NeuroImage
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Comparative Study
The influence of spatial resolution and smoothing on the detectability of resting-state and task fMRI.
Functional MRI blood oxygen level-dependent (BOLD) signal changes can be subtle, motivating the use of imaging parameters and processing strategies that maximize the temporal signal-to-noise ratio (tSNR) and thus the detection power of neuronal activity-induced fluctuations. Previous studies have shown that acquiring data at higher spatial resolutions results in greater percent BOLD signal changes, and furthermore that spatially smoothing higher resolution fMRI data improves tSNR beyond that of data originally acquired at a lower resolution. However, higher resolution images come at the cost of increased acquisition time, and the number of image volumes also influences detectability. ⋯ Our results show that after spatially smoothing the data to the same intrinsic resolution, lower resolution acquisitions have a slightly higher detection power of task-activation in some, but not all, brain areas. There were no significant differences in functional connectivity as a function of resolution after smoothing. Similarly, the reduced tSNR of fMRI data acquired with a SENSE factor of 2 is offset by the greater number of images acquired, resulting in few significant differences in detection power of either functional activation or connectivity after spatial smoothing.
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The default mode network is part of the brain structure that shows higher neural activity and energy consumption when one is at rest. The key regions in the default mode network are highly interconnected as conveyed by both the white matter fiber tracing and the synchrony of resting-state functional magnetic resonance imaging signals. However, the causal information flow within the default mode network is still poorly understood. ⋯ Model comparison procedures favored a model wherein the MPFC sends information to the PCC and the bilateral inferior parietal lobule sends information to both the PCC and MPFC. Further analyses provide evidence that the endogenous connectivity might be higher in the right hemisphere than in the left hemisphere. These data provided insight into the functions of each node in the DMN, and also validate the usage of DCM on resting-state fMRI data.
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Polymicrogyria (PMG) is a cortical malformation characterized by multiple small gyri and altered cortical lamination, which may be associated with disrupted white matter connectivity. However, little is known about the topological patterns of white matter networks in PMG. We examined structural connectivity and network topology using individual primary gyral pattern-based nodes in PMG patients, overcoming the limitations of an atlas-based approach. ⋯ In relation to these results, gyral node-based graph theoretical analysis revealed significantly altered topological organization of the network (lower clustering and higher modularity) and disrupted network hub architecture in cortical association areas involved in cognitive and language functions in PMG patients. Furthermore, the network segregation in PMG patients decreased with the extent of PMG and the degree of language impairment. Our approach provides the first detailed findings and interpretations on altered cortical network topology in PMG related to abnormal cortical structure and brain function, and shows the potential for an individualized method to characterize network properties and alterations in connections that are associated with malformations of cortical development.
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Pain is a multidimensional experience emerging from the flow of information between multiple brain regions. A growing body of evidence suggests that pathological pain causes plastic changes of various brain regions. Here, we hypothesized that the induction of neuropathic pain alters distributed patterns of the resting-state brain activity in animal models, and capturing the altered pattern would enable identification of neuropathic pain at the individual level. ⋯ In contrast, predictive regions with decreased metabolism were observed in widespread cortical areas including secondary somatosensory cortex (S2), occipital cortex (OC), temporal cortex (TC), retrosplenial cortex (RSC), and the cerebellum (CBL). We also applied the univariate approach and obtained reduced prediction performance compared to MVPA. Our results suggest that developing neuroimaging-based diagnostic tools for pathological pain can be achieved by considering patterns of the resting-state brain activity.
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The magnetic susceptibility of tissue within and around an image voxel affects the magnetic field and thus the local frequency in that voxel. Recently, it has been shown that spatial maps of frequency can be used to quantify local susceptibility if the contributions of surrounding tissue can be deconvolved. Currently, such quantitative susceptibility mapping (QSM) methods employ gradient recalled echo (GRE) imaging to measure spatial differences in the signal phase evolution as a function of echo time, from which frequencies can be deduced. ⋯ WASSR uses direct saturation of water protons as a function of frequency irradiation offset to generate frequency maps without phase wraps, which can be combined with any image or spectroscopy acquisition. By utilizing a series of fast short-echo-time direct saturation images with multiple radiofrequency offsets, a frequency correction for field drift can be applied based on the individual image phases. Regions of interest were delineated with an automated atlas-based method, and the average magnetic susceptibilities calculated from frequency maps obtained from WASSR correlated well with those from the phase-based multi-echo GRE approach at 3T.