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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Withers, James;

    This thesis presents a method for the segmentation of dual-channel structural magnetic resonance imaging (MRI) volumes of the human brain into four tissue classes. The state-of-the-art FSL FAST segmentation software (Zhang et al., 2001) is in widespread clinical use, and so it is considered a benchmark. A significant proportion of FAST’s errors has been shown to be localised to cortical sulci and blood vessels; this issue has driven the developments in this thesis, rather than any particular clinical demand. The original theme lies in preserving and even restoring these thin structures, poorly resolved in typical clinical MRI. Bright plate-shaped sulci and dark tubular vessels are best contrasted from the other tissues using the T2- and PD-weighted data, respectively. A contrasting tube detector algorithm (based on Frangi et al., 1998) was adapted to detect both structures, with smoothing (based on Westin and Knutsson, 2006) of an intermediate tensor representation to ensure smoothness and fuller coverage of the maps. The segmentation strategy required the MRI volumes to be upscaled to an artificial high resolution where a small partial volume label set would be valid and the segmentation process would be simplified. A resolution enhancement process (based on Salvado et al., 2006) was significantly modified to smooth homogeneous regions and sharpen their boundaries in dual-channel data. In addition, it was able to preserve the mapped thin structures’ intensities or restore them to pure tissue values. Finally, the segmentation phase employed a relaxation-based labelling optimisation process (based on Li et al., 1997) to improve accuracy, rather than more efficient greedy methods which are typically used. The thin structure location prior maps and the resolution-enhanced data also helped improve the labelling accuracy, particularly around sulci and vessels. Testing was performed on the aged LBC1936 clinical dataset and on younger brain volumes acquired at the SHEFC Brain Imaging Centre (Western General Hospital, Edinburgh, UK), as well as the BrainWeb phantom. Overall, the proposed methods rivalled and often improved segmentation accuracy compared to FAST, where the ground truth was produced by a radiologist using software designed for this project. The performance in pathological and atrophied brain volumes, and the differences with the original segmentation algorithm on which it was based (van Leemput et al., 2003), were also examined. Among the suggestions for future development include a soft labelling consensus formation framework to mitigate rater bias in the ground truth, and contour-based models of the brain parenchyma to provide additional structural constraints.

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    Authors: Winkler, A;

    This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.

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    Oxford University Research Archive
    Other literature type . 2017
    License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Oxford University Re...arrow_drop_down
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      Oxford University Research Archive
      Other literature type . 2017
      License: CC BY
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    Authors: Humphreys, G; Allen, H; Mavritsaki, E;

    We review research from our laboratory that attempts to pull apart the functional and neural mechanisms of visual search using converging, inter-disciplinary evidence from experimental studies with normal participants, neuropsychological studies with brain lesioned patients, functional brain imaging and computational modelling. The work suggests that search is determined by excitatory mechanisms that support the selection of target stimuli, and inhibitory mechanisms that suppress irrelevant distractors. These mechanisms operate through separable though overlapping neural circuits which can be functionally decomposed by imposing model-based analyses on brain imaging data. The chapter highlights the need for inter-disciplinary research for understanding complex cognitive processes at several levels.

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    Oxford University Research Archive
    Other literature type . Part of book or chapter of book . 2009 . 2016 . Peer-reviewed
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    Part of book or chapter of book
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CORE (RIOXX-UK Aggre...arrow_drop_down
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      Oxford University Research Archive
      Other literature type . Part of book or chapter of book . 2009 . 2016 . Peer-reviewed
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      https://nottingham-repository....
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sen, Arjune; Capelli, Valentina; Husain, Masud;

