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Dive into the research topics where Martina F. Callaghan is active.

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Featured researches published by Martina F. Callaghan.


Neurobiology of Aging | 2014

Widespread age-related differences in the human brain microstructure revealed by quantitative magnetic resonance imaging

Martina F. Callaghan; Patrick Freund; Bogdan Draganski; Elaine J. Anderson; Marinella Cappelletti; Rumana Chowdhury; Joern Diedrichsen; Thomas H. B. FitzGerald; Peter Smittenaar; Gunther Helms; Antoine Lutti; Nikolaus Weiskopf

A pressing need exists to disentangle age-related changes from pathologic neurodegeneration. This study aims to characterize the spatial pattern and age-related differences of biologically relevant measures in vivo over the course of normal aging. Quantitative multiparameter maps that provide neuroimaging biomarkers for myelination and iron levels, parameters sensitive to aging, were acquired from 138 healthy volunteers (age range: 19–75 years). Whole-brain voxel-wise analysis revealed a global pattern of age-related degeneration. Significant demyelination occurred principally in the white matter. The observed age-related differences in myelination were anatomically specific. In line with invasive histologic reports, higher age-related differences were seen in the genu of the corpus callosum than the splenium. Iron levels were significantly increased in the basal ganglia, red nucleus, and extensive cortical regions but decreased along the superior occipitofrontal fascicle and optic radiation. This whole-brain pattern of age-associated microstructural differences in the asymptomatic population provides insight into the neurobiology of aging. The results help build a quantitative baseline from which to examine and draw a dividing line between healthy aging and pathologic neurodegeneration.


Proceedings of the National Academy of Sciences of the United States of America | 2016

Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome

Kirstie J. Whitaker; Petra E. Vértes; Rafael Romero-Garcia; Michael Moutoussis; Gita Prabhu; Nikolaus Weiskopf; Martina F. Callaghan; Konrad Wagstyl; Timothy Rittman; Roger Tait; Cinly Ooi; John Suckling; Becky Inkster; Peter Fonagy; R. J. Dolan; Peter B. Jones; Ian M. Goodyer; Edward T. Bullmore

Significance Adolescence is a period of human brain growth and high incidence of mental health disorders. Here, we show consistently in two MRI cohorts that human brain changes in adolescence were concentrated on the more densely connected hubs of the connectome (i.e., association cortical regions that mediated efficient connectivity throughout the human brain structural network). Hubs were less myelinated at 14 y but had faster rates of myelination and cortical shrinkage in the 14- to 24-y period. This topologically focused process of cortical consolidation was associated with expression of genes enriched for normal synaptic and myelin-related processes and risk of schizophrenia. Consolidation of anatomical network hubs could be important for normal and clinically disordered adolescent brain development. How does human brain structure mature during adolescence? We used MRI to measure cortical thickness and intracortical myelination in 297 population volunteers aged 14–24 y old. We found and replicated that association cortical areas were thicker and less myelinated than primary cortical areas at 14 y. However, association cortex had faster rates of shrinkage and myelination over the course of adolescence. Age-related increases in cortical myelination were maximized approximately at the internal layer of projection neurons. Adolescent cortical myelination and shrinkage were coupled and specifically associated with a dorsoventrally patterned gene expression profile enriched for synaptic, oligodendroglial- and schizophrenia-related genes. Topologically efficient and biologically expensive hubs of the brain anatomical network had greater rates of shrinkage/myelination and were associated with overexpression of the same transcriptional profile as cortical consolidation. We conclude that normative human brain maturation involves a genetically patterned process of consolidating anatomical network hubs. We argue that developmental variation of this consolidation process may be relevant both to normal cognitive and behavioral changes and the high incidence of schizophrenia during human brain adolescence.


Current Opinion in Neurology | 2015

Advances in MRI-based computational neuroanatomy: from morphometry to in-vivo histology

Nikolaus Weiskopf; Siawoosh Mohammadi; Antoine Lutti; Martina F. Callaghan

PURPOSE OF REVIEW Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.


