Changes in cortical thickness and layers of motor and visual areas of the human brain from birth to 20 years old

AbstractThe visuotopic organization of dorsal visual cortex rostral to area V2 in primates has been a longstanding source of controversy. Using sub-millimeter phase-encoded retinotopic fMRI mapping, we recently provided evidence for a surprisingly similar visuotopic organization in dorsal visual cortex of macaques compared to previously published maps in New world monkeys (Zhu and Vanduffel, Proc Natl Acad Sci USA 116:2306–2311, 2019). Although individual quadrant representations could be robustly delineated in that study, their grouping into hemifield representations remains a major challenge. Here, we combined in-vivo high-resolution myelin density mapping based on MR imaging (400 µm isotropic resolution) with fine-grained retinotopic fMRI to quantitatively compare myelin densities across retinotopically defined visual areas in macaques. Complementing previously documented differences in populational receptive-field (pRF) size and visual field signs, myelin densities of both quadrants of the dorsolateral posterior area (DLP) and area V3A are significantly different compared to dorsal and ventral area V3. Moreover, no differences in myelin density were observed between the two matching quadrants belonging to areas DLP, V3A, V1, V2 and V4, respectively. This was not the case, however, for the dorsal and ventral quadrants of area V3, which showed significant differences in MR-defined myelin densities, corroborating evidence of previous myelin staining studies. Interestingly, the pRF sizes and visual field signs of both quadrant representations in V3 are not different. Although myelin density correlates with curvature and anticorrelates with cortical thickness when measured across the entire cortex, exactly as in humans, the myelin density results in the visual areas cannot be explained by variability in cortical thickness and curvature between these areas. The present myelin density results largely support our previous model to group the two quadrants of DLP and V3A, rather than grouping DLP- with V3v into a single area VLP, or V3d with V3A+ into DM.

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The contribution of cortical thickness and surface area to gray matter asymmetries in the healthy human brain

Human Brain Mapping ◽

10.1002/hbm.22601 ◽

2014 ◽

Vol 35 (12) ◽

pp. 6011-6022 ◽

Cited By ~ 24

Author(s):

Katja Koelkebeck ◽

Jun Miyata ◽

Manabu Kubota ◽

Waldemar Kohl ◽

Shuraku Son ◽

...

Keyword(s):

Human Brain ◽

Surface Area ◽

Cortical Thickness ◽

Gray Matter ◽

Healthy Human

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Mapping multiple visual areas in the human brain with a short fMRI sequence

NeuroImage ◽

10.1016/j.neuroimage.2005.07.033 ◽

2006 ◽

Vol 29 (1) ◽

pp. 74-89 ◽

Cited By ~ 38

Author(s):

Peter Stiers ◽

Ronald Peeters ◽

Lieven Lagae ◽

Paul Van Hecke ◽

Stefan Sunaert

Keyword(s):

Human Brain ◽

Visual Areas

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REPRESENTATION OF 3-D VOLUMETRIC OBJECT FROM THE PANTOMIME EFFECT AND SHADING CUES IN HUMAN BRAIN

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001407005995 ◽

2007 ◽

Vol 21 (08) ◽

pp. 1307-1322

Author(s):

QI ZHANG ◽

KEN MOGI

Keyword(s):

Human Brain ◽

Visual Processing ◽

Visual Information ◽

Binocular Disparity ◽

Object Perception ◽

Human Beings ◽

Brain Areas ◽

Human Ability ◽

Visual Areas ◽

Visual Phenomenon

Human ability to process visual information of outside world is yet far ahead of man-made systems in accuracy and speed. In particular, human beings can perceive 3-D object from various cues, such as binocular disparity and monocular shading cues. Understanding of the mechanism of human visual processing will lead to a breakthrough in creating artificial visual systems. Here, we study the human 3-D volumetric object perception that is induced by a visual phenomenon named as the pantomime effect and by the monocular shading cues. We measured human brain activities using fMRI when the subjects were observing the visual stimuli. A coordinated system of brain areas, including those in the prefrontal and parietal cortex, in addition to the occipital visual areas was found to be involved in the volumetric object perception.

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Dissociable Neural Representations of Adversarially Perturbed Images in Convolutional Neural Networks and the Human Brain

Frontiers in Neuroinformatics ◽

10.3389/fninf.2021.677925 ◽

2021 ◽

Vol 15 ◽

Author(s):

Chi Zhang ◽

Xiao-Han Duan ◽

Lin-Yuan Wang ◽

Yong-Li Li ◽

Bin Yan ◽

...

