Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks

Neural computations can be framed as dynamical processes, whereby the structure of the dynamics within a neural network is a direct reflection of the computations that the network performs. A key step in generating mechanistic interpretations within this computation through dynamics framework is to establish the link among network connectivity, dynamics, and computation. This link is only partly understood. Recent work has focused on producing algorithms for engineering artificial recurrent neural networks (RNN) with dynamics targeted to a specific goal manifold. Some of these algorithms require only a set of vectors tangent to the target manifold to be computed and thus provide a general method that can be applied to a diverse set of problems. Nevertheless, computing such vectors for an arbitrary manifold in a high-dimensional state space remains highly challenging, which in practice limits the applicability of this approach. Here we demonstrate how topology and differential geometry can be leveraged to simplify this task by first computing tangent vectors on a low-dimensional topological manifold and then embedding these in state space. The simplicity of this procedure greatly facilitates the creation of manifold-targeted RNNs, as well as the process of designing task-solving, on-manifold dynamics. This new method should enable the application of network engineering–based approaches to a wide set of problems in neuroscience and machine learning. Our description of how fundamental concepts from differential geometry can be mapped onto different aspects of neural dynamics is a further demonstration of how the language of differential geometry can enrich the conceptual framework for describing neural dynamics and computation

Guided Act and Feel Indonesia (GAF-ID) – Internet-based behavioral activation intervention for depression in Indonesia: study protocol for a randomized controlled trial

Background: Depression is a leading cause of disease burden across the world. However, in low-middle income countries (LMICs), access to mental health services is severely limited because of the insufficient number of mental health professionals available. The WHO initiated the Mental Health Gap Action Program (mhGAP) aiming to provide a coherent strategy for closing the gap between what is urgently needed and what is available in LMICs. Internet-based treatment is a promising strategy that can be made available to a large number of people now that Internet access is increasing rapidly throughout the world. The present study will investigate whether such an Internet-based treatment for depression is effective in Indonesia.  Methods: An Internet-based behavioral activation treatment, with support by lay counselors who will provide online feedback on the assignments and supportive phone contact to encourage participants to work in the program (Guided Act and Feel Indonesia/GAF-ID), is compared to an online-delivered minimal psychoeducation without any support (psychoeducation/PE). Initial assessment for inclusion is based on a Patient Health Questionnaire-9 (PHQ-9) score of at least 10 and meeting criteria for major depressive disorder or persistent depressive disorder as assessed using the Structured Clinical Interview for DSM-5 (SCID-5). Participants with depression (N=312) will be recruited and randomly assigned to GAF-ID or PE. Overall assessments will be done at baseline, post intervention (10 weeks from baseline) and follow-ups (3 months and 6 months from baseline). The primary outcome is the reduction of depression symptoms as measured by the PHQ-9 after 10 weeks from baseline.  Discussion: To our knowledge, this is the first study in Indonesia that examines the effectiveness of an Internet-based intervention for depression in a randomized controlled trial. The hope is that it can serve as a starting point for bridging the mental health gap in Indonesia and other LMICs. Trial registration: Nederlands Trial Register ( www.trialregister.nl ): NTR5920 , registered on 1 July 2016

A vigorous activity cycle mimicking a planetary system in HD200466

Stellar activity can be a source of radial velocity (RV) noise and can reproduce periodic RV variations similar to those produced by an exoplanet. We present the vigorous activity cycle in the primary of the visual binary HD200466, a system made of two almost identical solar-type stars with an apparent separation of 4.6 arcsec at a distance of 44+/-2 pc. High precision RV over more than a decade, adaptive optics (AO) images, and abundances have been obtained for both components. A linear trend in the RV is found for the secondary. We assumed that it is due to the binary orbit and once coupled with the astrometric data, it strongly constrains the orbital solution of the binary at high eccentricities (e~0.85) and quite small periastron of ~21 AU. If this orbital motion is subtracted from the primary radial velocity curve, a highly significant (false alarm probability <0.1%) period of about 1300 d is obtained, suggesting in a first analysis the presence of a giant planet, but it turned out to be due to the stellar activity cycle. Since our spectra do not include the Ca~II resonance lines, we measured a chromospheric activity indicator based on the Halpha line to study the correlation between activity cycles and long-term activity variations. While the bisector analysis of the line profile does not show a clear indication of activity, the correlation between the Halpha line indicator and the RV measurements identify the presence of a strong activity cycle.Comment: Accepted on Astronomy and Astrophysics Main Journal 2014, 16 pages, 18 figure

Quality of Care for Patients With Type 2 Diabetes in Primary Care in Norway Is Improving: Results of cross-sectional surveys of 33 general practices in 1995 and 2005

