Search

While striatal changes in Huntington's Disease (HD) are well established, few studies have investigated changes in the hippocampus, a key neuronal hub. Using MRI scans obtained from the IMAGE-HD study, hippocampi were manually traced and then analysed with the Spherical Harmonic Point Distribution Method (SPHARM-PDM) in 36 individuals with presymptomatic-HD, 37 with early symptomatic-HD, and 36 healthy matched controls. There were no significant differences in overall hippocampal volume between groups. Interestingly we found decreased bilateral hippocampal volume in people with symptomatic-HD who took selective serotonin reuptake inhibitors compared to those who did not, despite no significant differences in anxiety, depressive symptoms, or motor incapacity between the two groups. In symptomatic-HD, there was also significant shape deflation in the right hippocampal head, showing the utility of using manual tracing and SPHARM-PDM to characterise subtle shape changes which may be missed by other methods. This study confirms previous findings of the lack of hippocampal volumetric differentiation in presymptomatic-HD and symptomatic-HD compared to controls. We also find novel shape and volume findings in those with symptomatic-HD, especially in relation to decreased hippocampal volume in those treated with SSRIs.

High blood pressure variability (BPV) is a risk factor for cognitive decline and dementia, but its association with cortical thickness is not well understood. Here we use a topographical approach, to assess links between long-term BPV and cortical thickness in 478 (54% men at baseline) community dwelling older adults (70-88 years) from the ASPirin in Reducing Events in the Elderly NEURO sub-study. BPV was measured as average real variability, based on annual visits across three years. Higher diastolic BPV was significantly associated with reduced cortical thickness in multiple areas, including temporal (banks of the superior temporal sulcus), parietal (supramarginal gyrus, post-central gyrus), and posterior frontal areas (pre-central gyrus, caudal middle frontal gyrus), while controlling for mean BP. Higher diastolic BPV was associated with faster progression of cortical thinning across the three years. Diastolic BPV is an important predictor of cortical thickness, and trajectory of cortical thickness, independent of mean blood pressure. This finding suggests an important biological link in the relationship between BPV and cognitive decline in older age.

A major challenge in current cognitive neuroscience is how functional brain connectivity gives rise to human cognition. Functional magnetic resonance imaging (fMRI) describes brain connectivity based on cerebral oxygenation dynamics (hemodynamic connectivity), whereas [18F]-fluorodeoxyglucose functional positron emission tomography (FDG-fPET) describes brain connectivity based on cerebral glucose uptake (metabolic connectivity), each providing a unique characterization of the human brain. How these 2 modalities differ in their contribution to cognition and behavior is unclear. We used simultaneous resting-state FDG-fPET/fMRI to investigate how hemodynamic connectivity and metabolic connectivity relate to cognitive function by applying partial least squares analyses. Results revealed that although for both modalities the frontoparietal anatomical subdivisions related the strongest to cognition, using hemodynamic measures this network expressed executive functioning, episodic memory, and depression, whereas for metabolic measures this network exclusively expressed executive functioning. These findings demonstrate the unique advantages that simultaneous FDG-PET/fMRI has to provide a comprehensive understanding of the neural mechanisms that underpin cognition and highlights the importance of multimodality imaging in cognitive neuroscience research.

The field of neuroscience has largely overlooked the impact of motherhood on brain function outside the context of responses to infant stimuli. Here, we apply spectral dynamic causal modelling (spDCM) to resting-state fMRI data to investigate differences in brain function between a group of 40 first-time mothers at 1-year postpartum and 39 age- and education-matched women who have never been pregnant. Using spDCM, we investigate the directionality (top-down vs. bottom-up) and valence (inhibition vs excitation) of functional connections between six key left hemisphere brain regions implicated in motherhood: the dorsomedial prefrontal cortex, ventromedial prefrontal cortex, posterior cingulate cortex, parahippocampal gyrus, amygdala, and nucleus accumbens. We show a selective modulation of inhibitory pathways related to differences between (1) mothers and non-mothers, (2) the interactions between group and cognitive performance and (3) group and social cognition, and (4) differences related to maternal caregiving behaviour. Across analyses, we show consistent disinhibition between cognitive and affective regions suggesting more efficient, flexible, and responsive behaviour, subserving cognitive performance, social cognition, and maternal caregiving. Together our results support the interpretation of these key regions as constituting a parental caregiving network. The nucleus accumbens and the parahippocampal gyrus emerging as 'hub' regions of this network, highlighting the global importance of the affective limbic network for maternal caregiving, social cognition, and cognitive performance in the postpartum period.

This review provides a qualitative and quantitative analysis of cerebral glucose metabolism in ageing. We undertook a systematic literature review followed by pooled effect size and activation likelihood estimates (ALE) meta-analyses. Studies were retrieved from PubMed following the PRISMA guidelines. After reviewing 635 records, 21 studies with 22 independent samples (n = 911 participants) were included in the pooled effect size analyses. Eight studies with eleven separate samples (n = 713 participants) were included in the ALE analyses. Pooled effect sizes showed significantly lower cerebral metabolic rates of glucose for older versus younger adults for the whole brain, as well as for the frontal, temporal, parietal, and occipital lobes. Among the sub-cortical structures, the caudate showed a lower metabolic rate among older adults. In sub-group analyses controlling for changes in brain volume or partial volume effects, the lower glucose metabolism among older adults in the frontal lobe remained significant, whereas confidence intervals crossed zero for the other lobes and structures. The ALE identified nine clusters of lower glucose metabolism among older adults, ranging from 200 to 2640 mm3 . The two largest clusters were in the left and right inferior frontal and superior temporal gyri and the insula. Clusters were also found in the inferior temporal junction, the anterior cingulate and caudate. Taken together, the results are consistent with research showing less efficient glucose metabolism in the ageing brain. The findings are discussed in the context of theories of cognitive ageing and are compared to those found in neurodegenerative disease.

There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.