    Abstract With advances in healthcare and an ageing population, the number of older adults with epilepsy is set to rise substantially across the world. In developed countries the highest incidence of epilepsy is already in people over 65 and, as life expectancy increases, individuals who developed epilepsy at a young age are also living longer. Recent findings show that older persons with epilepsy are more likely to suffer from cognitive dysfunction and that there might be an important bidirectional relationship between epilepsy and dementia. Thus some people with epilepsy may be at a higher risk of developing dementia, while individuals with some forms of dementia, particularly Alzheimer’s disease and vascular dementia, are at significantly higher risk of developing epilepsy. Consistent with this emerging view, epidemiological findings reveal that people with epilepsy and individuals with Alzheimer’s disease share common risk factors. Recent studies in Alzheimer’s disease and late-onset epilepsy also suggest common pathological links mediated by underlying vascular changes and/or tau pathology. Meanwhile electrophysiological and neuroimaging investigations in epilepsy, Alzheimer’s disease, and vascular dementia have focused interest on network level dysfunction, which might be important in mediating cognitive dysfunction across all three of these conditions. In this review we consider whether seizures promote dementia, whether dementia causes seizures, or if common underlying pathophysiological mechanisms cause both. We examine the evidence that cognitive impairment is associated with epilepsy in older people (aged over 65) and the prognosis for patients with epilepsy developing dementia, with a specific emphasis on common mechanisms that might underlie the cognitive deficits observed in epilepsy and Alzheimer’s disease. Our analyses suggest that there is considerable intersection between epilepsy, Alzheimer’s disease and cerebrovascular disease raising the possibility that better understanding of shared mechanisms in these conditions might help to ameliorate not just seizures, but also epileptogenesis and cognitive dysfunction. Older people with epilepsy are more likely to suffer from dementia, while individuals with dementia are at higher risk of developing epilepsy. Sen et al. consider common mechanisms that might underlie the cognitive deficits observed in both groups by examining findings from epidemiological, neuropsychological, molecular, electrophysiological and brain imaging perspectives.

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    Brain
    Article . 2018
    Data sources: PubMed Central
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    Oxford University Research Archive
    Other literature type . 2018
    License: CC BY
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      Brain
      Article . 2018
      Data sources: PubMed Central
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      Oxford University Research Archive
      Other literature type . 2018
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  • Authors: Pearce, Matthew Craig;

    Matrix factorisation treats observations as linear combinations of basis vectors together with, possibly, additive noise. Notable techniques in this family are Principal Components Analysis and Independent Components Analysis. Applied to brain images, matrix factorisation provides insight into the spatial and temporal structure of data. We improve on current practice with methods that unify different stages of analysis simultaneously for all subjects in a dataset, including dimension estimation and reduction. This results in uncertainty information being carried coherently through the analysis. A computationally efficient approach to correlated multivariate normal distributions is set out. This enables spatial smoothing during the inference of basis vectors, to a level determined by the data. Applied to neuroimaging, this reduces the need for blurring of the data during preprocessing. Orthogonality constraints on the basis are relaxed, allowing for overlapping ‘networks’ of activity. We consider a nonparametric matrix factorisation model inferred using Markov Chain Monte Carlo (MCMC). This approach incorporates dimensionality estimation into the infer- ence process. Novel parallelisation strategies for MCMC on repeated graphs are provided to expedite inference. In simulations, modelling correlation structure is seen to improve source separation where latent basis vectors are not orthogonal. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) project obtained fMRI data while subjects watched a short film, on 30 of whose recordings we demonstrate the approach. To conduct inference on larger datasets, we provide a fixed dimension Structured Matrix Factorisation (SMF) model, inferred through Variational Bayes (VB). By modelling the components as a mixture, more general distributions can be expressed. The VB approach scaled to 600 subjects from Cam-CAN, enabling a comparison to, and validation of, the main findings of an earlier analysis; notably that subjects’ responses to movie watching became less synchronised with age. We discuss differences in results obtained under the MCMC and VB inferred models. This work was supported by the Medical Research Council at the Biostatistics Unit [Unit Programme number U105292687].

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    Apollo
    Thesis . 2018
    Data sources: Datacite
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      Apollo
      Thesis . 2018
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jia, Ke;

    Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet, evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer-scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high field (7T) functional imaging at sub-millimetre resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. Our results provide evidence for recurrent plasticity, by contrast to sensory encoding vs. feedback mechanisms. We demonstrate that learning alters orientation-specific representations in superficial rather than middle V1 layers, suggesting changes in read-out rather than input signals. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer-scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro- circuits of experience-dependent plasticity. $$ \ $$ See the file 'Description of uploaded data' for a detailed description of the dataset.

