Disrupted White Matter Functional Connectivity With the Cerebral Cortex in Migraine Patients

Background: In attempts to understand the migraine patients’ overall brain functional architecture, blood oxygenation level-dependent (BOLD) signals in the white matter (WM) and gray matter (GM) were considered in the current study. Migraine, a severe and multiphasic brain condition, is characterized by recurrent attacks of headaches. BOLD fluctuations in a resting state exhibit similar temporal and spectral profiles in both WM and GM. It is feasible to explore the functional interactions between WM tracts and GM regions in migraine.Methods: Forty-eight migraineurs without aura (MWoA) and 48 healthy controls underwent resting-state functional magnetic resonance imaging. Pearson’s correlations between the mean time courses of 48 white matter (WM) bundles and 82 gray matter (GM) regions were computed for each subject. Two-sample t-tests were performed on the Pearson’s correlation coefficients (CC) to compare the differences between the MWoA and healthy controls in the GM-averaged CC of each bundle and the WM-averaged CC of each GM region.Results: The MWoAs exhibited an overall decreased average temporal CC between BOLD signals in 82 GM regions and 48 WM bundles compared with healthy controls, while little was increased. In particular, WM bundles such as left anterior corona radiata, left external capsule and bilateral superior longitudinal fasciculus had significantly decreased mean CCs with GM in MWoA. On the other hand, 16 GM regions had significantly decreased mean CCs with WM in MWoA, including some areas that are parts of the somatosensory regions, auditory cortex, temporal areas, frontal areas, cingulate cortex, and parietal cortex.Conclusion: Decreased functional connections between WM bundles and GM regions might contribute to disrupted functional connectivity between the parts of the pain processing pathway in MWoAs, which indicated that functional and connectivity abnormalities in cortical regions may not be limited to GM regions but are instead associated with functional abnormalities in WM tracts.

Heterogeneity in PFC-amygdala connectivity in middle childhood, and concurrent interrelations with inhibitory control and anxiety symptomology.

The prefrontal cortex (PFC) is a key brain area in considering adaptive regulatory behaviors. This includes regulatory projections to regions of the limbic system such as the amygdala, where the nature of functional connections may confer lower risk for anxiety disorders. The PFC is also associated with behaviors like executive functioning. Inhibitory control is a behavior encompassed by executive functioning, and is generally viewed favorably for adaptive socioemotional development. Yet, some research suggests that high levels of inhibitory control may actually be a risk factor for some maladaptive developmental outcomes, like anxiety disorders. In a sample of 51 children ranging from 7-9 years old, we examined resting state functional connectivity between regions of the PFC and the amygdala. We used Subgrouping Group Iterative Multiple Model Estimation (S-GIMME) to identify and characterize data-driven subgroups of individuals with similar networks of connectivity between these brain regions. Generated subgroups were collapsed into children characterized by the presence or absence of recovered connections between the PFC and amygdala. We then tested whether inhibitory control, as measured by a stop signal task, moderated the relation between these subgroups and child-reported anxiety symptoms. We found an inverse relation between stop-signal reaction times and reported count of anxiety symptoms when controlling for connectivity group, suggesting that greater inhibitory control was actually related to greater anxiety symptoms, but only when accounting for patterns of PFC-amygdala connectivity. These data suggest that there is a great deal of heterogeneity in the nature of functional connections between the PFC and amygdala during this stage of development. The findings also provide support for the notion of high levels of inhibitory control as a risk factor for anxiety, but trait-level biopsychosocial factors may be important to consider in assessing the nature of risk.

Age-associated network controllability changes in first episode drug-naïve schizophrenia

Background Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain’s structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. Methods Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. Results Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. Conclusions By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.

