Publications
79 results found
De Simoni S, Grover PJ, Jenkins PO, et al., 2016, Disconnection between the default mode network and medial temporal lobes in post-traumatic amnesia, Brain, Vol: 139, Pages: 3137-3150, ISSN: 0006-8950
Post-traumatic amnesia is very common immediately after traumatic brain injury. It is characterised by a confused, agitated state and a pronounced inability to encode new memories and sustain attention. Clinically, post-traumatic amnesia is an important predictor of functional outcome. However, despite its prevalence and functional importance, the pathophysiology of post-traumatic amnesia is not understood. Memory processing relies on limbic structures such as the hippocampus, parahippocampus and parts of the cingulate cortex. These structures are connected within an intrinsic connectivity network, the Default Mode Network. Interactions within the Default Mode Network can be assessed using resting state functional magnetic resonance imaging, which can be acquired in confused patients unable to perform tasks in the scanner. Here we used this approach to test the hypothesis that the mnemonic symptoms of post-traumatic amnesia are caused by functional disconnection within the Default Mode Network. We assessed whether the hippocampus and parahippocampus showed evidence of transient disconnection from cortical brain regions involved in memory processing. 19 traumatic brain injury patients were classified into post-traumatic amnesia and traumatic brain injury control groups, based on their performance on a paired associates learning task. Cognitive function was also assessed with a detailed neuropsychological test battery. Functional interactions between brain regions were investigated using resting-state functional magnetic resonance imaging. Together with impairments in associative memory patients in post-traumatic amnesia demonstrated impairments in information processing speed and spatial working memory. Patients in post-traumatic amnesia showed abnormal functional connectivity between the parahippocampal gyrus and posterior cingulate cortex. The strength of this functional connection correlated with both associative memory and information processing speed and normal
Peress L, Violante IR, Scott G, et al., 2016, Thalamic magnetic resonance spectroscopy in highly active multiple sclerosis, 32nd Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Publisher: SAGE PUBLICATIONS LTD, Pages: 210-211, ISSN: 1352-4585
Feeney C, Scott GP, Cole JH, et al., 2016, Seeds of neuroendocrine doubt, Nature, Vol: 535, Pages: E1-E2, ISSN: 0028-0836
Fagerholm ED, Scott G, Shew WL, et al., 2016, Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice, Cerebral Cortex, Vol: 26, Pages: 3945-3952, ISSN: 1460-2199
Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such "scale-free" cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics.
Feeney C, Scott G, Raffel J, et al., 2016, Kinetic analysis of the translocator protein positron emission tomography ligand [18F]GE-180 in the human brain, European Journal of Nuclear Medicine and Molecular Imaging, Vol: 43, Pages: 2201-2210, ISSN: 1619-7089
PURPOSE: PET can image neuroinflammation by targeting the translocator protein (TSPO), which is upregulated in activated microglia. The high nonspecific binding of the first-generation TSPO radioligand [(11)C]PK-11195 limits accurate quantification. [(18)F]GE-180, a novel TSPO ligand, displays superior binding to [(11)C]PK-11195 in vitro. Our objectives were to: (1) evaluate tracer characteristics of [(18)F]GE-180 in the brains of healthy human subjects; and (2) investigate whether the TSPO Ala147Thr polymorphism influences outcome measures. METHODS: Ten volunteers (five high-affinity binders, HABs, and five mixed-affinity binders, MABs) underwent a dynamic PET scan with arterial sampling after injection of [(18)F]GE-180. Kinetic modelling of time-activity curves with one-tissue and two-tissue compartment models and Logan graphical analysis was applied to the data. The primary outcome measure was the total volume of distribution (V T) across various regions of interest (ROIs). Secondary outcome measures were the standardized uptake values (SUV), the distribution volume and SUV ratios estimated using a pseudoreference region. RESULTS: The two-tissue compartment model was the best model. The average regional delivery rate constant (K 1) was 