An ontologically consistent MRI-based atlas of the mouse diencephalon.

In topological terms, the diencephalon lies between the hypothalamus and the midbrain. It is made up of three segments, prosomere 1 (pretectum), prosomere 2 (thalamus), and prosomere 3 (the prethalamus). A number of MRI-based atlases of different parts of the mouse brain have already been published, but none of them displays the segments the diencephalon and their component nuclei. In this study we present a new volumetric atlas identifying 89 structures in the diencephalon of the male C57BL/6J 12 week mouse. This atlas is based on an average of MR scans of 18 mouse brains imaged with a 16.4T scanner. This atlas is available for download at www.imaging.org.au/AMBMC. Additionally, we have created an FSL package to enable nonlinear registration of novel data sets to the AMBMC model and subsequent automatic segmentation.

Maximum Pseudolikelihood Estimation for Model-Based Clustering of Time Series Data.

Mixture of autoregressions (MoAR) models provide a model-based approach to the clustering of time series data. The maximum likelihood (ML) estimation of MoAR models requires evaluating products of large numbers of densities of normal random variables. In practical scenarios, these products converge to zero as the length of the time series increases, and thus the ML estimation of MoAR models becomes infeasible without the use of numerical tricks. We propose a maximum pseudolikelihood (MPL) estimation approach as an alternative to the use of numerical tricks. The MPL estimator is proved to be consistent and can be computed with an EM (expectation-maximization) algorithm. Simulations are used to assess the performance of the MPL estimator against that of the ML estimator in cases where the latter was able to be calculated. An application to the clustering of time series data arising from a resting state fMRI experiment is presented as a demonstration of the methodology.

Evidence for Concerted and Mosaic Brain Evolution in Dragon Lizards.

The brain plays a critical role in a wide variety of functions including behaviour, perception, motor control, and homeostatic maintenance. Each function can undergo different selective pressures over the course of evolution, and as selection acts on the outputs of brain function, it necessarily alters the structure of the brain. Two models have been proposed to explain the evolutionary patterns observed in brain morphology. The concerted brain evolution model posits that the brain evolves as a single unit and the evolution of different brain regions are coordinated. The mosaic brain evolution model posits that brain regions evolve independently of each other. It is now understood that both models are responsible for driving changes in brain morphology; however, which factors favour concerted or mosaic brain evolution is unclear. Here, we examined the volumes of the 6 major neural subdivisions across 14 species of the agamid lizard genus Ctenophorus (dragons). These species have diverged multiple times in behaviour, ecology, and body morphology, affording a unique opportunity to test neuroevolutionary models across species. We assigned each species to an ecomorph based on habitat use and refuge type, then used MRI to measure total and regional brain volume. We found evidence for both mosaic and concerted brain evolution in dragons: concerted brain evolution with respect to body size, and mosaic brain evolution with respect to ecomorph. Specifically, all brain subdivisions increase in volume relative to body size, yet the tectum and rhombencephalon also show opposite patterns of evolution with respect to ecomorph. Therefore, we find that both models of evolution are occurring simultaneously in the same structures in dragons, but are only detectable when examining particular drivers of selection. We show that the answer to the question of whether concerted or mosaic brain evolution is detected in a system can depend more on the type of selection measured than on the clade of animals studied.

Robust methods to create ex vivo minimum deformation atlases for brain mapping.

Highly detailed ex vivo 3D atlases of average structure are of critical importance to neuroscience and its current push to understanding the global microstructure of the brain. Multiple single slice histology sections can no longer provide sufficient detail of inter-slice microstructure and lack out of plane resolution. Two ex vivo methods have emerged that can create such detailed models. High-field micro MRI with the addition of contrast media has allowed intact whole brain microstructure imaging with an isotropic resolution of 15 µm in mouse. Blockface imaging has similarly evolved to a point where it is now possible to image an entire brain in a rigorous fashion with an out of plane resolution of 10 µm. Despite the destruction of the tissue as part of this process it allows a reconstructed model that is free from cutting artifacts. Both of these methods have been utilised to create minimum deformation atlases that are representative of the respective populations. The MDA atlases allow us unprecedented insight into the commonality and differences in microstructure in cortical structures in specific taxa. In this paper we provide an overview of how to create such MDA models from ex vivo data.

