White matter microstructure and cognition in the Alzheimer’s Disease Connectome Project (ADCP).

Background: Alzheimer’s disease (AD) has been mainly thought of as a disease involving gray matter changes. However, despite known correlations between white matter integrity and cognition, less is known about how disruptions to white matter during the development of AD underpin cognitive impairment. This study tests the associations between disruptions to white matter along the AD clinical continuum (cognitive unimpaired (CU): cognitive impaired (CI) – Mild Cognitive Impairment (MCI) and AD) and cognition using diffusion tensor imaging (DTI) and multi‐tissue neurite and orientation dispersion and density imaging (mtNODDI) models of the multi‐shell connectome diffusion MRI (ms‐dMRI) data from the Alzheimer’s Disease Connectome Project (ADCP).

White matter integrity is lower in non‐amnestic than amnestic Alzheimer's disease and differs by clinical syndrome.

Background: Amnestic mild cognitive impairment and Alzheimer’s disease (aAD) exhibit degeneration of white matter (WM) tracts preceding overt cognitive decline. However, WM changes in non‐amnestic AD (naAD) are understudied. We hypothesized patterns of WM degeneration would differ between aAD and naAD.

The relationship between neighborhood disadvantage and the brain age gap.

Background: Accelerated aging is strongly linked to adverse social exposome and accelerated aging of the brain may be a dementia risk factor. Machine‐learning can estimate the biological “brain age” from neuroimages, which provides complementary information to the chronological/calendar age. The difference between biological and chronological age is referred to as the “brain age gap.

White matter integrity is lower in non‐amnestic than amnestic Alzheimer's disease and differs by clinical syndrome.

Background: Amnestic mild cognitive impairment and Alzheimer’s disease (aAD) exhibit degeneration of white matter (WM) tracts preceding overt cognitive decline. However, WM changes in non‐amnestic AD (naAD) are understudied. We hypothesized patterns of WM degeneration would differ between aAD and naAD.

MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI.

White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (DW-MRI) to qualitatively identify changes in white matter microstructure and connectivity. Yet, quantitative analysis of DW-MRI data is hindered by inconsistencies stemming from varying acquisition protocols.

Latent cognitive phenotypes in juvenile myoclonic epilepsy: Clinical, sociodemographic, and neuroimaging associations.

Objective: Application of cluster analytic procedures has advanced understanding of the cognitive heterogeneity inherent in diverse epilepsy syndromes and the associated clinical and neuroimaging features. Application of this unsupervised machine learning approach to the neuropsychological performance of persons with juvenile myoclonic epilepsy (JME) has yet to be attempted, which is the intent of this investigation.

Methods: A total of 77 JME participants, 19 unaffected siblings, and 44 unrelated controls, 12 to 25 years of age, were administered a comprehensive neuropsychological battery (intelligence, language, memory, executive function, and processing speed), which was subjected to factor analysis followed by K-means clustering of the resultant factor scores.

Characterizing white matter connectome abnormalities in patients with temporal lobe epilepsy using threshold-free network-based statistics.

Introduction: Emerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study.

Microstructural neural correlates of maximal grip strength in autistic children: the role of the cortico-cerebellar network and attention-deficit/hyperactivity disorder features.

Introduction: Maximal grip strength, a measure of how much force a person's hand can generate when squeezing an object, may be an effective method for understanding potential neurobiological differences during motor tasks. Grip strength in autistic individuals may be of particular interest due to its unique developmental trajectory. While autism-specific differences in grip-brain relationships have been found in adult populations, it is possible that such differences in grip-brain relationships may be present at earlier ages when grip strength is behaviorally similar in autistic and non-autistic groups.

Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease.

Introduction: Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes.

Purpose in life as a resilience factor for brain health: diffusion MRI findings from the Midlife in the U.S. study.

Introduction: A greater sense of purpose in life is associated with several health benefits relevant for active aging, but the mechanisms remain unclear. We evaluated if purpose in life was associated with indices of brain health.

Methods: We examined data from the Midlife in the United States (MIDUS) Neuroscience Project.

Structural brain morphometry differences and similarities between young patients with Crohn's disease in remission and healthy young and old controls.

Introduction: Crohn's disease (CD), one of the main phenotypes of inflammatory bowel disease (IBD), can affect any part of the gastrointestinal tract. It can impact the function of gastrointestinal secretions, as well as increasing the intestinal permeability leading to an aberrant immunological response and subsequent intestinal inflammation. Studies have reported anatomical and functional brain changes in Crohn's Disease patients (CDs), possibly due to increased inflammatory markers and microglial cells that play key roles in communicating between the brain, gut, and systemic immune system.

