NeuroImage
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Previous studies have reported that the spontaneous, resting-state time course of the default-mode network is negatively correlated with that of the "task-positive network", a collection of regions commonly recruited in demanding cognitive tasks. However, all studies of negative correlations between the default-mode and task-positive networks have employed some form of normalization or regression of the whole-brain average signal ("global signal"); these processing steps alter the time series of voxels in an uninterpretable manner as well as introduce spurious negative correlations. Thus, the extent of negative correlations with the default mode network without global signal removal has not been well characterized, and it is has recently been hypothesized that the apparent negative correlations in many of the task-positive regions could be artifactually induced by global signal pre-processing. ⋯ Physiological noise correction increased the spatial extent and magnitude of negative correlations, yielding negative correlations within task-positive regions at the group-level (p<0.05, uncorrected; no regions at the group level were significant at FDR=0.05). Furthermore, physiological noise correction caused region-specific decreases in positive correlations within the default-mode network, reducing apparent false positives. It was observed that the low-frequency respiratory volume and cardiac rate regressors used within the physiological noise correction algorithm displayed significant (but not total) shared variance with the global signal, and constitute a model-based alternative to correcting for non-neural global noise.
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Rates of brain atrophy derived from serial magnetic resonance (MR) studies may be used to assess therapies for Alzheimer's disease (AD). These measures may be confounded by changes in scanner voxel sizes. For this reason, the Alzheimer's Disease Neuroimaging Initiative (ADNI) included the imaging of a geometric phantom with every scan. ⋯ We used the registration algorithm to quantify any residual scaling errors, and found the algorithm to be unbiased, with no significant (p=0.97) difference between control (n=79) and AD subjects (n=50), but with a mean (SD) absolute volume change of 0.20 (0.20) % due to linear scalings. 9DOF registration was shown to be comparable to geometric phantom correction in terms of the effect on atrophy measurement and unbiased with respect to disease status. These results suggest that the additional expense and logistic effort of scanning a phantom with every patient scan can be avoided by registration-based scaling correction. Furthermore, based upon the atrophy rates in the AD subjects in this study, sample size requirements would be approximately 10-12% lower with (either) correction for voxel scaling than if no correction was used.
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Due to its crucial role for memory processes and its relevance in neurological and psychiatric disorders, the hippocampus has been the focus of neuroimaging research for several decades. In vivo measurement of human hippocampal volume and shape with magnetic resonance imaging has become an important element of neuroimaging research. Nevertheless, volumetric findings are still inconsistent and controversial for many psychiatric conditions including affective disorders. ⋯ These are major sources of variance between different protocols. In contrast, the definitions of the lateral, superior, and inferior borders are less disputed. Directing resources to replication studies that incorporate characteristics of the segmentation protocols presented herein may help resolve seemingly contradictory volumetric results between prior neuroimaging studies and facilitate the appropriate selection of protocols for manual or automated delineation of the hippocampus for future research purposes.
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The objective of this study was to investigate total volume and spatial distribution of white matter hyperintensities (WMH) in a large sample of newly diagnosed Parkinson's disease (PD) patients with and without mild cognitive impairment (MCI) compared to normal controls (NC). Furthermore, we aimed to examine the impact of the WMH on attention-executive performance in PD. MCI is regarded as a pre-dementia stage. ⋯ Analysis showed that there were no significant differences between the 3 groups in total volume or spatial distribution of WMH. In addition there was no significant relationship between total volume or spatial distribution of WMH and attention-executive functions in PD. We conclude that in this PD cohort, cognitive impairment seems to be independent of WMH damage.
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Both affective neuroscience and decision science focus on the role of emotions in decisions. Regret and disappointment are emotions experienced with negative decision outcomes. The present research examines the neural substrates of regret and disappointment as well as the role of regret and disappointment in decision making. ⋯ Both regret and disappointment activated anterior insula and dorsomedial prefrontal cortex relative to fixation, with greater activation in regret than in disappointment. In contrast to disappointment, regret also showed enhanced activation in the lateral orbitofrontal cortex. These findings suggest that regret and disappointment, emotions experienced during decision-related loss, share a general neural network but differ in both the magnitude of subjective feelings and with regret activating some regions with greater intensity.