Amyotrophic lateral sclerosis (ALS) results in progressive impairment of upper and lower motor neurons. Increasing evidence from both in vivo and ex vivo studies suggest that iron accumulation in the motor cortex is a neuropathological hallmark in ALS. An in vivo neuroimaging marker of iron dysregulation in ALS would be useful in disease diagnosis and prognosis. Magnetic resonance imaging (MRI), with its unique capability to generate a variety of soft tissue contrasts, provides opportunities to image iron distribution in the human brain with millimeter to sub-millimeter anatomical resolution. Conventionally, MRI T1-weighted, T2-weighted, and T2*-weighted images have been used to investigate iron dysregulation in the brain in vivo. Susceptibility weighted imaging has enhanced contrast for para-magnetic materials that provides superior sensitivity to iron in vivo. Recently, the development of quantitative susceptibility mapping (QSM) has realized the possibility of using quantitative assessments of magnetic susceptibility measures in brain tissues as a surrogate measurement of in vivo brain iron. In this review, we provide an overview of MRI techniques that have been used to investigate iron dysregulation in ALS in vivo. The potential uses, strengths, and limitations of these techniques in clinical trials, disease diagnosis, and prognosis are presented and discussed. We recommend further longitudinal studies with appropriate cohort characterization to validate the efficacy of these techniques. We conclude that quantitative iron assessment using recent advances in MRI including QSM holds great potential to be a sensitive diagnostic and prognostic marker in ALS. The use of multimodal neuroimaging markers in combination with iron imaging may also offer improved sensitivity in ALS diagnosis and prognosis that could make a major contribution to clinical care and treatment trials. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

This Special Issue of Human Brain Mapping is dedicated to a 10-year anniversary of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium. It reports updates from a broad range of international neuroimaging projects that pool data from around the world to answer fundamental questions in neuroscience. Since ENIGMA was formed in December 2009, the initiative grew into a worldwide effort with over 2,000 participating scientists from 45 countries, and over 50 working groups leading large-scale studies of human brain disorders. Over the last decade, many lessons were learned on how best to pool brain data from diverse sources. Working groups were created to develop methods to analyze worldwide data from anatomical and diffusion magnetic resonance imaging (MRI), resting state and task-based functional MRI, electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance spectroscopy (MRS). The quest to understand genetic effects on human brain development and disease also led to analyses of brain scans on an unprecedented scale. Genetic roadmaps of the human cortex were created by researchers worldwide who collaborated to perform statistically well-powered analyses of common and rare genetic variants on brain measures and rates of brain development and aging. Here, we summarize the 31 papers in this Special Issue, covering: (a) technical approaches to harmonize analysis of different types of brain imaging data, (b) reviews of the last decade of work by several of ENIGMA's clinical and technical working groups, and (c) new empirical papers reporting large-scale international brain mapping analyses in patients with substance use disorders, schizophrenia, bipolar disorders, major depression, posttraumatic stress disorder, obsessive compulsive disorder, epilepsy, and stroke.

The suppression of motion artefacts from MR images is a challenging task. The purpose of this paper was to develop a standalone novel technique to suppress motion artefacts in MR images using a data-driven deep learning approach. A simulation framework was developed to generate motion-corrupted images from motion-free images using randomly generated motion profiles. An Inception-ResNet deep learning network architecture was used as the encoder and was augmented with a stack of convolution and upsampling layers to form an encoder-decoder network. The network was trained on simulated motion-corrupted images to identify and suppress those artefacts attributable to motion. The network was validated on unseen simulated datasets and real-world experimental motion-corrupted in vivo brain datasets. The trained network was able to suppress the motion artefacts in the reconstructed images, and the mean structural similarity (SSIM) increased from 0.9058 to 0.9338. The network was also able to suppress the motion artefacts from the real-world experimental dataset, and the mean SSIM increased from 0.8671 to 0.9145. The motion correction of the experimental datasets demonstrated the effectiveness of the motion simulation generation process. The proposed method successfully removed motion artefacts and outperformed an iterative entropy minimization method in terms of the SSIM index and normalized root mean squared error, which were 5-10% better for the proposed method. In conclusion, a novel, data-driven motion correction technique has been developed that can suppress motion artefacts from motion-corrupted MR images. The proposed technique is a standalone, post-processing method that does not interfere with data acquisition or reconstruction parameters, thus making it suitable for routine clinical practice.

BACKGROUND: Predicting long-term visual outcomes and axonal loss following acute optic neuritis (ON) is critical for choosing treatment. Predictive models including all clinical and paraclinical measures of optic nerve dysfunction following ON are lacking. OBJECTIVES: Using a prospective study method, to identify 1 and 3 months predictors of 6 and 12 months visual outcome (low contrast letter acuity 2.5%) and axonal loss [retinal nerve fiber layer thickness and multifocal evoked potential (mfVEP) amplitude] following acute ON. METHODS: In total, 37 patients of acute ON onset were evaluated within 14 days using between-eye asymmetry of visual acuity, color vision (Ishihara plates), optical coherence tomography, mfVEP, and optic nerve magnetic resonance imaging [magnetic transfer ratio (MTR) and diffusion tensor imaging (DTI)]. RESULTS: Visual outcome at 6 and 12 months was best predicted by Ishihara asymmetry at 1 and 3 months following ON onset. Axonal loss at 6 and 12 months was reliably predicted by Ishihara asymmetry at 1 month. Optic nerve MTR and DTI at 3 months post-acute ON could predict axonal loss at 6 and 12 months. CONCLUSIONS: Simple Ishihara asymmetry testing 1 month after acute ON onset can best predict visual outcome and axonal loss at 6 and 12 months in a clinical or research setting.

BACKGROUND: "Functional" [18F]-fluorodeoxyglucose positron emission tomography (FDG-fPET) is a new approach for measuring glucose uptake in the human brain. The goal of FDG-fPET is to maintain a constant plasma supply of radioactive FDG in order to track, with high temporal resolution, the dynamic uptake of glucose during neuronal activity that occurs in response to a task or at rest. FDG-fPET has most often been applied in simultaneous BOLD-fMRI/FDG-fPET (blood oxygenation level-dependent functional MRI fluorodeoxyglucose functional positron emission tomography) imaging. BOLD-fMRI/FDG-fPET provides the capability to image the 2 primary sources of energetic dynamics in the brain, the cerebrovascular haemodynamic response and cerebral glucose uptake. FINDINGS: In this Data Note, we describe an open access dataset, Monash DaCRA fPET-fMRI, which contrasts 3 radiotracer administration protocols for FDG-fPET: bolus, constant infusion, and hybrid bolus/infusion. Participants (n = 5 in each group) were randomly assigned to each radiotracer administration protocol and underwent simultaneous BOLD-fMRI/FDG-fPET scanning while viewing a flickering checkerboard. The bolus group received the full FDG dose in a standard bolus administration, the infusion group received the full FDG dose as a slow infusion over the duration of the scan, and the bolus-infusion group received 50% of the FDG dose as bolus and 50% as constant infusion. We validate the dataset by contrasting plasma radioactivity, grey matter mean uptake, and task-related activity in the visual cortex. CONCLUSIONS: The Monash DaCRA fPET-fMRI dataset provides significant reuse value for researchers interested in the comparison of signal dynamics in fPET, and its relationship with fMRI task-evoked activity.