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    Apollo
    Dataset
    License: CC BY
    Data sources: Apollo
    Apollo
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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      Apollo
      Dataset
      License: CC BY
      Data sources: Apollo
      Apollo
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Job, Dominic; Gonzalez, Rodriguez; Wardlaw, Joanna;

    Brain Research Imaging Centre (BRIC) Here we present a brief discussion of current challenges to data integration and sharing in the field of human neuroimaging at Edinburgh University.

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    Edinburgh Research Archive
    Conference object . 2014
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      Edinburgh Research Archive
      Conference object . 2014
  • Authors: Ledig, Christian; Schuh, Andreas; Guerrero, Ricardo; Heckemann, Rolf A.; +1 Authors

    Data accompanying the article: C. Ledig, A. Schuh, R. Guerrero, R. Heckemann, D. Rueckert, Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database, Scientific Reports, 2018. Data derived from 5074 images from the ADNI cohort: - structural segmentations (138 regions, MALPEM); - binary brain masks (pincram); - features (volumes, asymmetry, atrophy rates) and disease labels; - lists of processed images IsSupplementTo: Ledig C, Schuh A, Guerrero R, Heckemann RA, Rueckert D (2018) Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database. Scientific Reports, 2018. https://doi.org/10.1038/s41598-018-29295-9

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    Authors: Papmeyer, Martina;

    Bipolar disorder (BD) and major depressive disorder (MDD) are characterised by a fundamental disturbance of mood, with strong support for overlapping causal pathways. Structural brain and neurocognitive abnormalities have been associated with mood disorders, but it is unknown whether these reflect early adverse effects predisposing to mood disorders or emerge as a consequence of illness onset. The Bipolar Family Study is well-suited to examine the origin of structural brain and neuropsychological abnormalities in mood disorders further. The volumes of subcortical brain regions, cortical thickness and surface area measures of frontal and temporal regions of interest and neuropsychological performance over a two-year time interval was compared at baseline and longitudinally between three groups: young individuals at high risk of mood disorders who subsequently developed MDD during the follow-up period (HR-MDD), individuals at high risk of mood disorders who remained well (HR-well), and healthy control subjects (HC). The longitudinal analysis of cortical thickness revealed significant group effects for the right parahippocampal and right fusiform gyrus. Cortical thickness in both of these brain regions across the two time points was reduced in both high-risk groups relative to controls, with the HR-MDD group displaying a thinner parahippocampus gyrus than the HR-well group. Moreover, a significant interaction effect was observed for the left inferior frontal and left precentral gyrus. The HR-well subjects had progressive thickness reductions in these brain regions relative to controls, while the HR-MDD group showed cortical thickening of these areas. Finally, longitudinal analyses of neuropsychological performance revealed a significant group effect for long delay verbal memory and extradimensional set-shifting performance. Reduced neurocognitive performance during both tasks across the two time points was found in the HR-well group relative to controls, with the HR-MDD group displaying decreased extradimensional set-shifting abilities as compared to the HC group only. These findings indicate, that reduced left parahippocampal and fusiform thickness constitute a familial trait marker for vulnerability to mood disorders and may thus form potential neuroanatomic endophenotypes. Particularly strong thickness reductions of the parahippocampal gyrus appear be linked to an onset of MDD. Moreover, progressive thickness reductions in the left inferior frontal and precentral gyrus in early adulthood form a familial trait marker for vulnerability to mood disorders, potentially reflecting early neurodegenerative processes. By contrast, an absence of cortical thinning of these brain regions in early adulthood appears to be linked to the onset of MDD, potentially reflecting a lack or delay of normal synaptic pruning processes. Reduced long delay verbal memory and extradimensional set-shifting performance across time constitute a familial trait marker for vulnerability to mood disorders, likely representing disturbances of normal brain development predisposing to illness. These findings advance our understanding of the origin of structural brain and neurocognitive abnormalities in mood disorders.

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    Authors: Franke, Barbara; Stein, Jason L; Ripke, Stephan; Anttila, Verneri; +30 Authors

    Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between schizophrenia cases and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. The current study provides proof-of-concept (albeit based on a limited set of structural brain measures), and defines a roadmap for future studies investigating the genetic covariance between structural/functional brain phenotypes and risk for psychiatric disorders.