Frontiers in Neuroscience | 2015

Whole-Brain In-vivo Measurements of the Axonal G-Ratio in a Group of 37 Healthy Volunteers.

Siawoosh Mohammadi; Daniel Carey; Fred Dick; Joern Diedrichsen; Martin I. Sereno; Marco Reisert; Martina F. Callaghan; Nikolaus Weiskopf

The g-ratio, quantifying the ratio between the inner and outer diameters of a fiber, is an important microstructural characteristic of fiber pathways and is functionally related to conduction velocity. We introduce a novel method for estimating the MR g-ratio non-invasively across the whole brain using high-fidelity magnetization transfer (MT) imaging and single-shell diffusion MRI. These methods enabled us to map the MR g-ratio in vivo across the brains prominent fiber pathways in a group of 37 healthy volunteers and to estimate the inter-subject variability. Effective correction of susceptibility-related distortion artifacts was essential before combining the MT and diffusion data, in order to reduce partial volume and edge artifacts. The MR g-ratio is in good qualitative agreement with histological findings despite the different resolution and spatial coverage of MRI and histology. The MR g-ratio holds promise as an important non-invasive biomarker due to its microstructural and functional relevance in neurodegeneration.


Magnetic Resonance in Medicine | 2015

A general linear relaxometry model of R1 using imaging data

Martina F. Callaghan; Gunther Helms; Antoine Lutti; Siawoosh Mohammadi; Nikolaus Weiskopf

The longitudinal relaxation rate (R1) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort.


NeuroImage | 2016

Specific white matter tissue microstructure changes associated with obesity

Stephanie Kullmann; Martina F. Callaghan; Martin Heni; Nikolaus Weiskopf; Klaus Scheffler; Hans-Ulrich Häring; Andreas Fritsche; Ralf Veit; Hubert Preissl

Obesity-related structural brain alterations point to a consistent reduction in gray matter with increasing body mass index (BMI) but changes in white matter have proven to be more complex and less conclusive. Hence, more recently diffusion tensor imaging (DTI) has been employed to investigate microstructural changes in white matter structure. Altogether, these studies have mostly shown a loss of white matter integrity with obesity-related factors in several brain regions. However, the variety of these obesity-related factors, including inflammation and dyslipidemia, resulted in competing influences on the DTI indices. To increase the specificity of DTI results, we explored specific brain tissue properties by combining DTI with quantitative multi-parameter mapping in lean, overweight and obese young adults. By means of multi-parameter mapping, white matter structures showed differences in MRI parameters consistent with reduced myelin, increased water and altered iron content with increasing BMI in the superior longitudinal fasciculus, anterior thalamic radiation, internal capsule and corpus callosum. BMI-related changes in DTI parameters revealed mainly alterations in mean and axial diffusivity with increasing BMI in the corticospinal tract, anterior thalamic radiation and superior longitudinal fasciculus. These alterations, including mainly fiber tracts linking limbic structures with prefrontal regions, could potentially promote accelerated aging in obese individuals leading to an increased risk for cognitive decline.


Frontiers in Neuroscience | 2015

An evaluation of prospective motion correction (PMC) for high resolution quantitative MRI

Martina F. Callaghan; Oliver Josephs; Michael Herbst; Maxim Zaitsev; Nick Todd; Nikolaus Weiskopf