Image processing plays a crucial role in maximising diagnostic quality of positron emission tomography (PET) images. Recently, deep learning methods developed across many fields have shown tremendous potential when applied to medical image enhancement, resulting in a rich and rapidly advancing literature surrounding this subject. This review encapsulates methods for integrating deep learning into PET image reconstruction and post-processing for low-dose imaging and resolution enhancement. A brief introduction to conventional image processing techniques in PET is firstly presented. We then review methods which integrate deep learning into the image reconstruction framework as either deep learning-based regularisation or as a fully data-driven mapping from measured signal to images. Deep learning-based post-processing methods for low-dose imaging, temporal resolution enhancement and spatial resolution enhancement are also reviewed. Finally, the challenges associated with applying deep learning to enhance PET images in the clinical setting are discussed and future research directions to address these challenges are presented.

INTRODUCTION: Neuroimaging-based 'brain age' can identify individuals with 'advanced' or 'resilient' brain aging. Brain-predicted age difference (brain-PAD) is predictive of cognitive and physical health outcomes. However, it is unknown how individual health and lifestyle factors may modify the relationship between brain-PAD and future cognitive or functional performance. We aimed to identify health-related subgroups of older individuals with resilient or advanced brain-PAD, and determine if membership in these subgroups is differentially associated with changes in cognition and frailty over three to five years. METHODS: Brain-PAD was predicted from T1-weighted images acquired from 326 community-dwelling older adults (73.8 ± 3.6 years, 42.3% female), recruited from the larger ASPREE (ASPirin in Reducing Events in the Elderly) trial. Participants were grouped as having resilient (n=159) or advanced (n=167) brain-PAD, and latent class analysis (LCA) was performed using a set of cognitive, lifestyle, and health measures. We examined associations of class membership with longitudinal change in cognitive function and frailty deficit accumulation index (FI) using linear mixed models adjusted for age, sex and education. RESULTS: Subgroups of resilient and advanced brain aging were comparable in all characteristics before LCA. Two typically similar latent classes were identified for both subgroups of brain agers: class 1 were characterized by low prevalence of obesity and better physical health and class 2 by poor cardiometabolic, physical and cognitive health. Among resilient brain agers, class 1 was associated with a decrease in cognition, and class 2 with an increase over 5 years, though was a small effect that was equivalent to a 0.04 standard deviation difference per year. No significant class distinctions were evident with FI. For advanced brain agers, there was no evidence of an association between class membership and changes in cognition or FI. CONCLUSION: These re

Evidence suggests classic psychedelics reduce the precision of belief updating and enable access to a range of alternate hypotheses that underwrite how we make sense of the world. This process, in the higher cortices, has been postulated to explain the therapeutic efficacy of psychedelics for the treatment of internalizing disorders. We argue reduced precision also underpins change to consciousness, known as "ego dissolution," and that alterations to consciousness and attention under psychedelics have a common mechanism of reduced precision of Bayesian belief updating. Evidence, connecting the role of serotonergic receptors to large-scale connectivity changes in the cortex, suggests the precision of Bayesian belief updating may be a mechanism to modify and investigate consciousness and attention.

OBJECTIVE: Emerging evidences suggest that the trans-neural propagation of phosphorylated 43-kDa transactive response DNA-binding protein (pTDP-43) contributes to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). We investigated whether Network Diffusion Model (NDM), a biophysical model of spread of pathology via the brain connectome, could capture the severity and progression of neurodegeneration (atrophy) in ALS. METHODS: We measured degeneration in limb-onset ALS patients (n = 14 at baseline, 12 at 6-months, and 9 at 12 months) and controls (n = 12 at baseline) using FreeSurfer analysis on the structural T1-weighted Magnetic Resonance Imaging (MRI) data. The NDM was simulated on the canonical structural connectome from the IIT Human Brain Atlas. To determine whether NDM could predict the atrophy pattern in ALS, the accumulation of pathology modelled by NDM was correlated against atrophy measured using MRI. In order to investigate whether network spread on the brain connectome derived from healthy individuals were significant findings, we compared our findings against network spread simulated on random networks. RESULTS: The cross-sectional analyses revealed that the network diffusion seeded from the inferior frontal gyrus (pars triangularis and pars orbitalis) significantly predicts the atrophy pattern in ALS compared to controls. Whereas, atrophy over time with-in the ALS group was best predicted by seeding the network diffusion process from the inferior temporal gyrus at 6-month and caudal middle frontal gyrus at 12-month. Network spread simulated on the random networks showed that the findings using healthy brain connectomes are significantly different from null models. INTERPRETATION: Our findings suggest the involvement of extra-motor regions in seeding the spread of pathology in ALS. Importantly, NDM was able to recapitulate the dynamics of pathological progression in ALS. Understanding the spatial shifts in the seeds of degeneration over time can p

Simultaneous magnetic resonance and positron emission tomography provides an opportunity to measure brain haemodynamics and metabolism in a single scan session, and to identify brain activations from multimodal measurements in response to external stimulation. However, there are few analysis methods available for jointly analysing the simultaneously acquired blood-oxygen-level dependant functional MRI (fMRI) and 18-F-fluorodeoxyglucose functional PET (fPET) datasets. In this work, we propose a new multimodality concatenated ICA (mcICA) method to identify joint fMRI-fPET brain activations in response to a visual stimulation task. The mcICA method produces a fused map from the multimodal datasets with equal contributions of information from both modalities, measured by entropy. We validated the method in silico, and applied it to an in vivo visual stimulation experiment. The mcICA method estimated the activated brain regions in the visual cortex modulated by both BOLD and FDG signals. The mcICA provides a fully data-driven analysis approach to analyse cerebral haemodynamic response and glucose uptake signals arising from exogenously induced neuronal activity.