Keyword(s):

Neural Networks ◽

Human Brain ◽

Convolutional Neural Networks ◽

Brain Activity ◽

Neural Responses ◽

Neural Representations ◽

Artificial Neurons ◽

Visual Areas ◽

Two Systems ◽

Visual Tasks

Despite the remarkable similarities between convolutional neural networks (CNN) and the human brain, CNNs still fall behind humans in many visual tasks, indicating that there still exist considerable differences between the two systems. Here, we leverage adversarial noise (AN) and adversarial interference (AI) images to quantify the consistency between neural representations and perceptual outcomes in the two systems. Humans can successfully recognize AI images as the same categories as their corresponding regular images but perceive AN images as meaningless noise. In contrast, CNNs can recognize AN images similar as corresponding regular images but classify AI images into wrong categories with surprisingly high confidence. We use functional magnetic resonance imaging to measure brain activity evoked by regular and adversarial images in the human brain, and compare it to the activity of artificial neurons in a prototypical CNN—AlexNet. In the human brain, we find that the representational similarity between regular and adversarial images largely echoes their perceptual similarity in all early visual areas. In AlexNet, however, the neural representations of adversarial images are inconsistent with network outputs in all intermediate processing layers, providing no neural foundations for the similarities at the perceptual level. Furthermore, we show that voxel-encoding models trained on regular images can successfully generalize to the neural responses to AI images but not AN images. These remarkable differences between the human brain and AlexNet in representation-perception association suggest that future CNNs should emulate both behavior and the internal neural presentations of the human brain.

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Normative cerebral cortical thickness for human visual areas

10.1101/676726 ◽

2019 ◽

Author(s):

Ivan Alvarez ◽

Andrew J. Parker ◽

Holly Bridge

Keyword(s):

Cortical Thickness ◽

List Type ◽

Statistical Comparison ◽

Broad Agreement ◽

Visual Systems ◽

Human Connectome Project ◽

Subject Variability ◽

Visual Areas ◽

Abnormal Visual ◽

Within Subject Variability

1AbstractStudies of changes in cerebral neocortical thickness often rely on small control samples for comparison with specific populations with abnormal visual systems. We present a normative dataset for FreeSurfer-derived cortical thickness across 25 human visual areas derived from 960 participants in the Human Connectome Project. Cortical thickness varies systematically across visual areas, in broad agreement with canonical visual system hierarchies in the dorsal and ventral pathways. In addition, cortical thickness estimates show consistent within-subject variability and reliability. Importantly, cortical thickness estimates in visual areas are well described by a normal distribution, making them amenable to direct statistical comparison.HighlightsNormative neocortical thickness values for human visual areas measured with FreeSurferA gradient of increasing neocortical thickness with visual area hierarchyConsistent within- and between-subject variability in neocortical thickness across visual areas

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BigBrain 3D atlas of cortical layers: cortical and laminar thickness gradients diverge in sensory and motor cortices

10.1101/580597 ◽

2019 ◽

Cited By ~ 2

Author(s):

Konrad Wagstyl ◽

Stéphanie Larocque ◽

Guillem Cucurull ◽

Claude Lepage ◽

Joseph Paul Cohen ◽

...

Keyword(s):

Cerebral Cortex ◽

Human Brain ◽

Cortical Thickness ◽

Functional Organization ◽

Functional Neuroanatomy ◽

Cortical Layers ◽

Opposite Pattern ◽

Isotropic Resolution ◽

Brain Microstructure ◽

Laminar Thickness

AbstractHistological atlases of the cerebral cortex, such as those made famous by Brodmann and von Economo, are invaluable for understanding human brain microstructure and its relationship with functional organization in the brain. However, these existing atlases are limited to small numbers of manually annotated samples from a single cerebral hemisphere, measured from 2D histological sections. We present the first whole-brain quantitative 3D laminar atlas of the human cerebral cortex. This atlas was derived from a 3D histological model of the human brain at 20 micron isotropic resolution (BigBrain), using a convolutional neural network to segment, automatically, the cortical layers in both hemispheres. Our approach overcomes many of the historical challenges with measurement of histological thickness in 2D and the resultant laminar atlas provides an unprecedented level of precision and detail.We utilized this BigBrain cortical atlas to test whether previously reported thickness gradients, as measured by MRI in sensory and motor processing cortices, were present in a histological atlas of cortical thickness, and which cortical layers were contributing to these gradients. Cortical thickness increased across sensory processing hierarchies, primarily driven by layers III, V and VI. In contrast, fronto-motor cortices showed the opposite pattern, with decreases in total and pyramidal layer thickness. These findings illustrate how this laminar atlas will provide a link between single-neuron morphology, mesoscale cortical layering, macroscopic cortical thickness and, ultimately, functional neuroanatomy.