Role of autonomic, nociceptive, and limbic brainstem nuclei in core autism features.

Although multiple theories have speculated about the brainstem reticular formation's involvement in autistic behaviors, the in vivo imaging of brainstem nuclei needed to test these theories has proven technologically challenging. Using methods to improve brainstem imaging in children, this study set out to elucidate the role of the autonomic, nociceptive, and limbic brainstem nuclei in the autism features of 145 children (74 autistic children, 6.0-10.

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status.

Background: Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited.

Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males.

Association of neighborhood deprivation with white matter connectome abnormalities in temporal lobe epilepsy.

Objective: Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality.

Methods: Participants including 74 TLE patients (47 male, mean age = 39.

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations.

Multi-shell connectome DWI-based graph theory measures for the prediction of temporal lobe epilepsy and cognition.

Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE.

How we get a grip: Microstructural neural correlates of manual grip strength in children.

Maximal grip strength is associated with a variety of health-related outcome measures and thus may be reflective of the efficiency of foundational brain-body communication. Non-human primate models of grip strength strongly implicate the cortical lateral grasping network, but little is known about the translatability of these models to human children. Further, it is unclear how supplementary networks that provide proprioceptive information and cerebellar-based motor command modification are associated with maximal grip strength.

Application of data harmonization and tract-based spatial statistics reveals white matter structural abnormalities in pediatric patients with focal cortical dysplasia.

Our study assessed diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) in pediatric subjects with epilepsy secondary to Focal Cortical Dysplasia (FCD) to improve our understanding of structural network changes associated with FCD related epilepsy. We utilized a data harmonization (DH) approach to minimize confounding effects induced by MRI protocol differences. We also assessed correlations between DTI metrics and neurocognitive measures of the fluid reasoning index (FRI), verbal comprehension index (VCI), and visuospatial index (VSI).

Brainstem white matter microstructure is associated with hyporesponsiveness and overall sensory features in autistic children.

Background: Elevated or reduced responses to sensory stimuli, known as sensory features, are common in autistic individuals and often impact quality of life. Little is known about the neurobiological basis of sensory features in autistic children. However, the brainstem may offer critical insights as it has been associated with both basic sensory processing and core features of autism.

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI.

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset.

Improving Imaging of the Brainstem and Cerebellum in Autistic Children: Transformation-Based High-Resolution Diffusion MRI (TiDi-Fused) in the Human Brainstem.

Diffusion-weighted magnetic resonance imaging (dMRI) of the brainstem is technically challenging, especially in young autistic children as nearby tissue-air interfaces and motion (voluntary and physiological) can lead to artifacts. This limits the availability of high-resolution images, which are desirable for improving the ability to study brainstem structures. Furthermore, inherently low signal-to-noise ratios, geometric distortions, and sensitivity to motion not related to molecular diffusion have resulted in limited techniques for high-resolution data acquisition compared to other modalities such as T1-weighted imaging.

Age-related differences in white matter microstructure measured by advanced diffusion MRI in healthy older adults at risk for Alzheimer's disease.

Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion imaging technique, which can detect more distinct microstructural features compared to conventional Diffusion Tensor Imaging (DTI). NODDI allows the signal to be divided into multiple water compartments and derive measures for orientation dispersion index (ODI), neurite density index (NDI) and volume fraction of isotropic diffusion compartment (FISO). This study aimed to investigate which diffusion metric-fractional anisotropy (FA), mean diffusivity (MD), NDI, ODI, or FISO-is most influenced by aging and reflects cognitive function in a population of healthy older adults at risk for Alzheimer's disease (AD).

Differences in Diffusion Tensor Imaging White Matter Integrity Related to Verbal Fluency Between Young and Old Adults.

Throughout adulthood, the brain undergoes an array of structural and functional changes during the typical aging process. These changes involve decreased brain volume, reduced synaptic density, and alterations in white matter (WM). Although there have been some previous neuroimaging studies that have measured the ability of adult language production and its correlations to brain function, structural gray matter volume, and functional differences between young and old adults, the structural role of WM in adult language production in individuals across the life span remains to be thoroughly elucidated.

Individual variation in white matter microstructure is related to better recovery from negative stimuli.

The uncinate fasciculus is a white matter tract that may facilitate emotion regulation by carrying connections from the prefrontal cortex to regions of the temporal lobe, including the amygdala. Depression and anxiety are associated with reduced uncinate fasciculus fractional anisotropy (FA)-a diffusion tensor imaging measure related to white matter integrity. In the current study, we tested whether FA in the uncinate fasciculus is associated with individual differences in emotional recovery measured with corrugator supercilii electromyography in response to negative, neutral, and positive images in 108 participants from the Midlife in the US (MIDUS; http://midus.