OBJECTIVE—To assess changes in the quality of care in Norway for patients with type 2 diabetes

Variable stars in the open cluster NGC 6791 and its surrounding field

Aims: This work presents a high--precision variability survey in the field of the old, super metal-rich open cluster NGC 6791. Methods: The data sample consists of more than 75,000 high-precision CCD time series measurements in the V band obtained mainly at the Canada-France-Hawaii Telescope, with additional data from S. Pedro Martir and Loiano observatories, over a time span of ten nights. The field covers an area of 42x28 arcmin^2. Results: We have discovered 260 new variables and re-determined periods and amplitudes of 70 known variable stars. By means of a photometric evaluation of the membership in NGC 6791, and a preliminary membership based on the proper motions, we give a full description of the variable content of the cluster and surrounding field in the range 16<V<23.5. Accurate periods can be given for the variables with P<4.0 d, while for ones with longer periods the limited time-baseline hampered precise determinations. We categorized the entire sample as follows: 6 pulsating, 3 irregular, 3 cataclysmic, 89 rotational variables and 61 eclipsing systems; moreover, we detected 168 candidate variables for which we cannot give a variability class since their periods are much longer than our time baseline. Conclusions: On the basis of photometric considerations, and of the positions of the stars with respect to the center of the cluster, we inferred that 11 new variable stars are likely members of the cluster, for 22 stars the membership is doubtful and 137 are likely non-members. We also detected an outburst of about 3 mag in the light curve of a very faint blue star belonging to the cluster and we suggest that this star could be a new U Gem (dwarf nova) cataclysmic variable.Comment: 24 pages, 19 Figures, A&A accepte

BrainGlobe Atlas API: a common interface for neuroanatomical atlases

Summary: Neuroscientists routinely perform experiments aimed at recording or manipulating neural activity, uncovering physiological processes underlying brain function or elucidating aspects of brain anatomy. Understanding how the brain generates behaviour ultimately depends on merging the results of these experiments into a unified picture of brain anatomy and function. Brain atlases are crucial in this endeavour: by outlining the organization of brain regions they provide a reference upon which our understanding of brain function can be anchored. More recently, digital high-resolution 3d atlases have been produced for several model organisms providing an invaluable resource for the research community. Effective use of these atlases depends on the availability of an application programming interface (API) that enables researchers to develop software to access and query atlas data. However, while some atlases come with an API, these are generally specific for individual atlases, and this hinders the development and adoption of open-source neuroanatomy software. The BrainGlobe atlas API (BG-Atlas API) overcomes this problem by providing a common interface for programmers to download and process data across a variety of model organisms. By adopting the BG-Atlas API, software can then be developed agnostic to the atlas, increasing adoption and interoperability of packages in neuroscience and enabling direct integration of different experimental modalities and even comparisons across model organisms

Visualizing anatomically registered data with Brainrender

Three-dimensional (3D) digital brain atlases and high-throughput brain wide imaging techniques generate large multidimensional datasets that can be registered to a common reference frame. Generating insights from such datasets depends critically on visualization and interactive data exploration, but this a challenging task. Currently available software is dedicated to single atlases, model species or data types, and generating 3D renderings that merge anatomically registered data from diverse sources requires extensive development and programming skills. Here, we present brainrender: an open-source Python package for interactive visualization of multidimensional datasets registered to brain atlases. Brainrender facilitates the creation of complex renderings with different data types in the same visualization and enables seamless use of different atlas sources. High-quality visualizations can be used interactively and exported as high-resolution figures and animated videos. By facilitating the visualization of anatomically registered data, brainrender should accelerate the analysis, interpretation, and dissemination of brain-wide multidimensional data

Coordinated X-ray and Optical observations of Star-Planet Interaction in HD 17156

The large number of close-in Jupiter-size exoplanets prompts the question whether star-planet interaction (SPI) effects can be detected. We focused our attention on the system HD 17156, having a Jupiter-mass planet in a very eccentric orbit. Here we present results of the XMM-Newton observations and of a five months coordinated optical campaign with the HARPS-N spectrograph. We observed HD 17156 with XMM-Newton when the planet was approaching the apoastron and then at the following periastron passage, quasi simultaneously with HARPS-N. We obtained a clear ($\approx 5.5\sigma$) X-ray detection only at the periastron visit, accompanied by a significant increase of the $R'_{\rm HK}$ chromospheric index. We discuss two possible scenarios for the activity enhancement: magnetic reconnection and flaring or accretion onto the star of material tidally stripped from the planet. In any case, this is possibly the first evidence of a magnetic SPI effect caught in action