Emer Hughes

Fasting biases brain reward systems towards high-calorie foods.

Nutritional state (e.g. fasted vs. fed) and different food stimuli (e.g. high‐calorie vs. low‐calorie, or appetizing vs. bland foods) are both recognized to change activity in brain reward systems. Using functional magnetic resonance imaging, we have studied the interaction between nutritional state and different food stimuli on brain food reward systems. We examined how blood oxygen level‐dependent activity within a priori regions of interest varied while viewing pictures of high‐calorie and low‐calorie foods. Pictures of non‐food household objects were included as control stimuli. During scanning, subjects rated the appeal of each picture. Twenty non‐obese healthy adults [body mass index 22.1 ± 0.5 kg/m2 (mean ± SEM), age range 19–35 years, 10 male] were scanned on two separate mornings between 11:00 and 12:00 h, once after eating a filling breakfast (‘fed’: 1.6 ± 0.1 h since breakfast), and once after an overnight fast but skipping breakfast (‘fasted’: 15.9 ± 0.3 h since supper) in a randomized cross‐over design. Fasting selectively increased activation to pictures of high‐calorie over low‐calorie foods in the ventral striatum, amygdala, anterior insula, and medial and lateral orbitofrontal cortex (OFC). Furthermore, fasting enhanced the subjective appeal of high‐calorie more than low‐calorie foods, and the change in appeal bias towards high‐calorie foods was positively correlated with medial and lateral OFC activation. These results demonstrate an interaction between homeostatic and hedonic aspects of feeding behaviour, with fasting biasing brain reward systems towards high‐calorie foods.

Regional changes in thalamic shape and volume with increasing age.

The thalamus undergoes significant volume loss and microstructural change with increasing age. Alterations in thalamo-cortical connectivity may contribute to the decline in cognitive ability associated with aging. The aim of this study was to assess changes in thalamic shape and in the volume and diffusivity of thalamic regions parcellated by their connectivity to specific cortical regions in order to test the hypothesis age related thalamic change primarily affects thalamic nuclei connecting to the frontal cortex. Using structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI), we assessed thalamic volume and diffusivity in 86 healthy volunteers, median (range) age 44 (20–74) years. Regional thalamic micro and macro structural changes were assessed by segmenting the thalamus based on connectivity to the frontal, parietal, temporal and occipital cortices and determining the volumes and mean diffusivity of the thalamic projections. Linear regression analysis was performed to test the relationship between increasing age and (i) normalised thalamic volume, (ii) whole thalamus diffusion measures, (iii) mean diffusivity (MD) of the thalamo-cortical projections, and (iv) volumes of the thalamo-cortical projections. We also assessed thalamic shape change using vertex analysis. We observed a significant reduction in the volume and a significant increase in MD of the whole thalamus with increasing age. The volume of the thalamo-frontal projections decreased significantly with increasing age, however there was no significant relationship between the volumes of the thalamo-cortical projections to the parietal, temporal, and occipital cortex and age. Thalamic shape analysis showed that the greatest shape change was in the anterior thalamus, incorporating regions containing the anterior nucleus, the ventroanterior nucleus and the dorsomedial nucleus. To explore these results further we studied two additional groups of subjects (a younger and an older aged group, n = 20), which showed that the volume of the thalamo-frontal projections was correlated to executive functions scores, as assessed by the Stroop test. These data suggest that atrophy of the frontal thalamo-cortical unit may explain, at least in part, disorders of attention, working memory and executive function associated with increasing age.

Early development of structural networks and the impact of prematurity on brain connectivity

ABSTRACT Preterm infants are at high risk of neurodevelopmental impairment, which may be due to altered development of brain connectivity. We aimed to (i) assess structural brain development from 25 to 45 weeks gestational age (GA) using graph theoretical approaches and (ii) test the hypothesis that preterm birth results in altered white matter network topology. Sixty‐five infants underwent MRI between 25+3 and 45+6 weeks GA. Structural networks were constructed using constrained spherical deconvolution tractography and were weighted by measures of white matter microstructure (fractional anisotropy, neurite density and orientation dispersion index). We observed regional differences in brain maturation, with connections to and from deep grey matter showing most rapid developmental changes during this period. Intra‐frontal, frontal to cingulate, frontal to caudate and inter‐hemispheric connections matured more slowly. We demonstrated a core of key connections that was not affected by GA at birth. However, local connectivity involving thalamus, cerebellum, superior frontal lobe, cingulate gyrus and short range cortico‐cortical connections was related to the degree of prematurity and contributed to altered global topology of the structural brain network. The relative preservation of core connections at the expense of local connections may support more effective use of impaired white matter reserve following preterm birth. Graphical abstract Figure. No Caption available. HighlightsFirst characterisation of preterm brain networks weighted by microstructural features.Preterm brain is resistant to disruptions in development of core connections.Peripheral connections associated with cognition and behaviour are more vulnerable.

A dedicated neonatal brain imaging system

The goal of the Developing Human Connectome Project is to acquire MRI in 1000 neonates to create a dynamic map of human brain connectivity during early development. High‐quality imaging in this cohort without sedation presents a number of technical and practical challenges.