0.01 mL cm(-3) min(-1) indicating low extraction across the blood-brain barrier (1 %). The estimated median V T across all ROIs was also low, ranging from 0.16 mL cm(-3) in the striatum to 0.38 mL cm(-3) in the thalamus. There were no significant differences in V T between HABs and MABs across all ROIs. CONCLUSION: A reversible two-tissue compartment model fitted the data well and determined that the tracer has a low first-pass extraction (approximately 1 %) and low V T estimates in healthy individuals. There was no observable dependency on the rs6971 polymorphism as compared to other second-generation TSPO PET tracers. Investigation of [(18)F]GE-180 in populations with neuroinflammatory disease is nee
Campos-Pires R, Armstrong S, Sebastiani A, et al., 2016, Xenon provides short-term and long-term neuroprotection in a rodent model of traumatic brain injury, International Brain Injury Association’s Eleventh World Congress on Brain Injury, Publisher: Taylor & Francis, Pages: 653-653, ISSN: 1362-301X
Scott G, Gunn RN, Matthews PM, et al., 2016, Minocycline reduces microglial activation after traumatic brain injury measured using [11C]-PBR28 positron emission tomography, International Brain Injury Association’s Eleventh World Congress on Brain Injury, Publisher: Taylor & Francis, Pages: 686-687, ISSN: 1362-301X
Zimmerman K, Scott G, Violante I, et al., 2016, Magnetic resonance spectroscopy of the thalamus in chronic traumatic brain injury, International Brain Injury Association’s Eleventh World Congress on Brain Injury, Publisher: Taylor &; Francis, Pages: 660-661, ISSN: 1362-301X
Dinov M, Lorenz R, Scott G, et al., 2016, Novel modeling of task versus rest brain state predictability using a dynamic time warping spectrum: comparisons and contrasts with other standard measures of brain dynamics, Frontiers in Computational Neuroscience, Vol: 10, ISSN: 1662-5188
Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT) are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches and the sum squared error (SSE) from a multilayer perceptron (MLP) prediction of the EEG timeseries, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach.
Datta G, Battaglini M, Scott G, et al., 2016, Cortical [11C]PBR28 PET Measures of Microglial Inflammation Explain Differences in Cognitive Performance of People with MS, 68th Annual Meeting of the American-Academy-of-Neurology (AAN), Publisher: LIPPINCOTT WILLIAMS & WILKINS, ISSN: 0028-3878
- Author Web Link
- Cite
- Citations: 1
Jamall O, Feeney C, Zaw-Linn J, et al., 2016, Prevalence and correlates of vitamin D deficiency in adults after traumatic brain injury, Clinical Endocrinology, Vol: 85, Pages: 636-644, ISSN: 1365-2265
Objectives: Traumatic brain injury (TBI) is a major cause of long-term disability with variable recovery. Preclinicalstudies suggest that vitamin D status influences recovery after TBI. However, there is no publishedclinical data on links between vitamin D status and TBI outcomes. To determine the: (i) prevalence ofvitamin D deficiency/insufficiency, and associations of vitamin D status with (ii) demographic factors andTBI severity, and with (iii) cognitive function, symptoms and quality of life, in adults after TBI.Design: Retrospective audit of patients seen between July 2009 and March 2015. Serum vitamin D (25-hydroxy-cholecalciferol) was categorised as deficient (<40nmol/L), insufficient (40-70nmol/L) or replete(>70nmol/L).Patients: 353 adults seen in tertiary hospital clinic (75.4% lighter-skinned, 74.8% male, age median 35.1y,range 26.6-48.3y), 0.3-56.5 months after TBI (74.5% moderate-severe).Measurements: Serum vitamin D concentrations; Addenbrooke’s Cognitive Examination (ACE-R), BeckDepression Inventory II (BDI-II), SF-36 Quality of Life, Pittsburgh Sleep Quality Index.Results: 46.5% of patients after TBI had vitamin D deficiency and 80.2% insufficiency/deficiency. Patientswith vitamin D deficiency had lower ACE-R scores than those vitamin D replete (mean effect size ± SEM 4.5± 2.1, P=0.034), and higher BDI-II scores than those vitamin D insufficient (4.5 ± 1.6, P=0.003), correcting forage, gender, time since TBI, TBI severity. There was no association between vitamin D status and markers ofTBI severity, sleep or quality of life.Conclusion: Vitamin D deficiency is common in patients after TBI and associated with impaired cognitivefunction and more severe depressive symptoms.
