The WU-Minn Human Connectome Project: An Overview

Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

A multi-modal parcellation of human cerebral cortex

In this review, we consider the potential functional role of beta-band oscillations, which at present is not yet well understood. We discuss evidence from recent studies on top-down mechanisms involved in cognitive processing, on the motor system and on the pathophysiology of movement disorders that suggest a unifying hypothesis: beta-band activity seems related to the maintenance of the current sensorimotor or cognitive state. We hypothesize that beta oscillations and/or coupling in the beta-band are expressed more strongly if the maintenance of the status quo is intended or predicted, than if a change is expected. Moreover, we suggest that pathological enhancement of beta-band activity is likely to result in an abnormal persistence of the status quo and a deterioration of flexible behavioural and cognitive control.

Beta-band oscillations--signalling the status quo?

Function in the human connectome: Task-fMRI and individual differences in behavior

Functional connectomics from resting-state fMRI

https://pure.mpg.de/pubman/item/item_1747052_7/component/file_1835422/Schoffelen_2013_neuroimage.pdf

Adding dynamics to the Human Connectome Project with MEG.

Spontaneous brain activity is spatially and temporally organized in the absence of any stimulation or task in networks of cortical and subcortical regions that appear largely segregated when imaged at slow temporal resolution with functional magnetic resonance imaging (fMRI). When imaged at high temporal resolution with magneto-encephalography (MEG), these resting-state networks (RSNs) show correlated fluctuations of band-limited power in the beta frequency band (14-25 Hz) that alternate between epochs of strong and weak internal coupling. This study presents 2 novel findings on the fundamental issue of how different brain regions or networks interact in the resting state. First, we demonstrate the existence of multiple dynamic hubs that allow for across-network coupling. Second, dynamic network coupling and related variations in hub centrality correspond to increased global efficiency. These findings suggest that the dynamic organization of across-network interactions represents a property of the brain aimed at optimizing the efficiency of communication between distinct functional domains (memory, sensory-attention, motor). They also support the hypothesis of a dynamic core network model in which a set of network hubs alternating over time ensure efficient global communication in the whole brain.

/pdf/a-dynamic-core-network-and-global-efficiency-in-the-resting-4r7lzsgoza.pdf

A Dynamic Core Network and Global Efficiency in the Resting Human Brain

http://neuroinformation.incf.org/public/ueditor/php/upload/file/20150525/1432573289168227.pdf

F. de Pasquale

Papers

Adding dynamics to the Human Connectome Project with MEG.

A Dynamic Core Network and Global Efficiency in the Resting Human Brain

Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure

Cortical cores in network dynamics.

Empirical Markov Chain Monte Carlo Bayesian analysis of fMRI data