Microstructure of Human Corpus Callosum across the Lifespan: Regional Variations in Axon Caliber, Density, and Myelin Content.

The myeloarchitecture of the corpus callosum (CC) is characterized as a mosaic of distinct differences in fiber density of small- and large-diameter axons along the anterior-posterior axis; however, regional and age differences across the lifespan are not fully understood. Using multiecho T2 magnetic resonance imaging combined with multi-T2 fitting, the myelin water fraction (MWF) and geometric-mean of the intra-/extracellular water T2 (geomT2IEW) in 395 individuals (7-85 years; 41% males) were examined. The approach was validated where regional patterns along the CC closely resembled the histology; MWF matched mean axon diameter and geomT2IEW mirrored the density of large-caliber axons. Across the lifespan, MWF exhibited a quadratic association with age in all 10 CC regions with evidence of a positive linear MWF-age relationship among younger participants and minimal age differences in the remainder of the lifespan. Regarding geomT2IEW, a significant linear age × region interaction reflected positive linear age dependence mostly prominent in the regions with the highest density of small-caliber fibers-genu and splenium. In all, these two indicators characterize distinct attributes that are consistent with histology, which is a first. In addition, these results conform to rapid developmental progression of CC myelination leveling in middle age as well as age-related degradation of axon sheaths in older adults.

Differences in steady-state glutamate levels and variability between 'non-task-active' conditions: Evidence from 1H fMRS of the prefrontal cortex.

Proton functional magnetic resonance spectroscopy (1H fMRS) is a noninvasive neuroimaging technique capable of detecting dynamic changes in glutamate related to task-related demands at a temporal resolution under 1 min. Several recent 1H fMRS studies demonstrated elevated steady-state levels of glutamate of 2% or greater during different 'task-active' conditions, relative to a 'non-task-active' control condition. However, the 'control' condition from these studies does vary with respect to the degree of constraining behavior, which may lead to different glutamate levels or variability between 'control' conditions. The purpose of this 1H fMRS study was to compare the steady-state levels and variability of glutamate in the left dorsolateral prefrontal cortex (dlPFC) of 16 healthy adults across four different putative 'non-task-active' conditions: relaxed with eyes closed, passive visual fixation crosshair, visual flashing checkerboard, and finger tapping. Results showed significantly lower glutamate levels during the passive visual fixation crosshair than the visual flashing checkerboard and the finger tapping conditions. Moreover, glutamate was significantly less variable during the passive visual fixation crosshair and the visual flashing checkerboard than the relaxed eyes closed condition. Of the four conditions, the passive visual fixation crosshair condition demonstrated the lowest and least variable glutamate levels potentially reflecting the least dlPFC engagement, but greatest behavioral constraint. These results emphasize the importance of selecting a proper 'control' condition to reflect accurately a 'non-task-active' steady-state level of glutamate with minimal variability during 1H MRS investigations.

Selective vulnerability and resilience to Alzheimer's disease tauopathy as a function of genes and the connectome.

Brain regions in Alzheimer's (AD) exhibit distinct vulnerability to the disease's hallmark pathology, with the entorhinal cortex and hippocampus succumbing early to tau tangles while others like primary sensory cortices remain resilient. The quest to understand how local/regional genetic factors, pathogenesis, and network-mediated spread of pathology together govern this selective vulnerability (SV) or resilience (SR) is ongoing. Although many risk genes in AD are known from gene association and transgenic studies, it is still not known whether and how their baseline expression signatures confer SV or SR to brain structures. Prior analyses have yielded conflicting results, pointing to a disconnect between the location of genetic risk factors and downstream tau pathology. We hypothesize that a full accounting of genes' role in mediating SV/SR would require the modeling of network-based vulnerability, whereby tau misfolds, aggregates, and propagates along fiber projections. We therefore employed an extended network diffusion model (eNDM) and tested it on tau pathology PET data from 196 AD patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Thus the fitted eNDM model becomes a reference process from which to assess the role of innate genetic factors. Using the residual (observed - model-predicted) tau as a novel target outcome, we obtained its association with 100 top AD risk-genes, whose baseline spatial transcriptional profiles were obtained from the Allen Human Brain Atlas (AHBA). We found that while many risk genes at baseline showed a strong association with regional tau, many more showed a stronger association with residual tau. This suggests that both direct vulnerability, related to the network, as well as network-independent vulnerability, are conferred by risk genes. We then classified risk genes into four classes: network-related SV (SV-NR), network-independent SV (SV-NI), network-related SR (SR-NR), and network-independent SR (SR-NI). Each class has a distinct spatial signature and associated vulnerability to tau. Remarkably, we found from gene-ontology analyses, that genes in these classes were enriched in distinct functional processes and encompassed different functional networks. These findings offer new insights into the factors governing innate vulnerability or resilience in AD pathophysiology and may prove helpful in identifying potential intervention targets.

Connectome-based biophysics models of Alzheimer's disease diagnosis and prognosis.

