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Guy B. Williams

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13 papers

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YNIMG Journal 2023 Journal Article

Reduced emergent character of neural dynamics in patients with a disrupted connectome

Andrea I. Luppi
Pedro A.M. Mediano
Fernando E. Rosas
Judith Allanson
John D. Pickard
Guy B. Williams
Michael M. Craig
Paola Finoia

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.

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YNIMG Journal 2022 Journal Article

Small world topologies are thought to provide a valuable insight into human brain organisation and consciousness. However, functional magnetic resonance imaging studies in consciousness have not yielded consistent results. Given the importance of dynamics for both consciousness and cognition, here we investigate how the diversity of small world dynamics (quantified by sample entropy; dSW-E 1 1 dSW-E= dynamic small world entropy ) scales with decreasing levels of awareness (i. e. , sedation and disorders of consciousness). Paying particular attention to result reproducibility, we show that dSW-E is a consistent predictor of levels of awareness even when controlling for the underlying functional connectivity dynamics. We find that dSW-E of subcortical, and cortical areas are predictive, with the former showing higher and more robust effect sizes across analyses. We find that the network dynamics of intermodular communication in the cerebellum also have unique predictive power for levels of awareness. Consequently, we propose that the dynamic reorganisation of the functional information architecture, in particular of the subcortex, is a characteristic that emerges with awareness and has explanatory power beyond that of the complexity of dynamic functional connectivity.

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YNICL Journal 2021 Journal Article

Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury

Andrea I. Luppi
Michael M. Craig
Peter Coppola
Alexander R.D. Peattie
Paola Finoia
Guy B. Williams
Judith Allanson
John D. Pickard

Self-similarity is ubiquitous throughout natural phenomena, including the human brain. Recent evidence indicates that fractal dimension of functional brain networks, a measure of self-similarity, is diminished in patients diagnosed with disorders of consciousness arising from severe brain injury. Here, we set out to investigate whether loss of self-similarity is observed in the structural connectome of patients with disorders of consciousness. Using diffusion MRI tractography from N = 11 patients in a minimally conscious state (MCS), N = 10 patients diagnosed with unresponsive wakefulness syndrome (UWS), and N = 20 healthy controls, we show that fractal dimension of structural brain networks is diminished in DOC patients. Remarkably, we also show that fractal dimension of structural brain networks is preserved in patients who exhibit evidence of covert consciousness by performing mental imagery tasks during functional MRI scanning. These results demonstrate that differences in fractal dimension of structural brain networks are quantitatively associated with chronic loss of consciousness induced by severe brain injury, highlighting the close connection between structural organisation of the human brain and its ability to support cognitive function.

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YNICL Journal 2020 Journal Article

Correlation of microglial activation with white matter changes in dementia with Lewy bodies

Nicolas Nicastro
Elijah Mak
Guy B. Williams
Ajenthan Surendranathan
W Richard Bevan-Jones
Luca Passamonti
Patricia Vàzquez Rodrìguez
Li Su

C]-PK11195 binding in frontal, temporal, and occipital lobes. However, microglial activation was not significantly associated with grey matter changes. Our study suggests that increased microglial activation is associated with a relative preservation of white matter and cognition in DLB, positioning neuroinflammation as a potential early marker of DLB etio-pathogenesis.

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YNIMG Journal 2020 Journal Article

Multi-centre, multi-vendor reproducibility of 7T QSM and R2* in the human brain: Results from the UK7T study

Catarina Rua
William T. Clarke
Ian D. Driver
Olivier Mougin
Andrew T. Morgan
Stuart Clare
Susan Francis
Keith W. Muir

