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  • Journal article
    Li L, Ribeiro Violante I, Leech R, Hampshire A, Opitz A, McArhur D, Carmichael D, Sharp Det al., 2019,

    Cognitive enhancement with Salience Network electrical stimulation is influenced by network structural connectivity

    , NeuroImage, Vol: 185, Pages: 425-433, ISSN: 1053-8119

    The Salience Network (SN) and its interactions are important for cognitive control. We have previously shown that structural damage to the SN is associated with abnormal functional connectivity between the SN and Default Mode Network (DMN), abnormal DMN deactivation, and impaired response inhibition, which is an important aspect of cognitive control. This suggests that stimulating the SN might enhance cognitive control. Here, we tested whether non-invasive transcranial direct current stimulation (TDCS) could be used to modulate activity within the SN and enhance cognitive control. TDCS was applied to the right inferior frontal gyrus/anterior insula cortex during performance of the Stop Signal Task (SST) and concurrent functional (f)MRI. Anodal TDCS improved response inhibition. Furthermore, stratification of participants based on SN structural connectivity showed that it was an important influence on both behavioural and physiological responses to anodal TDCS. Participants with high fractional anisotropy within the SN showed improved SST performance and increased activation of the SN with anodal TDCS, whilst those with low fractional anisotropy within the SN did not. Cathodal stimulation of the SN produced activation of the right caudate, an effect which was not modulated by SN structural connectivity. Our results show that stimulation targeted to the SN can improve response inhibition, supporting the causal influence of this network on cognitive control and confirming it as a target to produce cognitive enhancement. Our results also highlight the importance of structural connectivity as a modulator of network to TDCS, which should guide the design and interpretation of future stimulation studies.

  • Journal article
    Azor AM, Cole JH, Holland AJ, Dumba M, Patel MC, Sadlon A, Goldstone AP, Manning KEet al., 2019,

    Increased brain age in adults with Prader-Willi syndrome

    , NeuroImage: Clinical, Vol: 21, ISSN: 2213-1582

    Prader-Willi syndrome (PWS) is the most common genetic obesity syndrome, with associated learning difficulties, neuroendocrine deficits, and behavioural and psychiatric problems. As the life expectancy of individuals with PWS increases, there is concern that alterations in brain structure associated with the syndrome, as a direct result of absent expression of PWS genes, and its metabolic complications and hormonal deficits, might cause early onset of physiological and brain aging. In this study, a machine learning approach was used to predict brain age based on grey matter (GM) and white matter (WM) maps derived from structural neuroimaging data using T1-weighted magnetic resonance imaging (MRI) scans. Brain-predicted age difference (brain-PAD) scores, calculated as the difference between chronological age and brain-predicted age, are designed to reflect deviations from healthy brain aging, with higher brain-PAD scores indicating premature aging. Two separate adult cohorts underwent brain-predicted age calculation. The main cohort consisted of adults with PWS (n = 20; age mean 23.1 years, range 19.8-27.7; 70.0% male; body mass index (BMI) mean 30.1 kg/m2, 21.5-47.7; n = 19 paternal chromosome 15q11-13 deletion) and age- and sex-matched controls (n = 40; age 22.9 years, 19.6-29.0; 65.0% male; BMI 24.1 kg/m2, 19.2-34.2) adults (BMI PWS vs. control P = .002). Brain-PAD was significantly greater in PWS than controls (effect size mean ± SEM +7.24 ± 2.20 years [95% CI 2.83, 11.63], P = .002). Brain-PAD remained significantly greater in PWS than controls when restricting analysis to a sub-cohort matched for BMI consisting of n = 15 with PWS with BMI range 21.5-33.7 kg/m2, and n = 29 controls with BMI 21.7-34.2 kg/m2 (effect size +5.51 ± 2.56 years [95% CI 3.44, 10.38], P = .037). In the PWS group, brain-PAD scores were not associated with intelligence quotient (IQ), use of hormonal and psychotropic medications, nor severity of repetitive or disruptive

  • Journal article
    Brooker H, Wesnes KA, Ballard C, Hampshire A, Aarsland D, Khan Z, Stenton R, Megalogeni M, Corbett Aet al., 2019,

    The relationship between the frequency of number-puzzle use and baseline cognitive function in a large online sample of adults aged 50 and over