Scott GPT, Ramlackhansingh A, Edison P, et al., 2016, Amyloid pathology and axonal injury after brain trauma, Neurology, Vol: 86, Pages: 821-828, ISSN: 0028-3878
Objective: To image amyloid-β (Aβ) plaque burden in long-term survivors of traumatic brain injury (TBI), test whether traumatic axonal injury and Aβ are correlated, and compare the spatial distribution of Aβ to Alzheimer’s disease.Methods: Patients 11 months to 17 years after moderate-severe TBI had 11C-Pittsburgh compound-B (PIB) PET, structural and diffusion MRI and neuropsychological examination. Healthy aged controls and AD patients had PET and structural MRI. Binding potential (BPND) images of 11C-PIB, which index Aβ plaque density, were computed using an automatic reference region extraction procedure. Voxelwise and regional differences in BPND were assessed. In TBI, a measure of white matter integrity, fractional anisotropy (FA), was estimated and correlated with 11C-PIB BPND.Results: 28 participants (9 TBI, 9 controls, 10 AD) were assessed. Increased 11C-PIB BPND was found in TBI versus controls in the posterior cingulate cortex (PCC) and cerebellum. Binding in the PCC increased with decreasing FA of associated white matter tracts, and increased with time since injury. Compared to AD, binding after TBI was lower in neocortical regions, but increased in the cerebellum. Conclusions: Increased Aβ burden was observed in TBI. The distribution overlaps with, but is distinct from, that of AD. This suggests a mechanistic link between TBI and the development of neuropathological features of dementia, which may relate to axonal damage produced by the injury.
Scott G, Hellyer PJ, Ramlackhansingh AF, et al., 2015, Thalamic inflammation after brain trauma is associated with thalamo-cortical white matter damage, Journal of Neuroinflammation, Vol: 12, ISSN: 1742-2094
BackgroundTraumatic brain injury can trigger chronic neuroinflammation, which may predispose to neurodegeneration. Animal models and human pathological studies demonstrate persistent inflammation in the thalamus associated with axonal injury, but this relationship has never been shown in vivo.FindingsUsing [11C]-PK11195 positron emission tomography, a marker of microglial activation, we previously demonstrated thalamic inflammation up to 17 years after traumatic brain injury. Here, we use diffusion MRI to estimate axonal injury and show that thalamic inflammation is correlated with thalamo-cortical tract damage.ConclusionsThese findings support a link between axonal damage and persistent inflammation after brain injury.
Li LM, Leech R, Scott GT, et al., 2015, The effect of oppositional parietal transcranial direct current stimulation on lateralized brain functions, European Journal of Neuroscience, Vol: 42, Pages: 2904-2914, ISSN: 1460-9568
Cognitive functions such as numerical processing and spatial attention show varying degrees of lateralization. Transcranial direct current stimulation (tDCS) can be used to investigate how modulating cortical excitability affects performance of these tasks. This study investigated the effect of bi-parietal tDCS on numerical processing, spatial and sustained attention. It was hypothesized that tDCS would have distinct effects on these tasks because of varying lateralization (numerical processing left, spatial attention right) and that these effects are partly mediated by modulation of sustained attention. A single-blinded, crossover, sham-controlled study was performed. Eighteen healthy right-handed participants performed cognitive tasks during three sessions of oppositional parietal tDCS stimulation: sham; right anodal with left cathodal (RA/LC); and right cathodal with left anodal (RC/LA). Participants performed a number comparison task, a modified Posner task, a choice reaction task (CRT) and the rapid visual processing task (RVP). RA/LC tDCS impaired number comparison performance compared with sham, with slower responses to numerically close numbers pairs. RA/LC and RC/LA tDCS had distinct effects on CRT performance, specifically affecting vigilance level during the final block of the task. No effect of stimulation on the Posner task or RVP was found. It was demonstrated that oppositional parietal tDCS affected both numerical performance and vigilance level in a polarity-dependent manner. The effect of tDCS on numerical processing may partly be due to attentional effects. The behavioural effects of tDCS were specifically observed under high task demands, demonstrating the consequences of an interaction between stimulation type and cognitive load.
