Brain network analyses of diffusion tensor imaging for brain aging

Progressive Voxel-Wise Homotopic Connectivity from childhood to adulthood: Age-related functional asymmetry in resting-state functional magnetic resonance imaging

Homotopic connectivity during resting state has been proposed as a risk marker for neurologic and psychiatric conditions, but a precise characterization of its trajectory through development is currently lacking. Voxel-Mirrored Homotopic Connectivity (VMHC) was evaluated in a sample of 85 neurotypical individuals aged 7-18 years. VMHC associations with age, handedness, sex, and motion were explored at the voxel-wise level. VMHC correlates were also explored within 14 functional networks. Primary and secondary outcomes were repeated in a sample of 107 adults aged 21-50 years. In adults, VMHC was negatively correlated with age only in the posterior insula (false discovery rate p < .05, >30-voxel clusters), while a distributed effect among the medial axis was observed in minors. Four out of 14 considered networks showed significant negative correlations between VMHC and age in minors (basal ganglia r = -.280, p = .010; anterior salience r = -.245, p = .024; language r = -.222, p = .041; primary visual r = -.257, p = .017), but not adults. In minors, a positive effect of motion on VMHC was observed only in the putamen. Sex did not significantly influence age effects on VMHC. The current study showed a specific decrease in VMHC for minors as a function of age, but not adults, supporting the notion that interhemispheric interactions can shape late neurodevelopment.

Graph Transformer Geometric Learning of Brain Networks Using Multimodal MR Images for Brain Age Estimation

Brain age is considered as an important biomarker for detecting aging-related diseases such as Alzheimer's Disease (AD). Magnetic resonance imaging (MRI) have been widely investigated with deep neural networks for brain age estimation. However, most existing methods cannot make full use of multimodal MRIs due to the difference in data structure. In this paper, we propose a graph transformer geometric learning framework to model the multimodal brain network constructed by structural MRI (sMRI) and diffusion tensor imaging (DTI) for brain age estimation. First, we build a two-stream convolutional autoencoder to learn the latent representations for each imaging modality. The brain template with prior knowledge is utilized to calculate the features from the regions of interest (ROIs). Then, a multi-level construction of the brain network is proposed to establish the hybrid ROI connections in space, feature and modality. Next, a graph transformer network is proposed to model the cross-modal interaction and fusion by geometric learning for brain age estimation. Finally, the difference between the estimated age and the chronological age is used as an important biomarker for AD diagnosis. Our method is evaluated with the sMRI and DTI data from UK Biobank and Alzheimer's Disease Neuroimaging Initiative database. Experimental results demonstrate that our method has achieved promising performances for brain age estimation and AD diagnosis.

Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients

Introduction

Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data.

Methods

The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed.

Results

Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength.

Discussion

Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.

The effect of hyperbaric oxygen therapy on cognition, performance, proteomics, and telomere length—The difference between zero and one: A case report

Introduction

Hyperbaric oxygen (HBO2) therapy has recently been suggested for the treatment of different brain injuries as well as for physical and cognitive enhancement. The author recently carried out a self-experiment to obtain objective information on the effects of HBO2 therapy on neurocognition, cardiopulmonary function, neuroimaging and its effect on novel biomarkers such as telomere length and proteomics. In the following case report, the author will present and discuss the results and the differences between zero and one.

Methods

This is a personal case report on a single subject, myself, who underwent a protocol of 60 daily HBO2 therapy sessions within 3 months. Pre- and post-therapy objective evaluation measured included computerized cognitive assessment, brain imaging, cardiopulmonary exercise test, physical assessments and blood tests including telomere length and proteomics.

Results

Neurocognitive results showed a 3.1–3.8% improvements in global cognitive function as well as all other cognitive function domains. In the perfusion MRI, there was a relative increase ranging from 43.3 to 52.3% in cerebral perfusion in various areas subserving memory, coordination, and visual motor cortex function. Similar improvements in cerebral perfusion were seen in the SPECT scans, which ranged from 8.79 to 16.12% increased perfusion in the temporal pole and entorhinal cortex subserving memory, as well as in the subcallosal area and lingual gyrus. MRI-DTI showed prominent increases in fractional anisotropy in several white matter areas including 9% in the body of the corpus callosum, 16.85% in for the fornix and 22.06% in the tapetum. In the physical domains, there were improvements in both anaerobic threshold, exercise endurance, muscle strength, gait speed and grip strength in the 7–15% range. The telomeres length was doubled and clusters of inflammatory proteins dropped around the 40th session and remained low at the 60th session.

Conclusion

The difference between zero and one in this single case study of HBO2 therapy confirmed improvement in objective biomarkers which measured cognition, memory, brain processing speed, athletic performance and neuroimaging modalities measuring cerebral perfusion, blood flow and tractography. Additional studies with larger sample size and randomized clinical trials using similar biomarkers are needed to confirm the results and to delineate the longevity of these improvements.