A5047790667- Pulsars and Gravitational Waves Research
- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Geophysics and Gravity Measurements
- Gamma-ray bursts and supernovae
- Advanced MRI Techniques and Applications
- Astrophysical Phenomena and Observations
- Cosmology and Gravitation Theories
- Neural dynamics and brain function
- Experimental and Theoretical Physics Studies
- Geophysics and Sensor Technology
- Astronomical Observations and Instrumentation
- Seismic Waves and Analysis
- Advanced Frequency and Time Standards
- Health, Environment, Cognitive Aging
- Radio Astronomy Observations and Technology
- MRI in cancer diagnosis
- Complex Network Analysis Techniques
- Relativity and Gravitational Theory
- Statistical and numerical algorithms
- Visual perception and processing mechanisms
- Dementia and Cognitive Impairment Research
- Face Recognition and Perception
- Computational Physics and Python Applications
- Synthesis and characterization of novel inorganic/organometallic compounds
Cardiff University
2017-2025
California Institute of Technology
2007-2016
Max Planck Society
2008
The University of Western Australia
2008
Max Planck Innovation
2008
University of Wisconsin–Milwaukee
2004-2007
University of Florida
2003-2007
The foundations are laid for the numerical computation of actual worldline a particle orbiting black hole and emitting gravitational waves. essential practicalities this illustrated here scalar infinitesimal size small but finite charge. This deviates from geodesic because it interacts with its own retarded field ${\ensuremath{\psi}}^{\mathrm{ret}}.$ A recently introduced Green's function ${G}^{\mathrm{S}}$ precisely determines singular part ${\ensuremath{\psi}}^{\mathrm{S}}$ field. exerts...
Abstract Recognizing emotion in faces is important human interaction and survival, yet existing studies do not paint a consistent picture of the neural representation supporting this task. To address this, we collected magnetoencephalography (MEG) data while participants passively viewed happy, angry neutral faces. Using time‐resolved decoding sensor‐level data, show that responses to can be discriminated from happy as early 90 ms after stimulus onset only 10 later than scrambled stimuli,...
Structural brain networks derived from diffusion magnetic resonance imaging data have been used extensively to describe the human brain, and graph theory has allowed quantification of their network properties. Schemes construct graphs that represent structural differ in metrics they use as edge weights algorithms define topologies. In this work, twenty construction schemes were considered. The number streamlines, fractional anisotropy, mean diffusivity or other attributes tracts weights,...
Abstract This paper introduces the Welsh Advanced Neuroimaging Database (WAND), a multi-scale, multi-modal imaging dataset comprising in vivo brain data from 170 healthy volunteers (aged 18–63 years), including 3 Tesla (3 T) magnetic resonance (MRI) with ultra-strong (300 mT/m) field gradients, structural and functional MRI nuclear spectroscopy at T 7 T, magnetoencephalography (MEG), transcranial stimulation (TMS), together trait questionnaire cognitive data. Data are organised using Brain...
For a particle of mass $\ensuremath{\mu}$ and scalar charge $q$, we compute the effects field self-force upon circular orbits, slightly eccentric orbits innermost stable orbit (ISCO) Schwarzschild black hole $m$. is outward causes angular frequency at given radius to decrease. decreases rate precession orbit. The effect moves inward by $0.122\text{ }701\ifmmode\times\else\texttimes\fi{}{q}^{2}/\ensuremath{\mu}$, it increases ISCO fraction $0.029\text{ }165\text{...
Abstract Understanding how human brain microstructure influences functional connectivity is an important endeavor. In this work, magnetic resonance imaging data from 90 healthy participants were used to calculate structural matrices using the streamline count, fractional anisotropy, radial diffusivity, and a myelin measure (derived multicomponent relaxometry) assign connection strength. Unweighted binarized also constructed. Magnetoencephalography resting-state those matrices, via...
Motivation: Advances in MRI have increased our understanding of the human brain but are frequently limited by single modality study designs. Combining data from multiple modalities/MR contrasts can enhance complex multi-scale neural relationships that underpin behaviour. Goal(s): Our goal was to create an open-access multi-scale, multi-modal imaging database healthy brain. Approach: The Welsh Advanced Neuroimaging Database (WAND) includes micro and macro-structural, functional spectroscopic...
We describe the current status of search for gravitational waves from inspiralling compact binary systems in LIGO data. review result first scientific run (S1). present goals data taken second (S2) and differences between methods used S1 S2.
Magnetoencephalography (MEG) is increasingly being used to study brain function because of its excellent temporal resolution and direct association with activity at the neuronal level. One possible cause error in analysis MEG data comes from fact that participants, even MEG-experienced ones, move their head system. Head movement can source localization errors during data, which result appearance variability does not reflect activity. The community places great importance eliminating this as...
Alzheimer's disease (AD) is the most common form of dementia with genetic and environmental risk contributing to its development. Graph theoretical analyses brain networks constructed from structural functional magnetic resonance imaging (MRI) measurements have identified connectivity changes in AD individuals mild cognitive impairment. However, asymptomatic at remains poorly understood.
