Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

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Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex. / Osher, D.E.; Saxe, R.R.; Koldewyn, K. et al.
Yn: Cerebral Cortex, Cyfrol 26, Rhif 4, 26.01.2015, t. 1668-1683.

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

HarvardHarvard

Osher, DE, Saxe, RR, Koldewyn, K, Gabrieli, JD, Kanwisher, N & Saygin, ZM 2015, 'Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex', Cerebral Cortex, cyfrol. 26, rhif 4, tt. 1668-1683. https://doi.org/10.1093/cercor/bhu303

APA

Osher, D. E., Saxe, R. R., Koldewyn, K., Gabrieli, J. D., Kanwisher, N., & Saygin, Z. M. (2015). Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex. Cerebral Cortex, 26(4), 1668-1683. https://doi.org/10.1093/cercor/bhu303

CBE

MLA

VancouverVancouver

Osher DE, Saxe RR, Koldewyn K, Gabrieli JD, Kanwisher N, Saygin ZM. Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex. Cerebral Cortex. 2015 Ion 26;26(4):1668-1683. doi: 10.1093/cercor/bhu303

Author

Osher, D.E. ; Saxe, R.R. ; Koldewyn, K. et al. / Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex. Yn: Cerebral Cortex. 2015 ; Cyfrol 26, Rhif 4. tt. 1668-1683.

RIS

TY - JOUR

T1 - Structural connectivity fingerprints predict cortical selectivity for multiple visual categories across cortex

AU - Osher, D.E.

AU - Saxe, R.R.

AU - Koldewyn, K.

AU - Gabrieli, J.D.

AU - Kanwisher, N.

AU - Saygin, Z.M.

PY - 2015/1/26

Y1 - 2015/1/26

N2 - fundamental and largely unanswered question in neuroscience is whether extrinsic connectivity and function are closely related at a fine spatial grain across the human brain. Using a novel approach, we found that the anatomical connectivity of individual gray-matter voxels (determined via diffusion-weighted imaging) alone can predict functional magnetic resonance imaging (fMRI) responses to 4 visual categories (faces, objects, scenes, and bodies) in individual subjects, thus accounting for both functional differentiation across the cortex and individual variation therein. Furthermore, this approach identified the particular anatomical links between voxels that most strongly predict, and therefore plausibly define, the neural networks underlying specific functions. These results provide the strongest evidence to date for a precise and fine-grained relationship between connectivity and function in the human brain, raise the possibility that early-developing connectivity patterns may determine later functional organization, and offer a method for predicting fine-grained functional organization in populations who cannot be functionally scanned

AB - fundamental and largely unanswered question in neuroscience is whether extrinsic connectivity and function are closely related at a fine spatial grain across the human brain. Using a novel approach, we found that the anatomical connectivity of individual gray-matter voxels (determined via diffusion-weighted imaging) alone can predict functional magnetic resonance imaging (fMRI) responses to 4 visual categories (faces, objects, scenes, and bodies) in individual subjects, thus accounting for both functional differentiation across the cortex and individual variation therein. Furthermore, this approach identified the particular anatomical links between voxels that most strongly predict, and therefore plausibly define, the neural networks underlying specific functions. These results provide the strongest evidence to date for a precise and fine-grained relationship between connectivity and function in the human brain, raise the possibility that early-developing connectivity patterns may determine later functional organization, and offer a method for predicting fine-grained functional organization in populations who cannot be functionally scanned

UR - https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/cercor/26/4/10.1093_cercor_bhu303/1/bhu303_Supplementary_Data.zip?Expires=1618479543&Signature=ToCv1-a-iuZL9k0cgPMFkSrFGa-FeJD0ZictAej04uF69IrfYLiUSXfQkPtIPU5-zqBQFpteeiQtN5ij0Nbl01Br7QdHyuC120d3M4iBm2~im0-oIvXe97NAg6FQfy3OXOgfSdn1yon934tq89q8Cdzs9ZC76cjr1zyzG9bXQjJ2ydEm~olAbkb1Xq0B7IJLweWEDJiCv5k6u8KOzDrR4Tv5AzkfWHgwY~oNpzK0Dq0VsOHJARbcFsTCnPgAXQb3olrQe~bYtNC02gmqwjZ7TUh8Fr5pge3T8OukNLF4qbsaupBQUMewxvRw3nT1wcmxbv5kpROQiP5vCNK71o0VLA__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA

U2 - 10.1093/cercor/bhu303

DO - 10.1093/cercor/bhu303

M3 - Article

VL - 26

SP - 1668

EP - 1683

JO - Cerebral Cortex

JF - Cerebral Cortex

SN - 1047-3211

IS - 4

ER -