A segmentation protocol and MRI atlas of the C57BL/6J mouse neocortex.

The neocortex is the largest component of the mammalian cerebral cortex. It integrates sensory inputs with experiences and memory to produce sophisticated responses to an organism's internal and external environment. While areal patterning of the mouse neocortex has been mapped using histological techniques, the neocortex has not been comprehensively segmented in magnetic resonance images. This study presents a method for systematic segmentation of the C57BL/6J mouse neocortex. We created a minimum deformation atlas, which was hierarchically segmented into 74 neocortical and cortical-related regions, making it the most detailed atlas of the mouse neocortex currently available. In addition, we provide mean volumes and relative intensities for each structure as well as a nomenclature comparison between the two most cited histological atlases of the mouse brain. This MR atlas is available for download, and it should enable researchers to perform automated segmentation in genetic models of cortical disorders.

Brain templates and atlases.

The core concept within the field of brain mapping is the use of a standardized, or "stereotaxic", 3D coordinate frame for data analysis and reporting of findings from neuroimaging experiments. This simple construct allows brain researchers to combine data from many subjects such that group-averaged signals, be they structural or functional, can be detected above the background noise that would swamp subtle signals from any single subject. Where the signal is robust enough to be detected in individuals, it allows for the exploration of inter-individual variance in the location of that signal. From a larger perspective, it provides a powerful medium for comparison and/or combination of brain mapping findings from different imaging modalities and laboratories around the world. Finally, it provides a framework for the creation of large-scale neuroimaging databases or "atlases" that capture the population mean and variance in anatomical or physiological metrics as a function of age or disease. However, while the above benefits are not in question at first order, there are a number of conceptual and practical challenges that introduce second-order incompatibilities among experimental data. Stereotaxic mapping requires two basic components: (i) the specification of the 3D stereotaxic coordinate space, and (ii) a mapping function that transforms a 3D brain image from "native" space, i.e. the coordinate frame of the scanner at data acquisition, to that stereotaxic space. The first component is usually expressed by the choice of a representative 3D MR image that serves as target "template" or atlas. The native image is re-sampled from native to stereotaxic space under the mapping function that may have few or many degrees of freedom, depending upon the experimental design. The optimal choice of atlas template and mapping function depend upon considerations of age, gender, hemispheric asymmetry, anatomical correspondence, spatial normalization methodology and disease-specificity. Accounting, or not, for these various factors in defining stereotaxic space has created the specter of an ever-expanding set of atlases, customized for a particular experiment, that are mutually incompatible. These difficulties continue to plague the brain mapping field. This review article summarizes the evolution of stereotaxic space in term of the basic principles and associated conceptual challenges, the creation of population atlases and the future trends that can be expected in atlas evolution.

Segmentation of the C57BL/6J mouse cerebellum in magnetic resonance images.

The C57BL mouse is the centerpiece of efforts to use gene-targeting technology to understand cerebellar pathology, thus creating a need for a detailed magnetic resonance imaging (MRI) atlas of the cerebellum of this strain. In this study we present a methodology for systematic delineation of the vermal and hemispheric lobules of the C57BL/6J mouse cerebellum in magnetic resonance images. We have successfully delineated 38 cerebellar and cerebellar-related structures. The higher signal-to-noise ratio achieved by group averaging facilitated the identification of anatomical structures. In addition, we have calculated average region volumes and created probabilistic maps for each structure. The segmentation method and the probabilistic maps we have created will provide a foundation for future studies of cerebellar disorders using transgenic mouse models.

A fully segmented 3D anatomical atlas of a lizard brain.

