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In this work the nuclear structure of exotic nuclei and superheavy nuclei is studied in a relativistic framework. In the relativistic mean-field (RMF) approximation, the nucleons interact with each other through the exchange of various effective mesons (scalar, vector, isovector-vector). Ground state properties of exotic nuclei and superheavy nuclei are studied in the RMF theory with the three different parameter sets (ChiM, NL3, NL-Z2). Axial deformation of nuclei within two drip lines are performed with the parameter set (ChiM). The position of drip lines are investigated with three different parameter sets (ChiM, NL3, NL-Z2) and compared with the experimental drip line nuclei. In addition, the structure of hypernuclei are studied and for a certain isotope, hyperon halo nucleus is predicted.
Background: Transfer entropy (TE) is a measure for the detection of directed interactions. Transfer entropy is an information theoretic implementation of Wiener's principle of observational causality. It offers an approach to the detection of neuronal interactions that is free of an explicit model of the interactions. Hence, it offers the power to analyze linear and nonlinear interactions alike. This allows for example the comprehensive analysis of directed interactions in neural networks at various levels of description. Here we present the open-source MATLAB toolbox TRENTOOL that allows the user to handle the considerable complexity of this measure and to validate the obtained results using non-parametrical statistical testing. We demonstrate the use of the toolbox and the performance of the algorithm on simulated data with nonlinear (quadratic) coupling and on local field potentials (LFP) recorded from the retina and the optic tectum of the turtle (Pseudemys scripta elegans) where a neuronal one-way connection is likely present.
Results: In simulated data TE detected information flow in the simulated direction reliably with false positives not exceeding the rates expected under the null hypothesis. In the LFP data we found directed interactions from the retina to the tectum, despite the complicated signal transformations between these stages. No false positive interactions in the reverse directions were detected.
Conclusions: TRENTOOL is an implementation of transfer entropy and mutual information analysis that aims to support the user in the application of this information theoretic measure. TRENTOOL is implemented as a MATLAB toolbox and available under an open source license (GPL v3). For the use with neural data TRENTOOL seamlessly integrates with the popular FieldTrip toolbox.
The Taiwan cobra (Naja naja atra) chymotrypsin inhibitor (NACI) consists of 57 amino acids and is related to other Kunitz-type inhibitors such as bovine pancreatic trypsin inhibitor (BPTI) and Bungarus fasciatus fraction IX (BF9), another chymotrypsin inhibitor. Here we present the solution structure of NACI. We determined the NMR structure of NACI with a root-mean-square deviation of 0.37 Å for the backbone atoms and 0.73 Å for the heavy atoms on the basis of 1,075 upper distance limits derived from NOE peaks measured in its NOESY spectra. To investigate the structural characteristics of NACI, we compared the three-dimensional structure of NACI with BPTI and BF9. The structure of the NACI protein comprises one 310-helix, one α-helix and one double-stranded antiparallel β-sheet, which is comparable with the secondary structures in BPTI and BF9. The RMSD value between the mean structures is 1.09 Å between NACI and BPTI and 1.27 Å between NACI and BF9. In addition to similar secondary and tertiary structure, NACI might possess similar types of protein conformational fluctuations as reported in BPTI, such as Cys14–Cys38 disulfide bond isomerization, based on line broadening of resonances from residues which are mainly confined to a region around the Cys14–Cys38 disulfide bond.
Gamma synchronization has generally been associated with grouping processes in the visual system. Here, we examine in monkey V1 whether gamma oscillations play a functional role in segmenting surfaces of plaid stimuli. Local field potentials (LFPs) and spiking activity were recorded simultaneously from multiple sites in the opercular and calcarine regions while the monkeys were presented with sequences of single and superimposed components of plaid stimuli. In accord with the previous studies, responses to the single components (gratings) exhibited strong and sustained gamma-band oscillations (30–65 Hz). The superposition of the second component, however, led to profound changes in the temporal structure of the responses, characterized by a drastic reduction of gamma oscillations in the spiking activity and systematic shifts to higher frequencies in the LFP (~10% increase). Comparisons between cerebral hemispheres and across monkeys revealed robust subject-specific spectral signatures. A possible interpretation of our results may be that single gratings induce strong cooperative interactions among populations of cells that share similar response properties, whereas plaids lead to competition. Overall, our results suggest that the functional architecture of the cortex is a major determinant of the neuronal synchronization dynamics in V1. Key words: attention , gamma , gratings , oscillation , visual cortex
Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach
(2020)
During the mammalian preimplantation phase, cells undergo two subsequent cell fate decisions. During the first decision, the trophectoderm and the inner cell mass are formed. Subsequently, the inner cell mass segregates into the epiblast and the primitive endoderm. Inner cell mass organoids represent an experimental model system, mimicking the second cell fate decision. It has been shown that cells of the same fate tend to cluster stronger than expected for random cell fate decisions. Three major processes are hypothesised to contribute to the cell fate arrangements: (1) chemical signalling; (2) cell sorting; and (3) cell proliferation. In order to quantify the influence of cell proliferation on the observed cell lineage type clustering, we developed an agent-based model accounting for mechanical cell–cell interaction, i.e. adhesion and repulsion, cell division, stochastic cell fate decision and cell fate heredity. The model supports the hypothesis that initial cell fate acquisition is a stochastically driven process, taking place in the early development of inner cell mass organoids. Further, we show that the observed neighbourhood structures can emerge solely due to cell fate heredity during cell division.
