Deep Learning for Neuroimaging: a Validation Study

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager’s toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data

Modular Organization of Functional Network Connectivity in Healthy Controls and Patients with Schizophrenia during the Resting State

Neuroimaging studies have shown that functional brain networks composed from select regions of interest have a modular community structure. However, the organization of functional network connectivity (FNC), comprising a purely data-driven network built from spatially independent brain components, is not yet clear. The aim of this study is to explore the modular organization of FNC in both healthy controls (HCs) and patients with schizophrenia (SZs). Resting state functional magnetic resonance imaging data of HCs and SZs were decomposed into independent components (ICs) by group independent component analysis (ICA). Then weighted brain networks (in which nodes are brain components) were built based on correlations between ICA time courses. Clustering coefficients and connectivity strength of the networks were computed. A dynamic branch cutting algorithm was used to identify modules of the FNC in HCs and SZs. Results show stronger connectivity strength and higher clustering coefficient in HCs with more and smaller modules in SZs. In addition, HCs and SZs had some different hubs. Our findings demonstrate altered modular architecture of the FNC in schizophrenia and provide insights into abnormal topological organization of intrinsic brain networks in this mental illness

Ultrathin compound semiconductor on insulator layers for high performance nanoscale transistors

Over the past several years, the inherent scaling limitations of electron devices have fueled the exploration of high carrier mobility semiconductors as a Si replacement to further enhance the device performance. In particular, compound semiconductors heterogeneously integrated on Si substrates have been actively studied, combining the high mobility of III-V semiconductors and the well-established, low cost processing of Si technology. This integration, however, presents significant challenges. Conventionally, heteroepitaxial growth of complex multilayers on Si has been explored. Besides complexity, high defect densities and junction leakage currents present limitations in the approach. Motivated by this challenge, here we utilize an epitaxial transfer method for the integration of ultrathin layers of single-crystalline InAs on Si/SiO2 substrates. As a parallel to silicon-on-insulator (SOI) technology14,we use the abbreviation "XOI" to represent our compound semiconductor-on-insulator platform. Through experiments and simulation, the electrical properties of InAs XOI transistors are explored, elucidating the critical role of quantum confinement in the transport properties of ultrathin XOI layers. Importantly, a high quality InAs/dielectric interface is obtained by the use of a novel thermally grown interfacial InAsOx layer (~1 nm thick). The fabricated FETs exhibit an impressive peak transconductance of ~1.6 mS/{\mu}m at VDS=0.5V with ON/OFF current ratio of greater than 10,000 and a subthreshold swing of 107-150 mV/decade for a channel length of ~0.5 {\mu}m

Review of Radiation-Induced Effects in Polyimide

Polyimide (PI, Kapton-H®) films are widely utilized in the spacecraft industry for their insulating properties, mechanical durability, light weight, and chemical resistance to radiation. Still PI materials remain exposed to a combination of high-energy electrons, protons, and ultraviolet (UV) photons, particles primarily responsible for radiation-induced damage in geosynchronous Earth orbit (GEO), which drastically change PI’s properties. This work reviews the effect of electron, proton, and UV photon irradiation on the material properties (morphology, absorption, mechanical properties, and charge transport) of PI. The different damaging mechanisms and chemical consequences that drive changes in the material properties of PI caused by each individual kind of irradiation will be discussed in detail

Pan-European phylogeography of the European roe deer (Capreolus capreolus)

To provide the most comprehensive picture of species phylogeny and phylogeography of European roe deer (Capreolus capreolus), we analyzed mtDNA control region (610 bp) of 1469 samples of roe deer from Central and Eastern Europe and included into the analyses additional 1541 mtDNA sequences from GenBank from other regions of the continent. We detected two mtDNA lineages of the species: European and Siberian (an introgression of C. pygargus mtDNA into C. capreolus). The Siberian lineage was most frequent in the eastern part of the continent and declined toward Central Europe. The European lineage contained three clades (Central, Eastern, and Western) composed of several haplogroups, many of which were separated in space. The Western clade appeared to have a discontinuous range from Portugal to Russia. Most of the haplogroups in the Central and the Eastern clades were under expansion during the Weichselian glacial period before the Last Glacial Maximum (LGM), while the expansion time of the Western clade overlapped with the Eemian interglacial. The high genetic diversity of extant roe deer is the result of their survival during the LGM probably in a large, contiguous range spanning from the Iberian Peninsula to the Caucasus Mts and in two northern refugia