Publications by authors named "Oliver Lyttelton"

Recent imaging studies have demonstrated that levels of resting γ-aminobutyric acid (GABA) in the visual cortex predict the degree of stimulus-induced activity in the same region. These studies have used the presentation of discrete visual stimulus; the change from closed eyes to open also represents a simple visual stimulus, however, and has been shown to induce changes in local brain activity and in functional connectivity between regions. We thus aimed to investigate the role of the GABA system, specifically GABA(A) receptors, in the changes in brain activity between the eyes closed (EC) and eyes open (EO) state in order to provide detail at the receptor level to complement previous studies of GABA concentrations.

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Awareness is an essential feature of the human mind that can be directed internally, that is, toward our self, or externally, that is, toward the environment. The combination of internal and external information is crucial to constitute our sense of self. Although the underlying neuronal networks, the so-called intrinsic and extrinsic systems, have been well-defined, the associated biochemical mechanisms still remain unclear.

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A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such resting-state networks (RSNs), which was implemented with k-means clustering. The core of the method consists in bootstrapping the available datasets to replicate the clustering process a large number of times and quantify the stable features across all replications.

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Introduction: Tourette syndrome (TS) implicates the disinhibition of the cortico-striatal-thalamic-cortical circuitry (CSTC). Previous studies used a volumetric approach to investigate this circuitry with inconsistent findings. Cortical thickness may represent a more reliable measure than volume due to the low variability in the cytoarchitectural structure of the grey matter.

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Previous studies of cortical asymmetry have relied mainly on voxel-based morphometry (VBM), or manual segmentation of regions of interest. This study uses fully automated, surface-based techniques to analyse position and surface area asymmetry for the mid-surfaces of 112 right-handed subjects' cortical hemispheres from a cohort of young adults. Native space measurements of local surface area asymmetry and vertex position asymmetry were calculated from surfaces registered to a previously validated hemisphere-unbiased surface-based template.

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We investigated the scale relationship between size and cortical structure of human brains in a large sample of magnetic resonance imaging data. Cortical structure was estimated with several measures (cortical volume, surface area, and thickness, sulcal depth, and absolute mean curvature in sulcal regions and sulcal walls) using three-dimensional surface-based methods in 148 normal subjects (n [men/women]: 83/65, age [mean +/- standard deviation]: 25.0 +/- 4.

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Accurate alignment of explicit surface representations of human cerebral cortices is necessary in order to compare local individual differences in cortical morphometric measurements (thickness, surface area, gyrification, etc.) in both normal and clinical populations. This paper presents a methodology for developing unbiased, high resolution iterative registration templates from a group of 222 subject hemispheres and shows that the resulting template provides better alignment of a separate set of test data than single-subject templates.

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