Abstract A critical question in network neuroscience is how nodes cluster together to form communities, the mesoscale organisation of brain. Various algorithms have been proposed for identifying such each different communities within same network. Here, (using test–retest data from Human Connectome Project), repeatability thirty‐three community detection algorithms, paired with seven graph construction schemes were assessed. Repeatability partition depended heavily on both algorithm and...
Prior work on the Image Quality Transfer Diffusion MRI (dMRI) has shown significant improvement over traditional interpolation methods. However, difficulty in obtaining ultra-high resolution scans poses a problem training neural networks to obtain high-resolution dMRI scans. Here we hypothesise that inclusion of structural images, which can be acquired at much higher resolutions, used as guide more accurate output. To test our hypothesis, have constructed novel framework incorporates...
We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer's disease, using magnetic resonance imaging (MRI) and genotype data from Avon Longitudinal Study Parents Children. Diffusion MRI were used perform whole-brain tractography generate connectome, default mode, limbic visual subnetworks. The mean clustering coefficient, betweenness centrality, characteristic path length, global efficiency nodal strength calculated these networks, each...
The link between brain structural connectivity and schizotypy was explored in two healthy participant cohorts, collected at different neuroimaging centres, comprising 140 115 participants, respectively. participants completed the Schizotypal Personality Questionnaire (SPQ), through which their scores were calculated. Diffusion-MRI data used to perform tractography generate networks of participants. edges weighted with inverse radial diffusivity. Graph theoretical metrics default mode,...
Abstract Background Alzheimer’s Disease (AD) is the most common form of dementia with genetic and environmental risk contributing to its development. Graph theoretical analyses brain networks constructed from structural functional MRI measurements have identified connectivity changes in AD individuals mild cognitive impairment (MCI). However, asymptomatic at remains poorly understood. Methods We analysed diffusion-weighted magnetic resonance imaging (dMRI) data 160 (38-71 years) Cardiff...
Abstract The link between brain structural connectivity and schizotypy was explored in two healthy-participant cohorts, collected at different neuroimaging centres, comprising 140 115 participants respectively. completed the Schizotypal Personality Questionnaire (SPQ), through which their scores were calculated. Diffusion-MRI data used to perform tractography generate networks of participants. edges weighted with inverse radial diffusivity. Graph theoretical metrics default-mode,...
Convection-enhanced delivery (CED) is an innovative method of drug to the human brain, that bypasses blood-brain barrier by injecting directly into brain. CED aims target pathological tissue for central nervous system conditions such as Parkinson's and Huntington's disease, epilepsy, brain tumors, ischemic stroke. Computational fluid dynamics models have been constructed predict distribution in CED, allowing clinicians advance planning procedure. These require patient-specific information...
We aimed to identify potential redundancies in microstructural measures between major white matter tracts and asked which metrics correlate most within a tract. Using combination of imaging techniques, including diffusion imaging, relaxometry quantitative magnetisation transfer we identified strong correlations homologous left right fasciculi the cingulum bundles, inferior longitudinal fasciculi, uncinate arcuate as well similar patterns tissue microstructure heterologous tracts. However,...
This work explores the link between topological properties of brain structural networks and APOE-epsilon4 in young asymptomatic adults. We investigated sensorimotor, visual default-mode networks. found evidence that there are differences mean clustering coefficient sensorimotor network carriers versus non-carriers, with left caudal middle frontal, precentral, right postcentral precentral gyri driving differences. Interestingly, was higher compared to non-carriers. In contrast, no were for or
Quantifying the intricate relationship between brain structure and function is of extreme importance in neuroscience. In this work, we present a comprehensive framework for mapping structural connectivity measured via diffusion-MRI to resting-state functional magnetoencephalography, utilizing deep-learning model based on Graph Multi-Head Attention AutoEncoder. We compare results those from an analytical that utilizes shortest-path- length search-information communication mechanisms. The...
Motivation: Substantial effort has been invested into understanding how brain structure constrains function. However, research primarily focused on structure, rather than linking dynamics to it. Goal(s): Compare oscillation propagation delays estimated using neuronal avalanches from MEG resting-state data with the underlying white matter through tractography. Approach: We characterised relationship between pathways length and related delays, deterministic probabilistic approaches, looking at...
Motivation: Many cortical pathologies are invisible via conventional MRI, making it difficult for clinicians to correctly diagnose and treat patients. Goal(s): Our aim was optimize advanced MRI acquisitions, them sensitive subtle while at the same time reducing acquisition times clinically-feasible durations. Approach: We calculated combined relaxation-diffusion signal encompass surface relaxivity T2 effects. used Monte-Carlo simulations model from healthy pathological neurons different PGSE...
Abstract A critical question in network neuroscience is how nodes cluster together to form communities, the mesoscale organization of brain. Various algorithms have been proposed for identifying such each different communities within same network. Here, (using test-retest data from Human Connectome Project), repeatability 33 community detection algorithms, paired with 7 graph construction schemes was assessed. Repeatability partition depended heavily on both algorithm and scheme. Hard (in...