    , International Journal of Geriatric Psychiatry, ISSN: 0885-6230

    © 2019 John Wiley & Sons, Ltd. Objective: Establishing affordable lifestyle interventions that might preserve cognitive function in the aging population and subsequent generations is a growing area of research focus. Data from the PROTECT study has been utilised to examine whether number-puzzle use is related to cognitive function in older adults. Methods: Data from 19 078 healthy volunteers aged 50 to 93 years old enrolled on the online PROTECT study were evaluated for self-reported frequency of performing number puzzles. Two cognitive-test batteries were employed to assess core aspects of cognitive function including reasoning, focussed and sustained attention, information processing, executive function, working memory, and episodic memory. Analysis of covariance was used to establish the differences between the six frequency groups. Results: Highly statistically significant main effects of the frequency of performing number puzzles were seen on all 14 cognitive measures, with P values of less than 0.0004. Interestingly, participants who reported engaging in number puzzles more than once a day had superior cognitive performance on 10 core measures compared with all other frequency groups, although not all were statistically significant. Conclusions: This study has identified a close relationship between frequency of number-puzzle use and the quality of cognitive function in adults aged 50 to 93 years old. In order to determine the value of these findings as a potential intervention, further research should explore the type and difficulty of the number puzzles. These findings further contribute to the growing evidence that engaging in mentally stimulating activities could benefit the brain function of the ageing population.

  • Journal article
    Montaldo P, Kaforou M, Pollara G, Hervás-Maríne D, Calabria I, Panadero J, Pedrola L, Lally PJ, Oliveira V, Kage A, Atreja G, Mendoza J, Soe A, Pattnayak S, Shankaranh S, Vento M, Herberg J, Thayyil Set al., 2019,

    Whole blood gene expression reveals specific transcriptome changes in neonatal encephalopathy

    , Neonatology, Vol: 115, Pages: 68-76, ISSN: 1661-7800

    BackgroundVariable responses to hypothermic neuroprotection are related to the clinical heterogeneity of encephalopathic babies, hence better disease stratification may facilitate the development of individualized neuroprotective therapies.ObjectivesWe examined if whole blood gene expression analysis can identify specific transcriptome profiles in neonatal encephalopathy. Material and MethodsWe performed next generation sequencing on whole blood RNA from twelve babies with neonatal encephalopathy, and six time-matched healthy term babies. The significantly differentially expressed genes between encephalopathic and control babies were identified. This set of genes was then compared to the host RNA response in septic neonates and subjected to pathway analysis. ResultsWe identified 950 statistically significant genes discriminating perfectly between the healthy controls and neonatal encephalopathy. The major pathways in neonatal encephalopathy were axonal guidance signaling (p =0.0009), granulocyte adhesion and diapedesis (p = 0.003), IL-12 Signaling and Production in Macrophages (p= 0.003) and hypoxia-inducible factor 1α signaling (p = 0.004). There were only 137 genes in common between neonatal encephalopathy and bacterial sepsis sets. ConclusionBabies with neonatal encephalopathy have striking differences in gene expression profiles compared with healthy control and septic babies. Gene expression profile may be useful for disease stratification based and for developing personalized neuroprotective therapies.

  • Journal article
    Lally PJ, Montaldo P, Oliveira V, Soe A, Swamy R, Bassett P, Mendoza J, Atreja G, Kariholu U, Pattnayak S, Sashikumar P, Harizaj H, Mitchell M, Ganesh V, Harigopal S, Dixon J, English P, Clarke P, Muthukumar P, Satodia P, Wayte S, Abernethy LJ, Yajamanyam K, Bainbridge A, Price D, Huertas A, Sharp DJ, Kalra V, Chawla S, Shankaran S, Thayyil Set al., 2019,

    Magnetic resonance spectroscopy assessment of brain injury after moderate hypothermia in neonatal encephalopathy: a prospective multi-centre study