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    Nature Neuroscience
    Article . 2016
    Data sources: PubMed Central
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      Nature Neuroscience
      Article . 2016
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Withers, James;

    This thesis presents a method for the segmentation of dual-channel structural magnetic resonance imaging (MRI) volumes of the human brain into four tissue classes. The state-of-the-art FSL FAST segmentation software (Zhang et al., 2001) is in widespread clinical use, and so it is considered a benchmark. A significant proportion of FAST’s errors has been shown to be localised to cortical sulci and blood vessels; this issue has driven the developments in this thesis, rather than any particular clinical demand. The original theme lies in preserving and even restoring these thin structures, poorly resolved in typical clinical MRI. Bright plate-shaped sulci and dark tubular vessels are best contrasted from the other tissues using the T2- and PD-weighted data, respectively. A contrasting tube detector algorithm (based on Frangi et al., 1998) was adapted to detect both structures, with smoothing (based on Westin and Knutsson, 2006) of an intermediate tensor representation to ensure smoothness and fuller coverage of the maps. The segmentation strategy required the MRI volumes to be upscaled to an artificial high resolution where a small partial volume label set would be valid and the segmentation process would be simplified. A resolution enhancement process (based on Salvado et al., 2006) was significantly modified to smooth homogeneous regions and sharpen their boundaries in dual-channel data. In addition, it was able to preserve the mapped thin structures’ intensities or restore them to pure tissue values. Finally, the segmentation phase employed a relaxation-based labelling optimisation process (based on Li et al., 1997) to improve accuracy, rather than more efficient greedy methods which are typically used. The thin structure location prior maps and the resolution-enhanced data also helped improve the labelling accuracy, particularly around sulci and vessels. Testing was performed on the aged LBC1936 clinical dataset and on younger brain volumes acquired at the SHEFC Brain Imaging Centre (Western General Hospital, Edinburgh, UK), as well as the BrainWeb phantom. Overall, the proposed methods rivalled and often improved segmentation accuracy compared to FAST, where the ground truth was produced by a radiologist using software designed for this project. The performance in pathological and atrophied brain volumes, and the differences with the original segmentation algorithm on which it was based (van Leemput et al., 2003), were also examined. Among the suggestions for future development include a soft labelling consensus formation framework to mitigate rater bias in the ground truth, and contour-based models of the brain parenchyma to provide additional structural constraints.

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    Authors: Winkler, A;

    This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.

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    Oxford University Research Archive
    Other literature type . 2017
    License: CC BY
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      Oxford University Research Archive
      Other literature type . 2017
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    Authors: Humphreys, G; Allen, H; Mavritsaki, E;

    We review research from our laboratory that attempts to pull apart the functional and neural mechanisms of visual search using converging, inter-disciplinary evidence from experimental studies with normal participants, neuropsychological studies with brain lesioned patients, functional brain imaging and computational modelling. The work suggests that search is determined by excitatory mechanisms that support the selection of target stimuli, and inhibitory mechanisms that suppress irrelevant distractors. These mechanisms operate through separable though overlapping neural circuits which can be functionally decomposed by imposing model-based analyses on brain imaging data. The chapter highlights the need for inter-disciplinary research for understanding complex cognitive processes at several levels.

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    Oxford University Research Archive
    Other literature type . Part of book or chapter of book . 2009 . 2016 . Peer-reviewed
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      Other literature type . Part of book or chapter of book . 2009 . 2016 . Peer-reviewed
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      https://nottingham-repository....
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sen, Arjune; Capelli, Valentina; Husain, Masud;

