Evolutionarily conserved neural responses to affective touch in monkeys transcend consciousness and change with age.

Affective touch-a slow, gentle, and pleasant form of touch-activates a different neural network than which is activated during discriminative touch in humans. Affective touch perception is enabled by specialized low-threshold mechanoreceptors in the skin with unmyelinated fibers called C tactile (CT) afferents. These CT afferents are conserved across mammalian species, including macaque monkeys. However, it is unknown whether the neural representation of affective touch is the same across species and whether affective touch's capacity to activate the hubs of the brain that compute socioaffective information requires conscious perception. Here, we used functional MRI to assess the preferential activation of neural hubs by slow (affective) vs. fast (discriminative) touch in anesthetized rhesus monkeys (Macaca mulatta). The insula, anterior cingulate cortex (ACC), amygdala, and secondary somatosensory cortex were all significantly more active during slow touch relative to fast touch, suggesting homologous activation of the interoceptive-allostatic network across primate species during affective touch. Further, we found that neural responses to affective vs. discriminative touch in the insula and ACC (the primary cortical hubs for interoceptive processing) changed significantly with age. Insula and ACC in younger animals differentiated between slow and fast touch, while activity was comparable between conditions for aged monkeys (equivalent to >70 y in humans). These results, together with prior studies establishing conserved peripheral nervous system mechanisms of affective touch transduction, suggest that neural responses to affective touch are evolutionarily conserved in monkeys, significantly impacted in old age, and do not necessitate conscious experience of touch.

In vivo evidence of microstructural hypo-connectivity of brain white matter in 22q11.2 deletion syndrome.

22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12-15 years) and those undergoing typical development (8-18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6-52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.

Novel insights into axon diameter and myelin content in late childhood and adolescence.

White matter microstructural development in late childhood and adolescence is driven predominantly by increasing axon density and myelin thickness. Ex vivo studies suggest that the increase in axon diameter drives developmental increases in axon density observed with pubertal onset. In this cross-sectional study, 50 typically developing participants aged 8-18 years were scanned using an ultra-strong gradient magnetic resonance imaging scanner. Microstructural properties, including apparent axon diameter $({d}_a)$, myelin content, and g-ratio, were estimated in regions of the corpus callosum. We observed age-related differences in ${d}_a$, myelin content, and g-ratio. In early puberty, males had larger ${d}_a$ in the splenium and lower myelin content in the genu and body of the corpus callosum, compared with females. Overall, this work provides novel insights into developmental, pubertal, and cognitive correlates of individual differences in apparent axon diameter and myelin content in the developing human brain.

White matter microstructure in face and body networks predicts facial expression and body posture perception across development.

Facial expression and body posture recognition have protracted developmental trajectories. Interactions between face and body perception, such as the influence of body posture on facial expression perception, also change with development. While the brain regions underpinning face and body processing are well-defined, little is known about how white-matter tracts linking these regions relate to perceptual development. Here, we obtained complementary diffusion magnetic resonance imaging (MRI) measures (fractional anisotropy [FA], spherical mean Sµ ), and a quantitative MRI myelin-proxy measure (R1), within white-matter tracts of face- and body-selective networks in children and adolescents and related these to perceptual development. In tracts linking occipital and fusiform face areas, facial expression perception was predicted by age-related maturation, as measured by Sµ and R1, as well as age-independent individual differences in microstructure, captured by FA and R1. Tract microstructure measures linking posterior superior temporal sulcus body region with anterior temporal lobe (ATL) were related to the influence of body on facial expression perception, supporting ATL as a site of face and body network convergence. Overall, our results highlight age-dependent and age-independent constraints that white-matter microstructure poses on perceptual abilities during development and the importance of complementary microstructural measures in linking brain structure and behaviour.

MICRA: Microstructural image compilation with repeated acquisitions.

We provide a rich multi-contrast microstructural MRI dataset acquired on an ultra-strong gradient 3T Connectom MRI scanner comprising 5 repeated sets of MRI microstructural contrasts in 6 healthy human participants. The availability of data sets that support comprehensive simultaneous assessment of test-retest reliability of multiple microstructural contrasts (i.e., those derived from advanced diffusion, multi-component relaxometry and quantitative magnetisation transfer MRI) in the same population is extremely limited. This unique dataset is offered to the imaging community as a test-bed resource for conducting specialised analyses that may assist and inform their current and future research. The Microstructural Image Compilation with Repeated Acquisitions (MICRA) dataset includes raw data and computed microstructure maps derived from multi-shell and multi-direction encoded diffusion, multi-component relaxometry and quantitative magnetisation transfer acquisition protocols. Our data demonstrate high reproducibility of several microstructural MRI measures across scan sessions as shown by intra-class correlation coefficients and coefficients of variation. To illustrate a potential use of the MICRA dataset, we computed sample sizes required to provide sufficient statistical power a priori across different white matter pathways and microstructure measures for different statistical comparisons. We also demonstrate whole brain white matter voxel-wise repeatability in several microstructural maps. The MICRA dataset will be of benefit to researchers wishing to conduct similar reliability tests, power estimations or to evaluate the robustness of their own analysis pipelines.

