Stéphanie Larocque

Automated segmentation of cortical layers in BigBrain reveals divergent cortical and laminar thickness gradients in sensory and motor cortices.

Konrad Wagstyl

Stéphanie Larocque

Guillem Cucurull

Claude Lepage

Joseph Paul Cohen

Sebastian Bludau

Nicola Palomero-Gallagher

L. Lewis

Thomas Funck

Hannah Spitzer

Timo Dicksheid

Paul C Fletcher

Adriana Romero Soriano

Karl Zilles

Katrin Amunts

Yoshua Bengio

Alan C. Evans

Abstract Large-scale in vivo neuroimaging datasets offer new possibilities for reliable, well-powered measures of interregional structural d… (voir plus)ifferences and biomarkers of pathological changes in a wide variety of neurological and psychiatric diseases. However, so far studies have been structurally and functionally imprecise, being unable to relate pathological changes to specific cortical layers or neurobiological processes. We developed artificial neural networks to segment cortical and laminar surfaces in the BigBrain, a 3D histological model of the human brain. We sought 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. Identifying common gradients of cortical organisation enables us to meaningfully relate microstructural, macrostructural and functional cortical parameters. Analysis of thickness gradients across sensory cortices, using our fully segmented six-layered model, was consistent with MRI findings, showing increasing thickness moving up the processing hierarchy. In contrast, fronto-motor cortices showed the opposite pattern with changes in thickness of layers III, V and VI being the primary drivers of these gradients. As well as identifying key differences between sensory and motor gradients, our findings show how the use of this laminar atlas offers insights that will be key to linking single-neuron morphological changes, mesoscale cortical layers and macroscale cortical thickness.

2019-03-17

bioRxiv (prépublication)

doi.org

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

Konrad Wagstyl

Stéphanie Larocque

Guillem Cucurull

Claude Lepage

Joseph Paul Cohen

Sebastian Bludau

Nicola Palomero-Gallagher

L. Lewis

Thomas Funck

Hannah Spitzer

Timo Dicksheid

Paul C Fletcher

Adriana Romero Soriano

Karl Zilles

Katrin Amunts

Yoshua Bengio

Alan C. Evans

Histological atlases of the cerebral cortex, such as those made famous by Brodmann and von Economo, are invaluable for understanding human b… (voir plus)rain 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.

2019-03-17

bioRxiv (prépublication)

doi.org

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

Konrad Wagstyl

Stéphanie Larocque

Guillem Cucurull

Claude Lepage

Joseph Paul Cohen

Sebastian Bludau

Nicola Palomero-Gallagher

L. Lewis

Thomas Funck

Hannah Spitzer

Timo Dicksheid

Paul C Fletcher

Adriana Romero Soriano

Karl Zilles

Katrin Amunts

Yoshua Bengio

Alan C. Evans

Histological atlases of the cerebral cortex, such as those made famous by Brodmann and von Economo, are invaluable for understanding human b… (voir plus)rain 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.

2019-03-17

bioRxiv (prépublication)

doi.org

BigBrain: 1D convolutional neural networks for automated sementation of cortical layers

Konrad Wagstyl

Claude Lepage

Karl Zilles

Sebastian Bludau

G. Cucurul

Alan C. Evans

Paul C Fletcher

Adriana Romero Soriano