    Abstract With advances in healthcare and an ageing population, the number of older adults with epilepsy is set to rise substantially across the world. In developed countries the highest incidence of epilepsy is already in people over 65 and, as life expectancy increases, individuals who developed epilepsy at a young age are also living longer. Recent findings show that older persons with epilepsy are more likely to suffer from cognitive dysfunction and that there might be an important bidirectional relationship between epilepsy and dementia. Thus some people with epilepsy may be at a higher risk of developing dementia, while individuals with some forms of dementia, particularly Alzheimer’s disease and vascular dementia, are at significantly higher risk of developing epilepsy. Consistent with this emerging view, epidemiological findings reveal that people with epilepsy and individuals with Alzheimer’s disease share common risk factors. Recent studies in Alzheimer’s disease and late-onset epilepsy also suggest common pathological links mediated by underlying vascular changes and/or tau pathology. Meanwhile electrophysiological and neuroimaging investigations in epilepsy, Alzheimer’s disease, and vascular dementia have focused interest on network level dysfunction, which might be important in mediating cognitive dysfunction across all three of these conditions. In this review we consider whether seizures promote dementia, whether dementia causes seizures, or if common underlying pathophysiological mechanisms cause both. We examine the evidence that cognitive impairment is associated with epilepsy in older people (aged over 65) and the prognosis for patients with epilepsy developing dementia, with a specific emphasis on common mechanisms that might underlie the cognitive deficits observed in epilepsy and Alzheimer’s disease. Our analyses suggest that there is considerable intersection between epilepsy, Alzheimer’s disease and cerebrovascular disease raising the possibility that better understanding of shared mechanisms in these conditions might help to ameliorate not just seizures, but also epileptogenesis and cognitive dysfunction. Older people with epilepsy are more likely to suffer from dementia, while individuals with dementia are at higher risk of developing epilepsy. Sen et al. consider common mechanisms that might underlie the cognitive deficits observed in both groups by examining findings from epidemiological, neuropsychological, molecular, electrophysiological and brain imaging perspectives.

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    Brain
    Article . 2018
    Data sources: PubMed Central
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    Oxford University Research Archive
    Other literature type . 2018
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  • Authors: Pearce, Matthew Craig;

    Matrix factorisation treats observations as linear combinations of basis vectors together with, possibly, additive noise. Notable techniques in this family are Principal Components Analysis and Independent Components Analysis. Applied to brain images, matrix factorisation provides insight into the spatial and temporal structure of data. We improve on current practice with methods that unify different stages of analysis simultaneously for all subjects in a dataset, including dimension estimation and reduction. This results in uncertainty information being carried coherently through the analysis. A computationally efficient approach to correlated multivariate normal distributions is set out. This enables spatial smoothing during the inference of basis vectors, to a level determined by the data. Applied to neuroimaging, this reduces the need for blurring of the data during preprocessing. Orthogonality constraints on the basis are relaxed, allowing for overlapping ‘networks’ of activity. We consider a nonparametric matrix factorisation model inferred using Markov Chain Monte Carlo (MCMC). This approach incorporates dimensionality estimation into the infer- ence process. Novel parallelisation strategies for MCMC on repeated graphs are provided to expedite inference. In simulations, modelling correlation structure is seen to improve source separation where latent basis vectors are not orthogonal. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) project obtained fMRI data while subjects watched a short film, on 30 of whose recordings we demonstrate the approach. To conduct inference on larger datasets, we provide a fixed dimension Structured Matrix Factorisation (SMF) model, inferred through Variational Bayes (VB). By modelling the components as a mixture, more general distributions can be expressed. The VB approach scaled to 600 subjects from Cam-CAN, enabling a comparison to, and validation of, the main findings of an earlier analysis; notably that subjects’ responses to movie watching became less synchronised with age. We discuss differences in results obtained under the MCMC and VB inferred models. This work was supported by the Medical Research Council at the Biostatistics Unit [Unit Programme number U105292687].

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    Thesis . 2018
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      Apollo
      Thesis . 2018
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    Authors: Jia, Ke;

    Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet, evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer-scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high field (7T) functional imaging at sub-millimetre resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. Our results provide evidence for recurrent plasticity, by contrast to sensory encoding vs. feedback mechanisms. We demonstrate that learning alters orientation-specific representations in superficial rather than middle V1 layers, suggesting changes in read-out rather than input signals. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer-scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro- circuits of experience-dependent plasticity. $$ \ $$ See the file 'Description of uploaded data' for a detailed description of the dataset.

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    Apollo
    Dataset
    License: CC BY
    Data sources: Apollo
    Apollo
    Dataset . 2020
    License: CC BY
    Data sources: Datacite