Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.

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Mapping the Structural Core of Human Cerebral Cortex

This study examined the role of self-regulation in emerging academic ability in one hundred and forty-one 3- to 5-year-old children from low-income homes. Measures of effortful control, false belief understanding, and the inhibitory control and attention-shifting aspects of executive function in preschool were related to measures of math and literacy ability in kindergarten. Results indicated that the various aspects of child self-regulation accounted for unique variance in the academic outcomes independent of general intelligence and that the inhibitory control aspect of executive function was a prominent correlate of both early math and reading ability. Findings suggest that curricula designed to improve self-regulation skills as well as enhance early academic abilities may be most effective in helping children succeed in school.

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Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten

http://semantics.uchicago.edu/kennedy/classes/s09/experimentalsemantics/feigenson-etal04.pdf

Core systems of number

Resting state functional connectivity MRI (fcMRI) is widely used to investigate brain networks that exhibit correlated fluctuations. While fcMRI does not provide direct measurement of anatomic connectivity, accumulating evidence suggests it is sufficiently constrained by anatomy to allow the architecture of distinct brain systems to be characterized. fcMRI is particularly useful for characterizing large-scale systems that span distributed areas (e.g., polysynaptic cortical pathways, cerebro-cerebellar circuits, cortical-thalamic circuits) and has complementary strengths when contrasted with the other major tool available for human connectomics-high angular resolution diffusion imaging (HARDI). We review what is known about fcMRI and then explore fcMRI data reliability, effects of preprocessing, analysis procedures, and effects of different acquisition parameters across six studies (n = 98) to provide recommendations for optimization. Run length (2-12 min), run structure (1 12-min run or 2 6-min runs), temporal resolution (2.5 or 5.0 s), spatial resolution (2 or 3 mm), and the task (fixation, eyes closed rest, eyes open rest, continuous word-classification) were varied. Results revealed moderate to high test-retest reliability. Run structure, temporal resolution, and spatial resolution minimally influenced fcMRI results while fixation and eyes open rest yielded stronger correlations as contrasted to other task conditions. Commonly used preprocessing steps involving regression of nuisance signals minimized nonspecific (noise) correlations including those associated with respiration. The most surprising finding was that estimates of correlation strengths stabilized with acquisition times as brief as 5 min. The brevity and robustness of fcMRI positions it as a powerful tool for large-scale explorations of genetic influences on brain architecture. We conclude by discussing the strengths and limitations of fcMRI and how it can be combined with HARDI techniques to support the emerging field of human connectomics.

https://www.physiology.org/doi/pdf/10.1152/jn.00783.2009

Intrinsic Functional Connectivity As a Tool For Human Connectomics: Theory, Properties, and Optimization

The success of diffusion magnetic resonance imaging (MRI) is deeply rooted in the powerful concept that during their random, diffusion-driven displacements molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. As diffusion is truly a three-dimensional process, molecular mobility in tissues may be anisotropic, as in brain white matter. With diffusion tensor imaging (DTI), diffusion anisotropy effects can be fully extracted, characterized, and exploited, providing even more exquisite details on tissue microstructure. The most advanced application is certainly that of fiber tracking in the brain, which, in combination with functional MRI, might open a window on the important issue of connectivity. DTI has also been used to demonstrate subtle abnormalities in a variety of diseases (including stroke, multiple sclerosis, dyslexia, and schizophrenia) and is currently becoming part of many routine clinical protocols. The aim of this article is to review the concepts behind DTI and to present potential applications.

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Diffusion tensor imaging: Concepts and applications

https://wiki.epfl.ch/hdstudio/documents/articles/dehaene_reviewnumber_curropneurobiol2004.pdf

Arithmetic and the brain.

http://www.unicog.org/publications/molko_turner_neuron_2003.pdf

Functional and Structural Alterations of the Intraparietal Sulcus in a Developmental Dyscalculia of Genetic Origin

Previous work has shown a relationship between parietal lobe anatomy and nonnative speech sound learning. We scanned a new group of phonetic learners using structural magnetic resonance imaging and diffusion tensor imaging. Voxel-based morphometry indicated higher white matter (WM) density in left Heschl's gyrus (HG) in faster compared with slower learners, and manual segmentation of this structure confirmed that the WM volume of left HG is larger in the former compared with the latter group. This finding was replicated in a reanalysis of the original groups tested in Golestani and others (2002, Anatomical correlates of learning novel speech sounds. Neuron 35:997-1010). We also found that faster learners have a greater asymmetry (left > right) in parietal lobe volumes than slower learners and that the right insula and HG are more superiorly located in slower compared with faster learners. These results suggest that left auditory cortex WM anatomy, which likely reflects auditory processing efficiency, partly predicts individual differences in an aspect of language learning that relies on rapid temporal processing. It also appears that a global displacement of components of a right hemispheric language network, possibly reflecting individual differences in the functional anatomy and lateralization of language processing, is predictive of speech sound learning.

/pdf/brain-structure-predicts-the-learning-of-foreign-speech-26xk3ak8p5.pdf

Brain Structure Predicts the Learning of Foreign Speech Sounds

http://www.unicog.org/publications/Bruandet_AcalculiaTurner_Neuropsychologia2003.pdf

Nicolas Molko

Papers

Diffusion tensor imaging: Concepts and applications

Arithmetic and the brain.

Functional and Structural Alterations of the Intraparietal Sulcus in a Developmental Dyscalculia of Genetic Origin

Brain Structure Predicts the Learning of Foreign Speech Sounds

A cognitive characterization of dyscalculia in Turner syndrome.