As the relevance of lizards in evolutionary neuroscience increases, so does the need for more accurate anatomical references. Moreover, the use of magnetic resonance imaging (MRI) in evolutionary neuroscience is becoming more widespread; this represents a fundamental methodological shift that opens new avenues of investigative possibility but also poses new challenges. Here, we aim to facilitate this shift by providing a three-dimensional segmentation atlas of the tawny dragon brain. The tawny dragon (Ctenophorus decresii) is an Australian lizard of increasing importance as a model system in ecology and, as a member of the agamid lizards, in evolution. Based on a consensus average 3D image generated from the MRIs of 13 male tawny dragon heads, we identify and segment 224 structures visible across the entire lizard brain. We describe the relevance of this atlas to the field of evolutionary neuroscience and propose further experiments for which this atlas can provide the foundation. This advance in defining lizard neuroanatomy will facilitate numerous studies in evolutionary neuroscience. The atlas is available for download as a supplementary material to this manuscript and through the Open Science Framework (OSF; https://doi.org/10.17605/OSF.IO/UJENQ ).

Cerebral white matter in early puberty is associated with luteinizing hormone concentrations.

Puberty is a period in which cerebral white matter grows considerably, whereas gray matter decreases. The first endocrinological marker of puberty in both boys and girls is an increased secretion of luteinizing hormone (LH). Here we investigated the phenotypic association between LH, global and focal gray and white matter in 104 healthy nine-year-old monozygotic and dizygotic twins. Volumetric MRI and voxel-based morphometry were applied to measure global gray and white matter and to estimate relative concentrations of regional cerebral gray and white matter, respectively. A possible common genetic origin of this association (genetic correlation) was examined. Results showed that higher LH levels are associated with a larger global white matter proportion and with higher regional white matter density. Areas of increased white matter density included the cingulum, middle temporal gyrus and splenium of the corpus callosum. No association between LH and global gray matter proportion or regional gray matter density was found. Our data indicate that a common genetic factor underlies the association between LH level and regional white matter density. We suggest that the increase of white matter growth during puberty reported earlier might be directly or indirectly mediated by LH production. In addition, genes involved in LH production may be promising candidate genes in neuropsychiatric illnesses with an onset in early adolescence.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.

A 3D MRI-based atlas of a lizard brain.

Magnetic resonance imaging (MRI) is an established technique for neuroanatomical analysis, being particularly useful in the medical sciences. However, the application of MRI to evolutionary neuroscience is still in its infancy. Few magnetic resonance brain atlases exist outside the standard model organisms in neuroscience and no magnetic resonance atlas has been produced for any reptile brain. A detailed understanding of reptilian brain anatomy is necessary to elucidate the evolutionary origin of enigmatic brain structures such as the cerebral cortex. Here, we present a magnetic resonance atlas for the brain of a representative squamate reptile, the Australian tawny dragon (Agamidae: Ctenophorus decresii), which has been the subject of numerous ecological and behavioral studies. We used a high-field 11.74T magnet, a paramagnetic contrasting-enhancing agent and minimum-deformation modeling of the brains of thirteen adult male individuals. From this, we created a high-resolution three-dimensional model of a lizard brain. The 3D-MRI model can be freely downloaded and allows a better comprehension of brain areas, nuclei, and fiber tracts, facilitating comparison with other species and setting the basis for future comparative evolution imaging studies. The MRI model and atlas of a tawny dragon brain (Ctenophorus decresii) can be viewed online and downloaded using the Wiley Biolucida Server at wiley.biolucida.net.

The Study of Neurocognitive Outcomes, Radiological and Retinal Effects of Aspirin in Sleep Apnoea- rationale and methodology of the SNORE-ASA study.