With the increasing prevalence of Alzheimer's disease (AD) among aging populations and the limited therapeutic options available to slow or reverse its progression, the need has never been greater for improved diagnostic tools for identifying patients in the preclinical and prodomal phases of AD. Biophysics models of the connectome-based spread of amyloid-beta (Aß) and microtubule-associated protein tau (τ) have enjoyed recent success as tools for predicting the time course of AD-related pathological changes. However, given the complex etiology of AD, which involves not only connectome-based spread of protein pathology but also the interactions of many molecular and cellular players over multiple spatiotemporal scales, more robust, complete biophysics models are needed to better understand AD pathophysiology and ultimately provide accurate patient-specific diagnoses and prognoses. Here we discuss several areas of active research in AD whose insights can be used to enhance the mathematical modeling of AD pathology as well as recent attempts at developing improved connectome-based biophysics models. These efforts toward a comprehensive yet parsimonious mathematical description of AD hold great promise for improving both the diagnosis of patients at risk for AD and our mechanistic understanding of how AD progresses.

Cellular underpinnings of the selective vulnerability to tauopathic insults in Alzheimer's disease.

Neurodegenerative diseases such as Alzheimer's disease (AD) exhibit pathological changes in the brain that proceed in a stereotyped and regionally specific fashion, but the cellular and molecular underpinnings of regional vulnerability are currently poorly understood. Recent work has identified certain subpopulations of neurons in a few focal regions of interest, such as the entorhinal cortex, that are selectively vulnerable to tau pathology in AD. However, the cellular underpinnings of regional susceptibility to tau pathology are currently unknown, primarily because whole-brain maps of a comprehensive collection of cell types have been inaccessible. Here, we deployed a recent cell-type mapping pipeline, Matrix Inversion and Subset Selection (MISS), to determine the brain-wide distributions of pan-hippocampal and neocortical neuronal and non-neuronal cells in the mouse using recently available single-cell RNA sequencing (scRNAseq) data. We then performed a robust set of analyses to identify general principles of cell-type-based selective vulnerability using these cell-type distributions, utilizing 5 transgenic mouse studies that quantified regional tau in 12 distinct PS19 mouse models. Using our approach, which constitutes the broadest exploration of whole-brain selective vulnerability to date, we were able to discover cell types and cell-type classes that conferred vulnerability and resilience to tau pathology. Hippocampal glutamatergic neurons as a whole were strongly positively associated with regional tau deposition, suggesting vulnerability, while cortical glutamatergic and GABAergic neurons were negatively associated. Among glia, we identified oligodendrocytes as the single-most strongly negatively associated cell type, whereas microglia were consistently positively correlated. Strikingly, we found that there was no association between the gene expression relationships between cell types and their vulnerability or resilience to tau pathology. When we looked at the explanatory power of cell types versus GWAS-identified AD risk genes, cell type distributions were consistently more predictive of end-timepoint tau pathology than regional gene expression. To understand the functional enrichment patterns of the genes that were markers of the identified vulnerable or resilient cell types, we performed gene ontology analysis. We found that the genes that are directly correlated to tau pathology are functionally distinct from those that constitutively embody the vulnerable cells. In short, we have demonstrated that regional cell-type composition is a compelling explanation for the selective vulnerability observed in tauopathic diseases at a whole-brain level and is distinct from that conferred by risk genes. These findings may have implications in identifying cell-type-based therapeutic targets.

The effects of microglia on tauopathy progression can be quantified using Nexopathy in silico (Nexis) models.

The prion-like transsynaptic propagation of misfolded tau along the brain's connectome has previously been modeled using connectome-based network diffusion models. In addition to the connectome, interactions between the general neurological "milieu" in the neurodegenerative brain and proteinopathic species can also contribute to pathology propagation. Such a molecular nexopathy framework posits that the distinct characteristics of neurodegenerative disorders stem from interactions between the network and surrounding molecular players. However, the effects of these modulators remain unquantified. Here, we present Nexopathy in silico ("Nexis"), a quantitative model of tau progression augmenting earlier models by including parameters of pathology propagation defined by the molecular modulators of connectome-based spread. Our Nexis:microglia model provides the first quantitative characterization of this effect on the whole brain by expanding previous models of neuropathology progression by incorporating microglial influence. We show that Trem2, but not microglial homeostasis genes, significantly improved the model's predictive power. Trem2 appears to reduce tau accumulation rate while increasing its interregional spread from the hippocampal seed area, causing higher tau burden in the striatum, pallidum, and contralateral hippocampus. Nexis provides an improved understanding and quantification of microglial contribution to tau propagation and can be flexibly modified to include other modulators of progressive neurodegeneration.

Test-retest and repositioning effects of white matter microstructure measurements in selected white matter tracts.

