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Journal articleTimmermann C, Spriggs MJ, Kaelen M, et al., 2017,
LSD modulates effective connectivity and neural adaptation mechanisms in an auditory oddball paradigm.
, Neuropharmacology, ISSN: 0028-3908Under the predictive coding framework, perceptual learning and inference are dependent on the interaction between top-down predictions and bottom-up sensory signals both between and within regions in a network. However, how such feedback and feedforward connections are modulated in the state induced by lysergic acid diethylamide (LSD) is poorly understood. In this study, an auditory oddball paradigm was presented to healthy participants (16 males, 4 female) under LSD and placebo, and brain activity was recorded using magnetoencephalography (MEG). Scalp level Event Related Fields (ERF) revealed reduced neural adaptation to familiar stimuli, and a blunted neural 'surprise' response to novel stimuli in the LSD condition. Dynamic causal modelling revealed that both the presentation of novel stimuli and LSD modulate backward extrinsic connectivity within a task-activated fronto-temporal network, as well as intrinsic connectivity in the primary auditory cortex. These findings show consistencies with those of previous studies of schizophrenia and ketamine but also studies of reduced consciousness - suggesting that rather than being a marker of conscious level per se, backward connectivity may index modulations of perceptual learning common to a variety of altered states of consciousness, perhaps united by a shared altered sensitivity to environmental stimuli. Since recent evidence suggests that the psychedelic state may correspond to a heightened 'level' of consciousness with respect to the normal waking state, our data warrant a re-examination of the top-down hypotheses of conscious level and suggest that several altered states may feature this specific biophysical effector.
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Journal articleVaghi MM, Hampshire A, Fineberg NA, et al., 2017,
Hypoactivation and Dysconnectivity of a Frontostriatal Circuit During Goal-Directed Planning as an Endophenotype for Obsessive-Compulsive Disorder
, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, Vol: 2, Pages: 655-663, ISSN: 2451-9022© 2017 Society of Biological Psychiatry Background The symptoms of obsessive-compulsive disorder (OCD) have been postulated to result from impaired executive functioning and excessive habit formation at the expense of goal-directed control and have been objectively demonstrated using neuropsychological tests in such patients. This study tested whether there is functional hypoactivation as well as dysconnectivity of discrete frontostriatal pathways during goal-directed planning in patients with OCD and in their unaffected first-degree relatives. Methods In total, 21 comorbidity-free patients with OCD, 19 clinically asymptomatic first-degree relatives of these patients, and 20 control participants were tested on a functional magnetic resonance optimized version of the Tower of London task. Group differences in brain activation during goal-directed planning were measured together with associated frontostriatal functional connectivity. Results Patients with OCD and their clinically asymptomatic relatives manifested hypoactivation of the right dorsolateral prefrontal cortex during goal-directed planning coupled with reduced functional connectivity between this cortical region and the basal ganglia (putamen). Conclusions Hypoactivation of cortical regions associated with goal-directed planning and associated frontostriatal dysconnectivity represent a candidate endophenotype for OCD. These findings accord with abnormalities in neural networks supporting the balance between goal-directed and habitual behavior, with implications for recent neuropsychological theories of OCD and the major neurobiological model for this disorder.
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Journal articleFallon SJ, Bor D, Hampshire A, et al., 2017,
Spatial structure normalises working memory performance in Parkinson's disease.
, Cortex, Vol: 96, Pages: 73-82Cognitive deficits are a frequent symptom of Parkinson's disease (PD), particularly in the domain of spatial working memory (WM). Despite numerous demonstrations of aberrant WM in patients, there is a lack of understanding about how, if at all, their WM is fundamentally altered. Most notably, it is unclear whether span - the yardstick upon which most WM models are built - is compromised by the disease. Moreover, it is also unknown whether WM deficits occur in all patients or only exist in a sub-group who are executively impaired. We assessed the factors that influenced spatial span in medicated patients by varying the complexity of to-be-remembered items. Principally, we manipulated the ease with which items could enter - or be blocked from - WM by varying the level of structure in memoranda. Despite having similar levels of executive performance to controls, PD patients were only impaired when remembering information that lacked spatial, easy-to-chunk, structure. Patients' executive function, however, did not influence this effect. The ease with which patients could control WM was further examined by presenting irrelevant information during encoding, varying the level of structure in irrelevant information and manipulating the amount of switching between relevant and irrelevant information. Disease did not significantly alter the effect of these manipulations. Rather, patients' executive performance constrained the detrimental effect of irrelevant information on WM. Thus, PD patients' spatial span is predominantly determined by level of structure in to-be-remembered information, whereas their level of executive function may mitigate against the detrimental effect of irrelevant information.