Quantitative imaging aims to provide in vivo neuroimaging biomarkers with high research and diagnostic value that are sensitive to underlying tissue microstructure. In order to use these data to examine intra-cortical differences or to define boundaries between different myelo-architectural areas, high resolution data are required. The quality of such measurements is degraded in the presence of motion hindering insight into brain microstructure. Correction schemes are therefore vital for high resolution, whole brain coverage approaches that have long acquisition times and greater sensitivity to motion. Here we evaluate the use of prospective motion correction (PMC) via an optical tracking system to counter intra-scan motion in a high resolution (800 μm isotropic) multi-parameter mapping (MPM) protocol. Data were acquired on six volunteers using a 2 × 2 factorial design permuting the following conditions: PMC on/off and motion/no motion. In the presence of head motion, PMC-based motion correction considerably improved the quality of the maps as reflected by fewer visible artifacts and improved consistency. The precision of the maps, parameterized through the coefficient of variation in cortical sub-regions, showed improvements of 11–25% in the presence of deliberate head motion. Importantly, in the absence of motion the PMC system did not introduce extraneous artifacts into the quantitative maps. The PMC system based on optical tracking offers a robust approach to minimizing motion artifacts in quantitative anatomical imaging without extending scan times. Such a robust motion correction scheme is crucial in order to achieve the ultra-high resolution required of quantitative imaging for cutting edge in vivo histology applications.


NeuroImage | 2015

Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking

Nick Todd; Oliver Josephs; Martina F. Callaghan; Antoine Lutti; Nikolaus Weiskopf

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequences RF excitation and gradient waveforms such that the field-of-view was realigned to match the subjects head movement. Task-free fMRI experiments on five healthy volunteers followed a 2 × 2 × 3 factorial design with the following factors: PMC on or off; 3.0 mm or 1.5 mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5 mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p < 0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.


Journal of Neuroscience Methods | 2017

Flexible head-casts for high spatial precision MEG

Sofie S. Meyer; James John Bonaiuto; Mark Lim; Holly Rossiter; Sheena Waters; David Bradbury; Sven Bestmann; Matthew J. Brookes; Martina F. Callaghan; Nikolaus Weiskopf; Gareth R. Barnes

Highlights • We propose a method for constructing flexible head-casts to stabilize the head during MEG scanning.• Co-registration error is minimized by using MRI images to pre-define fiducial coil locations.• Within- and between-session movement is <0.25 and <1 mm respectively.• This enables high reproducibility of source level results.


Current Biology | 2017

The Brain Basis for Misophonia

Sukhbinder Kumar; Olana Tansley-Hancock; William Sedley; Joel S. Winston; Martina F. Callaghan; Micah Allen; Thomas E. Cope; Phillip E. Gander; Doris-Eva Bamiou; Timothy D. Griffiths

Summary Misophonia is an affective sound-processing disorder characterized by the experience of strong negative emotions (anger and anxiety) in response to everyday sounds, such as those generated by other people eating, drinking, chewing, and breathing [1, 2, 3, 4, 5, 6, 7, 8]. The commonplace nature of these sounds (often referred to as “trigger sounds”) makes misophonia a devastating disorder for sufferers and their families, and yet nothing is known about the underlying mechanism. Using functional and structural MRI coupled with physiological measurements, we demonstrate that misophonic subjects show specific trigger-sound-related responses in brain and body. Specifically, fMRI showed that in misophonic subjects, trigger sounds elicit greatly exaggerated blood-oxygen-level-dependent (BOLD) responses in the anterior insular cortex (AIC), a core hub of the “salience network” that is critical for perception of interoceptive signals and emotion processing. Trigger sounds in misophonics were associated with abnormal functional connectivity between AIC and a network of regions responsible for the processing and regulation of emotions, including ventromedial prefrontal cortex (vmPFC), posteromedial cortex (PMC), hippocampus, and amygdala. Trigger sounds elicited heightened heart rate (HR) and galvanic skin response (GSR) in misophonic subjects, which were mediated by AIC activity. Questionnaire analysis showed that misophonic subjects perceived their bodies differently: they scored higher on interoceptive sensibility than controls, consistent with abnormal functioning of AIC. Finally, brain structural measurements implied greater myelination within vmPFC in misophonic individuals. Overall, our results show that misophonia is a disorder in which abnormal salience is attributed to particular sounds based on the abnormal activation and functional connectivity of AIC.

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Micah Allen

Wellcome Trust Centre for Neuroimaging

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Geraint Rees

University College London

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Gabriel Ziegler

Otto-von-Guericke University Magdeburg

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