Quantum-inspired feature and parameter optimization of evolving spiking neural networks with a case study from ecological modelling

The paper introduces a framework and implementation of an integrated connectionist system, where the features and the parameters of an evolving spiking neural network are optimised together using a quantum representation of the features and a quantum inspired evolutionary algorithm for optimisation. The proposed model is applied on ecological data modeling problem demonstrating a significantly better classification accuracy than traditional neural network approaches and a more appropriate feature subset selected from a larger initial number of features. Results are compared to a naive Bayesian classifier

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?; and, 2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset.The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch.Comment: 8 pages, 3 figure

AIGO: towards a unified framework for the analysis and the inter-comparison of GO functional annotations

BACKGROUND: In response to the rapid growth of available genome sequences, efforts have been made to develop automatic inference methods to functionally characterize them. Pipelines that infer functional annotation are now routinely used to produce new annotations at a genome scale and for a broad variety of species. These pipelines differ widely in their inference algorithms, confidence thresholds and data sources for reasoning. This heterogeneity makes a comparison of the relative merits of each approach extremely complex. The evaluation of the quality of the resultant annotations is also challenging given there is often no existing gold-standard against which to evaluate precision and recall. RESULTS: In this paper, we present a pragmatic approach to the study of functional annotations. An ensemble of 12 metrics, describing various aspects of functional annotations, is defined and implemented in a unified framework, which facilitates their systematic analysis and inter-comparison. The use of this framework is demonstrated on three illustrative examples: analysing the outputs of state-of-the-art inference pipelines, comparing electronic versus manual annotation methods, and monitoring the evolution of publicly available functional annotations. The framework is part of the AIGO library (http://code.google.com/p/aigo) for the Analysis and the Inter-comparison of the products of Gene Ontology (GO) annotation pipelines. The AIGO library also provides functionalities to easily load, analyse, manipulate and compare functional annotations and also to plot and export the results of the analysis in various formats. CONCLUSIONS: This work is a step toward developing a unified framework for the systematic study of GO functional annotations. This framework has been designed so that new metrics on GO functional annotations can be added in a very straightforward way

Musical practice and cognitive aging: two cross-sectional studies point to phonemic fluency as a potential candidate for a use-dependent adaptation

Because of permanent use-dependent brain plasticity, all lifelong individuals' experiences are believed to influence the cognitive aging quality. In older individuals, both former and current musical practices have been associated with better verbal skills, visual memory, processing speed, and planning function. This work sought for an interaction between musical practice and cognitive aging by comparing musician and non-musician individuals for two lifetime periods (middle and late adulthood). Long-term memory, auditory-verbal short-term memory, processing speed, non-verbal reasoning, and verbal fluencies were assessed. In Study 1, measures of processing speed and auditory-verbal short-term memory were significantly better performed by musicians compared with controls, but both groups displayed the same age-related differences. For verbal fluencies, musicians scored higher than controls and displayed different age effects. In Study 2, we found that lifetime period at training onset (childhood vs. adulthood) was associated with phonemic, but not semantic, fluency performances (musicians who had started to practice in adulthood did not perform better on phonemic fluency than non-musicians). Current frequency of training did not account for musicians' scores on either of these two measures. These patterns of results are discussed by setting the hypothesis of a transformative effect of musical practice against a non-causal explanation

Stability of Top-Points in Scale Space

Abstract. This paper presents an algorithm for computing stability of top-points in scale-space. The potential usefulness of top-points in scalespace has already been shown for a number of applications, such as image reconstruction and image retrieval. In order to improve results only reliable top-points should be used. The algorithm is based on perturbation theory and noise propagation

Validation of Tissue Modelization and Classification Techniques in T1-Weighted MR Brain Images

We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this validation study. Two of them are based on Finite Gaussian Mixture (FGM) model. The first one consists only in pure gaussian distributions (FGM-EM). The second one uses a different model for partial volume (PV) (FGM-GA). The third one is based on a Hidden Markov Random Field (HMRF) model. All methods have been tested on a Digital Brain Phantom image considered as the ground truth. Noise and intensity non-uniformities have been added to simulate real image conditions. Also the effect of an anisotropic filter is considered. Results demonstrate that methods relying in both intensity and spatial information are in general more robust to noise and inhomogeneities. However, in some cases there is no significant differences between all presented methods

Tectonic and climatic controls on rift escarpments: Erosion and flexural rebound of the Dhofar passive margin (Gulf of Aden, Oman)

