream consists of several areas that are considered processing stages essential for perception and recognition. A fundamental microanatomical feature differentiating areas is cytoarchitecture, which refers to the distribution, size, and density of cells across cortical layers. Because cytoarchitectonic structure is measured in 20-micron-thick histological slices of postmortem tissue, it is difficult to assess (a) how anatomically consistent these areas are across brains and (b) how they relate to brain parcellations obtained with prevalent neuroimaging methods, acquired at the millimeter and centimeter scale. Therefore, the goal of this study was to (a) generate a cross-validated cytoarchitectonic atlas of the human ventral visual stream on a whole brain template that is commonly used in neuroimaging studies and (b) to compare this atlas to a recently published retinotopic parcellation of visual cortex (Wang et al., 2014). To achieve this goal, we generated an atlas of eight cytoarchitectonic areas: four areas in the occipital lobe (hOc1-hOc4v) and four in the fusiform gyrus (FG1-FG4), then we tested how the different alignment techniques affect the accuracy of the resulting atlas. Results show that both cortex-based alignment (CBA) and nonlinear volumetric alignment (NVA) generate an atlas with better cross-validation performance than affine volumetric alignment (AVA). Additionally, CBA outperformed NVA in 6/8 of the cytoarchitectonic areas. Finally, the comparison of the cytoarchitectonic atlas to a retinotopic atlas shows a clear correspondence between cytoarchitectonic and retinotopic areas in the ventral visual stream. The successful performance of CBA suggests a coupling between cytoarchitectonic areas and macroanatomical landmarks in the human ventral visual stream, and furthermore, that this coupling can be utilized for generating an accurate group atlas. In addition, the coupling between cytoarchitecture and retinotopy highlights the potential use of this atlas in understanding how anatomical features contribute to brain function. We make this cytoarchitectonic atlas freely available in both BrainVoyager and FreeSurfer formats (http://vpnl.stanford.edu/vcAtlas). The availability of this atlas will enable future studies to link cytoarchitectonic organization to other parcellations of the human ventral visual stream with potential to advance the understanding of this pathway in typical and atypical populations.


Asunto(s)
Atlas como Asunto , Imagen por Resonancia Magnética/métodos , Neuroimagen/métodos , Lóbulo Occipital/citología , Lóbulo Occipital/diagnóstico por imagen , Lóbulo Temporal/citología , Lóbulo Temporal/diagnóstico por imagen , Percepción Visual , Adulto , Femenino , Humanos , Masculino , Lóbulo Occipital/patología , Lóbulo Temporal/patología
6.
Data Brief ; 12: 327-332, 2017 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-28487876

RESUMEN

The data presented here are related to the research article: "A cross-validated cytoarchitectonic atlas of the human ventral visual stream" in which we developed a cytoarchitectonic atlas of ventral visual cortex. Here, we provide two additional quantifications of this cytoarchitectonic atlas: First, we quantify the effect of brain template on cross-validation performance. The data show a comparison between cortex-based alignment to two templates: the postmortem average brain and the FreeSurfer average brain. Second, we quantify the relationship between this cytoarchitectonic atlas and a recently published multimodal atlas of the human brain (Glasser et al., 2016).

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