Connectivity Of Voxels Research Articles

A.2 Understanding Grit in healthy older adults at-risk for Alzheimer’s disease

Background: Adherence to healthy lifestyle behaviours or to prescribed medication requires perseverance with stamina, and this is captured by Grit, a non-cognitive trait defined as perseverance and passion for long-term goals. Despite predicting cognitive decline and physical, emotional, and social functioning, Grit remains poorly understood and its neural substrates are unknown in cognitive aging. Methods: Ninety-five cognitively unimpaired older adults with a family history of Alzheimer’s disease were recruited through the PREVENT-AD longitudinal cohort. Participants completed tests that assess grit and conscientiousness and underwent resting-state functional magnetic resonance imaging (fMRI). Multivariate pattern analyses (MVPA), a rigorous data-driven whole-brain approach, were used to examine if resting-state functional connectivity of connectome-wide voxels were associated with grit scores, controlling for age, sex, APOE ε4 carriership, mean displacement, and conscientiousness. Results: Our analyses identified two large (≥54 voxels) and statistically significant (p<0.01 corrected for family-wise error) clusters in the right ventrolateral prefrontal cortex and the left orbitofrontal cortex underlying grit. Conclusions: Being the first to identify functional neural correlates supporting grit in the aging population while accounting for the variance of conscientiousness, our study provides unique insights into the construct which has important applications in adherence to clinical and empirical neurological interventions as well as in successful aging.

2 Intentionality of Self-Generated Thought: Contributions of Mind Wandering to Creativity

Objective:Studies suggest that internally oriented cognitive processes are central to creativity. Here, we distinguish between intentional and unintentional forms of mind wandering and explore their component contributions to creativity. Furthermore, we describe resting-state connectivity profiles associated with these trait-level measures of mind wandering. Bearing in mind the role of the DMN in internally directed cognitive processes, we hypothesize that, in general, mind wandering will be associated with increased connectivity of voxels in the medial prefrontal and posterior cingulate cortices, key nodes in the DMN. We further hypothesize that intentional and unintentional mind wandering will be associated with distinct patterns of connectivity across DMN core regions.Participants and Methods:We used a sample of 155 healthy adults from the mind-brain-body dataset, all of whom completed resting-state fMRI scans and trait-level measures of mind wandering. We analyzed intentional and unintentional mind wandering tendencies using self-report measures. Next, we explored the relationship between mind wandering tendencies and creativity, as measured by a divergent thinking task. Additionally, we describe patterns of resting-state network connectivity associated with mind wandering, using graph theory (weighted degree) functional connectivity analysis.Results:At the behavioral level, results showed a significant positive association between creativity and both intentional and unintentional mind wandering. Neuroimaging analysis revealed higher weighted degree connectivity associated with both forms of mind wandering, implicating core regions of the default network and the left temporal pole. We observed topological connectivity differences within the default network: intentional mind wandering was associated with degree connectivity in posterior regions, whereas unintentional mind wandering showed greater involvement of prefrontal areas.Conclusions:In this study, we highlight patterns of resting-state network connectivity associated with intentional and unintentional mind wandering, and provide novel evidence of a link between mind wandering and creativity. These findings represent a promising step towards understanding the neurocognitive mechanisms that underlie productive mind wandering and demonstrate its relevance for the study of creative thinking.

A voxel-based three-dimensional framework for flash drought identification in space and time

Flash drought (FD) is an extreme event causing severe impacts on ecosystems and agriculture due to its fast velocity of evolution and high frequency. Here, we develop a voxel-based three-dimensional FD (V3DFD) method to track the spatio-temporal dynamics of FD based on the soil moisture (SM) decline method proposed by Yuan et al. (2019). The key idea of V3DFD is that FD is identified in terms of the connectivity of drought voxels (i.e., cubes with width, length and height representing latitude, longitude and time, respectively) in 3D space instead of directly forming the drought events by merging drought clusters. The V3DFD is systematically evaluated and compared with the commonly used 3D severity-area-duration (SAD) method in four provinces in China: Guangdong (GD), Guangxi (GX), Guizhou (GZ), and Yunnan (YN). Results show that V3DFD can better reflect the dynamic development and recovery of FD events compared with SAD. Regional analyses indicate that FD occurs more frequent with a larger intensity and longer duration in GD and GX than YN and GZ. The onset (terminal) of FD in YN occurs mostly in April-May (April-June). The onset of FD in GX and GD is scattered at the intra-annual scale, but the terminal occurs mostly in November. In addition, the first FD event in a year is mostly located during April-May in YN and GZ, while the last FD event of a year occurs mostly during October-November in GX and GD.

Structural connectivity predicts functional activation during lexical and sublexical reading

A critical question in neuroscience is the extent to which structural connectivity of the brain predicts localization of brain function. Recent research has suggested that anatomical connectivity can predict functional magnetic resonance imaging (fMRI) responses in several cognitive domains, including face, object, scene, and body processing, and development of word recognition skills (Osher et al., 2016; Saygin et al., 2016). However, this technique has not yet been extended to skilled word reading. Thus, we developed a computational model that relates anatomical connectivity (measured using probabilistic tractography) of individual cortical voxels to fMRI responses of the same voxels during lexical and sublexical reading tasks. Our results showed that the model built from structural connectivity was able to accurately predict functional responses of individual subjects based on their structural connectivity alone. This finding was apparent across the cortex, as well as to specific regions of interest associated with reading, language, and spatial attention. Further, we identified the structural connectivity networks associated with different aspects of skilled reading using connectivity analyses, and showed that interconnectivity between left hemisphere language and right hemisphere attentional areas underlies both lexical and sublexical reading. This work has important implications for understanding how structural connectivity contributes to reading and suggests that there is a relationship between skilled reading and neuroanatomical brain connectivity that future research should continue to explore.