Dyslexia is characterised by poor reading ability. Its aetiology is probably multifactorial, with abnormal visual processing playing an important role. Among adults with normal reading ability, there is a larger representation of central visual field in the primary visual cortex (V1) in those with more efficient visuospatial attention. In this study, we tested the hypothesis that poor reading ability in school-aged children (17 children with dyslexia, 14 control children with normal reading ability) is associated with deficits in visuospatial attention using a visual search task. We corroborated the psychophysical findings with neuroimaging, by measuring the functional size of V1 in response to a central 12° visual stimulus. Consistent with other literature, visual search was impaired and less efficient in the dyslexic children, particularly with more distractor elements in the search array (p=0.04). We also found atypical interhemispheric asymmetry in functional V1 size in the dyslexia group (p=0.02). Reading impaired children showed poorer visual search efficiency (p=0.01), needing more time per unit distractor (higher ms/item). Reading ability was also correlated with V1 size asymmetry (p=0.03), such that poorer readers showed less left hemisphere bias relative to the right hemisphere. Our findings support the view that dyslexic children have abnormal visuospatial attention and interhemispheric V1 asymmetry, relative to chronological age-matched peers, and that these factors may contribute to inter-individual variation in reading performance in children.

Functional positron emission tomography (fPET) imaging using continuous infusion of [18F]-fluorodeoxyglucose (FDG) is a novel neuroimaging technique to track dynamic glucose utilization in the brain. In comparison to conventional static or dynamic bolus PET, fPET maintains a sustained supply of glucose in the blood plasma which improves sensitivity to measure dynamic glucose changes in the brain, and enables mapping of dynamic brain activity in task-based and resting-state fPET studies. However, there is a trade-off between temporal resolution and spatial noise due to the low concentration of FDG and the limited sensitivity of multi-ring PET scanners. Images from fPET studies suffer from partial volume errors and residual scatter noise that may cause the cerebral metabolic functional maps to be biased. Gaussian smoothing filters used to denoise the fPET images are suboptimal, as they introduce additional partial volume errors. In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images. The performance of the MR guided method was compared with conventional denosing methods using both simulated and in vivo task fPET datasets. The results demonstrate that the MR-guided fPET framework denoises the fPET images and improves the partial volume correction, consequently enhancing the sensitivity to identify brain activation, and improving the anatomical accuracy for mapping changes of brain metabolism in response to a visual stimulation task. The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.

OBJECTIVE: Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. METHODS: A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole-brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. RESULTS: The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5-2.6). Cerebellar gray matter alterations were most pronounced in lobules I-VI (d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d = 0.6) and corticospinal tracts (d = 1.4). Earlier onset age predicted less volume in the motor cerebellum (rmax = 0.35) and peduncles (rmax = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax = -0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. INTERPRETATION: FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570-583.

An accurate measure of the complexity of patterns of cortical folding or gyrification is necessary for understanding normal brain development and neurodevelopmental disorders. Conventional gyrification indices (GIs) are calculated based on surface curvature (curvature-based GI) or an outer hull surface of the cortex (outer surface-based GI). The latter is dependent on the definition of the outer hull surface and a corresponding function between surfaces. In the present study, we propose the Laplace Beltrami-based gyrification index (LB-GI). This is a new curvature-based local GI computed using the first three Laplace Beltrami eigenfunction level sets. As with outer surface-based GI methods, this method is based on the hypothesis that gyrification stems from a flat surface during development. However, instead of quantifying gyrification with reference to corresponding points on an outer hull surface, LB-GI quantifies the gyrification at each point on the cortical surface with reference to their surrounding gyral points, overcoming several shortcomings of existing methods. The LB-GI was applied to investigate the cortical maturation profile of the human brain from preschool to early adulthood using the PING database. The results revealed more detail in patterns of cortical folding than conventional curvature-based methods, especially on frontal and posterior tips of the brain, such as the frontal pole, lateral occipital, lateral cuneus, and lingual. Negative associations of cortical folding with age were observed at cortical regions, including bilateral lingual, lateral occipital, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results also indicated positive significant associations between age and the LB-GI of bilateral insula, the medial orbitofrontal, frontal pole and rostral anterior cingulate regions. It is anticipated that the LB-GI will be advantageous in providing further insights in the understanding of brain development and degeneration

(Neuron 101, 365–369; February 6, 2019) In the original publication of this NeuroView, the member list for the Australian Brain Alliance was omitted. This has now been corrected online. Neuron apologizes for the error.

An implementation of Non‐Fourier chirp‐encoding in 3D Gradient Recalled Echo (GRE), susceptibility‐weighted imaging (SWI) and Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequences is presented with compressive sensing reconstruction. 3D GRE and MPRAGE sequences were designed, in which the phase encoding (PE) direction was encoded with spatially selective chirp encoding Radio Frequency (RF) pulses, while the slice and the readout directions were Fourier encoded using gradients. During each excitation along the PE direction, a different spatially‐selective RF excitation pulse was used to encode the PE direction with a complete set of unitary chirp encoding basis. Multichannel compressive sensing reconstruction on the undersampled in vivo data demonstrated that images reconstructed from chirp encoded data were able to preserve the spatial resolution better than the Fourier encoding. The mean Structural Similarity (SSIM) across five subjects at the acceleration factor of 6, for chirp encoded MPRAGE was 0.934 compared to 0.912 for Fourier encoded MPRAGE. The implementation of prospective undersampling demonstrated the feasibility of using chirp encoding in clinical practice for accelerated imaging. The minimum intensity projection of the compressive sensing (CS) reconstructed susceptibility weighted images revealed that chirp encoding is able to delineate small vessels better than the Fourier encoding with the SSIM of 0.960 for chirp encoding compared to the SSIM of 0.949 for the Fourier encoding. Improved performance of chirp encoding for CS reconstruction and SWI, along with the feasibility of implementation makes them a practical candidate for clinical MRI scans.

