Search results for "Neural"
showing 10 items of 2783 documents
Single cell 3’UTR analysis identifies changes in alternative polyadenylation throughout neuronal differentiation and in autism
2020
SUMMARYAutism spectrum disorder (ASD) is a neurodevelopmental disease affecting social behavior. Many of the high-confident ASD risk genes relate to mRNA translation. Specifically, many of these genes are involved in regulation of gene expression for subcellular compartmentalization of proteins1. Cis-regulatory motifs that often localize to 3’- and 5’-untranslated regions (UTRs) offer an additional path for posttranscriptional control of gene expression. Alternative cleavage and polyadenylation (APA) affect 3’UTR length thereby influencing the presence or absence of regulatory elements. However, APA has not yet been addressed in the context of neurodevelopmental disorders. Here we used sing…
On Analytical vs . Schizophrenic Procedures for Computing Music
2009
The authors present a perspective on computer music, which is based on some particular definitions of music in relation to oral culture and cybernetics. They describe some experiments with different models of neural architectures which generate original music, and then suggest that if such neural systems are rich, effective and intuitive enough to produce ‘live’ music, the understanding of their behaviour may require the development of some ‘schizophrenic’ procedures, as well as analytical ones.
Molecular mode-coupling theory applied to a liquid of diatomic molecules
2000
We study the molecular mode coupling theory for a liquid of diatomic molecules. The equations for the critical tensorial nonergodicity parameters ${\bf F}_{ll'}^m(q)$ and the critical amplitudes of the $\beta$ - relaxation ${\bf H}_{ll'}^m(q)$ are solved up to a cut off $l_{co}$ = 2 without any further approximations. Here $l,m$ are indices of spherical harmonics. Contrary to previous studies, where additional approximations were applied, we find in agreement with simulations, that all molecular degrees of freedom vitrify at a single temperature $T_c$. The theoretical results for the non ergodicity parameters and the critical amplitudes are compared with those from simulations. The qualitat…
Segmentation-Free Estimation of Aortic Diameters from MRI Using Deep Learning
2021
Accurate and reproducible measurements of the aortic diameters are crucial for the diagnosis of cardiovascular diseases and for therapeutic decision making. Currently, these measurements are manually performed by healthcare professionals, being time consuming, highly variable, and suffering from lack of reproducibility. In this work we propose a supervised deep-learning method for the direct estimation of aortic diameters. The approach is devised and tested over 100 magnetic resonance angiography scans without contrast agent. All data was expert-annotated at six aortic locations typically used in clinical practice. Our approach makes use of a 3D+2D convolutional neural network (CNN) that ta…
Misguided Effort with Elusive Implications
2016
Good self-control has been linked to adaptive outcomes such as better health, cohesive personal relationships, success in the workplace and at school, and less susceptibility to crime and addictions. In contrast, self-control failure is linked to maladaptive outcomes. Understanding the mechanisms by which self-control predicts behavior may assist in promoting better regulation and outcomes. A popular approach to understanding self-control is the strength or resource depletion model. Self-control is conceptualized as a limited resource that becomes depleted after a period of exertion resulting in self-control failure. The model has typically been tested using a sequential-task experimental p…
An implicitly parallel EDA based on restricted boltzmann machines
2014
We present a parallel version of RBM-EDA. RBM-EDA is an Estimation of Distribution Algorithm (EDA) that models dependencies between decision variables using a Restricted Boltzmann Machine (RBM). In contrast to other EDAs, RBM-EDA mainly uses matrix-matrix multiplications for model estimation and sampling. Hence, for implementation, standard libraries for linear algebra can be used. This allows an easy parallelization and leads to a high utilization of parallel architectures. The probabilistic model of the parallel version and the version on a single core are identical. We explore the speedups gained from running RBM-EDA on a Graphics Processing Unit. For problems of bounded difficulty like …
Connecting temporal identity to mitosis: the regulation of Hunchback in Drosophila neuroblast lineages.
2006
Both in vertebrates and invertebrates, neural stem cells generate different cell types at different times during development. It has been suggested that this process depends on temporal identity transitions of neural progenitors, but the underlying mechanism has not been resolved, yet. Recently, Drosophila neuroblasts (NBs) have been shown to be an excellent model system to investigate this subject. Here, changes in temporal identity are regulated by sequential and transient expression of transcription factors in the NB, such as Hunchback (Hb) and Kruppel (Kr). The temporal expression profile is maintained in the progeny. Hb is expressed first and thus defines the earliest identity in a giv…
On the Robustness of Deep Features for Audio Event Classification in Adverse Environments
2018
Deep features, responses to complex input patterns learned within deep neural networks, have recently shown great performance in image recognition tasks, motivating their use for audio analysis tasks as well. These features provide multiple levels of abstraction which permit to select a sufficiently generalized layer to identify classes not seen during training. The generalization capability of such features is very useful due to the lack of complete labeled audio datasets. However, as opposed to classical hand-crafted features such as Mel-frequency cepstral coefficients (MFCCs), the performance impact of having an acoustically adverse environment has not been evaluated in detail. In this p…
Reverse engineering expert visual observations: From fixations to the learning of spatial filters with a neural-gas algorithm
2013
Human beings can become experts in performing specific vision tasks, for example, doctors analysing medical images, or botanists studying leaves. With sufficient knowledge and experience, people can become very efficient at such tasks. When attempting to perform these tasks with a machine vision system, it would be highly beneficial to be able to replicate the process which the expert undergoes. Advances in eye-tracking technology can provide data to allow us to discover the manner in which an expert studies an image. This paper presents a first step towards utilizing these data for computer vision purposes. A growing-neural-gas algorithm is used to learn a set of Gabor filters which give h…
An integrated framework for risk profiling of breast cancer patients following surgery.
2006
Objective: An integrated decision support framework is proposed for clinical oncologists making prognostic assessments of patients with operable breast cancer. The framework may be delivered over a web interface. It comprises a triangulation of prognostic modelling, visualisation of historical patient data and an explanatory facility to interpret risk group assignments using empirically derived Boolean rules expressed directly in clinical terms. Methods and materials: The prognostic inferences in the interface are validated in a multicentre longitudinal cohort study by modelling retrospective data from 917 patients recruited at Christie Hospital, Wilmslow between 1983 and 1989 and predictin…