PURPOSE: Sleep disordered breathing (SDB) is highly prevalent in older adults. Increasing evidence links SDB to the risk of dementia, mediated via a number of pathways, some of which may be attenuated by low-dose aspirin. This study will evaluate, in a healthy older cohort, the prospective relationship between SDB and cognitive function, changes in retinal and cerebral microvasculature, and determine whether low-dose aspirin ameliorates the effects of SDB on these outcomes over 3years. DESIGN: SNORE-ASA is a sub-study of the ASPirin in Reducing Events in the Elderly (ASPREE) randomised, multi-centre, placebo-controlled trial evaluating the effect of daily 100mg aspirin on disability-free and dementia-free survival in the healthy older adult aged 70 and over. At baseline, 1400 ASPREE participants successfully underwent a home sleep study with a home sleep study screening device for SDB; and 296 underwent both 1.5 Tesla brain magnetic resonance imaging (MRI) and retinal vascular imaging (RVI). Cognitive testing, brain MRI and RVI is being repeated after 3years. PRIMARY OUTCOME MEASURES: Change in the modified mini-mental state examination score. Secondary outcome measures are changes in other cognitive tests, and changes in abnormal parameters on RVI and volume of white matter hyper-intensities on brain MRI. CONCLUSION: Identifying preventive therapies for delaying the onset of dementia is of paramount importance. The results of this study will help clarify the impact of the SDB on risk of cognitive decline and cerebral small vessel disease, and whether low-dose aspirin can ameliorate cognitive decline in the setting of SDB. SNORE-ASA TRIAL REGISTRATION: ACTRN12612000891820: The Principal ASPREE study is registered with the International Standardized Randomized Controlled Trials Register, ASPirin in Reducing Events in the Elderly, Number: ISRCTN83772183 and clinicaltrials.gov Number NCT01038583.

MINC 2.0: A Flexible Format for Multi-Modal Images.

It is often useful that an imaging data format can afford rich metadata, be flexible, scale to very large file sizes, support multi-modal data, and have strong inbuilt mechanisms for data provenance. Beginning in 1992, MINC was developed as a system for flexible, self-documenting representation of neuroscientific imaging data with arbitrary orientation and dimensionality. The MINC system incorporates three broad components: a file format specification, a programming library, and a growing set of tools. In the early 2000's the MINC developers created MINC 2.0, which added support for 64-bit file sizes, internal compression, and a number of other modern features. Because of its extensible design, it has been easy to incorporate details of provenance in the header metadata, including an explicit processing history, unique identifiers, and vendor-specific scanner settings. This makes MINC ideal for use in large scale imaging studies and databases. It also makes it easy to adapt to new scanning sequences and modalities.

Dynamics of gray matter loss in Alzheimer's disease.

We detected and mapped a dynamically spreading wave of gray matter loss in the brains of patients with Alzheimer's disease (AD). The loss pattern was visualized in four dimensions as it spread over time from temporal and limbic cortices into frontal and occipital brain regions, sparing sensorimotor cortices. The shifting deficits were asymmetric (left hemisphere > right hemisphere) and correlated with progressively declining cognitive status (p < 0.0006). Novel brain mapping methods allowed us to visualize dynamic patterns of atrophy in 52 high-resolution magnetic resonance image scans of 12 patients with AD (age 68.4 +/- 1.9 years) and 14 elderly matched controls (age 71.4 +/- 0.9 years) scanned longitudinally (two scans; interscan interval 2.1 +/- 0.4 years). A cortical pattern matching technique encoded changes in brain shape and tissue distribution across subjects and time. Cortical atrophy occurred in a well defined sequence as the disease progressed, mirroring the sequence of neurofibrillary tangle accumulation observed in cross sections at autopsy. Advancing deficits were visualized as dynamic maps that change over time. Frontal regions, spared early in the disease, showed pervasive deficits later (>15% loss). The maps distinguished different phases of AD and differentiated AD from normal aging. Local gray matter loss rates (5.3 +/- 2.3% per year in AD v 0.9 +/- 0.9% per year in controls) were faster in the left hemisphere (p < 0.029) than the right. Transient barriers to disease progression appeared at limbic/frontal boundaries. This degenerative sequence, observed in vivo as it developed, provides the first quantitative, dynamic visualization of cortical atrophic rates in normal elderly populations and in those with dementia.

