NeuroImage
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We examined 3D patterns of volume differences in the brain associated with blindness, in subjects grouped according to early and late onset. Using tensor-based morphometry, we mapped volume reductions and gains in 16 early-onset (EB) and 16 late-onset (LB) blind adults (onset <5 and >14 years old, respectively) relative to 16 matched sighted controls. Each subject's structural MRI was fluidly registered to a common template. ⋯ EBs but not LBs showed deficits in the splenium and the isthmus. Gains in the non-occipital white matter were more widespread in the EBs. These differences may reflect regional alterations in late neurodevelopmental processes, such as myelination, that continue into adulthood.
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To examine the functional association between brain and autonomic activities accompanying decision-making, we simultaneously recorded regional cerebral blood flow using (15)O-water positron emission tomography and event-related brain potentials (ERPs) time-locked to feedback of reward and punishment, as well as cardiovascular parameters, during a stochastic decision-making task. We manipulated the uncertainty of outcomes in the task; specifically, we compared a condition with high predictability of reward/punishment (contingent-reward condition) and a condition with low predictability of reward/punishment (random-reward condition). The anterior cingulate cortex (ACC) was commonly activated in both conditions. ⋯ Activation of these brain regions correlated with a positive component of ERPs locked to feedback signals (feedback-related positivity), which showed an association with behavioral decision-making in the contingent-reward condition. Furthermore, cardiovascular responses were attenuated in the random-reward condition, where continuous attention and contingency monitoring were needed, and such attenuation of cardiovascular responses was mediated by vagal activity that was governed by the rostral ACC. These findings suggest that the prefrontal-striatal network provides a neural basis for decision-making and modulation over the peripheral autonomic activity accompanying decision-making.
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Biomarkers to monitor neurological dysfunction in autosomal dominant inherited spinocerebellar ataxias (SCA) are lacking. We therefore aimed to visualize, quantify and correlate localized brain atrophy with clinical symptoms in SCA1, SCA3, and SCA6. ⋯ Our data provide strong evidence that MRI is an attractive surrogate marker for clinical studies of SCA. In each SCA genotype clinical dysfunction may be caused by different patho-anatomical processes.
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While several studies have shown the benefit of cardiac gating in diffusion MRI with single-shot EPI acquisition, cardiac gating is still not commonly used. This is probably because it requires additional time and many investigators may not be convinced that cardiac gating is worth the extra effort. Here, we tested a clinically feasible protocol with a minimal increase in scan time, and quantified the effect of cardiac gating under partial or full Fourier acquisition. ⋯ For full Fourier acquisition, minimum time gating slightly decreased the uncertainties but the efficiency was worse. A minimum trigger delay might not be the optimal scheme to avoid the majority of systole but it allows clinically acceptable scan times. We have demonstrated that cardiac gating, especially of partial Fourier acquisitions, can reduce the uncertainties of DTI derived parameters in a time-efficient manner.
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FMRI studies of the orbitofrontal cortex or the inferior temporal lobes are often compromised by susceptibility artefacts, which may result in signal reduction or loss in gradient echo (GE) EPI. Spin echo (SE) EPI is considerably more robust against susceptibility-related signal loss, but its intrinsic sensitivity to changes in the blood oxygenation level dependent (BOLD) contrast is generally lower. In this study, we performed a direct comparison of GE and SE fMRI using a single-shot dual echo EPI acquisition scheme. ⋯ Furthermore, a general method is proposed to combine the GE and SE data into a single hybrid data set that provides optimum sensitivity in the whole brain. This method can be applied to any experimental design that can be expressed in terms of a generalised linear model. The feasibility of this approach is demonstrated both theoretically and experimentally.