A cortical surface-based meta-analysis of human reasoning

Recent advances in neuroimaging have augmented numerous findings in the human reasoning process but have yielded varying results. One possibility for this inconsistency is that reasoning is such an intricate cognitive process, involving attention, memory, executive functions, symbolic processing, and fluid intelligence, whereby various brain regions are inevitably implicated in orchestrating the process. Therefore, researchers have used meta-analyses for a better understanding of neural mechanisms of reasoning. However, previous meta-analysis techniques include weaknesses such as an inadequate representation of the cortical surface’s highly folded geometry. Accordingly, we developed a new meta-analysis method called Bayesian meta-analysis of the cortical surface (BMACS). BMACS offers a fast, accurate, and accessible inference of the spatial patterns of cognitive processes from peak brain activations across studies by applying spatial point processes to the cortical surface. Using BMACS, we found that the common pattern of activations from inductive and deductive reasoning was colocalized with the multiple-demand system, indicating that reasoning is a high-level convergence of complex cognitive processes. We hope surface-based meta-analysis will be facilitated by BMACS, bringing more profound knowledge of various cognitive processes

Anomalous Multiplicity Fluctuations from Phase Transitions in Heavy Ion Collisions

Event-by-event fluctuations and correlations between particles produced in relativistic nuclear collisions are studied. The fluctuations in positive, negative, total and net charge are closely related through correlations. In the event of a phase transitions to a quark-gluon plasma, fluctuations in total and net charge can be enhanced and reduced respectively which, however, is very sensitive to the acceptance and centrality. If the colliding system experiences strong density fluctuations due, e.g., to droplet formation in a first-order phase transition, all fluctuations can be enhanced substantially. The importance of fluctuations and correlations is exemplified by event-by-event measurement of the multiplicities of $J/\Psi$'s and charged particles since these observables should anti-correlate in the presence of co-mover or anomalous absorption.Comment: revised version to appear in Phys. Rev. C, 5 page

The critical role of interference control in metaphor comprehension evidenced by the drift–diffusion model

We address the question of, among several executive functions, which one has a strong influence on metaphor comprehension. To this end, participants took part in a metaphor comprehension task where metaphors had varying levels of familiarity (familiar vs. novel metaphors) with different conditions of context (supporting vs. opposing contexts). We scrutinized each participant's detailed executive functions using seven neuropsychological tests. More interestingly, we modelled their responses in metaphor comprehension using the drift-diffusion model, in an attempt to provide more systematic accounts of the processes underlying metaphor comprehension. Results showed that there were significant negative correlations between response times in metaphor comprehension and scores of the Controlled Oral Word Association Test (COWAT)-Semantic, suggesting that better performances in comprehending metaphors were strongly associated with better interference control. Using the drift-diffusion model, we found that the familiarity, compared to context, had greater leverage in the decision process for metaphor comprehension. Moreover, individuals with better performance in the COWAT-Semantic test demonstrated higher drift rates. In conclusion, with more fine-grained analysis of the decisions involved in metaphor comprehension using the drift-diffusion model, we argue that interference control plays an important role in processing metaphors

Black Hole Feedback On The First Galaxies

We study how the first galaxies were assembled under feedback from the accretion onto a central black hole (BH) that is left behind by the first generation of metal-free stars through self-consistent, cosmological simulations. X-ray radiation from the accretion of gas onto BH remnants of Population III (Pop III) stars, or from high-mass X-ray binaries (HMXBs), again involving Pop III stars, influences the mode of second generation star formation. We track the evolution of the black hole accretion rate and the associated X-ray feedback starting with the death of the Pop III progenitor star inside a minihalo and following the subsequent evolution of the black hole as the minihalo grows to become an atomically cooling galaxy. We find that X-ray photoionization heating from a stellar-mass BH is able to quench further star formation in the host halo at all times before the halo enters the atomic cooling phase. X-ray radiation from a HMXB, assuming a luminosity close to the Eddington value, exerts an even stronger, and more diverse, feedback on star formation. It photoheats the gas inside the host halo, but also promotes the formation of molecular hydrogen and cooling of gas in the intergalactic medium and in nearby minihalos, leading to a net increase in the number of stars formed at early times. Our simulations further show that the radiative feedback from the first BHs may strongly suppress early BH growth, thus constraining models for the formation of supermassive BHs.Astronom

Resting-state functional connectivity in mathematical expertise

To what extent are different levels of expertise reflected in the functional connectivity of the brain? We addressed this question by using resting-state functional magnetic resonance imaging (fMRI) in mathematicians versus non-mathematicians. To this end, we investigated how the two groups of participants differ in the correlation of their spontaneous blood oxygen level-dependent fluctuations across the whole brain regions during resting state. Moreover, by using the classification algorithm in machine learning, we investigated whether the resting-state fMRI networks between mathematicians and non-mathematicians were distinguished depending on features of functional connectivity. We showed diverging involvement of the frontal–thalamic–temporal connections for mathematicians and the medial–frontal areas to precuneus and the lateral orbital gyrus to thalamus connections for non-mathematicians. Moreover, mathematicians who had higher scores in mathematical knowledge showed a weaker connection strength between the left and right caudate nucleus, demonstrating the connections’ characteristics related to mathematical expertise. Separate functional networks between the two groups were validated with a maximum classification accuracy of 91.19 using the distinct resting-state fMRI-based functional connectivity features. We suggest the advantageous role of preconfigured resting-state functional connectivity, as well as the neural efficiency for experts’ successful performance

Mechanism of enhanced light output in InGaN-based microlight emitting diodes

Micro-light emitting diode (LED) arrays with diameters of 4 to 20 mum have been fabricated and were found to be much more efficient light emitters compared to their broad-area counterparts, with up to five times enhancement in optical power densities. The possible mechanisms responsible for the improvement in performance were investigated. Strain relaxation in the microstructures as measured by Raman spectroscopy was not observed, arguing against theories of an increase in internal quantum efficiency due to a reduction of the piezoelectric field put forward by other groups. Optical microscope images show intense light emission at the periphery of the devices, as a result of light scattering off the etched sidewalls. This increases the extraction efficiency relative to broad area devices and boosts the forward optical output. In addition, spectra of the forward emitted light reveal the presence of resonant cavity modes [whispering gallery (WG) modes in particular] which appear to play a role in enhancing the optical output

Isobar of an ideal Bose gas within the grand canonical ensemble

We investigate the isobar of an ideal Bose gas confined in a cubic box within the grand canonical ensemble, for a large yet finite number of particles, N. After solving the equation of the spinodal curve, we derive precise formulae for the supercooling and the superheating temperatures which reveal an N^{-1/3} or N^{-1/4} power correction to the known Bose-Einstein condensation temperature in the thermodynamic limit. Numerical computations confirm the accuracy of our analytical approximation, and further show that the isobar zigzags on the temperature-volume plane if N is greater than or equal to 14393. In particular, for the Avogadro's number of particles, the volume expands discretely about 10^5 times. Our results quantitatively agree with a previous study on the canonical ensemble within 0.1% error.Comment: 6 pages, 2 figures; Reference added. Accepted for publication in Phys. Rev.

Spatiotemporal Stochastic Resonance in Fully Frustrated Josephson Ladders

We consider a Josephson-junction ladder in an external magnetic field with half flux quantum per plaquette. When driven by external currents, periodic in time and staggered in space, such a fully frustrated system is found to display spatiotemporal stochastic resonance under the influence of thermal noise. Such resonance behavior is investigated both numerically and analytically, which reveals significant effects of anisotropy and yields rich physics.Comment: 8 pages in two columns, 8 figures, to appear in Phys. Rev.