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Journal articleBai W, Sinclair M, Tarroni G, et al., 2017,
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks
Cardiovascular magnetic resonance (CMR) imaging is a standard imagingmodality for assessing cardiovascular diseases (CVDs), the leading cause ofdeath globally. CMR enables accurate quantification of the cardiac chambervolume, ejection fraction and myocardial mass, providing information fordiagnosis and monitoring of CVDs. However, for years, clinicians have beenrelying on manual approaches for CMR image analysis, which is time consumingand prone to subjective errors. It is a major clinical challenge toautomatically derive quantitative and clinically relevant information from CMRimages. Deep neural networks have shown a great potential in image patternrecognition and segmentation for a variety of tasks. Here we demonstrate anautomated analysis method for CMR images, which is based on a fullyconvolutional network (FCN). The network is trained and evaluated on alarge-scale dataset from the UK Biobank, consisting of 4,875 subjects with93,500 pixelwise annotated images. The performance of the method has beenevaluated using a number of technical metrics, including the Dice metric, meancontour distance and Hausdorff distance, as well as clinically relevantmeasures, including left ventricle (LV) end-diastolic volume (LVEDV) andend-systolic volume (LVESV), LV mass (LVM); right ventricle (RV) end-diastolicvolume (RVEDV) and end-systolic volume (RVESV). By combining FCN with alarge-scale annotated dataset, the proposed automated method achieves a highperformance on par with human experts in segmenting the LV and RV on short-axisCMR images and the left atrium (LA) and right atrium (RA) on long-axis CMRimages.
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Journal articleVan Zoest RA, Underwood J, De Francesco D, et al., 2017,
Structural brain abnormalities in successfully treated HIV infection: associations with disease and cerebrospinal fluid biomarkers.
, Journal of Infectious Diseases, Vol: 217, Pages: 69-81, ISSN: 0022-1899Background: Brain structural abnormalities have been reported in persons with HIV (PWH) on suppressive combination antiretroviral therapy (cART), but their pathophysiology remains unclear. Methods: We investigated factors associated with brain tissue volumes and white matter microstructure (fractional anisotropy) in 134 PWH on suppressive cART and 79 comparable HIV-negative controls, aged ≥45 years from the Co-morBidity in Relation to AIDS (COBRA) cohort, using multimodal neuroimaging and cerebrospinal fluid (CSF) biomarkers. Results: Compared to controls, PWH had lower grey matter volumes (-13.7 mL [95%-confidence interval -25.1, -2.2 mL]) and fractional anisotropy (-0.0073 [-0.012, -0.0024]), with the largest differences observed in those with prior clinical AIDS. Hypertension and CSF soluble CD14 concentration were associated with lower fractional anisotropy. These associations were independent of HIV serostatus (Pinteraction=0.32 and Pinteraction=0.59, respectively) and did not explain the greater abnormalities in brain structure in relation to HIV. Conclusions: The presence of lower grey matter volumes and more white matter microstructural abnormalities in well-treated PWH partly reflect a combination of historical effects of AIDS, as well as the more general influence of systemic factors such as hypertension and ongoing neuroinflammation. Additional mechanisms explaining the accentuation of brain structure abnormalities in treated HIV infection remain to be identified.
