Keywords: Aging, Aging, parcellation

Motivation: The human brain undergoes a remarkable development from newborn to adulthood in cortex, white matter, and connectivity in previous studies. We speculated connectivity-based cortical parcellation may also change during this process.

Goal(s): To explore whether and how connectivity-based parcellations of different cortices changed from neonate to adult.

Approach: We utilized diffusion MRI (dMRI) to investigate the structure connectivity-based parcellations of cortical sub-regions and compared the parcellation-related features among infants, toddlers, and adults. 

Results: We observed significantly altered parcellation profiles and changing connectivity patterns during developed. Especially, we found larger alternations in high-order cortex, such as insula, compared to primary sensory and motor cortices.

Impact: Connectivity-based parcellation provided a new insight to assess the development of human brain. Primary cortex has developed sufficiently in early life while high-order cortex developed significantly from newborn to adult. Future studies will fill the gap from toddler to adult.

Keywords: Structural Connectivity, Brain Connectivity, Adolescents

Motivation: Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear.

Goal(s): We aim to model how the maturational pattern of cortical morphology is shaped by white matter connectome architecture.

Approach: We integrated neuroimaging, connectome,  transcriptome analyses and computational modeling.

Results: We found that the maturational patterns of cortical morphology are constrained by the white matter connectome and are particularly represented using a network-based diffusion model. Such constraints are predominantly located in frontoparietal nodes and are linked with the expression of genes associated with microstructural developmental processes.

Impact: Our results highlight the importance of white matter network structure in shaping the coordinated maturation of regional cortical morphology, which demonstrates the feasibility of using a network model to reveal the maturational principle of cortical morphology from childhood to adolescence.

Keywords: Aging, Aging, Human Connectome Project, choroid plexus

Motivation: Analyzing ChP changes in normal aging is essential for grasping its role in neurological disorders.
 

Goal(s): To evaluate ChP changes with age using diffusion and perfusion MRI in a lifespan HCP-aging dataset.  
 

Approach: MR images of 641 healthy participants aged from 36 to 90 years old were analyzed to extract diffusion and perfusion measurements of ChP to investigate their age-related changes.
 

Results: With age, the ChP undergoes significant changes, including increased volume, reduced blood flow, elevated MD values, and a more rapid decline in blood flow compared to gray and white matter.

Impact: This study offers a comprehensive evaluation of age-related changes in the ChP, enhancing our comprehension of its potential involvement in age-related cognitive decline. Furthermore, age-related ChP alterations exhibit distinct patterns compared to changes in gray and white matter.   

Keywords: Spectroscopy, Data Analysis, Macromolecules, LCModel, ultra-high field

Motivation: Macromolecular signals mainly originate from amino-acids within flexible cytosolic proteins, contributing to ¹H-MR spectra. Previous studies have yielded inconsistent results regarding age-related differences in macromolecular resonances.

Goal(s): To investigate the macromolecular content across a wide age range in a large cohort of healthy participants.

Approach: Spectroscopy data were acquired at 7 T. The macromolecular content was investigated in 134 datasets from a cohort ranging in age from 19 to 89 years.

Results: Age-related effects were observed for macromolecular peaks. Some macromolecular resonances had significantly higher content at 30-40 years of age while others at 60-70 years of age.

Impact: Our findings strengthen the necessity of using age-matched measured macromolecules during quantification of metabolite concentrations. The ability to detect differences in macromolecular content may be helpful for understanding the neurodegenerative processes associated with aging.

Keywords: Aging, Aging, Brain Age, Volumetry, White Matter Hyperintensity

Motivation: In an aging population, a subset of individuals at any age group present with low white matter hyperintensity (WMH) volume in the brain, while another subset has intermediate to high WMH load.

Goal(s): To establish a Brain Age Estimation model involving WMH lesion quantification as a clinical indicator of Brain Health.

Approach:  We have investigated the ‘Brain Health’ in terms of Brain Age using neuroanatomic volume, thickness together with WMH load across cognitively normal, impaired and Alzheimer’s Disease subjects.
 

Results: An increased Brain Age gap is observed for the subjects with elevated WMH load compared to the brains with low WMH.

Impact: Brain health is a composite representation of structural, fiber and vascular health. For the first time, a MR based quantitative platform with WMH load and comprehensive neuroanatomic volumetry is established, which estimates ‘Brain Age’ as an indicator of Brain Health.

Keywords: White Matter, Diffusion Tensor Imaging

Motivation: It is currently difficult to compute normative models for diffusion MRI metrics of the brain’s white matter across the lifespan due to scanner/protocol effects that are hard to eliminate during harmonization.