KEY POINTS: Unpleasant respiratory sensations contribute to morbidity in pulmonary disease. In rodents, these sensations are processed by nodose and jugular vagal sensory neurons, two distinct cell populations that differentially project to the airways and brainstem. Whether similar differences exist in bronchopulmonary sensory pathways in humans is unknown. We use functional magnetic resonance imaging during inhalation of capsaicin and ATP, showing that airway nodose pathways project centrally to the nucleus of the solitary tract, whereas jugular pathways input into the trigeminal brainstem nuclei. We also show differences between the efficacy of nodose and jugular stimuli to evoke cough and activity in motor control regions of the brain. Our data suggest that humans have two distinct vagal sensory neural systems governing airway sensations and this may have implications for the development of new antitussive therapies. ABSTRACT: In rodents, nodose vagal sensory neurons preferentially innervate the distal airways and terminate centrally in the nucleus of the solitary tract. By contrast, jugular vagal sensory neurons preferentially innervate the proximal airways and terminate in the paratrigeminal nucleus in the dorsolateral medulla. This differential organization suggests distinct roles for nodose and jugular pathways in respiratory sensory processing. However, it is unknown whether bronchopulmonary afferent pathways are similarly arranged in humans. We set out to investigate this using high resolution brainstem and whole brain functional magnetic resonance imaging in healthy human participants when they were inhaling stimuli known to differentially activate nodose and jugular pathways. Inhalation of capsaicin or ATP evoked respiratory sensations described as an urge-to-cough, although ATP was significantly less effective compared to capsaicin at evoking the motor act of coughing. The nodose and jugular neuron stimulant capsaicin increased blood oxygen level-depend

Resting-state connectivity measures the temporal coherence of the spontaneous neural activity of spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in the relative concentration of oxygenated and deoxygenated haemoglobin cause fluctuations in the MRI T2* signal. Since the BOLD signal detects changes in relative concentrations of oxy/deoxy-haemoglobin, individual differences in haemoglobin levels may influence the BOLD signal-to-noise ratio in a manner independent of the degree of neural activity. In this study, we examined whether group differences in haemoglobin may confound measures of functional connectivity. We investigated whether relationships between measures of functional connectivity and cognitive performance could be influenced by individual variability in haemoglobin. Finally, we mapped the neuroanatomical distribution of the influence of haemoglobin on functional connectivity to determine where group differences in functional connectivity are manifest. In a cohort of 518 healthy elderly subjects (259 men), each sex group was median-split into two groups with high and low haemoglobin concentration. Significant differences were obtained in functional connectivity between the high and low haemoglobin groups for both men and women (Cohen's d 0.17 and 0.03 for men and women respectively). The haemoglobin connectome in males showed a widespread systematic increase in functional connectivity correlation values, whilst the female connectome showed predominantly parietal and subcortical increases and temporo-parietal decreases. Despite the haemoglobin groups having no differences in cognitive measures, significant differences in the linear relationships between cognitive performance and functional connectivity were obtained for all 5 cognitive tests in males, and 4 out of 5 tests in females. Our findings confirm that individual variability in haemoglobin levels that give rise to group di

Friedreich ataxia is a progressive neurodegenerative disorder with reported abnormalities in cerebellar, brainstem, and cerebral white matter. White matter structure can be measured using in vivo neuroimaging indices sensitive to different white matter features. For the first time, we examined the relative sensitivity and relationship between multiple white matter indices in Friedreich ataxia to more richly characterize disease expression and infer possible mechanisms underlying the observed white matter abnormalities. Diffusion-tensor, magnetization transfer, and T1-weighted structural images were acquired from 31 individuals with Friedreich ataxia and 36 controls. Six white matter indices were extracted: fractional anisotropy, diffusivity (mean, axial, radial), magnetization transfer ratio (microstructure), and volume (macrostructure). For each index, whole-brain voxel-wise between-group comparisons and correlations with disease severity, onset age, and gene triplet-repeat length were undertaken. Correlations between pairs of indices were assessed in the Friedreich ataxia cohort. Spatial similarities in the voxel-level pattern of between-group differences across the indices were also assessed. Microstructural abnormalities were maximal in cerebellar and brainstem regions, but evident throughout the brain, while macroscopic abnormalities were restricted to the brainstem. Poorer microstructure and reduced macrostructural volume correlated with greater disease severity and earlier onset, particularly in peri-dentate nuclei and brainstem regions. Microstructural and macrostructural abnormalities were largely independent. Reduced fractional anisotropy was most strongly associated with axial diffusivity in cerebral tracts, and magnetization transfer in cerebellar tracts. Multiple mechanisms likely underpin white matter abnormalities in Friedreich ataxia, with differential impacts in cerebellar and cerebral pathways.

Pregnancy and the early postpartum period alter the structure of the brain; particularly in regions related to parental care. However, the enduring effects of this period on human brain structure and cognition in late life is unknown. Here we use magnetic resonance imaging to examine differences in cortical thickness related to parenthood in late life, for both sexes. In 235 healthy older women, we find a positive relationship between parity (number of children parented) and memory performance in mothers. Parity was also associated with differences in cortical thickness in women in the parahippocampus, precuneus, cuneus and pericalcarine sulcus. We also compared non-parents to parents of one child, in a sub-sample of older women (N = 45) and men (N = 35). For females, six regions differed in cortical thickness between parents and non-parents; these regions were consistent with those seen earlier in life in previous studies. For males, five regions differed in cortical thickness between parents and non-parents. We are first to reveal parenthood-related brain differences in late-life; our results are consistent with previously identified areas that are altered during pregnancy and the postpartum period. This study provides preliminary evidence to suggest that neural changes associated with early stages of parenthood persist into older age, and for women, may be related to marginally better cognitive outcomes.

Simultaneous [18 F]-fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging (FDG-PET/fMRI) provides the capability to image two sources of energetic dynamics in the brain - cerebral glucose uptake and the cerebrovascular haemodynamic response. Resting-state fMRI connectivity has been enormously useful for characterising interactions between distributed brain regions in humans. Metabolic connectivity has recently emerged as a complementary measure to investigate brain network dynamics. Functional PET (fPET) is a new approach for measuring FDG uptake with high temporal resolution and has recently shown promise for assessing the dynamics of neural metabolism. Simultaneous fMRI/fPET is a relatively new hybrid imaging modality, with only a few biomedical imaging research facilities able to acquire FDG PET and BOLD fMRI data simultaneously. We present data for n = 27 healthy young adults (18-20 yrs) who underwent a 95-min simultaneous fMRI/fPET scan while resting with their eyes open. This dataset provides significant re-use value to understand the neural dynamics of glucose metabolism and the haemodynamic response, the synchrony, and interaction between these measures, and the development of new single- and multi-modality image preparation and analysis procedures.

Neuroethics is central to the Australian Brain Initiative's aim to sustain a thriving and responsible neurotechnology industry. Diverse and inclusive community and stakeholder engagement and a trans-disciplinary approach to neuroethics will be key to the success of the Australian Brain Initiative.