Aberrant Resting-State Functional Connectivity of the Dorsal Attention Network in Tinnitus

Previous functional magnetic resonance imaging (fMRI) analyses have shown that the dorsal attention network (DAN) is involved in the pathophysiological changes of tinnitus, but few relevant studies have been conducted, and the conclusions to date are not uniform. The purpose of this research was to test whether there is a change in intrinsic functional connectivity (FC) patterns between the DAN and other brain regions in tinnitus patients. Thirty-one patients with persistent tinnitus and thirty-three healthy controls were enrolled in this study. A group independent component analysis (ICA), degree centrality (DC) analysis, and seed-based FC analysis were conducted. In the group ICA, the tinnitus patients showed increased connectivity in the left superior parietal gyrus in the DAN compared to the healthy controls. Compared with the healthy controls, the tinnitus patients showed increased DC in the left inferior parietal gyrus and decreased DC in the left precuneus within the DAN. The clusters within the DAN with significant differences in the ICA or DC analysis between the tinnitus patients and the healthy controls were selected as regions of interest (ROIs) for seeds. The tinnitus patients exhibited significantly increased FC from the left superior parietal gyrus to several brain regions, including the left inferior parietal gyrus, the left superior marginal gyrus, and the right superior frontal gyrus, and decreased FC to the right anterior cingulate cortex. The tinnitus patients exhibited decreased FC from the left precuneus to the left inferior occipital gyrus, left calcarine cortex, and left superior frontal gyrus compared with the healthy controls. The findings of this study show that compared with healthy controls, tinnitus patients have altered functional connections not only within the DAN but also between the DAN and other brain regions. These results suggest that it may be possible to improve the disturbance and influence of tinnitus by regulating the DAN.

Profiling of a shaped worm cutter for shaping gears with non-involute tooth profile

Of the mechanical transmissions used in mechanical engineering, the most common are gears with an involute profile of the teeth flanks. Gears made up of such wheels have a number of advantages, but they also have a number of significant disadvantages. Therefore jne of the current trends is the study of gears with a complex non-involute profile of the teeth flank which have advantages over involute gears in a number of applications, as well as the development of tools for their processing. There are two ways of gear teeth cutting: the copying method and the rolling-in method. The rolling-in method has advantages. The profile of the tool working by the rolling-in method does not depend on the number of teeth of the gear being cut, therefore, the same tool can be used to cut gears with any number of teeth. The accuracy of a gear made by the rolling-in method is significantly higher than the accuracy of a gear made by the copying method. This is primarily due to the continuity of the rolling-in process. When cutting teeth by the rolling method, the tooth surface is formed as a result of processing with a tool, the cutting edges of which are the tooth profile of the mating rack or the tooth profile of the mating gear, and during processing the tool and the workpiece form a mating gear pair. The most common gear cutting tool is the hob cutter. For the machining of gear wheels with a non-involute tooth profile widely used in industry equipment is used. One of the options for a rolling gear cutting tool for shaping gear wheels with a non-involute tooth profile can be a shaped worm cutter. The article describes the method of profiling of the cutting part of shaped hob cutter for machining of gear wheels with normal accuracy. To solve the problem the unified mathematical base – the apparatus of multiparameter mappings of space – the unified structure of mappings for gears and a compact set of unified operators, parameters and functional connections is used.

Association between aerobic fitness and the functional connectome in patients with schizophrenia

Schizophrenia is accompanied by widespread alterations in static functional connectivity associated with symptom severity and cognitive deficits. Improvements in aerobic fitness have been demonstrated to ameliorate symptomatology and cognition in people with schizophrenia, but the intermediary role of macroscale connectivity patterns remains unknown. Therefore, we aim to explore the relation between aerobic fitness and the functional connectome in individuals with schizophrenia. Further, we investigate clinical and cognitive relevance of the identified fitness-connectivity links. 58 patients with schizophrenia were included in the resting-state fMRI analysis. Multilevel Bayesian partial correlations between aerobic fitness and functional connections across the whole brain as well as between static functional connectivity patterns and clinical and cognitive outcome were performed. Preliminary causal inferences were enabled based on a mediation analysis. Static functional connectivity between the subcortical nuclei and the cerebellum as well as between temporal seeds mediated the attenuating impact of aerobic fitness on total symptom severity. Functional connections between cerebellar seeds affected the positive link between aerobic fitness and global cognition, while the functional interplay between central and limbic seeds drove the beneficial relation between aerobic fitness and emotion recognition. The current study provides first insights into the interactions between aerobic fitness, the functional connectome and clinical and cognitive outcome in people with schizophrenia, but results have to be interpreted carefully. Further interventional aerobic exercise studies are needed in order to replicate the current findings and to enable conclusive causal inferences.

