128 research outputs found
A search for distant radio-loud quasars in the CLASS survey: three new radio-selected quasars at z>4
We report on the search for distant radio-loud quasars in the Cosmic Lens All
Sky Survey (CLASS) of flat spectrum radio sources with S_5GHz>30 mJy.
Unresolved optical counterparts were selected from APM scans of POSS-I plates,
with e2.0 colours, in an effective area of ~6400 deg^2. Four
sources were found to be quasars with z>4, of which one was previously known.
This sample bridges the gap between the strong radio surveys with S_5GHz>200
mJy and the samples of radio-weak quasars that can be generated via radio
observations of optically selected quasars.
In addition, 4 new quasars at z>3 have been found. The selection criteria
result in a success-rate of ~1:7 for radio-loud quasars at z>4, which is a
significant improvement over previous studies. This search yields a surface
density of 1 per 1600 deg^2, which is about a factor of ~15 lower than that
found in a similar search for radio-quiet quasars at z>4. The study presented
here is strongly biased against quasars beyond z>4.5, since the e-passband of
the POSS-I only samples the spectra shortward of 1200 Angstrom at these
redshifts.Comment: LaTeX, 7 pages, 5 Figs: to be published in MNRA
Dynamics of trimming the content of face representations for categorization in the brain
To understand visual cognition, it is imperative to determine when, how and with what information the human brain categorizes the visual input. Visual categorization consistently involves at least an early and a late stage: the occipito-temporal N170 event related potential related to stimulus encoding and the parietal P300 involved in perceptual decisions. Here we sought to understand how the brain globally transforms its representations of face categories from their early encoding to the later decision stage over the 400 ms time window encompassing the N170 and P300 brain events. We applied classification image techniques to the behavioral and electroencephalographic data of three observers who categorized seven facial expressions of emotion and report two main findings: (1) Over the 400 ms time course, processing of facial features initially spreads bilaterally across the left and right occipito-temporal regions to dynamically converge onto the centro-parietal region; (2) Concurrently, information processing gradually shifts from encoding common face features across all spatial scales (e.g. the eyes) to representing only the finer scales of the diagnostic features that are richer in useful information for behavior (e.g. the wide opened eyes in 'fear'; the detailed mouth in 'happy'). Our findings suggest that the brain refines its diagnostic representations of visual categories over the first 400 ms of processing by trimming a thorough encoding of features over the N170, to leave only the detailed information important for perceptual decisions over the P300
US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report
This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in
Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference
The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe
The preponderance of matter over antimatter in the early Universe, the
dynamics of the supernova bursts that produced the heavy elements necessary for
life and whether protons eventually decay --- these mysteries at the forefront
of particle physics and astrophysics are key to understanding the early
evolution of our Universe, its current state and its eventual fate. The
Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed
plan for a world-class experiment dedicated to addressing these questions. LBNE
is conceived around three central components: (1) a new, high-intensity
neutrino source generated from a megawatt-class proton accelerator at Fermi
National Accelerator Laboratory, (2) a near neutrino detector just downstream
of the source, and (3) a massive liquid argon time-projection chamber deployed
as a far detector deep underground at the Sanford Underground Research
Facility. This facility, located at the site of the former Homestake Mine in
Lead, South Dakota, is approximately 1,300 km from the neutrino source at
Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino
charge-parity symmetry violation and mass ordering effects. This ambitious yet
cost-effective design incorporates scalability and flexibility and can
accommodate a variety of upgrades and contributions. With its exceptional
combination of experimental configuration, technical capabilities, and
potential for transformative discoveries, LBNE promises to be a vital facility
for the field of particle physics worldwide, providing physicists from around
the globe with opportunities to collaborate in a twenty to thirty year program
of exciting science. In this document we provide a comprehensive overview of
LBNE's scientific objectives, its place in the landscape of neutrino physics
worldwide, the technologies it will incorporate and the capabilities it will
possess.Comment: Major update of previous version. This is the reference document for
LBNE science program and current status. Chapters 1, 3, and 9 provide a
comprehensive overview of LBNE's scientific objectives, its place in the
landscape of neutrino physics worldwide, the technologies it will incorporate
and the capabilities it will possess. 288 pages, 116 figure
The Temporal Winner-Take-All Readout
How can the central nervous system make accurate decisions about external stimuli
at short times on the basis of the noisy responses of nerve cell populations? It
has been suggested that spike time latency is the source of fast decisions.