Development of MRI-based atlases of non-human brains.

Brain atlases are a fundamental resource for neuroscience research. In the past few decades they have undergone a transition from traditional printed histological atlases to digital atlases made up of multiple data sets from multiple modalities, and atlases based on magnetic resonance imaging (MRI) have become widespread. Here we discuss the methods involved in making an MRI brain atlas, including registration of multiple data sets into a model, ontological classification, segmentation of a minimum deformation model, dissemination strategies, and applications of these atlases. Finally, we discuss possible future directions in the development of brain atlases.

Blood pressure, brain structure, and cognition: opposite associations in men and women.

BACKGROUND: Research on associations between blood pressure, brain structure, and cognitive function has produced somewhat inconsistent results. In part, this may be due to differences in age ranges studied and because of sex differences in physiology and/or exposure to risk factors, which may lead to different time course or patterns in cardiovascular disease progression. The aim of this study was to investigate the impact of sex on associations between blood pressure, regional cerebral volumes, and cognitive function in older individuals. METHODS: In this cohort study, brachial blood pressure was measured twice at rest in 266 community-based individuals free of dementia aged 68-73 years who had also undergone a brain scan and a neuropsychological assessment. Associations between mean blood pressure (MAP), regional brain volumes, and cognition were investigated with voxel-wise regression analyses. RESULTS: Positive associations between MAP and regional volumes were detected in men, whereas negative associations were found in women. Similarly, there were sex differences in the brain-volume cognition relationship, with a positive relationship between regional brain volumes associated with MAP in men and a negative relationship in women. CONCLUSIONS: In this cohort of older individuals, higher MAP was associated with larger regional volume and better cognition in men, whereas opposite findings were demonstrated in women. These effects may be due to different lifetime risk exposure or because of physiological differences between men and women. Future studies investigating the relationship between blood pressure and brain structure or cognitive function should evaluate the potential for differential sex effects.

Improved prediction of final infarct volume using bolus delay-corrected perfusion-weighted MRI: implications for the ischemic penumbra.

BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI)-based perfusion measures using dynamic susceptibility contrast are extremely useful for identification of ischemic penumbral tissue in acute stroke. However, errors in the measurement of cerebral blood flow (CBF) and mean transit time (MTT) can occur. The aim of this study was to investigate whether bolus delay-corrected (BDC) perfusion measures enable better delineation of the ischemic penumbra. METHODS: Diffusion-weighted MRI (DWI) and perfusion-weighted MRI data were acquired from 19 acute stroke patients. Perfusion abnormalities were manually defined on BDC perfusion maps (corrected MTT [cMTT] and corrected CBF [cCBF]), and on maps derived from an arterial input function placed within the contralateral (CBF, MTT) and ipsilateral (ipsilateral CBF [iCBF] and ipsilateral MTT [iMTT]) middle cerebral artery. Perfusion lesion volumes were correlated with 30-day T2-weighted MRI lesion volumes and with clinical outcome using the National Institutes of Health Stroke Scale (NIHSS). RESULTS: Spearman correlation coefficients for comparing lesion volumes delineated on DWI, CBF, iCBF, cCBF, MTT, iMTT, and cMTT maps with 30-day T2-weighted lesion volumes were 0.72, 0.87, 0.88, 0.90, 0.84, 0.92, and 0.96, respectively (all P<0.001). The analogous correlation coefficients for comparing 30-day National Institutes of Health Stroke Scale (NIHSS) scores were 0.39 (NS), 0.69 (NS), 0.75 (P<0.001), 0.62 (NS), 0.72 (P<0.001), 0.78 (P<0.001), and 0.83 (P<0.001), respectively. CONCLUSIONS: Uncorrected perfusion lesion volumes overestimated the extent of ischemic injury. BDC perfusion measures (cMTT) correlated more accurately with final lesion volume and clinical outcome. Such measures offer an improved estimation of the final infarct size in acute stroke.

