32,687 research outputs found
Word contexts enhance the neural representation of individual letters in early visual cortex
Visual context facilitates perception, but how this is neurally implemented remains unclear. One example of contextual facilitation is found in reading, where letters are more easily identified when embedded in a word. Bottom-up models explain this word advantage as a post-perceptual decision bias, while top-down models propose that word contexts enhance perception itself. Here, we arbitrate between these accounts by presenting words and nonwords and probing the representational fidelity of individual letters using functional magnetic resonance imaging. In line with top-down models, we find that word contexts enhance letter representations in early visual cortex. Moreover, we observe increased coupling between letter information in visual cortex and brain activity in key areas of the reading network, suggesting these areas may be the source of the enhancement. Our results provide evidence for top-down representational enhancement in word recognition, demonstrating that word contexts can modulate perceptual processing already at the earliest visual regions
Cognitive performance in multiple system atrophy
The cognitive performance of a group of patients with multiple system atrophy (MSA) of striato-nigral predominance was compared with that of age and IQ matched control subjects, using three tests sensitive to frontal lobe dysfunction and a battery sensitive to memory and learning deficits in Parkinson's disease and dementia of the Alzheimer type. The MSA group showed significant deficits in all three of the tests previously shown to be sensitive to frontal lobe dysfunction. Thus, a significant proportion of patients from the MSA group failed an attentional set-shifting test, specifically at the stage when an extra-dimensional shift was required. They were also impaired in a subject-ordered test of spatial working memory. The MSA group showed deficits mostly confined to measures of speed of thinking, rather than accuracy, on the Tower of London task. These deficits were seen in the absence of consistent impairments in language or visual perception. Moreover, the MSA group showed no significant deficits in tests of spatial and pattern recognition previously shown to be sensitive to patients early in the course of probable Alzheimer's disease and only a few patients exhibited impairment on the Warrington Recognition Memory Test. There were impairments on other tests of visual memory and learning relative to matched controls, but these could not easily be related to fundamental deficits of memory or learning. Thus, on a matching-to-sample task the patients were impaired at simultaneous but not delayed matching to sample, whereas difficulties in a pattern-location learning task were more evident at its initial, easier stages. The MSA group showed no consistent evidence of intellectual deterioration as assessed from their performance on subtests of the Wechsler Adult Intelligence Scale (WAIS) and the National Adult Reading Test (NART). Consideration of individual cases showed that there was some heterogeneity in the pattern of deficits in the MSA group, with one patient showing no impairment, even in the face of considerable physical disability. The results show a distinctive pattern of cognitive deficits, unlike those previously seen using the same tests in patients with Parkinson's and Alzheimer's diseases, and suggesting a prominent frontal-lobe-like component. The implications for concepts of 'subcortical' dementia and 'fronto-striatal' cognitive dysfunction are considered
The Paths to Choreography Extraction
Choreographies are global descriptions of interactions among concurrent
components, most notably used in the settings of verification (e.g., Multiparty
Session Types) and synthesis of correct-by-construction software (Choreographic
Programming). They require a top-down approach: programmers first write
choreographies, and then use them to verify or synthesize their programs.
However, most existing software does not come with choreographies yet, which
prevents their application.
To attack this problem, we propose a novel methodology (called choreography
extraction) that, given a set of programs or protocol specifications,
automatically constructs a choreography that describes their behavior. The key
to our extraction is identifying a set of paths in a graph that represents the
symbolic execution of the programs of interest. Our method improves on previous
work in several directions: we can now deal with programs that are equipped
with a state and internal computation capabilities; time complexity is
dramatically better; we capture programs that are correct but not necessarily
synchronizable, i.e., they work because they exploit asynchronous
communication
Direct microwave measurement of Andreev-bound-state dynamics in a proximitized semiconducting nanowire
The modern understanding of the Josephson effect in mesosopic devices derives
from the physics of Andreev bound states, fermionic modes that are localized in
a superconducting weak link. Recently, Josephson junctions constructed using
semiconducting nanowires have led to the realization of superconducting qubits
with gate-tunable Josephson energies. We have used a microwave circuit QED
architecture to detect Andreev bound states in such a gate-tunable junction
based on an aluminum-proximitized InAs nanowire. We demonstrate coherent
manipulation of these bound states, and track the bound-state fermion parity in
real time. Individual parity-switching events due to non-equilibrium
quasiparticles are observed with a characteristic timescale . The of a topological nanowire
junction sets a lower bound on the bandwidth required for control of Majorana
bound states
Magnetooptical sum rules close to the Mott transition
We derive new sum rules for the real and imaginary parts of the
frequency-dependent Hall constant and Hall conductivity. As an example, we
discuss their relevance to the doped Mott insulator that we describe within the
dynamical mean-field theory of strongly correlated electron systems.Comment: 4 pages, 4 ps figures; accepted for publication in PR
A calcium ion in a cavity as a controlled single-photon source
We present a single calcium ion, coupled to a high-finesse cavity, as an almost ideal system for the controlled generation of single photons. Photons from a pump beam are Raman-scattered by the ion into the cavity mode, which subsequently emits the photon into a well-defined output channel. In contrast with comparable atomic systems, the ion is localized at a fixed position in the cavity mode for indefinite times, enabling truly continuous operation of the device. We have performed numeric calculations to assess the performance of the system and present the first experimental indication of single-photon emission in our set-up
Quantum-state input-output relations for absorbing cavities
The quantized electromagnetic field inside and outside an absorbing high-
cavity is studied, with special emphasis on the absorption losses in the
coupling mirror and their influence on the outgoing field. Generalized operator
input-output relations are derived, which are used to calculate the Wigner
function of the outgoing field. To illustrate the theory, the preparation of
the outgoing field in a Schr\"{o}dinger cat-like state is discussed.Comment: 12 pages, 5 eps figure
Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data
Since most analysis software for genome-wide association studies (GWAS)
currently exploit only unrelated individuals, there is a need for efficient
applications that can handle general pedigree data or mixtures of both
population and pedigree data. Even data sets thought to consist of only
unrelated individuals may include cryptic relationships that can lead to false
positives if not discovered and controlled for. In addition, family designs
possess compelling advantages. They are better equipped to detect rare
variants, control for population stratification, and facilitate the study of
parent-of-origin effects. Pedigrees selected for extreme trait values often
segregate a single gene with strong effect. Finally, many pedigrees are
available as an important legacy from the era of linkage analysis.
Unfortunately, pedigree likelihoods are notoriously hard to compute. In this
paper we re-examine the computational bottlenecks and implement ultra-fast
pedigree-based GWAS analysis. Kinship coefficients can either be based on
explicitly provided pedigrees or automatically estimated from dense markers.
Our strategy (a) works for random sample data, pedigree data, or a mix of both;
(b) entails no loss of power; (c) allows for any number of covariate
adjustments, including correction for population stratification; (d) allows for
testing SNPs under additive, dominant, and recessive models; and (e)
accommodates both univariate and multivariate quantitative traits. On a typical
personal computer (6 CPU cores at 2.67 GHz), analyzing a univariate HDL
(high-density lipoprotein) trait from the San Antonio Family Heart Study
(935,392 SNPs on 1357 individuals in 124 pedigrees) takes less than 2 minutes
and 1.5 GB of memory. Complete multivariate QTL analysis of the three
time-points of the longitudinal HDL multivariate trait takes less than 5
minutes and 1.5 GB of memory
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