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Conference paperSharp D, 2017,
Long-term inflammatory and neurodegenerative consequences of traumatic brain injury
, 23rd World Congress of Neurology (WCN), Publisher: ELSEVIER SCIENCE BV, Pages: 11-11, ISSN: 0022-510X -
Conference paperSharp D, 2017,
Precision medicine in TBI: Lessons from dopaminergic treatment of cognitive impairment
, 23rd World Congress of Neurology (WCN), Publisher: ELSEVIER SCIENCE BV, Pages: 1-2, ISSN: 0022-510X -
Conference paperSinclair M, Bai W, Puyol-Antón E, et al., 2017,
Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets
, International Conference On Medical Image Computing & Computer Assisted Intervention, Pages: 332-340, ISSN: 0302-9743© Springer International Publishing AG 2017. Cardiac magnetic resonance (CMR) can be used for quantitative analysis of heart function. However, CMR imaging typically involves acquiring 2D image planes during separate breath-holds, often resulting in misalignment of the heart between image planes in 3D. Accurate quantitative analysis requires a robust 3D reconstruction of the heart from CMR images, which is adversely affected by such motion artifacts. Therefore, we propose a fully automated method for motion correction of CMR planes using segmentations produced by fully convolutional neural networks (FCNs). FCNs are trained on 100 UK Biobank subjects to produce short-axis and long-axis segmentations, which are subsequently used in an iterative registration algorithm for correcting breath-hold induced motion artifacts. We demonstrate significant improvements in motion-correction over image-based registration, with strong correspondence to results obtained using manual segmentations. We also deploy our automatic method on 9,353 subjects in the UK Biobank database, demonstrating significant improvements in 3D plane alignment.
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Journal articleOktay O, Ferrante E, Kamnitsas K, et al., 2017,
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
, IEEE Transactions on Medical Imaging, Vol: 37, Pages: 384-395, ISSN: 0278-0062Incorporation of prior knowledge about organ shape and location is key to improve performance of image analysis approaches. In particular, priors can be useful in cases where images are corrupted and contain artefacts due to limitations in image acquisition. The highly constrained nature of anatomical objects can be well captured with learning based techniques. However, in most recent and promising techniques such as CNN based segmentation it is not obvious how to incorporate such prior knowledge. State-of-the-art methods operate as pixel-wise classifiers where the training objectives do not incorporate the structure and inter-dependencies of the output. To overcome this limitation, we propose a generic training strategy that incorporates anatomical prior knowledge into CNNs through a new regularisation model, which is trained end-to-end. The new framework encourages models to follow the global anatomical properties of the underlying anatomy (e.g. shape, label structure) via learnt non-linear representations of the shape. We show that the proposed approach can be easily adapted to different analysis tasks (e.g. image enhancement, segmentation) and improve the prediction accuracy of the state-of-the-art models. The applicability of our approach is shown on multi-modal cardiac datasets and public benchmarks. Additionally, we demonstrate how the learnt deep models of 3D shapes can be interpreted and used as biomarkers for classification of cardiac pathologies.
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Journal articleOliveira V, Singhvi DP, Montaldo P, et al., 2017,
Therapeutic hypothermia in mild neonatal encephalopathy: a national survey of practice in the UK
, Archives of Disease in Childhood. Fetal and Neonatal Edition, Vol: 103, Pages: F388-F390, ISSN: 1359-2998Although major cooling trials (and subsequent guidelines) excluded babies with mild encephalopathy, anecdotal evidence suggests that cooling is often offered to these infants. We report a national survey on current cooling practices for babies with mild encephalopathy in the UK. From 74 neonatal units contacted, 68 were cooling centres. We received 54 responses (79%) and included 48 (five excluded due to incomplete data and one found later not to offer cooling). Of these, 36 centres (75%) offered cooling to infants with mild encephalopathy. Although most of the participating units reported targeting 33-34°C core temperature, seven (19%) considered initiating cooling beyond 6 hours of age and 13 (36%) discontinued cooling prior to 72 hours. Babies were ventilated for cooling in two (6%) units and 13 (36%) sedated all cooled babies. Enteral feeding was withheld in 15 (42%) units and reduced below 25% of requirements in eight (22%) units. MRI and neurodevelopmental outcome evaluation were offered to all cooled babies in 29 (80%) and 27 (75%) units, respectively. Further research is necessary to ensure optimal neuroprotection in mild encephalopathy.
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