Certain perceptual measures have been proposed as indirect assays of brain neurochemical status in people with migraine. One such measure is binocular rivalry, however, previous studies have not measured rivalry characteristics and brain neurochemistry together in people with migraine. This study compared spectroscopy-measured levels of GABA and Glx (glutamine and glutamate complex) in visual cortex between 16 people with migraine and 16 non-headache controls, and assessed whether the concentration of these neurochemicals explains, at least partially, inter-individual variability in binocular rivalry perceptual measures. Mean Glx level was significantly reduced in migraineurs relative to controls, whereas mean occipital GABA levels were similar between groups. Neither GABA levels, nor Glx levels correlated with rivalry percept duration. Our results thus suggest that the previously suggested relationship between rivalry percept duration and GABAergic inhibitory neurotransmitter concentration in visual cortex is not strong enough to enable rivalry percept duration to be reliably assumed to be a surrogate for GABA concentration, at least in the context of healthy individuals and those that experience migraine.

According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity.

BACKGROUND: Attenuation correction is one of the most crucial correction factors for accurate PET data quantitation in hybrid PET/MR scanners, and computing accurate attenuation coefficient maps from MR brain acquisitions is challenging. Here, we develop a method for accurate bone and air segmentation using MR ultrashort echo time (UTE) images. METHODS: MR UTE images from simultaneous MR and PET imaging of five healthy volunteers was used to generate a whole head, bone and air template image for inclusion into an improved MR derived attenuation correction map, and applied to PET image data for quantitative analysis. Bone, air and soft tissue were segmented based on Gaussian Mixture Models with probabilistic tissue maps as a priori information. We present results for two approaches for bone attenuation coefficient assignments: one using a constant attenuation correction value; and another using an estimated continuous attenuation value based on a calibration fit. Quantitative comparisons were performed to evaluate the accuracy of the reconstructed PET images, with respect to a reference image reconstructed with manually segmented attenuation maps. RESULTS: The DICE coefficient analysis for the air and bone regions in the images demonstrated improvements compared to the UTE approach, and other state-of-the-art techniques. The most accurate whole brain and regional brain analyses were obtained using constant bone attenuation coefficient values. CONCLUSIONS: A novel attenuation correction method for PET data reconstruction is proposed. Analyses show improvements in the quantitative accuracy of the reconstructed PET images compared to other state-of-the-art AC methods for simultaneous PET/MR scanners. Further evaluation is needed with radiopharmaceuticals other than FDG, and in larger cohorts of participants.

In humans, activity in the anterior midcingulate cortex (aMCC) is associated with both subjective thirst and swallowing. This region is therefore likely to play a prominent role in the regulation of drinking in response to dehydration. Using functional MRI, we investigated this possibility during a period of "drinking behavior" represented by a conjunction of preswallow and swallowing events. These events were examined in the context of a thirsty condition and an "oversated" condition, the latter induced by compliant ingestion of excess fluid. Brain regions associated with swallowing showed increased activity for drinking behavior in the thirsty condition relative to the oversated condition. These regions included the cingulate cortex, premotor areas, primary sensorimotor cortices, the parietal operculum, and the supplementary motor area. Psychophysical interaction analyses revealed increased functional connectivity between the same regions and the aMCC during drinking behavior in the thirsty condition. Functional connectivity during drinking behavior was also greater for the thirsty condition relative to the oversated condition between the aMCC and two subcortical regions, the cerebellum and the rostroventral medulla, the latter containing nuclei responsible for the swallowing reflex. Finally, during drinking behavior in the oversated condition, ratings of swallowing effort showed a negative association with functional connectivity between the aMCC and two cortical regions, the sensorimotor cortex and the supramarginal gyrus. The results of this study provide evidence that the aMCC helps facilitate swallowing during a state of thirst and is therefore likely to contribute to the regulation of drinking after dehydration.

Purpose: Quantitative susceptibility mapping (QSM) enables cerebral venous characterization and physiological measurements, such as oxygen extraction fraction (OEF). The exquisite sensitivity of QSM to deoxygenated blood makes it possible to image small veins; however partial volume effects must be addressed for accurate quantification. We present a new method, Iterative Cylindrical Fitting (ICF), to estimate voxel-based partial volume effects for susceptibility maps and use it to improve OEF quantification of small veins with diameters between 1.5 and 4 voxels. Materials and Methods: Simulated QSM maps were generated to assess the performance of the ICF method over a range of vein geometries with varying echo times and noise levels. The ICF method was also applied to in vivo human brain data to assess the feasibility and behavior of OEF measurements compared to the maximum intensity voxel (MIV) method. Results: Improved quantification of OEF measurements was achieved for vessels with contrast to noise greater than 3.0 and vein radii greater than 0.75 voxels. The ICF method produced improved quantitative accuracy of OEF measurement compared to the MIV approach (mean OEF error 7.7 vs. 12.4%). The ICF method provided estimates of vein radius (mean error <27%) and partial volume maps (root mean-squared error <13%). In vivo results demonstrated consistent estimates of OEF along vein segments. Conclusion: OEF quantification in small veins (1.5-4 voxels in diameter) had lower error when using partial volume estimates from the ICF method.

Numerous studies have explored the effects of transcranial electrical stimulation (tES) - including anodal transcranial direct current stimulation (a-tDCS), cathodal transcranial direct current stimulation (c-tDCS), transcranial alternative current stimulation (tACS), transcranial random noise stimulation (tRNS) and transcranial pulsed current stimulation (tPCS) - on corticospinal excitability (CSE) in healthy populations. However, the efficacy of these techniques and their optimal parameters for producing robust results has not been studied. Thus, the aim of this systematic review was to consolidate current knowledge about the effects of various parameters of a-tDCS, c-tDCS, tACS, tRNS and tPCS on the CSE of the primary motor cortex (M1) in healthy people. Leading electronic databases were searched for relevant studies published between January 1990 and February 2017; 126 articles were identified, and their results were extracted and analysed using RevMan software. The meta-analysis showed that a-tDCS application on the dominant side significantly increases CSE (P < 0.01) and that the efficacy of a-tDCS is dependent on current density and duration of application. Similar results were obtained for stimulation of M1 on the non-dominant side (P = 0.003). The effects of a-tDCS reduce significantly after 24 h (P = 0.006). Meta-analysis also revealed significant reduction in CSE following c-tDCS (P < 0.001) and significant increases after tRNS (P = 0.03) and tPCS (P = 0.01). However, tACS effects on CSE were only significant when the stimulation frequency was ≥140 Hz. This review provides evidence that tES has substantial effects on CSE in healthy individuals for a range of stimulus parameters.

