NeuroImage
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Triggered event-related functional magnetic resonance imaging requires sparse intervals of temporally resolved functional data acquisitions, whose initiation corresponds to the occurrence of an event, typically an epileptic spike in the electroencephalographic trace. However, conventional fMRI time series are greatly affected by non-steady-state magnetization effects, which obscure initial blood oxygen level-dependent (BOLD) signals. Here, conventional echo-planar imaging and a post-processing solution based on principal component analysis were employed to remove the dominant eigenimages of the time series, to filter out the global signal changes induced by magnetization decay and to recover BOLD signals starting with the first functional volume. ⋯ As an application of the method, the detectability of the initial transient BOLD response in the auditory cortex, which is elicited by the onset of acoustic scanner noise, was used to demonstrate that post-processing-based removal of magnetization effects allows to detect brain activity patterns identical with those obtained using the radiofrequency preparation. Using the auditory responses as an ideal experimental model of triggered brain activity, our results suggest that reducing the initial magnetization effects by removing a few principal components from fMRI data may be potentially useful in the analysis of triggered event-related echo-planar time series. The implications of this study are discussed with special caution to remaining technical limitations and the additional neurophysiological issues of the triggered acquisition.
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Randomized Controlled Trial
Effects of oxygen saturation on BOLD and arterial spin labelling perfusion fMRI signals studied in a motor activation task.
Effects of oxygen availability on blood oxygenation level dependent (BOLD) and arterial spin labelling (ASL) perfusion functional magnetic resonance imaging (fMRI) signal changes upon motor activation were studied. Mild hypoxic hypoxia was induced by reducing the inspired oxygen content (FIO(2)) to 12%, decreasing blood oxygen saturation (Y) from 0.99 +/- 0.01 to 0.85 +/- 0.03. The fMRI signal characteristics were determined during finger tapping. ⋯ On one hand, neither BOLD nor ASL fMRI signal changes are influenced by hypoxia during motor activation. On the other hand, hypoxia attenuates increase in both BOLD and perfusion fMRI signals upon finger tapping from the levels determined in normoxia. These observations indicate that haemodynamic and metabolic responses may be heterogeneous in brain during execution of motor functions in mild hypoxia.
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When performing or perceiving music, we experience the melodic (spatial) and rhythmic aspects as a unified whole. Moreover, the motor program theory stipulates that the relative timing and the serial order of the movement are invariant features of a motor program. Still, clinical and psychophysical observations suggest independent processing of these two aspects, in both production and perception. ⋯ We found that the medial occipital lobe, the superior temporal lobe, the rostral cingulate cortex, the putamen and the cerebellum process the melodic information, whereas the lateral occipital and the inferior temporal cortex, the left supramarginal gyrus, the left inferior and ventral frontal gyri, the caudate nucleus, and the cerebellum process the rhythmic information. Thus, we suggest a dissociate involvement of the dorsal visual stream in the spatial pitch processing and the ventral visual stream in temporal movement preparation. We propose that this dissociate organization may be important for fast learning and flexibility in motor control.
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Diffusion tensor imaging (DTI) has seen increased usage in clinical and basic science research in the past decade. By assessing the water diffusion anisotropy within biological tissues, e.g. brain, researchers can infer different fiber structures important for neural pathways. A typical DTI data set contains at least one base image and six diffusion-weighted images along non-collinear encoding directions. ⋯ This assumption is generally false, as the large diffusion-weighting gradients would usually induce eddy currents to generate diffusion-weighting direction-dependent field gradients, leading to mis-registration within the DTI data set. Traditional methods for correcting magnetic field-induced distortions do not usually take into account these direction-dependent eddy currents unique for DTI, and they are usually time-consuming because multiple phase images need to be acquired. In this report, we describe our theory and implementation of an efficient and effective method to correct for the main field and eddy current-induced direction-dependent distortions for DTI images under a unified framework to facilitate the daily practice of DTI acquisitions.
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Magnetic resonance diffusion tensor tractography is a powerful tool for the non-invasive depiction of the white matter architecture in the human brain. However, due to limitations in the underlying tensor model, the technique is often unable to reconstruct correct trajectories in heterogeneous fiber arrangements, such as axonal crossings. A novel tractography method based on fast marching (FM) is proposed which is capable of resolving fiber crossings and also permits trajectories to branch. ⋯ The performance of the technique is demonstrated in artificial data and in the healthy human brain. Comparisons with standard FM tractography and conventional line propagation algorithms show that, in the presence of interfering structures, the proposed method is more accurate in reconstructing trajectories. The in vivo results illustrate that the elucidated major white matter pathways are consistent with known anatomy and that multiple crossings and tract branching are handled correctly.