The variability of MR axon radii estimates in the human white matter.

The noninvasive quantification of axonal morphology is an exciting avenue for gaining understanding of the function and structure of the central nervous system. Accurate non-invasive mapping of micron-sized axon radii using commonly applied neuroimaging techniques, that is, diffusion-weighted MRI, has been bolstered by recent hardware developments, specifically MR gradient design. Here the whole brain characterization of the effective MR axon radius is presented and the inter- and intra-scanner test-retest repeatability and reproducibility are evaluated to promote the further development of the effective MR axon radius as a neuroimaging biomarker. A coefficient-of-variability of approximately 10% in the voxelwise estimation of the effective MR radius is observed in the test-retest analysis, but it is shown that the performance can be improved fourfold using a customized along-tract analysis.

Impact of b-value on estimates of apparent fibre density.

Recent advances in diffusion magnetic resonance imaging (dMRI) analysis techniques have improved our understanding of fibre-specific variations in white matter microstructure. Increasingly, studies are adopting multi-shell dMRI acquisitions to improve the robustness of dMRI-based inferences. However, the impact of b-value choice on the estimation of dMRI measures such as apparent fibre density (AFD) derived from spherical deconvolution is not known. Here, we investigate the impact of b-value sampling scheme on estimates of AFD. First, we performed simulations to assess the correspondence between AFD and simulated intra-axonal signal fraction across multiple b-value sampling schemes. We then studied the impact of sampling scheme on the relationship between AFD and age in a developmental population (n = 78) aged 8-18 (mean = 12.4, SD = 2.9 years) using hierarchical clustering and whole brain fixel-based analyses. Multi-shell dMRI data were collected at 3.0T using ultra-strong gradients (300 mT/m), using 6 diffusion-weighted shells ranging from b = 0 to 6,000 s/mm2 . Simulations revealed that the correspondence between estimated AFD and simulated intra-axonal signal fraction was improved with high b-value shells due to increased suppression of the extra-axonal signal. These results were supported by in vivo data, as sensitivity to developmental age-relationships was improved with increasing b-value (b = 6,000 s/mm2 , median R2 = .34; b = 4,000 s/mm2 , median R2 = .29; b = 2,400 s/mm2 , median R2 = .21; b = 1,200 s/mm2 , median R2 = .17) in a tract-specific fashion. Overall, estimates of AFD and age-related microstructural development were better characterised at high diffusion-weightings due to improved correspondence with intra-axonal properties.

Mean Diffusivity in Striatum Correlates With Acute Neuronal Death but Not Lesser Neuronal Injury in a Pilot Study of Neonatal Piglets With Encephalopathy.

BACKGROUND: Diffusion MRI is routinely used to evaluate brain injury in neonatal encephalopathy. Although abnormal mean diffusivity (MD) is often attributed to cytotoxic edema, the specific contribution from neuronal pathology is unclear. PURPOSE: To determine whether MD from high-resolution diffusion tensor imaging (DTI) can detect variable degrees of neuronal degeneration and pathology in piglets with brain injury induced by excitotoxicity or global hypoxia-ischemia (HI) with or without overt infarction. STUDY TYPE: Prospective. ANIMAL MODEL: Excitotoxic brain injury was induced in six neonatal piglets by intrastriatal stereotaxic injection of the glutamate receptor agonist quinolinic acid (QA). Three piglets underwent global HI or a sham procedure. Piglets recovered for 20-96 hours before undergoing MRI (n = 9). FIELD STRENGTH/SEQUENCE: 3.0T MRI with DTI, T1 - and T2 -weighted imaging. ASSESSMENT: MD, fractional anisotropy (FA), and qualitative T2 injury were assessed in the putamen and caudate. The cell bodies of normal neurons, degenerating neurons (excitotoxic necrosis, ischemic necrosis, or necrosis-apoptosis cell death continuum), and injured neurons with equivocal degeneration were counted by histopathology. STATISTICAL TESTS: Spearman correlations were used to compare MD and FA to normal, degenerating, and injured neurons. T2 injury and neuron counts were evaluated by descriptive analysis. RESULTS: The QA insult generated titratable levels of neuronal pathology. In QA, HI, and sham piglets, lower MD correlated with higher ratios of degenerating-to-total neurons (P < 0.05), lower ratios of normal-to-total neurons (P < 0.05), and greater numbers of degenerating neurons (P < 0.05). MD did not correlate with abnormal neurons exhibiting nascent injury (P > 0.99). Neuron counts were not related to FA (P > 0.30) or to qualitative injury from T2 -weighted MRI. DATA CONCLUSION: MD is more accurate than FA for detecting neuronal degeneration and loss during acute recovery from neonatal excitotoxic and HI brain injury. MD does not reliably detect nonfulminant, nascent, and potentially reversible neuronal injury. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2020;52:1216-1226.

Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain.

Various diffusion MRI (dMRI) measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different dMRI measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. Indeed, it quickly becomes intractable for existing analysis pipelines to process multiple measurements at each voxel and at each vertex forming a streamline, highlighting the need for new ways to visualise or analyse such high-dimensional data. In a sample of 36 typically developing children aged 8-18 years, we profiled various commonly used dMRI measures across 22 brain pathways. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in these dMRI measures. The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We then demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. In summary, our findings demonstrate that dMRI analyses can benefit from dimensionality reduction techniques, to help disentangling the neurobiological underpinnings of white matter organisation.

Laser ablation-inductively coupled plasma-mass spectrometry imaging of white and gray matter iron distribution in Alzheimer's disease frontal cortex.

Iron deposition in the brain is a feature of normal aging, though in several neurodegenerative disorders, including Alzheimer's disease, the rate of iron accumulation is more advanced than in age-matched controls. Using laser ablation-inductively coupled plasma-mass spectrometry imaging we present here a pilot study that quantitatively assessed the iron content of white and gray matter in paraffin-embedded sections from the frontal cortex of Alzheimer's and control subjects. Using the phosphorus image as a confirmed proxy for the white/gray matter boundary, we found that increased intrusion of iron into gray matter occurs in the Alzheimer's brain compared to controls, which may be indicative of either a loss of iron homeostasis in this vulnerable brain region, or provide evidence of increased inflammatory processes as a response to chronic neurodegeneration. We also observed a trend of increasing iron within the white matter of the frontal cortex, potentially indicative of disrupted iron metabolism preceding loss of myelin integrity. Considering the known potential toxicity of excessive iron in the brain, our results provide supporting evidence for the continuous development of novel magnetic resonance imaging approaches for assessing white and gray matter iron accumulation in Alzheimer's disease.

Diffusion imaging of auditory and auditory-limbic connectivity in tinnitus: preliminary evidence and methodological challenges.

Subjective tinnitus, or "ringing in the ears," is perceived by 10 to 15 percent of the adult population and causes significant suffering in a subset of patients. While it was originally thought of as a purely auditory phenomenon, there is increasing evidence that the limbic system influences whether and how tinnitus is perceived, far beyond merely determining the patient's emotional reaction to the phantom sound. Based on functional imaging and electrophysiological data, recent articles frame tinnitus as a "network problem" arising from abnormalities in auditory-limbic interactions. Diffusion-weighted magnetic resonance imaging is a noninvasive method for investigating anatomical connections in vivo. It thus has the potential to provide anatomical evidence for the proposed changes in auditory-limbic connectivity. However, the few diffusion imaging studies of tinnitus performed to date have inconsistent results. In the present paper, we briefly summarize the results of previous studies, aiming to reconcile their results. After detailing analysis methods, we then report findings from a new dataset. We conclude that while there is some evidence for tinnitus-related increases in auditory and auditory-limbic connectivity that counteract hearing-loss related decreases in auditory connectivity, these results should be considered preliminary until several technical challenges have been overcome.

The developing hippocampus: Microstructural evolution through childhood and adolescence.

The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.

Developmental differences in canonical cortical networks: Insights from microstructure-informed tractography.

In response to a growing interest in refining brain connectivity assessments, this study focuses on integrating white matter fiber-specific microstructural properties into structural connectomes. Spanning ages 8-19 years in a developmental sample, it explores age-related patterns of microstructure-informed network properties at both local and global scales. First, the diffusion-weighted signal fraction associated with each tractography-reconstructed streamline was constructed. Subsequently, the convex optimization modeling for microstructure-informed tractography (COMMIT) approach was employed to generate microstructure-informed connectomes from diffusion MRI data. To complete the investigation, network characteristics within eight functionally defined networks (visual, somatomotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, and subcortical networks) were evaluated. The findings underscore a consistent increase in global efficiency across child and adolescent development within the visual, somatomotor, and default mode networks (p < 0.005). Additionally, mean strength exhibits an upward trend in the somatomotor and visual networks (p < 0.001). Notably, nodes within the dorsal and ventral visual pathways manifest substantial age-dependent changes in local efficiency, aligning with existing evidence of extended maturation in these pathways. The outcomes strongly support the notion of a prolonged developmental trajectory for visual association cortices. This study contributes valuable insights into the nuanced dynamics of microstructure-informed brain connectivity throughout different developmental stages.