Correlation of quantitative EEG in acute ischemic stroke with 30-day NIHSS score: comparison with diffusion and perfusion MRI.

BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI) methods such as diffusion- (DWI) and perfusion-weighted (PWI) imaging have been widely studied as surrogate markers to monitor stroke evolution and predict clinical outcome. The utility of quantitative electroencephalography (qEEG) as such a marker in acute stroke has not been intensively studied. The aim of the present study was to correlate ischemic cortical stroke patients' clinical outcomes with acute qEEG, DWI, and PWI data. MATERIALS AND METHODS: DWI and PWI data were acquired from 11 patients within 7 and 16 hours after onset of symptoms. Sixty-four channel EEG data were obtained within 2 hours after the initial MRI scan and 1 hour before the second MRI scan. The acute delta change index (aDCI), a measure of the rate of change of average scalp delta power, was compared with the National Institutes of Health Stroke Scale scores (NIHSSS) at 30 days, as were MRI lesion volumes. RESULTS: The aDCI was significantly correlated with the 30-day NIHSSS, as was the initial mean transit time (MTT) abnormality volume (rho=0.80, P<0.01 and rho=0.79, P<0.01, respectively). Modest correlations were obtained between the 15-hour DWI lesion volume and both the aDCI and 30-day NIHSSS (rho=0.62, P<0.05 and rho=0.73, P<0.05, respectively). CONCLUSIONS: In this small sample the significant correlation between 30-day NIHSSS and acute qEEG data (aDCI) was equivalent to that between the former and MTT abnormality volume. Both were greater than the modest correlation between acute DWI lesion volume and 30-day NIHSSS. These preliminary results indicate that acute qEEG data might be used to monitor and predict stroke evolution.

False discovery rate control in magnetic resonance imaging studies via Markov random fields.

Magnetic resonance imaging (MRI) is widely used to study population effects of factors on brain morphometry. Inference from such studies often require the simultaneous testing of millions of statistical hypotheses. Such scale of inference is known to lead to large numbers of false positive results. Control of the false discovery rate (FDR) is commonly employed to mitigate against such outcomes. However, current methodologies in FDR control only account for the marginal significance of hypotheses, and are not able to explicitly account for spatial relationships, such as those between MRI voxels. In this article, we present novel methods that incorporate spatial dependencies into the process of controlling FDR through the use of Markov random fields. Our method is able to automatically estimate the relationships between spatially dependent hypotheses by means of maximum pseudo-likelihood estimation and the pseudo-likelihood information criterion. We show that our methods have desirable statistical properties with regards to FDR control and are able to outperform noncontexual methods in simulations of dependent hypothesis scenarios. Our method is applied to investigate the effects of aging on brain morphometry using data from the PATH study. Evidence of whole brain and component level effects that correspond to similar findings in the literature is found in our investigation.

Relating education, brain structure, and cognition: the role of cardiovascular disease risk factors.

The protective effect of education on cognitive and brain health is well established. While the direct effects of individual cardiovascular disease (CVD) risk factors (i.e., hypertension, smoking, diabetes, and obesity) on cerebral structure have been investigated, little is understood about the possible interaction between the protective effect of education and the deleterious effects of CVD risk factors in predicting brain ageing and cognition. Using data from the PATH Through Life study (N = 266), we investigated the protective effect of education on cerebral structure and function and tested a possible mediating role of CVD risk factors. Higher education was associated with larger regional grey/white matter volumes in the prefrontal cortex in men only. The association between education and cognition was mediated by brain volumes but only for grey matter and only in relation to information processing speed. CVD risk factors did not mediate the association between regional volumes and cognition. This study provides additional evidence in support for a protective effect of education on cerebral structures and cognition. However, it does not provide support for a mediating role of CVD risk factors in these associations.