title: Structural Connectivity Fingerprints Predict Cortical Selectivity for Multiple Visual Categories across Cortex.
abstract: A 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.
authors: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA.
authors: David E
authors: DE
authors: Osher
authors: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors: Rebecca R
authors: RR
authors: Saxe
authors: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA School of Psychology, Bangor University, Gwynedd, UK.
authors: Kami
authors: K
authors: Koldewyn
authors: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors: John D E
authors: JD
authors: Gabrieli
authors: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors: Nancy
authors: N
authors: Kanwisher
authors: McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors: Zeynep M
authors: ZM
authors: Saygin
mesh_terms: D000328:Adult; D001931:Brain Mapping / Q000379:methods; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D005260:Female; D066128:Gray Matter / Q000033:anatomy & histology / Q000502:physiology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D009434:Neural Pathways / Q000033:anatomy & histology / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology*; D055815:Young Adult
keywords: diffusion-weighted imaging; structure–function; tractography; visual perception
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