Random matrix model for QCD_3 staggered fermions

We show that the lowest part of the eigenvalue density of the staggered fermion operator in lattice QCD_3 at small lattice coupling constant beta has exactly the same shape as in QCD_4. This observation is quite surprising, since universal properties of the QCD_3 Dirac operator are expected to be described by a non-chiral matrix model. We show that this effect is related to the specific nature of the staggered fermion discretization and that the eigenvalue density evolves towards the non-chiral random matrix prediction when beta is increased and the continuum limit is approached. We propose a two-matrix model with one free parameter which interpolates between the two limits and very well mimics the pattern of evolution with beta of the eigenvalue density of the staggered fermion operator in QCD_3.Comment: 8 pages 4 figure

Two-color QCD with staggered fermions at finite temperature under the influence of a magnetic field

In this paper we investigate the influence of a constant external magnetic field on the finite-temperature phase structure and the chiral properties of a simplified lattice model for QCD. We assume an SU(2) gauge symmetry and employ dynamical staggered fermions of identical mass without rooting, corresponding to Nf=4 flavors of identical electric charge. For fixed mass (given in lattice units) the critical temperature is seen to rise with the magnetic field strength. For three fixed beta-values, selected such that we stay (i) within the chirally broken phase, (ii) within the transition region or (iii) within the chirally restored phase, we study the approach to the chiral limit for various values of the magnetic field. Within the chirally broken (confinement) phase the chiral condensate is found to increase monotonically with a growing magnetic field strength. In the chiral limit the increase starts linear in agreement with a chiral model studied by Shushpanov and Smilga. Within the chirally restored (deconfinement) phase the chiral condensate tends to zero in the chiral limit, irrespective of the strength of the magnetic field.Comment: 15 pages, 12 figures; version accepted by Physical Review

Implicit artificial syntax processing: Genes, preference, and bounded recursion

The first objective of this study was to compare the brain network engaged by preference classification and the standard grammaticality classification after implicit artificial syntax acquisition by re-analyzing previously reported event-related fMRI data. The results show that preference and grammaticality classification engage virtually identical brain networks, including Broca’s region, consistent with previous behavioral findings. Moreover, the results showed that the effects related to artificial syntax in Broca’s region were essentially the same when masked with variability related to natural syntax processing in the same participants. The second objective was to explore CNTNAP2-related effects in implicit artificial syntax learning by analyzing behavioral and event-related fMRI data from a subsample. The CNTNAP2 gene has been linked to specific language impairment and is controlled by the FOXP2 transcription factor. CNTNAP2 is expressed in language related brain networks in the developing human brain and the FOXP2–CNTNAP2 pathway provides a mechanistic link between clinically distinct syndromes involving disrupted language. Finally, we discuss the implication of taking natural language to be a neurobiological system in terms of bounded recursion and suggest that the left inferior frontal region is a generic on-line sequence processor that unifies information from various sources in an incremental and recursive manner

Neural mechanisms for voice recognition

We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The predefined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training histories on different tests. Cortical sensitivity to voice similarity appeared over different time-scales and at different representational stages. First, there were short-term adaptation effects: Increasing acoustic similarity to the directly preceding stimulus led to haemodynamic response reduction in the middle/posterior STS and in right ventrolateral prefrontal regions. Second, there were longer-term effects: Response reduction was found in the orbital/insular cortex for stimuli that were most versus least similar to the acoustic mean of all preceding stimuli, and, in the anterior temporal pole, the deep posterior STS and the amygdala, for stimuli that were most versus least similar to the trained voice-identity category mean. These findings are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values. The analyses also reveal anatomically separable voice representations: one in a voice-acoustics space and one in a voice-identity space. Voice-identity representations flexibly followed the trained identity shift, and listeners with a greater identity effect were more accurate at recognizing familiar voices. Voice recognition is thus supported by neural voice spaces that are organized around flexible ‘mean voice’ representations

Formal language hierarchy reflects different levels of cognitive complexity

Formal language hierarchy describes levels of increasing syntactic complexity (adjacent dependencies, nonadjacent nested, nonadjacent crossed) of which the transcription into a hierarchy of cognitive complexity remains under debate. The cognitive foundations of formal language hierarchy have been contradicted by two types of evidence: First, adjacent dependencies are not easier to learn compared to nonadjacent; second, crossed nonadjacent dependencies may be easier than nested. However, studies providing these findings may have engaged confounds: Repetition monitoring strategies may have accounted for participants’ high performance in nonadjacent dependencies, and linguistic experience may have accounted for the advantage of crossed dependencies. We conducted two artificial grammar learning experiments where we addressed these confounds by manipulating reliance on repetition monitoring and by testing participants inexperienced with crossed dependencies. Results showed relevant differences in learning adjacent versus nonadjacent dependencies and advantages of nested over crossed, suggesting that formal language hierarchy may indeed translate into a hierarchy of cognitive complexit

Improving the fluorescent probe acridonylalanine through a combination of theory and experiment

Acridonylalanine (Acd) is a useful fluorophore for studying proteins by fluorescence spectroscopy, but it can potentially be improved by being made longer wavelength or brighter. Here, we report the synthesis of Acd core derivatives and their photophysical characterization. We also performed ab initio calculations of the absorption and emission spectra of Acd derivatives, which agree well with experimental measurements. The amino acid aminoacridonylalanine (Aad) was synthesized in forms appropriate for genetic incorporation and peptide synthesis. We show that Aad is a superior Förster resonance energy transfer acceptor to Acd in a peptide cleavage assay and that Aad can be activated by an aminoacyl tRNA synthetase for genetic incorporation. Together, these results show that we can use computation to design enhanced Acd derivatives, which can be used in peptides and proteins