Introduction We present the reliability of ultra-high field T2* MRI at 7T, as part of the UK7T Network's “Travelling Heads” study. T2*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R2* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R2* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1. 5–3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R2* mapping at 7T, in readiness for future multi-site clinical studies. Methods Ten healthy volunteers were scanned with harmonised single- and multi-echo T2*-weighted gradient echo pulse sequences. Participants were scanned five times at each “home” site and once at each of four other sites. The five sites had 1× Philips, 2× Siemens Magnetom, and 2× Siemens Terra scanners. QSM and R2* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https: //github. com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space. Results and Discussion Mean susceptibility (χ) and R2* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0. 001–0. 005 ppm (χ) and 0. 0005–0. 001 ms−1 (R2*). For χ this is 2. 1–4. 8 fold better than 3T reports, and 1. 1–3. 4 fold better for R2*. The median ICC from within- and cross-site R2* data was 0. 98 and 0. 91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B0 inhomogeneity such as the inferior frontal cortex. Across sites, R2* values were more consistent than QSM in subcortical structures due to differences in B0-shimming. On a between-subject level, our measured χ and R2* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol. Conclusion The harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R2* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.

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YNICL Journal 2015 Journal Article

Longitudinal assessment of global and regional atrophy rates in Alzheimer's disease and dementia with Lewy bodies

Elijah Mak
Li Su
Guy B. Williams
Rosie Watson
Michael Firbank
Andrew M. Blamire
John T. O'Brien

Background & objective Percent whole brain volume change (PBVC) measured from serial MRI scans is widely accepted as a sensitive marker of disease progression in Alzheimer's disease (AD). However, the utility of PBVC in the differential diagnosis of dementia remains to be established. We compared PBVC in AD and dementia with Lewy bodies (DLB), and investigated associations with clinical measures. Methods 72 participants (14 DLBs, 25 ADs, and 33 healthy controls (HCs)) underwent clinical assessment and 3 Tesla T1-weighted MRI at baseline and repeated at 12 months. We used FSL-SIENA to estimate PBVC for each subject. Voxelwise analyses and ANCOVA compared PBVC between DLB and AD, while correlational tests examined associations of PBVC with clinical measures. Results AD had significantly greater atrophy over 1 year (1. 8%) compared to DLB (1. 0%; p = 0. 01) and HC (0. 9%; p < 0. 01) in widespread regions of the brain including periventricular areas. PBVC was not significantly different between DLB and HC (p = 0. 95). There were no differences in cognitive decline between DLB and AD. In the combined dementia group (AD and DLB), younger age was associated with higher atrophy rates (r = 0. 49, p < 0. 01). Conclusions AD showed a faster rate of global brain atrophy compared to DLB, which had similar rates of atrophy to HC. Among dementia subjects, younger age was associated with accelerated atrophy, reflecting more aggressive disease in younger people. PBVC could aid in differentiating between DLB and AD, however its utility as an outcome marker in DLB is limited.

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YNIMG Journal 2014 Journal Article

Comparing voxel-based iterative sensitivity and voxel-based morphometry to detect abnormalities in T2-weighted MRI

Lara Z. Diaz-de-Grenu
Julio Acosta-Cabronero
Guy B. Williams
Peter J. Nestor

This study aimed to test the superiority proposed by Abbott et al. (2011) of their Voxel based iterative sensitivity (VBIS) method over Voxel Based Morphometry using T2-weighted images (T2-VBM), in detecting intensity changes in Alzheimer's disease (AD). A comparison was made first in simulated intensity lesions and then in AD patients. Intensity changes were evaluated in the whole-brain with VBIS and with a simple intensity-based approach and in specific tissue classes with the conventional VBM method of using tissue probability segments. Results showed that VBIS performed well in the simulated environment though it showed no superiority in detecting the lesion compared to the much simpler VBM approach. The VBIS method, however, failed to detect any meaningful signal intensity reduction in AD patient data. Moreover, its whole brain approach was contaminated by the excess cerebrospinal fluid signal (very bright on T2-weighted scans) in areas of maximal measurable atrophy (mesial temporal lobes); this gave rise to spurious signal intensity increases in these regions in AD. The same artefact was observed for both intensity-based methods but not with the conventional VBM approach of performing statistics on grey matter segments. In conclusion, no evidence was found to indicate that VBIS offers benefits over T2-VBM in AD, nor in simulation intensity lesions. The study highlights the necessity of empirically testing voxel-based analysis techniques rather than merely claiming superiority of one method over another on theoretical grounds.