Goal(s): We set out to build large-scale multi-site normative models for DTI metrics of the white matter of the human brain. 

Approach: Hierarchical Bayesian Regression was run on ROI metrics derived using the ENIGMA-DTI protocol to determine the age trajectory and centile curves of DTI metrics.

Results: We built DTI reference models based on 52,719 subjects that allowed us to detect deviations from the norm for patients with brain diseases.

Impact: These reference models are valuable for detecting microstructural deviations from the normal range, while modeling scanner, protocol and cohort effects. They will be used in our ENIGMA consortium to map profiles of microstructural anomalies in >20 neurological and psychiatric conditions.

Keywords: Aging, Quantitative Susceptibility mapping, Heart, Brain, women, INOCA, Aging, Dementia

Motivation: The study's motivation lies in overcoming the low-resolution limitations of Quantitative susceptibility mapping (QSM) in 3T-MRI, which is critical for investigating brain aging and neurodegeneration.

Goal(s): We aimed to construct high-resolution QSM using submillimeter T2*-3D-EPI sequence to measure iron deposition in the cortical and deep gray matter of women with suspected coronary microvascular dysfunction.

Approach: The approach involved a novel imaging protocol, TGV-based QSM reconstruction, and statistical analysis correlating iron deposition with cardiovascular health markers.

Results: Results indicate a significant association between brain iron accumulation and microvascular heart conditions, pointing to a potential interconnected pathology in women with suspected coronary microvascular dysfunction.

Impact: The study's high-resolution QSM technique could revolutionize neuroimaging, allowing clinicians to detect microvascular changes early and personalize treatments. It opens avenues for exploring the systemic nature of microvascular diseases, potentially altering approaches to managing neurodegenerative and cardiovascular conditions.

Keywords: Functional Connectivity, Aging

Motivation: The healthy aging brain exhibits functional dedifferentiation, yet a consensus on its characterization remains elusive, hindering individual-level assessment of unhealthy aging.

Goal(s): We aim to utilize the functional hierarchical axis to elucidate primary alterations in functional dedifferentiation during healthy aging.

Approach: We developed a measure to quantify the heterogeneity of network dedifferentiation along the functional hierarchical axis, and assessed its relevance to cognition and neurological diseases at an individual level. 

Results: Functional dedifferentiation in attention and control networks captures substantial individual differences in aging, cognition, and diseases. The heterogeneity of functional dedifferentiation along the functional hierarchical axis predicts domain-specific disease risk. 

Impact: Brain aging primarily entails association and control network integrity deterioration on the functional hierarchical axis. The individual differences of functional dedifferentiation on this axis provide risk assessments of unhealthy brain aging.

Keywords: Dementia, Blood vessels, Arteriolosclerosis, Brain, Pathology, Ex-vivo applications, Gray matter, Neurodegeneration, Vascular

Motivation: Despite brain arteriolosclerosis being one of the most prevalent small vessel diseases in older adults, its association with regional brain volumes has not been investigated.

Goal(s): To investigate the association of brain arteriolosclerosis with regional gray matter volumes.

Approach: Regional brain volumetry on ex-vivo MRI and detailed neuropathological examination were combined in a large number of community-based older adults that came to autopsy.

Results: More severe brain arteriolosclerosis was associated with lower volume in a number of gray matter regions, including medial orbitofrontal, superior frontal, pericalcarine, cuneus, and lateral occipital areas, independently of the effects of other neuropathologies.

Impact: The finding that brain arteriolosclerosis is associated with lower regional gray matter volumes independently of the effects of other neuropathologies enhances our understanding of the brain anomalies associated with this common small vessel disease pathology.

Keywords: Parkinson's Disease, Parkinson's Disease

Motivation: Aging has been widely recognized as the primary risk factor for brain degeneration, and Parkinson’s disease (PD) tends to follow accelerated aging trajectories. 

Goal(s): The aim of this study was to investigate the influence of structural brain aging on large-scale functional network temporal dynamics in PD.

Approach: The level of brain aging was assessed by calculating global and local brain age gap estimates from T1-weighted images. Coactivation patterns of the whole brain were identified from fMRI to capture neural network activity.

Results: Accelerated structural brain aging in PD affected brain function, which manifested as aberrant brain network dynamics.

Impact: These findings relate whole-brain coactivation patterns to spatial variation in accelerated brain aging, providing insights into the neuropathological mechanisms in neurodegenerative diseases and implying the possibility of intervention for PD progression by slowing the brain aging process.