NeuroImage
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Review Meta Analysis
A meta-analysis of fMRI studies on Chinese orthographic, phonological, and semantic processing.
A growing body of neuroimaging evidence has shown that Chinese character processing recruits differential activation from alphabetic languages due to its unique linguistic features. As more investigations on Chinese character processing have recently become available, we applied a meta-analytic approach to summarize previous findings and examined the neural networks for orthographic, phonological, and semantic processing of Chinese characters independently. The activation likelihood estimation (ALE) method was used to analyze eight studies in the orthographic task category, eleven in the phonological and fifteen in the semantic task categories. ⋯ Functional dissociation was identified in the left inferior frontal gyrus, with the posterior dorsal part for phonological processing and the anterior ventral part for semantic processing. Moreover, bilateral involvement of the ventral occipito-temporal regions was found for both phonological and semantic processing. The results provide better understanding of the neural networks underlying Chinese orthographic, phonological, and semantic processing, and consolidate the findings of additional recruitment of the left middle frontal gyrus and the right fusiform gyrus for Chinese character processing as compared with the universal language network that has been based on alphabetic languages.
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Abnormalities of functional connectivity in the default mode network (DMN) recently have been reported in patients with amnestic mild cognitive impairment (aMCI), Alzheimer's disease (AD) or other psychiatric diseases. As such, these abnormalities may be epiphenomena instead of playing a causal role in AD progression. To date, few studies have investigated specific brain networks, which extend beyond the DMN involved in the early AD stages, especially in aMCI. ⋯ Furthermore, the disrupted intrinsic connectivity was associated with episodic memory (EM) deficits in the aMCI patients and not in the CN subjects. These findings demonstrated that the functional integration of the insula networks plays an important role in the EM process. They provided new insight into the neural mechanism underlying the memory deficits in aMCI patients.
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Resting state functional connectivity, which is defined as temporal correlation of spontaneous activity between diverse brain regions, has been reported to form resting state networks (RSNs), consisting of a specific set of brain regions, based on functional magnetic resonance imaging (fMRI). Recently, studies using near-infrared spectroscopy (NIRS) reported that NIRS signals also show temporal correlation between different brain regions. The local relationship between NIRS and fMRI signals has been examined by simultaneously recording these signals when participants perform tasks or respond to stimuli. ⋯ Finally, by calculating the correlation between NIRS signals at a channel and whole brain fMRI signals, we observed that NIRS signals correlate with fMRI signals not only within brain regions adjacent to NIRS channels but also within distant brain regions constituting RSNs, such as the dorsal attention, fronto-parietal control, and default mode networks. These results support the idea that NIRS signals obtained at several cortical regions during the resting state mainly reflect regional spontaneous hemodynamic fluctuations that originate from spontaneous cortical activity, and include information that characterizes the RSNs. Because NIRS is relatively easy to use and a less physically demanding neuroimaging technique, our findings should facilitate a broad application of this technique to examine RSNs, especially for clinical populations and conditions unsuitable for fMRI.
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In diffusion MRI, simultaneous multi-slice single-shot EPI acquisitions have the potential to increase the number of diffusion directions obtained per unit time, allowing more diffusion encoding in high angular resolution diffusion imaging (HARDI) acquisitions. Nonetheless, unaliasing simultaneously acquired, closely spaced slices with parallel imaging methods can be difficult, leading to high g-factor penalties (i.e., lower SNR). The CAIPIRINHA technique was developed to reduce the g-factor in simultaneous multi-slice acquisitions by introducing inter-slice image shifts and thus increase the distance between aliased voxels. ⋯ Here, we use pseudo-multiple replica SNR and bootstrapping metrics to assess the performance of the blipped-CAIPI method in 3× simultaneous multi-slice diffusion studies. Further, we introduce a novel image reconstruction method to reduce detrimental ghosting artifacts in these acquisitions. We show that data acquisition times for Q-ball and diffusion spectrum imaging (DSI) can be reduced 3-fold with a minor loss in SNR and with similar diffusion results compared to conventional acquisitions.
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Myelin water imaging, a magnetic resonance imaging technique capable of resolving the fraction of water molecules which are located between the layers of myelin, is a valuable tool for investigating both normal and pathological brain structure in vivo. There is a strong need for pulse sequences which improve the quality and applicability of myelin water imaging in a clinical setting. ⋯ Region of interest analysis indicates that this fast GRASE imaging sequence produces results which are in good agreement with pure spin echo measurements (R(2)=0.95, p<0.0001). This drastic improvement in speed and brain coverage compared to current spin echo standards will allow increased inclusion of myelin water imaging in neurological research protocols and opens up the possibility of applications in a clinical setting.