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YNIMG Journal 2011 Journal Article

Contrast-to-noise ratios for indices of anisotropy obtained from diffusion MRI: A study with standard clinical b-values at 3T

Marta Morgado Correia
Virginia F.J. Newcombe
Guy B. Williams

Over the past 15years, diffusion-weighted MRI data has been used to measure the degree of diffusion anisotropy in different regions in both the healthy and the pathological brain. In this study we compared the performance of several different anisotropy indices in terms of their ability to differentiate between tissue types, using both simulated and experimental data. Simulations were performed for one-, two- and three-fibre populations. The results obtained suggest that only indices derived from tensors of rank higher than two, and indices derived from model free approaches can differentiate between an isotropic voxel and a population of three orthogonal fibres. Indices such as geodesic anisotropy (GeoA), generalised anisotropy (GA), and scaled entropy (SE) produce greater contrast-to-noise ratios than fractional anisotropy (FA) for simulated data and large anisotropy differences between brain regions. However, the biological scatter seen within brain regions is large enough to mask the expected differences between indices when looking at small anisotropy differences in the brain. The comparison of different acquisition schemes revealed that the use of multiple b-values seems to result in improved contrast-to-noise ratios for indices derived from the traditional diffusion tensor model.

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YNIMG Journal 2011 Journal Article

MRI detection of tissue pathology beyond atrophy in Alzheimer's disease: Introducing T2-VBM

Lara Z. Diaz-de-Grenu
Julio Acosta-Cabronero
Joao M.S. Pereira
George Pengas
Guy B. Williams
Peter J. Nestor

Voxel-based morphometry (VBM) of T1-weighted magnetic resonance (MR) images has been widely used to identify regional atrophy in neurodegenerative conditions such as Alzheimer's disease (AD). In theory, however, T2-weighting should be more sensitive to tissue pathology, though until recently, volumetric T2-weighted images were unavailable. We tested the hypothesis that T2-VBM would be more sensitive to grey matter pathology in AD than T1-VBM using the recently-developed SPACE acquisition, which provides true-3D, high-resolution T2-weighted images. This was contrasted to conventional T1-weighted MPRAGE images acquired at the same session and resolution. All of the atrophic regions identified with T1-VBM were also identified with T2-VBM. Additional abnormalities were, however, identified with T2-VBM and the distribution of these bore a striking resemblance to the distribution of amyloid plaque deposition in AD, suggesting that T2-VBM detects signal changes due to histopathology over and above those attributable to atrophy. In keeping with this hypothesis, the relevant statistical tests demonstrated that the difference in sensitivity was caused by an apparent change in T2-weighted signal intensity that was not present in T1-weighted images. These results suggest that T2-VBM has the potential to advance VBM beyond atrophy detection to more expansive applications in tissue pathology mapping.

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YNIMG Journal 2008 Journal Article

Impact of inconsistent resolution on VBM studies

João M.S. Pereira
Peter J. Nestor
Guy B. Williams

This paper considers the effects of using magnetic resonance scans with different voxel dimensions in voxel-based morphometry studies. This is of potential relevance to many longitudinal studies or any ad-hoc study that relies on pre-existing databases of subjects. In order to study this effect, a group of controls were contrasted with a group of semantic dementia as well as with a group of Alzheimer's disease patients using a mixture of different voxel dimensions scans on each side of the statistical test. Scans were interpolated using a sinc function in order to obtain a different voxel depth. The effects were measured by comparing the output of each analysis to the benchmark in which all scans had the original depth (and highest resolution), both visually and through the computation of the root–mean–square error difference between the resulting t-maps. It was shown that the impact is highly dependent on the scan itself, with some images showing more robustness to the interpolation process, and hence yielding fewer differences. A measure of robustness is proposed, which may be used in order to understand the impact of mixing different dimensions or adjusting them for each scan. Indiscriminate use of voxel dimensions on both groups was found to produce more errors (false positives/false negatives) than does an approach involving the use of balanced groups and a voxel dimension nuisance covariate.

