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The Human Connectome: A Structural Description of the Human Brain

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TLDR
A research strategy to achieve the connection matrix of the human brain (the human “connectome”) is proposed, and its potential impact is discussed.
Abstract
The connection matrix of the human brain (the human “connectome”) represents an indispensable foundation for basic and applied neurobiological research. However, the network of anatomical connections linking the neuronal elements of the human brain is still largely unknown. While some databases or collations of large-scale anatomical connection patterns exist for other mammalian species, there is currently no connection matrix of the human brain, nor is there a coordinated research effort to collect, archive, and disseminate this important information. We propose a research strategy to achieve this goal, and discuss its potential impact.

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Journal ArticleDOI

Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging

TL;DR: This paper exploits the idea that each individual brain region has a specific connection profile to create parcellations of the cortical mantle using MR diffusion imaging using a K-means approach including spatial regularization.
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Local termination pattern analysis: a tool for comparing white matter morphology.

TL;DR: Here it is shown that local termination patterns from an individual are highly reproducible across the entire brain, and how LTPA can be deployed into a clinical database and used to characterize white matter morphology differences due to disease, developmental or genetic factors.
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Large-Scale Analysis of Gene Expression and Connectivity in the Rodent Brain: Insights through Data Integration.

TL;DR: Using multiple large-scale data sets obtained from public sources, this work identifies two novel patterns of mouse brain gene expression showing a strong degree of anti-correlation, and relates this to multiple data modalities including macroscale connectivity.
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Multidimensional encoding of brain connectomes.

TL;DR: A framework to encode structural brain connectomes and diffusion-weighted magnetic resonance (dMRI) data using multidimensional arrays is presented and it is demonstrated that the framework allows performing anatomical manipulations on white matter tracts for statistical inference and to study the white matter geometrical organization.
References
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Journal ArticleDOI

Distributed Hierarchical Processing in the Primate Cerebral Cortex

TL;DR: A summary of the layout of cortical areas associated with vision and with other modalities, a computerized database for storing and representing large amounts of information on connectivity patterns, and the application of these data to the analysis of hierarchical organization of the cerebral cortex are reported on.
Journal ArticleDOI

Sequence the Human Genome

TL;DR: This book aims to provide a history of Chinese modern art from 17th Century to the present day through the lens of 20th Century critics, practitioners, journalists, and mediaeval and modern-day critics.
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Dynamic causal modelling.

TL;DR: As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling, but unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
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Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

TL;DR: The results provide the first quantitative demonstration of reliable inference of anatomical connectivity between human gray matter structures using diffusion data and the first connectivity-based segmentation of gray matter.
Journal ArticleDOI

The columnar organization of the neocortex.

V B Mountcastle
- 01 Apr 1997 - 
TL;DR: The modular organization of nervous systems is a widely documented principle of design for both vertebrate and invertebrate brains of which the columnar organization of the neocortex is an example.
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