NeuroImage
-
Anticorrelated relationships in spontaneous signal fluctuation have been previously observed in resting-state functional magnetic resonance imaging (fMRI). In particular, it was proposed that there exists two systems in the brain that are intrinsically organized into anticorrelated networks, the default mode network, which usually exhibits task-related deactivations, and the task-positive network, which usually exhibits task-related activations during tasks that demands external attention. However, it is currently under debate whether the anticorrelations observed in resting state fMRI were valid or were instead artificially introduced by global signal regression, a common preprocessing technique to remove physiological and other noise in resting-state fMRI signal. ⋯ Specificity of the anticorrelations was similar between the two methods. Specificity and sensitivity for positive correlations were higher under CompCor compared to the global regression method. Our results suggest that anticorrelations observed in resting-state connectivity are not an artifact introduced by global signal regression and might have biological origins, and that the CompCor method can be used to examine valid anticorrelations during rest.
-
Characterizing the brain connectome using neuroimaging data and measures derived from graph theory emerged as a new approach that has been applied to brain maturation, cognitive function and neuropsychiatric disorders. For a broad application of this method especially for clinical populations and longitudinal studies, the reliability of this approach and its robustness to confounding factors need to be explored. Here we investigated test-retest reliability of graph metrics of functional networks derived from functional magnetic resonance imaging (fMRI) recorded in 33 healthy subjects during rest. ⋯ Methodologically, the use of a broader frequency band (0.008-0.15 Hz) yielded highest reliability indices (mean ICC=0.484), followed by the use of global regression (mean ICC=0.399). In general, the second order metrics (small-worldness, hierarchy, assortativity) studied here, tended to be more robust than first order metrics. In conclusion, our study provides methodological recommendations which allow the computation of sufficiently robust markers of network organization using graph metrics derived from fMRI data at rest.
-
This study investigated whether diffusion tensor imaging (DTI) could identify potential abnormalities in type 2 diabetes mellitus (T2DM) patients without cognitive complaints compared to healthy controls. In addition, the existence of associations between diffusion measures and clinical parameters was examined. Forty T2DM patients and 97 non-diabetic controls completed a clinical and biochemistry examination. ⋯ For the T2DM patients, however, the MD of the brain parenchyma was significantly increased compared to controls and was positively correlated with disease duration. The voxel based analyses revealed (i) a significantly decreased FA in the bilateral frontal WM compared to controls which was mainly caused by an increased TD and not a decreased AD within these regions; (ii) a significant association between disease duration and microstructural properties in several brain regions including bilateral cerebellum, temporal lobe WM, right caudate, bilateral cingulate gyrus, pons, and parahippocampal gyrus. Our findings indicate that microstructural WM abnormalities and associations with clinical measurements can be detected with DTI in T2DM patients.
-
Anatomical, clinical and imaging findings suggest that the cerebellum is engaged in cognitive and affective functions as well as motor control. Evidence from converging modalities also indicates that there is a functional topography in the human cerebellum for overt control of movement vs. higher functions, such that the cerebellum can be divided into zones depending on connectivity with sensorimotor vs. multimodal association cortices. Using functional MRI, we show that regions active during overt movement differ from those involved in higher-level language, spatial processing and working memory tasks. ⋯ The cerebellar functional topography identified in this study reflects the involvement of different cerebro-cerebellar circuits depending on the demands of the task being performed: overt movement activated sensorimotor cortices along with contralateral cerebellar lobules IV-V and VIII, whereas more cognitively demanding tasks engaged prefrontal and parietal cortices along with cerebellar lobules VI and VII. These findings provide further support for a cerebellar role in both motor and cognitive tasks, and better establish the existence of functional subregions in the cerebellum. Future studies are needed to determine the exact contribution of the cerebellum - and different cerebro-cerebellar circuits - to task performance.
-
Gradient-echo MRI has revealed anisotropic magnetic susceptibility in the brain white matter. This magnetic susceptibility anisotropy can be measured and characterized with susceptibility tensor imaging (STI). In this study, a method of fiber tractography based on STI is proposed and demonstrated in the mouse brain. ⋯ The relationship between STI and DTI fiber tracts was explored with similarities and differences identified. It is anticipated that the proposed method of STI tractography may provide a new way to study white matter fiber architecture. As STI tractography is based on physical principles that are fundamentally different from DTI, it may also be valuable for the ongoing validation of DTI tractography.