Glutamate, N-acetyl aspartate and psychotic symptoms in chronic ketamine users

RationaleKetamine, a non-competitive NMDA receptor antagonist, induces acute effects resembling the positive, negative and cognitive symptoms of schizophrenia. Chronic use has been suggested to lead to persistent schizophrenia-like neurobiological changes.ObjectivesThis study aims to test the hypothesis that chronic ketamine users have changes in brain neurochemistry and increased subthreshold psychotic symptoms compared to matched poly-drug users.MethodsFifteen ketamine users and 13 poly-drug users were included in the study. Psychopathology was assessed using the Comprehensive Assessment of At-Risk Mental State. Creatine-scaled glutamate (Glu/Cr), glutamate + glutamine (Glu + Gln/Cr) and N-acetyl aspartate (NAA/Cr) were measured in three brain regions—anterior cingulate, left thalamus and left medial temporal cortex using proton magnetic resonance spectroscopy.ResultsChronic ketamine users had higher levels of subthreshold psychotic symptoms (p < 0.005, Cohen’s d = 1.48) and lower thalamic NAA/Cr (p < 0.01, d = 1.17) compared to non-users. There were no differences in medial temporal cortex or anterior cingulate NAA/Cr or in Glu/Cr or Glu + Gln/Cr in any brain region between the two groups. In chronic ketamine users, CAARMS severity of abnormal perceptions was directly correlated with anterior cingulate Glu/Cr (p < 0.05, r = 0.61—uncorrected), but NAA/Cr was not related to any measures of psychopathology.ConclusionsThe finding of lower thalamic NAA/Cr in chronic ketamine users may be secondary to the effects of ketamine use compared to other drugs of abuse and resembles previous reports in individuals at genetic or clinical risk of schizophrenia.

Long-term heavy ketamine use is associated with spatial memory impairment and altered hippocampal activation

Ketamine, a non-competitive N-methyl-d-aspartate receptor antagonist, is rising in popularity as a drug of abuse. Preliminary evidence suggests that chronic, heavy ketamine use may have profound effects on spatial memory but the mechanism of these deficits is as yet unclear. This study aimed to examine the neural mechanism by which heavy ketamine use impairs spatial memory processing. In a sample of 11 frequent ketamine users and 15 poly-drug controls, matched for IQ, age, years in education. We used fMRI utilizing an ROI approach to examine the neural activity of three regions known to support successful navigation; the hippocampus, parahippocampal gyrus, and the caudate nucleus during a virtual reality task of spatial memory. Frequent ketamine users displayed spatial memory deficits, accompanied by and related to, reduced activation in both the right hippocampus and left parahippocampal gyrus during navigation from memory, and in the left caudate during memory updating, compared to controls. Ketamine users also exhibited schizotypal and dissociative symptoms that were related to hippocampal activation. Impairments in spatial memory observed in ketamine users are related to changes in medial temporal lobe activation. Disrupted medial temporal lobe function may be a consequence of chronic ketamine abuse and may relate to schizophrenia-like symptomatology observed in ketamine users.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

Multimodal surface matching with higher-order smoothness constraints.

&NA; In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies, and cortical surface‐based alignment has generally been accepted to be superior to volume‐based approaches at aligning cortical areas. However, human subjects have considerable variation in cortical folding, and in the location of functional areas relative to these folds. This makes alignment of cortical areas a challenging problem. The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. Using MSM, we have previously shown that driving cross‐subject surface alignment, using areal features, such as resting state‐networks and myelin maps, improves group task fMRI statistics and map sharpness. However, the initial implementation of MSMs regularisation function did not penalize all forms of surface distortion evenly. In some cases, this allowed peak distortions to exceed neurobiologically plausible limits, unless regularisation strength was increased to a level which prevented the algorithm from fully maximizing surface alignment. Here we propose and implement a new regularisation penalty, derived from physically relevant equations of strain (deformation) energy, and demonstrate that its use leads to improved and more robust alignment of multimodal imaging data. In addition, since spherical warps incorporate projection distortions that are unavoidable when mapping from a convoluted cortical surface to the sphere, we also propose constraints that enforce smooth deformation of cortical anatomies. We test the impact of this approach for longitudinal modelling of cortical development for neonates (born between 31 and 43 weeks of post‐menstrual age) and demonstrate that the proposed method increases the biological interpretability of the distortion fields and improves the statistical significance of population‐based analysis relative to other spherical methods. HighlightsAdvances the Multimodal Surface Matching (MSM) method, for cortical surface registration of cortical surfaces, by improving control over the smoothness of the deformation.Enhances alignment of multimodal features, including the feature set used for the Human Connectome Projects parcellation of the human cerebral cortex.Also allows statistical modelling of longitudinal patterns of cortical growth.

Sensitivity Encoding for Aligned Multishot Magnetic Resonance Reconstruction

This paper introduces a framework for the reconstruction of magnetic resonance images in the presence of rigid motion. The rationale behind our proposal is to make use of the partial k-space information provided by multiple receiver coils in order to estimate the position of the imaged object throughout the shots that contribute to the image. The estimated motion is incorporated into the reconstruction model in an iterative manner to obtain a motion-free image. The method is parameter-free, does not assume any prior model for the image to be reconstructed, avoids blurred images due to resampling, does not make use of external sensors, and does not require modifications in the acquisition sequence. Validation is performed using synthetically corrupted data to study the limits for full motion-recovered reconstruction in terms of the amount of motion, encoding trajectories, number of shots and availability of prior information, and to compare with the state of the art. Quantitative and visual results of its application to a highly challenging volumetric brain imaging cohort of 207 neonates are also presented, showing the ability of the proposed reconstruction to generally improve the quality of reconstructed images, as evaluated by both sparsity and gradient entropy based metrics.

Three‐dimensional motion corrected sensitivity encoding reconstruction for multi‐shot multi‐slice MRI: Application to neonatal brain imaging

To introduce a methodology for the reconstruction of multi‐shot, multi‐slice magnetic resonance imaging able to cope with both within‐plane and through‐plane rigid motion and to describe its application in structural brain imaging.