Several studies have attributed certain visual perceptual alterations in older adults to a likely decrease in GABA (Gamma Aminobutyric Acid) concentration in visual cortex, an assumption based on findings in aged non-human primates. However, to our knowledge, there is no direct evidence for an age-related decrease in GABA concentration in human visual cortex. Here, we estimated visual cortical GABA levels and Glx (combined estimate of glutamate and glutamine) levels using magnetic resonance spectroscopy. We also measured performance for two visual tasks that are hypothesised to be mediated, at least in part, by GABAergic inhibition: spatial suppression of motion and binocular rivalry. Our results show increased visual cortical GABA levels, and reduced Glx levels, in older adults. Perceptual performance differed between younger and older groups for both tasks. When subjects of all ages were combined, visual cortical GABA levels but not Glx levels correlated with perceptual performance. No relationship was found between perception and GABA levels in dorsolateral prefrontal cortex. Perceptual measures and GABA were not correlated when either age group was considered separately. Our results challenge current assumptions regarding neurobiological changes that occur within the aging human visual cortex and their association with certain age-related changes in visual perception.

Monitoring of pulmonary physiology is fundamental to the clinical management of patients with Cystic Fibrosis. The current standard clinical practise uses spirometry to assess lung function which delivers a clinically relevant functional readout of total lung function, however does not supply any visible or localised information. High Resolution Computed Tomography (HRCT) is a well-established current 'gold standard' method for monitoring lung anatomical changes in Cystic Fibrosis patients. HRCT provides excellent morphological information, however, the X-ray radiation dose can become significant if multiple scans are required to monitor chronic diseases such as cystic fibrosis. X-ray phase-contrast imaging is another emerging X-ray based methodology for Cystic Fibrosis lung assessment which provides dynamic morphological and functional information, albeit with even higher X-ray doses than HRCT. Magnetic Resonance Imaging (MRI) is a non-ionising radiation imaging method that is garnering growing interest among researchers and clinicians working with Cystic Fibrosis patients. Recent advances in MRI have opened up the possibilities to observe lung function in real time to potentially allow sensitive and accurate assessment of disease progression. The use of hyperpolarized gas or non-contrast enhanced MRI can be tailored to clinical needs. While MRI offers significant promise it still suffers from poor spatial resolution and the development of an objective scoring system especially for ventilation assessment.

Previous studies have reported diffusion tensor imaging (DTI) changes within the optic radiations of patients after optic neuritis (ON). We aimed to study optic radiation DTI changes over 12 months following acute ON and to study correlations between DTI parameters and damage to the optic nerve and primary visual cortex (V1). We measured DTI parameters [fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD)] from the optic radiations of 38 acute ON patients at presentation and 6 and 12 months after acute ON. In addition, we measured retinal nerve fibre layer thickness, visual evoked potential amplitude, optic radiation lesion load, and V1 thickness. At baseline, FA was reduced and RD and MD were increased compared to control. Over 12 months, FA reduced in patients at an average rate of -2.6% per annum (control = -0.51%; p = 0.006). Change in FA, RD, and MD correlated with V1 thinning over 12 months (FA: R = 0.450, p = 0.006; RD: R = -0.428, p = 0.009; MD: R = -0.365, p = 0.029). In patients with no optic radiation lesions, AD significantly correlated with RNFL thinning at 12 months (R = 0.489, p = 0.039). In conclusion, DTI can detect optic radiation changes over 12 months following acute ON that correlate with optic nerve and V1 damage.

Huntington disease (HD) is a fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Non-motor symptoms and signs such as psychiatric disturbances, sleep problems and metabolic dysfunction are part of the disease manifestation. These aspects may relate to changes in the hypothalamus, an area of the brain involved in the regulation of emotion, sleep and metabolism. Neuropathological and imaging studies using both voxel-based morphometry (VBM) of magnetic resonance imaging (MRI) as well as positron emission tomography (PET) have demonstrated pathological changes in the hypothalamic region during early stages in symptomatic HD. In this investigation, we aimed to establish a robust method for measurements of the hypothalamic volume in MRI in order to determine whether the hypothalamic dysfunction in HD is associated with the volume of this region. Using T1-weighted imaging, we describe a reproducible delineation procedure to estimate the hypothalamic volume which was based on the same landmarks used in histologically processed postmortem hypothalamic tissue. Participants included 36 prodromal HD (pre-HD), 33 symptomatic HD (symp-HD) and 33 control participants who underwent MRI scanning at baseline and 18 months follow-up as part of the IMAGE-HD study. We found no evidence of cross-sectional or longitudinal changes between groups in hypothalamic volume. Our results suggest that hypothalamic pathology in HD is not associated with volume changes.

BACKGROUND: Biomedical imaging research increasingly involves acquiring, managing and processing large amounts of distributed imaging data. Integrated systems that combine data, meta-data and workflows are crucial for realising the opportunities presented by advances in imaging facilities. METHODS: This paper describes the design, implementation and operation of a multi-modality research imaging data management system that manages imaging data obtained from biomedical imaging scanners operated at Monash Biomedical Imaging (MBI), Monash University in Melbourne, Australia. In addition to Digital Imaging and Communications in Medicine (DICOM) images, raw data and non-DICOM biomedical data can be archived and distributed by the system. Imaging data are annotated with meta-data according to a study-centric data model and, therefore, scientific users can find, download and process data easily. RESULTS: The research imaging data management system ensures long-term usability, integrity inter-operability and integration of large imaging data. Research users can securely browse and download stored images and data, and upload processed data via subject-oriented informatics frameworks including the Distributed and Reflective Informatics System (DaRIS), and the Extensible Neuroimaging Archive Toolkit (XNAT).

The antisaccade task provides a model paradigm that sets the inhibition of a reflexively driven behavior against the volitional control of a goal-directed behavior. The stability and adaptability of antisaccade performance was investigated in 23 neurologically healthy individuals. Behavior and brain function were measured using functional magnetic resonance imaging (fMRI) prior to and immediately following 2 weeks of daily antisaccade training. Participants performed antisaccade trials faster with no change in directional error rate following 2 weeks of training; however this increased speed came at the cost of the spatial accuracy of the saccade (gain) which became more hypometric following training. Training on the antisaccade task resulted in increases in fMRI activity in the fronto-basal ganglia-parietal-cerebellar ocular motor network. Following training, antisaccade latency was positively associated with fMRI activity in the frontal and supplementary eye fields, anterior cingulate and intraparietal sulcus; antisaccade gain was negatively associated with fMRI activity in supplementary eye fields, anterior cingulate, intraparietal sulcus, and cerebellar vermis. In sum, the results suggest that following training, larger antisaccade latency is associated with larger activity in fronto-parietal-cerebellar ocular motor regions, and smaller antisaccade gain is associated with larger activity in fronto-parietal ocular motor regions.