Relating Global and Local Connectome Changes to Dementia and Targeted Gene Expression in Alzheimer's Disease

Networks are present in many aspects of our lives, and networks in neuroscience have recently gained much attention leading to novel representations of brain connectivity. The integration of neuroimaging characteristics and genetics data allows a better understanding of the effects of the gene expression on brain structural and functional connections. The current work uses whole-brain tractography in a longitudinal setting, and by measuring the brain structural connectivity changes studies the neurodegeneration of Alzheimer's disease. This is accomplished by examining the effect of targeted genetic risk factors on the most common local and global brain connectivity measures. Furthermore, we examined the extent to which Clinical Dementia Rating relates to brain connections longitudinally, as well as to gene expression. For instance, here we show that the expression of PLAU gene increases the change over time in betweenness centrality related to the fusiform gyrus. We also show that the betweenness centrality metric impact dementia-related changes in distinct brain regions. Our findings provide insights into the complex longitudinal interplay between genetics and brain characteristics and highlight the role of Alzheimer's genetic risk factors in the estimation of regional brain connectivity alterations.

Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes

Background: Following mild traumatic brain injury (mTBI) compromised white matter structural integrity can result in alterations in functional connectivity of large-scale brain networks and may manifest in functional deficit including cognitive dysfunction . Advanced magnetic resonance neuroimaging techniques, specifically diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI), have demonstrated an increased sensitivity for detecting microstructural changes associated with mTBI. Identification of novel imaging biomarkers can facilitate early detection of these changes for effective treatment. In this study, we hypothesize that feature selection combining both structural and functional connectivity increases classification accuracy. Methods: 16 subjects with mTBI and 20 healthy controls underwent both DTI and resting state functional imaging. Structural connectivity matrices were generated from white matter tractography from DTI sequences. Functional connectivity was measured through pairwise correlations of rs-fMRI between brain regions. Features from both DTI and rs-fMRI were selected by identifying five brain regions with the largest group differences and were used to classify the generated functional and structural connectivity matrices, respectively. Classification was performed using linear support vector machines and validated with leave-one-out cross validation. Results: Group comparisons revealed increased functional connectivity in the temporal lobe and cerebellum as well as decreased structural connectivity in the temporal lobe. After training on structural connections only, a maximum classification accuracy of 78% was achieved when structural connections were selected based on their corresponding functional connectivity group differences. After training on functional connections only, a maximum classification accuracy of 69% was achieved when functional connections were selected based on their structural connectivity group differences. After training on both structural and functional connections, a maximum classification accuracy of 69% was achieved when connections were selected based on their structural connectivity. Conclusions: Our multimodal approach to ROI selection achieves at highest, a classification accuracy of 78%. Our results also implicate the temporal lobe in the pathophysiology of mTBI. Our findings suggest that white matter tractography can serve as a robust biomarker for mTBI when used in tandem with resting state functional connectivity.

Connectome-wide association analysis identified significant brain functional alteration in adults with attention-deficit/hyperactivity disorder

Adults with attention-deficit/hyperactivity disorder (ADHD), as an extreme-phenotype of ADHD, is still facing problems of inconsistency and undeciphered mechanisms for its neuropathology. To address this matter, our present study performed connecotome-wide voxel-based analyses with the resting-state fMRI data of 84 adults with ADHD and 89 healthy controls. We found that functional connectivity patterns of the left precuneus and the left middle temporal significantly altered in ADHD populations serving as potential neural biomarkers to distinguish ADHD with healthy controls, with subsequent seed-based analysis revealing the dysfunction of functional connections both intra- and inter- default mode and attention networks, among which middle temporal gyrus plays the key role of bridge linking the default mode and attention networks. After cognitive behavioral therapy, two of these ADHD-altered functional connections ameliorated accompanied with improvement of ADHD core symptoms. Additionally, imaging genetic analyses also revealed close relationships between the observed brain functional alterations and ADHD-risk genes. Taken together, our findings suggested the interference of default mode on attention networks in adults with ADHD, which would be severing as a potential biomarker for both ADHD pathogenesis and treatment effects.