Showing papers in "NeuroImage in 2004"

TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.

TL;DR: Results suggest that both common and distinct neural systems support various forms of reappraisal and that which particular prefrontal systems modulate the amygdala in different ways depends on the regulatory goal and strategy employed.

TL;DR: A set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation.

TL;DR: A novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models is presented, resulting in a robust and automated procedure that outperforms other publicly available skullstripping tools.

TL;DR: ReHo can consider as a complementary method to model-driven method, and it could help reveal the complexity of the human brain function, in which KCC was used to measure the similarity of the time series of a given voxels to those of its nearest neighbors in a voxel-wise way.

TL;DR: This work introduces to neuroimage modelling the approach of reference priors, which drives the choice of prior such that it is noninformative in an information-theoretic sense, and proposes two inference techniques at the top level for multilevel hierarchies.

TL;DR: This study proposes a novel method for estimating the fiber orientation distribution directly from high angular resolution diffusion-weighted MR data without the need for prior assumptions regarding the number of fiber populations present, assuming that all white matter fiber bundles in the brain share identical diffusion characteristics.

TL;DR: It is concluded that human attachment employs a push-pull mechanism that overcomes social distance by deactivating networks used for critical social assessment and negative emotions, while it bonds individuals through the involvement of the reward circuitry, explaining the power of love to motivate and exhilarate.

TL;DR: Quantitative modeling of the hemodynamic response, when combined with experimental data measuring both the BOLD and CBF responses, makes possible a more specific and quantitative assessment of brain physiology than is possible with standard BOLD imaging alone.

TL;DR: An atlas normalization procedure for head size correction using manual total intracranial volume (TIV) measurement as a reference is developed and validated and fails to support the hypothesis that large premorbid brain size moderates Alzheimer's disease.

TL;DR: This study examined cranio-cerebral correlation using magnetic resonance imaging (MRI) via the guidance of the international 10-20 system for electrode placement, which had originally been developed for electroencephalography.

TL;DR: In experiments with magnetoencephalographic and functional magnetic resonance imaging data, the method was able to show that expected components are reliable; furthermore, it pointed out components whose interpretation was not obvious but whose reliability should incite the experimenter to investigate the underlying technical or physical phenomena.

TL;DR: Empirically estimated hemodynamic response functions from primary motor and visual cortices and frontal and supplementary eye fields and correlated variation of time-to-peak values across several pairs of regions to highlight the benefits of determining the best possible HRF estimate and potential negative consequences of assuming HRF consistency across subjects or brain regions.

TL;DR: This paper reviews the more recent extension of PLS to the analysis of spatiotemporal patterns present in fMRI, ERP, and MEG data and discusses its role as an important tool in a pluralistic analytic approach to neuroimaging.

TL;DR: A new method for unbiased construction of atlases in the large deformation diffeomorphic setting in the child neuroimaging autism study is described and the segmentation of new subjects via atlas mapping is demonstrated.

TL;DR: By cross-referencing the axial, sagittal, and coronal plates from the original printed atlas, it is demonstrated that the discrepant area should be labeled middle frontal gyrus.

TL;DR: The combined use of Bayes factors and DCM allows one to evaluate competing scientific theories about the architecture of large-scale neural networks and the neuronal interactions that mediate perception and cognition.

TL;DR: A new method for characterizing inter-regional interactions using event-related functional magnetic resonance imaging (fMRI) data is introduced and it is found that the task requiring greater bimanual coordination induced stronger correlations between motor regions of the two hemispheres.

TL;DR: It is concluded that learning to read results in the progressive development of an inferotemporal region increasingly responsive to visual words, which is aptly named the visual word form area (VWFA).

TL;DR: Advances currently being made and issues to consider for improving optical image quality include the optimal selection of wavelengths to minimize random and systematic error propagation in the calculation of the hemoglobin concentrations.

TL;DR: The creation of such models is a first step toward full characterization of the depression phenotype at the neural systems level, with implications for the future development of brain-based algorithms to determine optimal treatment selection for individual patients.

TL;DR: On a real PET data set, it is found that, though the nonstationary tests have reduced sensitivity due to smoothness estimation variability, these tests have better sensitivity for clusters in rough regions compared to stationary cluster-size tests.

TL;DR: The findings show that atlas selection is an important issue in atlas-based segmentation and that, in particular, multi-classifier techniques can substantially increase the segmentation accuracy.

TL;DR: Doppler ultrasound suggests that a component of low-frequency BOLD signal fluctuations is mediated by CO(2)-induced changes in cerebral blood flow (CBF), which is a source of physiological noise and a potentially important confounding factor in fMRI paradigms that modify breathing.

TL;DR: The proposed TMCD method allows for the accurate, robust, and efficient estimation of partial volume model parameters, which is crucial to a variety of brain MRI data analysis procedures such as the accurate estimation of tissue volumes and the accurate delineation of the cortical surface.

TL;DR: A meta-analysis of neuroimaging studies of attention shifting and executive processes in working memory suggests that there is a common set of brain regions active in diverse executive control operations, however, within several of these regions, different types of switching produced spatially discriminable activation foci.

TL;DR: These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

TL;DR: A remarkable degree of overlap was observed in brain areas that activated to partner decisions in the two games, including commonly observed theory of mind areas, as well as severalbrain areas that have not been reported previously and may relate to immersion of participants in real social interactions that have personally meaningful consequences.

TL;DR: Craving-related changes in fMRI signal were identified in the hippocampus, insula, and caudate, three areas reported to be involved in drug craving, which supports the common substrate hypothesis for food and drug cravings.

TL;DR: The results suggest that the combination of EEG and fMRI permits an improved understanding of the spatiotemporal dynamics of brain activity.