Comprehensive quantification of Ni–Gd0.1Ce0.9O1.95 anode functional layer microstructures by three-dimensional reconstruction using a FIB/SEM dual beam system

The Microstructure of Ni–GDC anode functional layers (AFLs) for lower temperature solid oxide fuel cells (SOFCs) were investigated. AFLs with various Ni–GDC compositions (50–80 wt% NiO in AFL before reduction) were quantified by a 3D reconstruction technique using a focused ion beam (FIB)/scanning electron microscope (SEM) dual beam system. Each AFL sample was sectioned into 150 slices with 60 nm intervals. Amira software allowed for alignment, segmentation, and reconstruction of the 2D SEM images into a 3D image. From these reconstructions, volume fractions, effective particle size, phase gradient, and surface area for Ni, GDC, and pore phases were quantified. The estimated phase volume fraction was well matched with the theoretical value. The optimal effective particle size and highest surface area was observed at 49 vol% Ni AFL. The active triple phase boundaries were calculated based on the connectivity of voxels for each phase. The highest TPB density was also achieved at 49 vol% Ni AFL which is a 1:1 volume ratio of Ni to GDC phase. The TPB density shows an inverse proportionality to the electrode ASR measured from SOFC operation.

Investigating the Relationship between Body Weight and Brain Connectivity using Diffusion Tensor Imaging

Alkan A 2008. Diffusion-weighted imaging features of brain in obesity. Magnetic Resonance Imaging, vol. 26, no. 4, pp. 446-450. Anwander A 2007. Connectivity-based parcellation of Broca's area. Cerebral Cortex, vol. 17, no. 4, pp. 816-825.Haltia LT 2007. Brain white matter expansion in human obesity and the recovering effect of dieting. Journal of Clinical Endocrinology and Metabolism, vol. 92, no. 8, pp. 3278-3284. Jenkinson P 2002. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage, vol. 17, no. 2, pp. 825-841. Lohmann G 2001. Lipsia A new software system for the evaluation of functional magnetic resonance images of the human brain. Computerized Medical Imaging and Graphics, vol. 25, no. 6, pp. 449-457.Smith SM 2006. Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. NeuroImage, vol. 31, no. 4, pp. 1487-1505. Thirion J-P 1998. Image matching as a diffusion process: an analogy with Maxwell's demons, Medical Image Analysis. vol. 2, no. 3, pp. 243-260. Connectivity of voxels related to the negative BMI/FA-correlation overlaid onto a shrunken brain surface (based on a representative individual subject). The tractography indicates that the detected areas in the corpus callosum project to cortical regions in the frontal lobe. Voxel-wise GLM analysis of the FA values. The red dots show the fitted parameters for the factor BMI. There is a negative correlation between FA and BMI (adjusted for subject's age and gender) in anterior regions of the corpus callosum. TBSS analysis of FA maps of 53 subjects with a BMI between 18.9 and 50.7. The results (color-coded in red/yellow) show the negative correlation between BMI and FA (p<0.05 corrected for multiple comparisons). Thus, the greater the BMI, the smaller the FA in anterior regions of the corpus callosum.

Differential functional connectivity of prefrontal and medial temporal cortices during episodic memory retrieval

Some theories of brain function emphasize the interactions between brain areas as the major determinant of cognitive and behavioral operations. We explored such interactions in a PET study of episodic memory retrieval having three retrieval conditions, with differing levels of retrieval success. Functional connectivity of voxels located within Brodmann areas 10 and 45/47 in the right prefrontal cortex (RPFC) and the left hippocampus (LGH) with the rest of the brain was estimated using partial least squares. Area 10 and LGH showed an opposite pattern of functional connectivity, with a large expanse of bilateral limbic cortices that was equivalent in all tasks. However, during high retrieval, area 45/47 was included in this pattern. The results suggest that activity in portions of the RPFC reflects either memory retrieval mode or retrieval success, depending on other brain regions to which it is functionally linked.

Optimization of factors affecting the state of normality of a medical image

The purpose of this paper is to examine the first stage of the diagnostic process in medical imaging, namely determination of the state of normality, and to attempt to optimize factors contributing to this stage. An image of a given type is defined as abnormal if it does not belong to the appropriate class of normal images. All images must be pre-processed involving image registration and normalization to align and scale the images with respect to each other. Normal ranges may be determined for each voxel (or other appropriate region) from a representative normal sample using univariate analysis, obtaining mean and standard deviation images, or multivariate analysis, which accounts also for normal patterns of variation (represented as principal components). For a new image, the variation from normality (in SDs) for each region may be determined. Since the spatial distribution of this parameter is thought to be relevant, connectivity of abnormal voxels was considered as a possible factor. For the purposes of this study, SPECT images indicating regional cerebral blood flow were used. Images from 50 normal subjects formed the normal sample. A further 40 normal subjects and 200 patients referred with suspected dementia were then analysed using the normal ranges. ROC analysis, using number of SDs as a variable threshold, was used to optimize the factors. Normalization to global values followed by multivariate analysis using four or five principal components provided optimal discrimination. Connectivity of voxels emerged as an important factor, around 10 connected voxels being optimal for this study