International audienceWe investigate the respective roles of climatic parameters and the flexural rigidity of the lithosphere in the erosion history and behavior of two adjacent rift escarpments along the northern coast of the Gulf of Aden, in Oman. At this 25 Myr old passive margin, we define a type 1 scarp, which is high, sharp-crested and has retreated 25-30 km inland from its master fault, and a type 2 scarp, which exhibits a more rounded profile, lower relief, and still coincides with its mapped normal fault trace. Since about 15 Ma, the margin has been seasonally affected by monsoon precipitation but with contrasting effects at the type 1 and type 2 escarpments depending on the position of the Intertropical Convergence Zone in the geologic past: during peak monsoon conditions, both scarps experienced heavy rainfall and runoff, whereas during monsoon-starved conditions (such as today), the type 2 scarp experienced a foggy, moist climate while the type 1 scarp remained much drier. In order to assess the relative effects of climate and flexural parameters on the present-day morphology of the Dhofar margin, we present onedimensional numerical models of erosion and flexure along two profiles representative of the type 1 and type 2 scarps. Unlike most surface process models previously published, where present-day topography is the only criterion by which to evaluate the quality of model outputs, model behavior here is additionally constrained by independent estimates of denudation provided by geological cross sections, well-defined fault traces, and other stratigraphic markers. The best fitting models indicate that the type 1 escarpment formed under relatively arid climatic conditions and was affected by significant erosion, recession and flexural uplift due to a low (7 km) effective elastic thickness. In contrast, the morphology of the type 2 fault scarp was smoothed by a more humid climate, but a high effective elastic thickness ( 15 km) prevented it from uplifting or receding. In addition, we show that the sedimentary load acting at the foot of the escarpments exerts significant influence on their morphological evolution, though this parameter is often neglected in other scarp evolution models

The word as a unit of meaning. The role of context in words meaning

A unit of meaning is a word plus all those words within its contextual context that are needed to disambiguate this word to make it monosemous. A lot of research were made to study the influence of the context. They testify that there is usually in each word a hard core of relatively stable meaning and can be modified by the context within certain limits

Accelerated development of cerebral small vessel disease in young stroke patients.

OBJECTIVE: To study the long-term prevalence of small vessel disease after young stroke and to compare this to healthy controls. METHODS: This prospective cohort study comprises 337 patients with an ischemic stroke or TIA, aged 18-50 years, without a history of TIA or stroke. In addition, 90 age- and sex-matched controls were included. At follow-up, lacunes, microbleeds, and white matter hyperintensity (WMH) volume were assessed using MRI. To investigate the relation between risk factors and small vessel disease, logistic and linear regression were used. RESULTS: After mean follow-up of 9.9 (SD 8.1) years, 337 patients were included (227 with an ischemic stroke and 110 with a TIA). Mean age of patients was 49.8 years (SD 10.3) and 45.4% were men; for controls, mean age was 49.4 years (SD 11.9) and 45.6% were men. Compared with controls, patients more often had at least 1 lacune (24.0% vs 4.5%, p < 0.0001). In addition, they had a higher WMH volume (median 1.5 mL [interquartile range (IQR) 0.5-3.7] vs 0.4 mL [IQR 0.0-1.0], p < 0.001). Compared with controls, patients had the same volume WMHs on average 10-20 years earlier. In the patient group, age at stroke (β = 0.03, 95% confidence interval [CI] 0.02-0.04) hypertension (β = 0.22, 95% CI 0.04-0.39), and smoking (β = 0.18, 95% CI 0.01-0.34) at baseline were associated with WMH volume. CONCLUSIONS: Patients with a young stroke have a higher burden of small vessel disease than controls adjusted for confounders. Cerebral aging seems accelerated by 10-20 years in these patients, which may suggest an increased vulnerability to vascular risk factors.This is the final version of the article. It first appeared from Wolters Kluwer via https://doi.org/10.​1212/​WNL.​0000000000003123

Omineca Herald, October, 04, 1979

The relation between progression of cerebral small vessel disease (SVD) and gait decline is uncertain, and diffusion tensor imaging (DTI) studies on gait decline are lacking. We therefore investigated the longitudinal associations between (micro) structural brain changes and gait decline in SVD using DTI. 275 participants were included from the Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort (RUN DMC), a prospective cohort of participants with cerebral small vessel disease aged 50–85years. Gait (using GAITRite) and magnetic resonance imaging measures were assessed during baseline (2006–2007) and follow-up (2011−2012). Linear regression analysis was used to investigate the association between changes in conventional magnetic resonance and diffusion tensor imaging measures and gait decline. Tract-based spatial statistics analysis was used to investigate region-specific associations between changes in white matter integrity and gait decline. 56.2% were male, mean age was 62.9years (SD8.2), mean follow-up duration was 5.4years (SD0.2) and mean gait speed decline was 0.2m/s (SD0.2). Stride length decline was associated with white matter atrophy (β=0.16, p=0.007), and increase in mean white matter radial diffusivity and mean diffusivity, and decrease in mean fractional anisotropy (respectively, β=−0.14, p=0.009; β=−0.12, p=0.018; β=0.10, p=0.049), independent of age, sex, height, follow-up duration and baseline stride length. Tract-based spatial statistics analysis showed significant associations between stride length decline and fractional anisotropy decrease and mean diffusivity increase (primarily explained by radial diffusivity increase) in multiple white matter tracts, with the strongest associations found in the corpus callosum and corona radiata, independent of traditional small vessel disease markers. White matter atrophy and loss of white matter integrity are associated with gait decline in older adults with small vessel disease after 5years of follow-up. These findings suggest that progression of SVD might play an important role in gait decline. Keywords: Cerebral small vessel disease (SVD), MRI, Diffusion tensor imaging (DTI), Tract-based spatial statistics (TBSS), Gai