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  • The neural events that change perception

    28 January 2018

    © 2017 by De Gruyter. Neuroscientific research has made tremendous progress towards unravelling the neuronal codes that underlie our rich sensory perception and experience. From single neurons in primates' visual brain that predict perceptual choices to activity patterns in defined neuronal circuits, electrical activity across different levels correlates with perception. The key to how neuronal signals give rise to our visual experience lies in causal interventions directly applied to neurons and circuits, interventions that alter perception naturalistically and in predictable ways. The most powerful and reliable intervention method in primates remains invasive electrical micro-stimulation, which can change selectively the appearance of visual objects defined by more than one visual cue. Such artificial signals are integrated with visually evoked stimuli and with contextual factors like reward. Scaling up these methodologies presents opportunities for vision replacement through cortical neuro-prosthetics.

  • Oligogenic genetic variation of neurodegenerative disease genes in 980 postmortem human brains.

    1 February 2018

    BACKGROUND: Several studies suggest that multiple rare genetic variants in genes causing monogenic forms of neurodegenerative disorders interact synergistically to increase disease risk or reduce the age of onset, but these studies have not been validated in large sporadic case series. METHODS: We analysed 980 neuropathologically characterised human brains with Alzheimer's disease (AD), Parkinson's disease-dementia with Lewy bodies (PD-DLB), frontotemporal dementia-amyotrophic lateral sclerosis (FTD-ALS) and age-matched controls. Genetic variants were assessed using the American College of Medical Genetics criteria for pathogenicity. Individuals with two or more variants within a relevant disease gene panel were defined as 'oligogenic'. RESULTS: The majority of oligogenic variant combinations consisted of a highly penetrant allele or known risk factor in combination with another rare but likely benign allele. The presence of oligogenic variants did not influence the age of onset or disease severity. After controlling for the single known major risk allele, the frequency of oligogenic variants was no different between cases and controls. CONCLUSIONS: A priori, individuals with AD, PD-DLB and FTD-ALS are more likely to harbour a known genetic risk factor, and it is the burden of these variants in combination with rare benign alleles that is likely to be responsible for some oligogenic associations. Controlling for this bias is essential in studies investigating a potential role for oligogenic variation in neurodegenerative diseases.

  • Edge- and detail-preserving sparse image representations for deformable registration of chest MRI and CT volumes.

    28 January 2018

    Deformable medical image registration requires the optimisation of a function with a large number of degrees of freedom. Commonly-used approaches to reduce the computational complexity, such as uniform B-splines and Gaussian image pyramids, introduce translation-invariant homogeneous smoothing, and may lead to less accurate registration in particular for motion fields with discontinuities. This paper introduces the concept of sparse image representation based on supervoxels, which are edge-preserving and therefore enable accurate modelling of sliding organ motions frequently seen in respiratory and cardiac scans. Previous shortcomings of using supervoxels in motion estimation, in particular inconsistent clustering in ambiguous regions, are overcome by employing multiple layers of supervoxels. Furthermore, we propose a new similarity criterion based on a binary shape representation of supervoxels, which improves the accuracy of single-modal registration and enables multimodal registration. We validate our findings based on the registration of two challenging clinical applications of volumetric deformable registration: motion estimation between inhale and exhale phase of CT scans for radiotherapy planning, and deformable multi-modal registration of diagnostic MRI and CT chest scans. The experiments demonstrate state-of-the-art registration accuracy, and require no additional anatomical knowledge with greatly reduced computational complexity.

  • SIENA-XL for improving the assessment of gray and white matter volume changes on brain MRI.

    28 January 2018

    In this article, SIENA-XL, a new segmentation-based longitudinal pipeline is introduced, for: (i) increasing the precision of longitudinal volume change estimation for white (WM) and gray (GM) matter separately, compared with cross-sectional segmentation methods such as SIENAX; and (ii) avoiding potential biases in registration-based methods when Jacobians are used, with a smoothing extent larger than spatial scale between tissue-interfaces, which is where atrophy usually occurs. SIENA-XL implements a new brain extraction procedure and a multi-time-point intensity equalization step before performing the final segmentation that also includes separate segmentation of deep GM structures by using FMRIB's Integrated Registration and Segmentation Tool. The detection of GM and WM volume changes with SIENA-XL was evaluated using different healthy control (HC) and multiple sclerosis (MS) MRI datasets and compared with the traditional SIENAX and two Jacobian-based approaches, SPM12 and SIENAX-JI (a version of SIENAX including Jacobian integration - JI). In scan-rescan data from HCs, SIENA-XL showed: (i) a significant decrease in error, of 50-70% when compared with SIENAX; (ii) no significant differences in error when compared with SIENAX-JI and SPM12 in a scan-rescan HC dataset that included repositioning. When tested in a HC dataset with scan-rescan both at baseline and after 1 year of follow-up, SIENA-XL showed: (i) significantly higher precision (P < 0.01) than SIENAX; (ii) no significant differences to SIENAX-JI and SPM12. Finally, in a dataset of 79 MS patients with a 2 years follow-up, SIENA-XL showed a substantial reduction of sample size, by comparison with SIENAX, SIENAX-JI, and SPM12, for detecting treatment effects of 25, 30, and 50%. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

  • Apathy in Alzheimer's disease

    28 January 2018

    © 2017 Apathy is the most common neuropsychiatric symptom in patients with Alzheimer's disease (AD). The presence of apathy has been related to greater caregiver distress, decreased quality of life, and increased morbidity. Here we review the most recent studies on this neuropsychiatric syndrome, focusing on prevalence, impact on quality of life, behavioural and neuroimaging studies, and treatment options. The results of some investigations on the behavioural and neuroanatomical profile of apathy in AD point to a role of frontostriatal circuits, specifically involving the anterior cingulate cortex. However, small and heterogeneous samples, lack of control for disease severity, and non-specific apathy scales complicate interpretation of results. Future studies might benefit from studying multiple dimensions of apathy within conceptual frameworks which allow for a deconstruction of underlying mechanisms.