    , Lancet Neurology, Vol: 18, Pages: 35-45, ISSN: 1474-4422

    BackgroundIn neonatal encephalopathy (NE), the clinical manifestations of injury can only be reliably assessed several years after an intervention, complicating early prognostication and rendering trials of promising neuroprotectants slow and expensive. We aimed to determine the accuracy of thalamic proton magnetic resonance spectroscopy (1H MRS) biomarkers as early predictors of the neurodevelopmental abnormalities observed years after NE.MethodsWe conducted a prospective multi-centre cohort study across eight neonatal intensive care units, recruiting term neonates who received therapeutic hypothermia for NE. We obtained thalamic 1H MRS 4 to 14 days after birth, which were compared to clinical neurodevelopmental tests performed 18 to 24 months later. The primary endpoint was anabnormal outcome, defined as death, or moderate or severe disability. Receiver operating characteristic (ROC) curves were used to examine the strength of the relationship between selected biomarkers and this outcome.FindingsWe recruited 223 infants who all underwent MR imaging and spectroscopy at a median (IQR) age of 7 (5 to 10) days, with 190 (85%) followed up for neurological examination at a median (IQR) age of 23 (20 to 25) months. Of those followed up, 31 (16%) had moderate or severe disability, including one death. The thalamic concentration of Nacetylasparate, [NAA], had an area under the ROC curve (AUC) of 0·99 (95% CI 0·94 to 1·00, n=82), and lactate/NAA peak area ratio had an AUC of 0·94 (95% CI 0·89 to 0·97, n=160). From conventional MRI, abnormal signal in the posterior limb of the internal capsule (PLIC) gave an AUC of 0·82 (95% CI 0·76 to 0·87, n=190). Thalamic [NAA] was independentlyassociated with neurodevelopmental outcome scores on multivariable analysis, and had higher prognostic accuracy than conventional MR imaging (98% versus 87%; p<0·001).InterpretationThalamic 1H MRS measures acquired soon after

  • Journal article
    Peers PV, Astle DE, Duncan J, Murphy FC, Hampshire A, Das T, Manly Tet al., 2018,

    Dissociable effects of attention vs working memory training on cognitive performance and everyday functioning following fronto-parietal strokes

    , Neuropsychological Rehabilitation, ISSN: 0960-2011

    © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Difficulties with attention are common following stroke, particularly in patients with frontal and parietal damage, and are associated with poor outcome. Home-based online cognitive training may have the potential to provide an efficient and effective way to improve attentional functions in such patients. Little work has been carried out to assess the efficacy of this approach in stroke patients, and the lack of studies with active control conditions and rigorous evaluations of cognitive functioning pre and post-training means understanding is limited as to whether and how such interventions may be effective. Here, in a feasibility pilot study, we compare the effects of 20 days of cognitive training using either novel Selective Attention Training (SAT) or commercial Working Memory Training (WMT) programme, versus a waitlist control on a range of attentional and working memory tasks. We demonstrate separable effects of each training condition, with SAT leading to improvements in spatial and non-spatial aspects of attention and WMT leading to improvements on closely related working memory tasks. In addition, both training groups reported improvements in everyday functioning, which were associated with improvements in attention, suggesting that improving attention may be of particular importance in maximising functional improvements in this patient group.

  • Journal article
    Balaban G, Halliday BP, Costa CM, Bai W, Porter B, Rinaldi CA, Plank G, Rueckert D, Prasad SK, Bishop MJet al., 2018,

    Fibrosis Microstructure Modulates Reentry in Non-ischemic Dilated Cardiomyopathy: Insights From Imaged Guided 2D Computational Modeling

    , Frontiers in Physiology, Vol: 9, ISSN: 1664-042X

    Aims: Patients who present with non-ischemic dilated cardiomyopathy (NIDCM) andenhancement on late gadolinium magnetic resonance imaging (LGE-CMR), are at highrisk of sudden cardiac death (SCD). Further risk stratification of these patients basedon LGE-CMR may be improved through better understanding of fibrosis microstructure.Our aim is to examine variations in fibrosis microstructure based on LGE imaging, andquantify the effect on reentry inducibility and mechanism. Furthermore, we examine therelationship between transmural activation time differences and reentry.Methods and Results: 2D Computational models were created from a single short axisLGE-CMR image, with 401 variations in fibrosis type (interstitial, replacement) and density,as well as presence or absence of reduced conductivity (RC). Transmural activationtimes (TAT) were measured, as well as reentry incidence and mechanism. Reentrieswere inducible above specific density thresholds (0.8, 0.6 for interstitial, replacementfibrosis). RC reduced these thresholds (0.3, 0.4 for interstitial, replacement fibrosis) andincreased reentry incidence (48 no RC vs. 133 with RC). Reentries were classified as rotor,micro-reentry, or macro-reentry and depended on fibrosis micro-structure. Differencesin TAT at coupling intervals 210 and 500ms predicted reentry in the models (sensitivity89%, specificity 93%). A sensitivity analysis of TAT and reentry incidence showed thatthese quantities were robust to small changes in the pacing location.Conclusion: Computational models of fibrosis micro-structure underlying areas ofLGE in NIDCM provide insight into the mechanisms and inducibility of reentry, andtheir dependence upon the type and density of fibrosis. Transmural activation times,measured at the central extent of the scar, can potentially differentiate microstructureswhich support reentry.