Brain pathology in Friedreich ataxia is characterized by progressive degeneration of nervous tissue in the brainstem, cerebellum and cerebellar peduncles. Evidence of cerebral involvement is however equivocal. This brain imaging study investigates cerebello-cerebral white matter connectivity in Friedreich ataxia with diffusion MRI and tractography performed in 13 individuals homozygous for a GAA expansion in intron one of the frataxin gene and 14 age- and gender-matched control participants. New evidence is presented for disrupted cerebello-cerebral connectivity in the disease, leading to secondary effects in distant cortical and subcortical regions. Remote regions affected by primary cerebellar and brainstem pathology include the supplementary motor area, cingulate cortex, frontal cortices, putamen and other subcortical nuclei. The connectivity disruptions identified provide an explanation for some of the non-ataxic symptoms observed in the disease and support the notion of reverse cerebellar diaschisis. This is the first study to comprehensively map white matter connectivity disruptions in Friedreich ataxia using tractography, connectomic techniques and super-resolution track density imaging.

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research.

The aims of this study were to investigate regional white matter microstructural differences between very preterm (VPT) (<30 weeks' gestational age and/or <1250 g) and full term (FT) (≥37 weeks' gestational age) infants at term corrected age with diffusion tensor imaging, and to explore perinatal predictors of diffusion measures, and the relationship between regional diffusion measures and neurodevelopmental outcomes at age 7 years in VPT children. Mean (MD) (p = .003), axial (AD) (p = .008), and radial diffusivity (RD) (p = .003) in total white matter were increased in VPT compared with FT infants, with similar fractional anisotropy (FA) in the two groups. There was little evidence that group-wise differences were specific to any of the 8 regions studied for each hemisphere. Perinatal white matter abnormality and intraventricular hemorrhage (grade III or IV) were associated with increased diffusivity in the white matter of VPT infants. Higher white matter diffusivity measures of the inferior occipital and cerebellar region at term-equivalent age were associated with increased risk of impairments in motor and executive function at 7 years in VPT children, but there was little evidence for associations with IQ or memory impairment. In conclusion, myelination is likely disrupted or delayed in VPT infants, especially those with perinatal brain abnormality (BA). Altered diffusivity at term-equivalent age helps explain impaired functioning at 7 years. This study defines the nature of microstructural alterations in VPT infant white matter, assists in understanding the associated risk factors, and is the first study to reveal an important link between inferior occipital and cerebellar white matter disorganization in infancy, and executive and motor functioning 7 years later.

BACKGROUND AND AIM: High tidal volume (VT) ventilation during resuscitation of preterm lambs results in brain injury evident histologically within hours after birth. We aimed to investigate whether magnetic resonance spectroscopy (MRS) and/or diffusion tensor imaging (DTI) can be used for early in vivo detection of ventilation-induced brain injury in preterm lambs. METHODS: Newborn lambs (0.85 gestation) were stabilized with a "protective ventilation" strategy (PROT, n = 7: prophylactic Curosurf, sustained inflation, VT 7 mL/kg, positive end expiratory pressure (PEEP) 5 cmH2O) or an initial 15 minutes of "injurious ventilation" (INJ, n = 10: VT 12 mL/kg, no PEEP, late Curosurf) followed by PROT ventilation for the remainder of the experiment. At 1 hour, lambs underwent structural magnetic resonance imaging (Siemens, 3 Tesla). For measures of mean/axial/radial diffusivity (MD, AD, RD) and fractional anisotropy (FA), 30 direction DTI was performed. Regions of interests encompassed the thalamus, internal capsule, periventricular white matter and the cerebellar vermis. MRS was performed using a localized single-voxel (15×15×20 mm3, echo time 270 ms) encompassing suptratentorial deep nuclear grey matter and central white matter. Peak-area ratios for lactate (Lac) relative to N-acetylaspartate (NAA), choline (Cho) and creatine (Cr) were calculated. Groups were compared using 2-way RM-ANOVA, Mann-Whitney U-test and Spearman's correlations. RESULTS: No cerebral injury was seen on structural MR images. Lambs in the INJ group had higher mean FA and lower mean RD in the thalamus compared to PROT lambs, but not in the other regions of interest. Peak-area lactate ratios >1.0 was only seen in INJ lambs. A trend of higher mean peak-area ratios for Lac/Cr and Lac/Cho was seen, which correlated with lower pH in both groups. CONCLUSION: Acute changes in brain diffusion measures and metabolite peak-area ratios were observed after injurious ventilation. Early MRS/DTI is able to detect

Atrophy of the dentate nucleus is one of the major neuropathological changes in Friedreich ataxia (FRDA). Neuroimaging studies demonstrated white matter (WM) degeneration in FRDA. In this study, we used advanced tractography techniques to quantitatively measure WM changes in the dentato-thalamic and dentato-rubral tracts, and correlated these changes with cognitive profiles of FRDA. We also analysed diffusivity changes of the thalamo-cortical tract to assess whether neurological degeneration of WM extends beyond the primary site of involvement in FRDA. Twelve genetically proven individuals with FRDA and 14 controls were recruited. Sixty directions diffusion tensor images were acquired. The WM bundles from the dentate nucleus were estimated using a constrained spherical deconvolution method and the diffusivity characteristics measured. The Simon task was used to assess cognitive profile of FRDA. The dentato-rubral, dentato-thalamic and thalamo-cortical tracts manifested significantly lower fractional anisotropy, higher mean diffusivity and increased radial diffusivity in FRDA compared with controls. There was no difference in axial diffusivity between the two groups. The mean and radial diffusivity of the dentato-rubral tract was positively correlated with choice reaction time, congruent reaction time, incongruent reaction time and Simon effect reaction time and negatively with the larger GAA repeat. Significant changes in diffusivity characteristics were observed in the dentato-thalamic and thalamo-cortical tracts, suggesting extensive WM degeneration and affected WM structures in FRDA. Correlation of WM changes in the dentato-rubral tract with the cognitive assessment suggested that this tract is an important contributor to cognitive disturbances in FRDA.