There is a growing interest in incorporating biologically relevant white matter properties into the analysis of brain networks to obtain a more quantitative assessment of brain connectivity. In a developmental sample aged 8­19 years, we studied age-related patterns of local and global network properties. We generated microstructure-informed connectomes using diffusion MRI data, and computed network characteristics in eight functionally defined networks (visual, somatomotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, and subcortical networks). The findings reveal that throughout child and adolescent development, global efficiency increases in the visual, somatomotor, and default mode networks, and mean strength increases in the somatomotor and visual networks. Nodes belonging to the dorsal and ventral visual pathways demonstrate the largest age-dependence in local efficiency, supporting previous evidence of protracted maturation of dorsal and ventral visual pathways. The results provide compelling evidence that there is a prolonged development of visual association cortices.

MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression.

Neuroanatomical changes to the cortex during adolescence have been well documented using MRI, revealing ongoing cortical thinning and volume loss with age. However, the underlying cellular mechanisms remain elusive with conventional neuroimaging. Recent advances in MRI hardware and new biophysical models of tissue informed by diffusion MRI data hold promise for identifying the cellular changes driving these morphological observations. This study used ultra-strong gradient MRI to obtain high-resolution, in vivo estimates of cortical neurite and soma microstructure in sample of typically developing children and adolescents. Cortical neurite signal fraction, attributed to neuronal and glial processes, increased with age (mean R2 fneurite=.53, p<3.3e-11, 11.91% increase over age), while apparent soma radius decreased (mean R2 Rsoma=.48, p<4.4e-10, 1% decrease over age) across domain-specific networks. To complement these findings, developmental patterns of cortical gene expression in two independent post-mortem databases were analysed. This revealed increased expression of genes expressed in oligodendrocytes, and excitatory neurons, alongside a relative decrease in expression of genes expressed in astrocyte, microglia and endothelial cell-types. Age-related genes were significantly enriched in cortical oligodendrocytes, oligodendrocyte progenitors and Layer 5-6 neurons (pFDR<.001) and prominently expressed in adolescence and young adulthood. The spatial and temporal alignment of oligodendrocyte cell-type gene expression with neurite and soma microstructural changes suggest that ongoing cortical myelination processes contribute to adolescent cortical development. These findings highlight the role of intra-cortical myelination in cortical maturation during adolescence and into adulthood.

Evaluation of registration-based vs. manual segmentation of rhesus macaque brain MRIs.

With increasing numbers of magnetic resonance imaging (MRI) datasets becoming publicly available, researchers and clinicians alike have turned to automated methods of segmentation to enable population-level analyses of these data. Although prior research has evaluated the extent to which automated methods recapitulate "gold standard" manual segmentation methods in the human brain, such an evaluation has not yet been carried out for segmentation of MRIs of the macaque brain. Macaques offer the important opportunity to bridge gaps between microanatomical studies using invasive methods like tract tracing, neural recordings, and high-resolution histology and non-invasive macroanatomical studies using methods like MRI. As such, it is important to evaluate whether automated tools derive data of sufficient quality from macaque MRIs to bridge these gaps. We tested the relationship between automated registration-based segmentation using an open source and actively maintained NHP imaging analysis pipeline (AFNI) and gold standard manual segmentation of 4 structures (2 cortical: anterior cingulate cortex and insula; 2 subcortical: amygdala and caudate) across 37 rhesus macaques (Macaca mulatta). We identified some variability in the strength of correlation between automated and manual segmentations across neural regions and differences in relationships with demographic variables like age and sex between the two techniques.

Detecting microstructural deviations in individuals with deep diffusion MRI tractometry.

Most diffusion magnetic resonance imaging studies of disease rely on statistical comparisons between large groups of patients and healthy participants to infer altered tissue states in the brain; however, clinical heterogeneity can greatly challenge their discriminative power. There is currently an unmet need to move away from the current approach of group-wise comparisons to methods with the sensitivity to detect altered tissue states at the individual level. This would ultimately enable the early detection and interpretation of microstructural abnormalities in individual patients, an important step towards personalized medicine in translational imaging. To this end, Detect was developed to advance diffusion magnetic resonance imaging tractometry towards single-patient analysis. By operating on the manifold of white-matter pathways and learning normative microstructural features, our framework captures idiosyncrasies in patterns along white-matter pathways. Our approach paves the way from traditional group-based comparisons to true personalized radiology, taking microstructural imaging from the bench to the bedside.

