Literature DB >> 11459760

Structure--function spatial covariance in the human visual cortex.

M K Hasnain1, P T Fox, M G Woldorff.   

Abstract

The value of sulcal landmarks for predicting functional areas was quantitatively examined. Medial occipital sulci were identified using anatomical magnetic resonance images to create individual cortical-surface models. Functional visual areas were identified using retinotopically organized visual stimuli, and positron emission tomography subtraction imaging with intra-subject averaging. Functional areas were assigned labels by placement along the cortical surface from V1. Structure-function spatial covariances between sulci and functional areas, and spatial covariances among functional areas, were determined by projecting sulcal landmarks and functional areas into a standardized stereotaxic space and computing the 'r' statistics. A functional area was considered to spatially covary with a sulcus or another functional area if their geometric centers correlated significantly (P < 0.05) in two or more axes. Statistically significant spatial covariances were found for some, but not all comparisons. The finding of significant spatial covariances within a standardized stereotaxic space indicates that nine-parameter spatial normalization does not account for all the predictive value of structural or functional locations, and may be improved upon by using selected sulcal and functional landmarks. The present findings quantify for the first time the strength of structure--function spatial covariance and comment directly on developmental theories addressing the etiology of structure--function correspondence.

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Year:  2001        PMID: 11459760     DOI: 10.1093/cercor/11.8.702

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  18 in total

1.  Improvement in variability of the horizontal meridian of the primary visual area following high-resolution spatial normalization.

Authors:  P Kochunov; M Hasnain; J Lancaster; T Grabowski; P Fox
Journal:  Hum Brain Mapp       Date:  2003-02       Impact factor: 5.038

2.  Hemispheric asymmetry of sulcus-function correspondence: quantization and developmental implications.

Authors:  Mohammed K Hasnain; Peter T Fox; Marty G Woldorff
Journal:  Hum Brain Mapp       Date:  2006-04       Impact factor: 5.038

3.  Where is human V4? Predicting the location of hV4 and VO1 from cortical folding.

Authors:  Nathan Witthoft; Mai Lin Nguyen; Golijeh Golarai; Karen F LaRocque; Alina Liberman; Mary E Smith; Kalanit Grill-Spector
Journal:  Cereb Cortex       Date:  2013-04-16       Impact factor: 5.357

4.  A hierarchical method for whole-brain connectivity-based parcellation.

Authors:  David Moreno-Dominguez; Alfred Anwander; Thomas R Knösche
Journal:  Hum Brain Mapp       Date:  2014-04-17       Impact factor: 5.038

5.  Quantitative Folding Pattern Analysis of Early Primary Sulci in Human Fetuses with Brain Abnormalities.

Authors:  K Im; A Guimaraes; Y Kim; E Cottrill; B Gagoski; C Rollins; C Ortinau; E Yang; P E Grant
Journal:  AJNR Am J Neuroradiol       Date:  2017-05-18       Impact factor: 3.825

6.  Functional organization of human visual cortex in occipital polymicrogyria.

Authors:  Serge O Dumoulin; Jeffrey D Jirsch; Andrea Bernasconi
Journal:  Hum Brain Mapp       Date:  2007-12       Impact factor: 5.038

7.  Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

Authors:  V D Calhoun; T Adali; N R Giuliani; J J Pekar; K A Kiehl; G D Pearlson
Journal:  Hum Brain Mapp       Date:  2006-01       Impact factor: 5.038

Review 8.  The functional architecture of the ventral temporal cortex and its role in categorization.

Authors:  Kalanit Grill-Spector; Kevin S Weiner
Journal:  Nat Rev Neurosci       Date:  2014-06-25       Impact factor: 34.870

Review 9.  Sulcal pits and patterns in developing human brains.

Authors:  Kiho Im; P Ellen Grant
Journal:  Neuroimage       Date:  2018-03-27       Impact factor: 6.556

10.  Accurate prediction of V1 location from cortical folds in a surface coordinate system.

Authors:  Oliver P Hinds; Niranjini Rajendran; Jonathan R Polimeni; Jean C Augustinack; Graham Wiggins; Lawrence L Wald; H Diana Rosas; Andreas Potthast; Eric L Schwartz; Bruce Fischl
Journal:  Neuroimage       Date:  2007-11-06       Impact factor: 6.556

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