627 research outputs found
Towards segmentation and spatial alignment of the human embryonic brain using deep learning for atlas-based registration
We propose an unsupervised deep learning method for atlas based registration
to achieve segmentation and spatial alignment of the embryonic brain in a
single framework. Our approach consists of two sequential networks with a
specifically designed loss function to address the challenges in 3D first
trimester ultrasound. The first part learns the affine transformation and the
second part learns the voxelwise nonrigid deformation between the target image
and the atlas. We trained this network end-to-end and validated it against a
ground truth on synthetic datasets designed to resemble the challenges present
in 3D first trimester ultrasound. The method was tested on a dataset of human
embryonic ultrasound volumes acquired at 9 weeks gestational age, which showed
alignment of the brain in some cases and gave insight in open challenges for
the proposed method. We conclude that our method is a promising approach
towards fully automated spatial alignment and segmentation of embryonic brains
in 3D ultrasound
Vortex lattices in strong type-II superconducting two-dimensional strips
We show how to calculate semi-analytically the dense vortex state in strong
type-II superconducting nanostructures. For the specific case of a strip, we
find vortex lattice solutions which also incorporate surface superconductivity.
We calculate the energy cost to displace individual vortex rows parallel to the
surfaces and find that this energy oscillates with the magnetic field.
Remarkably, we also find that, at a critical field below , this
''shear'' energy becomes strictly zero for the surface rows due to an
unexpected mismatch with the bulk lattice.Comment: Title, abstract, and some text paragraphs have been rewritte
Mode locking of vortex matter driven through mesoscopic channels
We investigated the driven dynamics of vortices confined to mesoscopic flow
channels by means of a dc-rf interference technique. The observed mode-locking
steps in the -curves provide detailed information on how the number of rows
and lattice structure in the channel change with magnetic field. Minima in flow
stress occur when an integer number of rows is moving coherently, while maxima
appear when incoherent motion of mixed and row configurations is
predominant. Simulations show that the enhanced pinning at mismatch originates
from quasi-static fault zones with misoriented edge dislocations induced by
disorder in the channel edges.Comment: some minor changes were made, 4 pages, 4 figures, accepted for
publication in Phys. Rev. Let
Patterned Geometries and Hydrodynamics at the Vortex Bose Glass Transition
Patterned irradiation of cuprate superconductors with columnar defects allows
a new generation of experiments which can probe the properties of vortex
liquids by confining them to controlled geometries. Here we show that an
analysis of such experiments that combines an inhomogeneous Bose glass scaling
theory with the hydrodynamic description of viscous flow of vortex liquids can
be used to infer the critical behavior near the Bose glass transition. The
shear viscosity is predicted to diverge as at the Bose glass
transition, with the dynamical critical exponent.Comment: 5 pages, 4 figure
Patterned Irradiation of YBa_2Cu_3O_(7-x) Thin Films
We present a new experiment on YBa_2Cu_3O_{7-x} (YBCO) thin films using
spatially resolved heavy ion irradiation. Structures consisting of a periodic
array of strong and weak pinning channels were created with the help of metal
masks. The channels formed an angle of +/-45 Deg with respect to the symmetry
axis of the photolithographically patterned structures. Investigations of the
anisotropic transport properties of these structures were performed. We found
striking resemblance to guided vortex motion as it was observed in YBCO single
crystals containing an array of unidirected twin boundaries. The use of two
additional test bridges allowed to determine in parallel the resistivities of
the irradiated and unirradiated parts as well as the respective current-voltage
characteristics. These measurements provided the input parameters for a
numerical simulation of the potential distribution of the Hall patterning. In
contrast to the unidirected twin boundaries in our experiment both strong and
weak pinning regions are spatially extended. The interfaces between
unirradiated and irradiated regions therefore form a Bose-glass contact. The
experimentally observed magnetic field dependence of the transverse voltage
vanishes faster than expected from the numerical simulation and we interpret
this as a hydrodynamical interaction between a Bose-glass phase and a vortex
liquid.Comment: 7 pages, 8 Eps figures included. Submitted to PR
Entropy and information in neural spike trains: Progress on the sampling problem
The major problem in information theoretic analysis of neural responses and
other biological data is the reliable estimation of entropy--like quantities
from small samples. We apply a recently introduced Bayesian entropy estimator
to synthetic data inspired by experiments, and to real experimental spike
trains. The estimator performs admirably even very deep in the undersampled
regime, where other techniques fail. This opens new possibilities for the
information theoretic analysis of experiments, and may be of general interest
as an example of learning from limited data.Comment: 7 pages, 4 figures; referee suggested changes, accepted versio
Melting of two dimensional solids on disordered substrate
We study 2D solids with weak substrate disorder, using Coulomb gas
renormalisation. The melting transition is found to be replaced by a sharp
crossover between a high liquid with thermally induced dislocations, and a
low glassy regime with disorder induced dislocations at scales larger than
which we compute (, the Larkin and
translational correlation lengths). We discuss experimental consequences,
reminiscent of melting, such as size effects in vortex flow and AC response in
superconducting films.Comment: 4 pages, uses RevTeX, Amssymb, multicol,eps
Incommensuration Effects and Dynamics in Vortex Chains
We examine the motion of one-dimensional (1D) vortex matter embedded in a 2D
vortex system with weak pinning using numerical simulations. We confirm the
conjecture of Matsuda et al. [Science 294, 2136 (2001)] that the onset of the
temperature induced motion of the chain is due to an incommensuration effect of
the chain with the periodic potential created by the bulk vortices. In
addition, under an applied driving force we find a two stage depinning
transition, where the initial depinning of the vortex chain occurs through
soliton like pulses. When an ac drive is added to the dc drive, we observe
phase locking of the moving vortex chain.Comment: 4 pages, 4 postscript figure
Vortex Motion Noise in Micrometre-Sized Thin Films of the Amorphous Nb0.7Ge0.3 Weak-Pinning Superconductor
We report high-resolution measurements of voltage (V) noise in the mixed
state of micrometre-sized thin films of amorphous Nb0.7Ge0.3, which is a good
representative of weak-pinning superconductors. There is a remarkable
difference between the noise below and above the irreversibility field Birr.
Below Birr, in the presence of measurable pinning, the noise at small applied
currents resembles shot noise, and in the regime of flux flow at larger
currents decreases with increasing voltage due to a progressive ordering of the
vortex motion. At magnetic fields B between Birr and the upper critical field
Bc2 flux flow is present already at vanishingly small currents. In this regime
the noise scales with (1-B/Bc2)^2 V^2 and has a frequency (f) spectrum of 1/f
type. We interpret this noise in terms of the properties of strongly driven
depinned vortex systems at high vortex density.Comment: 8 pages, 5 figures, version accepted for publication in PR
Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale
Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp.
Author Summary
Sensory processing of time-varying stimuli, such as speech, is associated with high-frequency oscillatory cortical activity, the functional significance of which is still unknown. One possibility is that the oscillations are part of a stimulus-encoding mechanism. Here, we investigate a computational model of such a mechanism, a spiking neuronal network whose intrinsic oscillations interact with external input (waveforms simulating short speech segments in a single acoustic frequency band) to encode stimuli that extend over a time interval longer than the oscillation's period. The network implements a temporally sparse encoding, whose robustness to time warping and neuronal noise we quantify. To our knowledge, this study is the first to demonstrate that a biophysically plausible model of oscillations occurring in the processing of auditory input may generate a representation of signals that span multiple oscillation cycles.National Science Foundation (DMS-0211505); Burroughs Wellcome Fund; U.S. Air Force Office of Scientific Researc
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