Abnormal Trajectory of Intracortical Myelination in Schizophrenia Implicates White Matter in Disease Pathophysiology and the Therapeutic Mechanism of Action of Antipsychotics.

BACKGROUND: Postmortem and imaging studies provide converging evidence that the frontal lobe myelination trajectory is dysregulated in schizophrenia (SZ) and suggest that early in treatment, antipsychotic medications increase intracortical myelin (ICM). We used magnetic resonance imaging to examine whether the ICM trajectory in SZ is dysregulated and altered by antipsychotic treatment. METHODS: We examined 93 subjects with SZ (64 men and 29 women) taking second-generation oral antipsychotics with medication exposures of 0-333 months in conjunction with 80 healthy control subjects (52 men and 28 women). Frontal lobe ICM volume was estimated using a novel dual contrast magnetic resonance imaging method that combines two images that track different tissue components. RESULTS: When plotted against oral antipsychotic exposure duration, ICM of subjects with SZ was higher as a function of medication exposure during the first year of treatment but declined thereafter. In the age range examined, ICM of subjects with SZ was lower with increased age, while ICM of healthy control subjects was not. CONCLUSIONS: In adults with SZ, the relationship between length of exposure to oral second-generation antipsychotics and ICM was positive during the first year of treatment but was negative after this initial period, consistent with suboptimal later adherence after initial adherence. This ICM trajectory resembles clinically observed antipsychotic response trajectory with high rates of remission in the first year followed by progressively lower response rates. The results support postmortem evidence that SZ pathophysiology involves ICM deficits and suggest that correcting these deficits may be an important mechanism of action for antipsychotics.

Excessive early-life dietary exposure: a potential source of elevated brain iron and a risk factor for Parkinson's disease.

Iron accumulates gradually in the ageing brain. In Parkinson's disease, iron deposition within the substantia nigra is further increased, contributing to a heightened pro-oxidant environment in dopaminergic neurons. We hypothesise that individuals in high-income countries, where cereals and infant formulae have historically been fortified with iron, experience increased early-life iron exposure that predisposes them to age-related iron accumulation in the brain. Combined with genetic factors that limit iron regulatory capacity and/or dopamine metabolism, this may increase the risk of Parkinson's diseases. We propose to (a) validate a retrospective biomarker of iron exposure in children; (b) translate this biomarker to adults; (c) integrate it with in vivo brain iron in Parkinson's disease; and (d) longitudinally examine the relationships between early-life iron exposure and metabolism, brain iron deposition and Parkinson's disease risk. This approach will provide empirical evidence to support therapeutically addressing brain iron deposition in Parkinson's diseases and produce a potential biomarker of Parkinson's disease risk in preclinical individuals.

Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field.

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain-heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain-heart interactions.

Increased iron levels and decreased tissue integrity in hippocampus of Alzheimer's disease detected in vivo with magnetic resonance imaging.

BACKGROUND: Iron can catalyze damaging free radical reactions. With age, iron accumulates in brain gray matter regions and may contribute to the risk of developing age-related diseases such as Alzheimer's disease (AD). Prior MRI studies demonstrated increased iron deposits in basal ganglia regions; however, the hippocampus (Hipp), which is heavily damaged in AD, and comparator regions that are resistant to AD damage, such as thalamus (Th), have rarely been examined. OBJECTIVE: To assess iron levels and evidence of tissue damage in Hipp and Th of AD subjects and healthy controls. METHODS: Thirty-one AD and sixty-eight healthy control subjects participated in this study. High- and low-field strength MRI instruments were used in combination to quantify iron content of ferritin molecules (ferritin iron) using the field dependent relaxation rate increase (FDRI) method. Decreased transverse relaxation rate (R2) was used as an index of tissue damage. RESULTS: Compared with healthy controls, AD subjects had increased ferritin iron in Hipp (p = 0.019) but not Th (p = 0.637), and significantly decreased R2 in Hipp (p < 0.001) but not Th (p = 0.37). In the entire sample, FDRI and R2 were negatively correlated. CONCLUSION: The data shows that in AD, Hipp damage occurs in conjunction with ferritin iron accumulation. Prospective studies are needed to evaluate how increasing iron levels may influence the trajectory of tissue damage and cognitive and pathologic manifestations of AD.