We used intra-class effect decomposition (ICED) to evaluate the reliability of myelin water fraction (MWF) and geometric mean T2 relaxation time (geomT2IEW) estimated from a multi-echo MRI sequence. Our evaluation addressed test-retest reliability, with and without participant re-positioning, for seven commonly assessed white matter tracts: anterior and posterior limbs of the internal capsule, dorsal and ventral branches of the cingulum, the inferior fronto-occipital fasciculus, the superior longitudinal fasciculus, and the fornix in 20 healthy adults. We acquired two back-to-back scans in a single session, and a third after a break and repositioning the participant in the scanner. For both indices and for all white matter tracts assessed, reliability for an immediate retest, and after the participant's repositioning in the scanner was high. Variance partitioning revealed that in addition to measurement noise, which was significant in all regions, repositioning contributed to unreliability mainly in longer association fibers. Hemispheric location did not significantly contribute to unreliability in any region of interest (ROI). Thus, despite non-negligible error of measurement, for all ROIs, MWF and geomT2IEW have good test-retest reliability, regardless of the hemispheric location and are, therefore, suitable for longitudinal investigations in healthy adults.

White-matter microstructural properties of the corpus callosum: test-retest and repositioning effects in two parcellation schemes.

We investigated test-retest reliability of two MRI-derived indices of white-matter microstructural properties in the human corpus callosum (CC): myelin water fraction (MWF) and geometric mean T2 relaxation time of intra/extracellular water (geomT2IEW), using a 3D gradient and multi spin-echo sequence in 20 healthy adults (aged 24-69 years, 10 men). For each person, we acquired two back-to-back acquisitions in a single session, and the third after a break and repositioning the participant in the scanner. We assessed the contribution of session-related variance to reliability, using intra-class effect decomposition (ICED) while comparing two CC parcellation schemes that divided the CC into five and ten regions. We found high construct-level reliability of MWF and geomT2IEW in all regions of both schemes, except the posterior body-a slender region with a smaller number of large myelinated fibers. Only in that region, we observed significant session-specific variance in the MWF, interpreted as an effect of repositioning in the scanner. The geomT2IEW demonstrated higher reliability than MWF across both parcellation schemes and all CC regions. Thus, in both CC parcellation approaches, MWF and geomT2IEW have good test-retest reliability and are, therefore, suitable for longitudinal investigations in healthy adults. However, the five-region scheme appears more appropriate for MWF, whereas both schemes are suitable for geomT2IEW studies. Given the lower reliability in the posterior body, which may reflect sensitivity to the repositioning of the participant in the scanner, caution should be exercised in interpreting differential findings in that region.

Working Memory Modulates Glutamate Levels in the Dorsolateral Prefrontal Cortex during 1H fMRS.

Glutamate is involved in excitatory neurotransmission and metabolic processes related to brain function. Previous studies using proton functional magnetic resonance spectroscopy (1H fMRS) have demonstrated elevated cortical glutamate levels by 2-4% during visual and motor stimulation, relative to periods of no stimulation. Here, we extended this approach to working memory cognitive task performance, which has been consistently associated with dorsolateral prefrontal cortex (dlPFC) activation. Sixteen healthy adult volunteers completed a continuous visual fixation "rest" task followed by a letter 2-back working memory task during 1H fMRS acquisition of the left dlPFC, which encompassed Brodmann areas 45 and 46 over a 4.5-cm3 volume. Using a 100% automated fitting procedure integrated with LCModel, raw spectra were eddy current-, phase-, and shift-corrected prior to quantification resulting in a 32s temporal resolution or 8 averages per spectra. Task compliance was high (95 ± 11% correct) and the mean Cramer-Rao Lower Bound of glutamate was 6.9 ± 0.9%. Relative to continuous passive visual fixation, left dlPFC glutamate levels were significantly higher by 2.7% (0.32 mmol/kg wet weight) during letter 2-back performance. Elevated dlPFC glutamate levels reflect increased metabolic activity and excitatory neurotransmission driven by working memory-related cognitive demands. These results provide the first in vivo demonstration of elevated dlPFC glutamate levels during working memory.

Presence of two types of flowers with respect to nectar sugar in two gregariously flowering species.

Many species of animal-pollinated flowers are known to vary widely in the nectar content of flowers. Some proportion of flowers in many species is apparently nectarless,and such flowers are believed to be 'cheaters'. Cheating may explain a part of the variability in nectar content.If cheating exists as a qualitatively different strategy then we expect bimodality in the distribution of nectar content of flowers. It has been shown in a multispecies study that gregarious species have a higher proportion of cheater flowers. We studied the frequency distribution of total nectar sugar in two gregariously flowering species Lantana camara and Utricularia purpurascens, which differed in other floral and ecological characters. At the population level, both the species showed significant bimodality in the total sugar content of flowers. The obvious sources of heterogeneity in the data did not explain bimodality. In Lantana camara, bimodality was observed within flowers of some of the individual plants sampled. In Utricularia purpurascens the proportion of nectarless flowers was more in high-density patches, suggesting that the gregariousness hypothesis may work within a species as well. The results support the hypothesis of cheating as a distinct strategy since two distinct types of flowers were observed in both the species. The effect of density in Utricularia purpurascens also supports the gregariousness hypothesis.