Datta G, Battaglini M, Scott G, et al., 2015, Positron emission tomography imaging in multiple sclerosis highlights a diffuse inflammatory response in brain that appears normal on conventional magnetic resonance imaging, 31st Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Publisher: SAGE Publications (UK and US), Pages: 477-478, ISSN: 1477-0970
Shanahan MP, Hellyer P, Sharp DJ, et al., 2015, Cognitive flexibility through metastable neural dynamics is disrupted by damage to the structural connectome, Journal of Neuroscience, Vol: 35, Pages: 9050-9063, ISSN: 0270-6474
Current theory proposes that healthy neural dynamics operate in a metastable regime, where brain regions interact to simultaneously maximize integration and segregation. Metastability may confer important behavioral properties, such as cognitive flexibility. It is increasingly recognized that neural dynamics are constrained by the underlying structural connections between brain regions. An important challenge is, therefore, to relate structural connectivity, neural dynamics, and behavior. Traumatic brain injury (TBI) is a pre-eminent structural disconnection disorder whereby traumatic axonal injury damages large-scale connectivity, producing characteristic cognitive impairments, including slowed information processing speed and reduced cognitive flexibility, that may be a result of disrupted metastable dynamics. Therefore, TBI provides an experimental and theoretical model to examine how metastable dynamics relate to structural connectivity and cognition. Here, we use complementary empirical and computational approaches to investigate how metastability arises from the healthy structural connectome and relates to cognitive performance. We found reduced metastability in large-scale neural dynamics after TBI, measured with resting-state functional MRI. This reduction in metastability was associated with damage to the connectome, measured using diffusion MRI. Furthermore, decreased metastability was associated with reduced cognitive flexibility and information processing. A computational model, defined by empirically derived connectivity data, demonstrates how behaviorally relevant changes in neural dynamics result from structural disconnection. Our findings suggest how metastable dynamics are important for normal brain function and contingent on the structure of the human connectome.
Váša F, Shanahan M, Hellyer P, et al., 2015, Effects of lesions on synchrony and metastability in cortical networks, Neuroimage, Vol: 118, Pages: 456-467, ISSN: 1095-9572
At the macroscopic scale, the human brain can be described as a complex network of white matter tracts integrating grey matter assemblies — the human connectome. The structure of the connectome, which is often described using graph theoretic approaches, can be used to model macroscopic brain function at low computational cost. Here, we use the Kuramoto model of coupled oscillators with time-delays, calibrated with respect to empirical functional MRI data, to study the relation between the structure of the connectome and two aspects of functional brain dynamics — synchrony, a measure of general coherence, and metastability, a measure of dynamical flexibility. Specifically, we investigate the relationship between the local structure of the connectome, quantified using graph theory, and the synchrony and metastability of the model's dynamics. By removing individual nodes and all of their connections from the model, we study the effect of lesions on both global and local dynamics. Of the nine nodal graph-theoretical properties tested, two were able to predict effects of node lesion on the global dynamics. The removal of nodes with high eigenvector centrality leads to decreases in global synchrony and increases in global metastability, as does the removal of hub nodes joining topologically segregated network modules. At the level of local dynamics in the neighbourhood of the lesioned node, structural properties of the lesioned nodes hold more predictive power, as five nodal graph theoretical measures are related to changes in local dynamics following node lesions. We discuss these results in the context of empirical studies of stroke and functional brain dynamics.