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Stereoscopic Processing of Absolute and Relative Disparity in Human Visual Cortex

Journal of Neurophysiology ◽

10.1152/jn.01042.2003 ◽

2004 ◽

Vol 92 (3) ◽

pp. 1880-1891 ◽

Cited By ~ 105

Author(s):

Peter Neri ◽

Holly Bridge ◽

David J. Heeger

Keyword(s):

Visual Cortex ◽

Human Brain ◽

Firing Rate ◽

Stereoscopic Vision ◽

Relative Depth ◽

Absolute Distance ◽

Neuronal Responses ◽

Repeated Presentation ◽

Visual Areas ◽

Two Stages

Stereoscopic vision relies mainly on relative depth differences between objects rather than on their absolute distance in depth from where the eyes fixate. However, relative disparities are computed from absolute disparities, and it is not known where these two stages are represented in the human brain. Using functional MRI (fMRI), we assessed absolute and relative disparity selectivity with stereoscopic stimuli consisting of pairs of transparent planes in depth in which the absolute and relative disparity signals could be independently manipulated (at a local spatial scale). In experiment 1, relative disparity was kept constant, while absolute disparity was varied in one-half the blocks of trials (“mixed” blocks) and kept constant in the remaining one-half (“same” blocks), alternating between blocks. Because neuronal responses undergo adaptation and reduce their firing rate following repeated presentation of an effective stimulus, the fMRI signal reflecting activity of units selective for absolute disparity is expected to be smaller during “same” blocks as compared with “mixed” ones. Experiment 2 similarly manipulated relative disparity rather than absolute disparity. The results from both experiments were consistent with adaptation with differential effects across visual areas such that 1) dorsal areas (V3A, MT+/V5, V7) showed more adaptation to absolute than to relative disparity; 2) ventral areas (hV4, V8/V4α) showed an equal adaptation to both; and 3) early visual areas (V1, V2, V3) showed a small effect in both experiments. These results indicate that processing in dorsal areas may rely mostly on information about absolute disparities, while ventral areas split neural resources between the two types of stereoscopic information so as to maintain an important representation of relative disparity.

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Age- and gender-related regional variations of human brain cortical thickness, complexity, and gradient in the third decade

Human Brain Mapping ◽

10.1002/hbm.22369 ◽

2013 ◽

Vol 35 (6) ◽

pp. 2817-2835 ◽

Cited By ~ 9

Author(s):

Maud Creze ◽

Leslie Versheure ◽

Pierre Besson ◽

Chloe Sauvage ◽

Xavier Leclerc ◽

...

Keyword(s):

Human Brain ◽

Cortical Thickness ◽

Age And Gender ◽

Regional Variations ◽

The Third ◽

And Gender

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PTPN11 Gain-of-Function Mutations Affect the Developing Human Brain, Memory, and Attention

Cerebral Cortex ◽

10.1093/cercor/bhy158 ◽

2018 ◽

Vol 29 (7) ◽

pp. 2915-2923 ◽

Cited By ~ 5

Author(s):

Emily M Johnson ◽

Alexandra D Ishak ◽

Paige E Naylor ◽

David A Stevenson ◽

Allan L Reiss ◽

...

Keyword(s):

Human Brain ◽

Cortical Thickness ◽

Neural Development ◽

Mapk Pathway ◽

Gray Matter Volume ◽

Brain Regions ◽

Typically Developing ◽

Cellular Mechanisms ◽

Memory And Attention ◽

Behavioral Mechanisms

Abstract The Ras-MAPK pathway has an established role in neural development and synaptic signaling. Mutations in this pathway are associated with a collection of neurodevelopmental syndromes, Rasopathies; among these, Noonan syndrome (NS) is the most common (1:2000). Prior research has focused on identifying genetic mutations and cellular mechanisms of the disorder, however, effects of NS on the human brain remain unknown. Here, imaging and cognitive data were collected from 12 children with PTPN11-related NS, ages 4.0–11.0 years (8.98 ± 2.33) and 12 age- and sex-matched typically developing controls (8.79 ± 2.17). We observe reduced gray matter volume in bilateral corpus striatum (Cohen’s d = −1.0:−1.3), reduced surface area in temporal regions (d = −1.8:−2.2), increased cortical thickness in frontal regions (d = 1.2–1.3), and reduced cortical thickness in limbic regions (d = −1.6), including limbic structures integral to the circuitry of the hippocampus. Further, we find high levels of inattention, hyperactivity, and memory deficits in children with NS. Taken together, these results identify effects of NS on specific brain regions associated with ADHD and learning in children. While our research lays the groundwork for elucidating the neural and behavioral mechanisms of NS, it also adds an essential tier to understanding the Ras-MAPK pathway’s role in human brain development.

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