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A new era of brain cartography, powered by neuroimaging and machine learning

-- M GLASSER, D VAN ESSEN/WASHINGTON UNIVERSITY

– M GLASSER, D VAN ESSEN/WASHINGTON UNIVERSITY

Human brain mapped in unprece­dent­ed detail (Nature):

Think of a spin­ning globe and the patch­work of coun­tries it depicts: such maps help us to under­stand where we are, and that nations dif­fer from one anoth­er. Now, neu­ro­sci­en­tists have chart­ed an equiv­a­lent map of the brain’s out­er­most lay­er — the cere­bral cor­tex — sub­di­vid­ing each hemi­sphere’s moun­tain- and val­ley-like folds into 180 sep­a­rate parcels.

Nine­ty-sev­en of these areas have nev­er pre­vi­ous­ly been described, despite show­ing clear dif­fer­ences in struc­ture, func­tion and con­nec­tiv­i­ty from their neigh­bours. The new brain map is pub­lished today in Nature…

While the focus of this work was on cre­at­ing a beau­ti­ful, reli­able, aver­age brain tem­plate, it real­ly opens up the pos­si­bil­i­ty to fur­ther explore the unique inter­sec­tion of indi­vid­ual tal­ents with intel­lec­tu­al and cre­ative abil­i­ties — the things that make us unique­ly human,” says Rex Jung, a neu­ropsy­chol­o­gist at the Uni­ver­si­ty of New Mex­i­co in Albu­querque.

Study: A mul­ti-modal par­cel­la­tion of human cere­bral cor­tex (Nature; opens PDF)

  • Abstract: 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.

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As seen in The New York Times, The Wall Street Journal, BBC News, CNN, Reuters,  SharpBrains is an independent market research firm tracking how brain science can improve our health and our lives.

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