  • Journal article
    Zetterberg H, Winblad B, Bernick C, Yaffe K, Majdan M, Johansson G, Newcombe V, Nyberg L, Sharp D, Tenovuo O, Blennow Ket al., 2018,

    Head trauma in sports - clinical characteristics, epidemiology and biomarkers.

    , J Intern Med

    Traumatic brain injury (TBI) is clinically divided into a spectrum of severities, with mild TBI being the least severe form and a frequent occurrence in contact sports, such as ice hockey, American football, rugby, horse riding and boxing. Mild TBI is caused by blunt nonpenetrating head trauma that causes movement of the brain and stretching and tearing of axons, with diffuse axonal injury being a central pathogenic mechanism. Mild TBI is in principle synonymous with concussion; both have similar criteria in which the most important elements are acute alteration or loss of consciousness and/or post-traumatic amnesia following head trauma and no apparent brain changes on standard neuroimaging. Symptoms in mild TBI are highly variable and there are no validated imaging or fluid biomarkers to determine whether or not a patient with a normal computerized tomography scan of the brain has neuronal damage. Mild TBI typically resolves within a few weeks but 10-15% of concussion patients develop postconcussive syndrome. Repetitive mild TBI, which is frequent in contact sports, is a risk factor for a complicated recovery process. This overview paper discusses the relationships between repetitive head impacts in contact sports, mild TBI and chronic neurological symptoms. What are these conditions, how common are they, how are they linked and can they be objectified using imaging or fluid-based biomarkers? It gives an update on the current state of research on these questions with a specific focus on clinical characteristics, epidemiology and biomarkers.

  • Journal article
    Montaldo P, Lally PJ, Oliveira V, Thayyil Set al., 2018,

    Hypothermic neuroprotection for neonatal encephalopathy in low-and middle-income countries: a new approach to an old problem

    ,, Vol: 19, Pages: e735-e741, ISSN: 1526-9906

    Little progress has been made over the past decade in improving the outcomes of infants with neonatal encephalopathy in low-and middle-income countries (LMICs), and millions of infants still die or sustain permanent neurodisability every year. One of the key reasons for this lack of progress is a disconnect between encephalopathy research in high-income countries and LMICs. The majority of the neonatal encephalopathy research has been conducted in high-income countries with a low disease burden, without the involvement of LMICs. Here we discuss how a collaborative approach—particularly between middle-income countries and high-income countries—enables the use of state-of-the-art magnetic resonance biomarkers and host gene expression profiling for effective disease stratification. Using the example of the Hypothermia for Encephalopathy in Low-and middle-Income countries (HELIX) trial, we describe how this approach may result in a paradigm shift in global perinatal brain research over the next decade.

  • Conference paper
    Duan J, Schlemper J, Bai W, Dawes TJW, Bello G, Biffi C, Doumou G, De Marvao A, O’Regan DP, Rueckert Det al., 2018,

    Combining deep learning and shape priors for bi-ventricular segmentation of volumetric cardiac magnetic resonance images

    , MICCAI ShapeMI Workshop, Publisher: Springer Verlag, Pages: 258-267, ISSN: 0302-9743

    In this paper, we combine a network-based method with image registration to develop a shape-based bi-ventricular segmentation tool for short-axis cardiac magnetic resonance (CMR) volumetric images. The method first employs a fully convolutional network (FCN) to learn the segmentation task from manually labelled ground truth CMR volumes. However, due to the presence of image artefacts in the training dataset, the resulting FCN segmentation results are often imperfect. As such, we propose a second step to refine the FCN segmentation. This step involves performing a non-rigid registration with multiple high-resolution bi-ventricular atlases, allowing the explicit shape priors to be inferred. We validate the proposed approach on 1831 healthy subjects and 200 subjects with pulmonary hypertension. Numerical experiments on the two datasets demonstrate that our approach is capable of producing accurate, high-resolution and anatomically smooth bi-ventricular models, despite the artefacts in the input CMR volumes.

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