Here, we propose a simple and fast readout mechanism, the temporal
Winner-Take-All (tWTA), and undertake a study of its accuracy. The tWTA is
studied in the framework of a statistical model for the dynamic response of a
nerve cell population to an external stimulus. Each cell is characterized by a
preferred stimulus, a unique value of the external stimulus for which it
responds fastest. The tWTA estimate for the stimulus is the preferred stimulus
of the cell that fired the first spike in the entire population. We then pose
the questions: How accurate is the tWTA readout? What are the parameters that
govern this accuracy? What are the effects of noise correlations and baseline
firing? We find that tWTA sensitivity to the stimulus grows algebraically fast
with the number of cells in the population, N, in contrast to
the logarithmic slow scaling of the conventional rate-WTA sensitivity with
N. Noise correlations in first-spike times of different
cells can limit the accuracy of the tWTA readout, even in the limit of large
N, similar to the effect that has been observed in
population coding theory. We show that baseline firing also has a detrimental
effect on tWTA accuracy. We suggest a generalization of the tWTA, the
n-tWTA, which estimates the stimulus by the identity of the
group of cells firing the first n spikes and show how this
simple generalization can overcome the detrimental effect of baseline firing.
Thus, the tWTA can provide fast and accurate responses discriminating between a
small number of alternatives. High accuracy in estimation of a continuous
stimulus can be obtained using the n-tWTA
The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific
The world's oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized both genetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in which surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp). Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with 85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff. Using the metadata associated with each sample and sequencing library, we developed new comparative genomic and assembly methods. One comparative genomic method, termed “fragment recruitment,” addressed questions of genome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genes and gene families. A second method, termed “extreme assembly,” made possible the assembly and reconstruction of large segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we found extensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regions throughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individual sequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3) hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized into genetically isolated populations that have overlapping but independent distributions, implying distinct environmental preference. We present novel methods for measuring the genomic similarity between metagenomic samples and show how they may be grouped into several community types. Specific functional adaptations can be identified both within individual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence or absence of the phosphate-binding gene PstS
Old English macian, Its Origin and Dissemination
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66612/2/10.1177_007542428601900105.pd
Towards a Mathematical Theory of Cortical Micro-circuits
The theoretical setting of hierarchical Bayesian inference is gaining acceptance as a framework for understanding cortical computation. In this paper, we describe how Bayesian belief propagation in a spatio-temporal hierarchical model, called Hierarchical Temporal Memory (HTM), can lead to a mathematical model for cortical circuits. An HTM node is abstracted using a coincidence detector and a mixture of Markov chains. Bayesian belief propagation equations for such an HTM node define a set of functional constraints for a neuronal implementation. Anatomical data provide a contrasting set of organizational constraints. The combination of these two constraints suggests a theoretically derived interpretation for many anatomical and physiological features and predicts several others. We describe the pattern recognition capabilities of HTM networks and demonstrate the application of the derived circuits for modeling the subjective contour effect. We also discuss how the theory and the circuit can be extended to explain cortical features that are not explained by the current model and describe testable predictions that can be derived from the model
The Timing of the Cognitive Cycle
We propose that human cognition consists of cascading cycles of recurring brain
events. Each cognitive cycle senses the current situation, interprets it with
reference to ongoing goals, and then selects an internal or external action in
response. While most aspects of the cognitive cycle are unconscious, each cycle
also yields a momentary “ignition” of conscious broadcasting.
Neuroscientists have independently proposed ideas similar to the cognitive
cycle, the fundamental hypothesis of the LIDA model of cognition. High-level
cognition, such as deliberation, planning, etc., is typically enabled by
multiple cognitive cycles. In this paper we describe a timing model LIDA's
cognitive cycle. Based on empirical and simulation data we propose that an
initial phase of perception (stimulus recognition) occurs 80–100 ms from
stimulus onset under optimal conditions. It is followed by a conscious episode
(broadcast) 200–280 ms after stimulus onset, and an action selection phase
60–110 ms from the start of the conscious phase. One cognitive cycle would
therefore take 260–390 ms. The LIDA timing model is consistent with brain
evidence indicating a fundamental role for a theta-gamma wave, spreading forward
from sensory cortices to rostral corticothalamic regions. This posteriofrontal
theta-gamma wave may be experienced as a conscious perceptual event starting at
200–280 ms post stimulus. The action selection component of the cycle is
proposed to involve frontal, striatal and cerebellar regions. Thus the cycle is
inherently recurrent, as the anatomy of the thalamocortical system suggests. The
LIDA model fits a large body of cognitive and neuroscientific evidence. Finally,
we describe two LIDA-based software agents: the LIDA Reaction Time agent that
simulates human performance in a simple reaction time task, and the LIDA Allport
agent which models phenomenal simultaneity within timeframes comparable to human
subjects. While there are many models of reaction time performance, these
results fall naturally out of a biologically and computationally plausible
cognitive architecture
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