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YNIMG Journal 2008 Journal Article

Neural basis of abnormal response to negative feedback in unmedicated mood disorders

Joana V. Taylor Tavares
Luke Clark
Maura L. Furey
Guy B. Williams
Barbara J. Sahakian
Wayne C. Drevets

Depressed individuals show hypersensitivity to negative feedback during cognitive testing, which can precipitate subsequent errors and thereby impair a broad range of cognitive abilities. We studied the neural mechanisms underlying this feedback hypersensitivity using functional magnetic resonance imaging (fMRI) with a reversal learning task that required subjects to ignore misleading negative feedback on some trials. Thirteen depressed subjects with major depressive disorder (MDD), 12 depressed subjects with bipolar disorder (BD) and 15 healthy controls participated. The MDD group, but not the BD group, demonstrated enhanced sensitivity to negative feedback compared to controls, as indicated by the rates of rule reversal following misleading negative feedback. In the control and BD groups, hemodynamic activity was significantly higher in the dorsomedial and ventrolateral prefrontal cortices during reversal shifting, and significantly lower in the right amygdala in response to negative feedback. The extent to which the amygdala showed less activity during negative feedback correlated inversely with the behavioral tendency to reverse after misleading feedback. This effect was not present in the MDD group, who also failed to recruit the prefrontal cortex during behavioral reversal. Hypersensitivity to negative feedback is present in unmedicated depressed patients with MDD. Disrupted top-down control by the prefrontal cortex of the amygdala may underlie this abnormal response to negative feedback in unipolar depression.

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YNIMG Journal 2008 Journal Article

The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry

Julio Acosta-Cabronero
Guy B. Williams
João M.S. Pereira
George Pengas
Peter J. Nestor

This study evaluates the application of (i) skull-stripping methods (hybrid watershed algorithm (HWA), brain surface extractor (BSE) and brain-extraction tool (BET2)) and (ii) bias correction algorithms (nonparametric nonuniform intensity normalisation (N3), bias field corrector (BFC) and FMRIB's automated segmentation tool (FAST)) as pre-processing pipelines for the technique of voxel-based morphometry (VBM) using statistical parametric mapping v. 5 (SPM5). The pipelines were evaluated using a BrainWeb phantom, and those that performed consistently were further assessed using artificial-lesion masks applied to 10 healthy controls compared to the original unlesioned scans, and finally, 20 Alzheimer's disease (AD) patients versus 23 controls. In each case, pipelines were compared to each other and to those from default SPM5 methodology. The BET2+N3 pipeline was found to produce the least miswarping to template induced by real abnormalities, and performed consistently better than the other methods for the above experiments. Occasionally, the clusters of significant differences located close to the boundary were dragged out of the glass-brain projections—this could be corrected by adding background noise to low-probability voxels in the grey matter segments. This method was confirmed in a one-dimensional simulation and was preferable to threshold and explicit (simple) masking which excluded true abnormalities.

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YNIMG Journal 2005 Journal Article

Neural correlates of semantic and behavioural deficits in frontotemporal dementia

Guy B. Williams
Peter J. Nestor
John R. Hodges

Patients with frontotemporal dementia (FTD) can present with the clinical syndrome of semantic dementia due to a progressive loss of semantic knowledge or a neuropsychiatric syndrome characterised by aberrant social behaviours although frequently both co-exist. It has been assumed that the former is underpinned by damage to the temporal lobes and the latter, predominantly, by damage to the frontal lobes. Using the technique of voxel-based morphometry, we studied a group of FTD cases (n = 18) with a range of cognitive and neuropsychiatric features to correlate loss of semantic knowledge (as measured by the sum of two semantic tests) and aberrant behaviour (as measured by the neuropsychiatric inventory, NPI) with regional loss of grey matter volume. Semantic breakdown correlated with extensive loss of grey matter volume throughout the left anterior temporal lobe and less significantly with right temporal pole and subcallosal gyrus. Aberrant behaviour correlated with loss of grey matter volume in the dorso-mesial frontal lobe—paracingulate region, Brodmann areas 6/8/9—more so on the right. The frontal paracingulate correlation suggests that damage to this region may significantly contribute to the genesis of the behavioural syndrome seen in FTD.

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