Fagerholm ED, Hellyer PJ, Scott G, et al., 2015, Disconnection of network hubs and cognitive impairment after traumatic brain injury., Brain, Vol: 138, Pages: 1696-1709, ISSN: 0006-8950
Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These resul
Fagerholm ED, Lorenz R, Scott G, et al., 2015, Cascades and Cognitive State: Focused Attention Incurs Subcritical Dynamics, Journal of Neuroscience, Vol: 35, Pages: 4626-4634, ISSN: 1529-2401
Vijayan R, Scott G, Ahmed F, 2015, What is it about the number of stitches?, BMJ (Online), Vol: 350, ISSN: 0959-8146
Tillmann T, Gibson AR, Scott G, et al., 2015, Systems Medicine 2.0: Potential Benefits of Combining Electronic Health Care Records With Systems Science Models, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 17, ISSN: 1438-8871
- Author Web Link
- Cite
- Citations: 10
Vijayan R, Scott G, Brownlie W, et al., 2015, How Sharp is a "Sharp Scratch"? A Mixed Methods Study of Verbal Warnings Issued Before Venipuncture, PAIN PRACTICE, Vol: 15, Pages: 132-139, ISSN: 1530-7085
- Author Web Link
- Cite
- Citations: 1
Scott G, Fagerholm ED, Mutoh H, et al., 2014, Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics, The Journal of Neuroscience, Vol: 34, Pages: 16611-16620, ISSN: 0270-6474
Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain.
Scott G, Hellyer PJ, Hampshire A, et al., 2014, Exploring spatiotemporal network transitions in task functional MRI, Hum. Brain Mapp., Pages: n/a-n/a, ISSN: 1097-0193
Scott G, Sharp DJ, Ramlackhansingh A, et al., 2014, NEUROINFLAMMATION AND AMYLOID PATHOLOGY AFTER TBI, JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY, Vol: 85, ISSN: 0022-3050
MacFarlane JW, Payton OD, Keatley AC, et al., 2014, Lightweight aerial vehicles for monitoring, assessment and mapping of radiation anomalies, JOURNAL OF ENVIRONMENTAL RADIOACTIVITY, Vol: 136, Pages: 127-130, ISSN: 0265-931X
- Author Web Link
- Cite
- Citations: 66
Jilka SR, Scott G, Ham T, et al., 2014, Damage to the Salience Network and Interactions with the Default Mode Network, JOURNAL OF NEUROSCIENCE, Vol: 34, Pages: 10798-10807, ISSN: 0270-6474
- Author Web Link
- Cite
- Citations: 156
Leech R, Scott G, Carhart-Harris R, et al., 2014, Spatial Dependencies between Large-Scale Brain Networks, PLoS ONE, Vol: 9
<p>Functional neuroimaging reveals both increases (task-positive) and decreases (task-negative) in neural activation with many tasks. Many studies show a <italic>temporal</italic> relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a <italic>spatial</italic> relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental <italic>spatial</italic> relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks - implying that deactivation patterns are spatially dependent on activation patterns (and <italic>vice versa</italic>), and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third ‘rest’ dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function.</p>
Vijayan R, Scott G, Brownlie W, 2014, Out of sight, but not out of mind? Greater reported pain in patients who spontaneously look away during venepuncture, EJP, Pages: n/a-n/a, ISSN: 1532-2149
Sharp DJ, Scott G, Leech R, 2014, Network dysfunction after traumatic brain injury, NATURE REVIEWS NEUROLOGY, Vol: 10, Pages: 156-166, ISSN: 1759-4758
- Author Web Link
- Cite
- Citations: 427
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.