Aims: The examination of histological sections is still the gold standard in diagnostic pathology. Important histopathological diagnostic criteria are nuclear shapes and chromatin distribution as well as nucleus-cytoplasm relation and immunohistochemical properties of surface and intracellular proteins. The aim of this investigation was to evaluate the benefits and drawbacks of three-dimensional imaging of CD30+ cells in classical Hodgkin Lymphoma (cHL) in comparison to CD30+ lymphoid cells in reactive lymphoid tissues.
Materials and results: Using immunoflourescence confocal microscopy and computer-based analysis, we compared CD30+ neoplastic cells in Nodular Sclerosis cHL (NScCHL), Mixed Cellularity cHL (MCcHL), with reactive CD30+ cells in Adenoids (AD) and Lymphadenitis (LAD). We confirmed that the percentage of CD30+ cell volume can be calculated. The amount in lymphadenitis was approx. 1.5%, in adenoids around 2%, in MCcHL up to 4,5% whereas the values for NScHL rose to more than 8% of the total cell cytoplasm. In addition, CD30+ tumour cells (HRS-cells) in cHL had larger volumes, and more protrusions compared to CD30+ reactive cells. Furthermore, the formation of large cell networks turned out to be a typical characteristic of NScHL.
Conclusion: In contrast to 2D histology, 3D laser scanning offers a visualisation of complete cells, their network interaction and spatial distribution in the tissue. The possibility to differentiate cells in regards to volume, surface, shape, and cluster formation enables a new view on further diagnostic and biological questions. 3D includes an increased amount of information as a basis of bioinformatical calculations.
The human growth factor receptor MET is a receptor tyrosine kinase involved in cell proliferation, migration, and survival. MET is also hijacked by the intracellular pathogen Listeria monocytogenes. Its invasion protein, internalin B (InlB), binds to MET and promotes the formation of a signaling dimer that triggers the internalization of the pathogen. Here, we use a combination of structural biology, modeling, molecular dynamics simulations, and in situ single-molecule Förster resonance energy transfer (smFRET) experiments to elucidate the early events in MET activation by Listeria. Simulations show that InlB binding stabilizes MET in a conformation that promotes dimer formation. smFRET identifies the organization of the in situ signaling dimer. Further MD simulations of the dimer model are in quantitative agreement with smFRET. We accurately describe the structural dynamics underpinning an important cellular event and introduce a powerful methodological pipeline applicable to studying the activation of other plasma membrane receptors.
Effects of a phase transition on HBT correlations in an integrated Boltzmann+hydrodynamics approach
(2009)
A systematic study of HBT radii of pions, produced in heavy ion collisions in the intermediate energy regime (SPS), from an integrated (3+1)d Boltzmann+hydrodynamics approach is presented. The calculations in this hybrid approach, incorporating an hydrodynamic stage into the Ultra-relativistic Quantum Molecular Dynamics transport model, allow for a comparison of different equations of state retaining the same initial conditions and final freeze-out. The results are also compared to the pure cascade transport model calculations in the context of the available data. Furthermore, the effect of different treatments of the hydrodynamic freeze-out procedure on the HBT radii are investigated. It is found that the HBT radii are essentially insensitive to the details of the freeze-out prescription as long as the final hadronic interactions in the cascade are taken into account. The HBT radii RL and RO and the RO/RS ratio are sensitive to the EoS that is employed during the hydrodynamic evolution. We conclude that the increased lifetime in case of a phase transition to a QGP (via a Bag Model equation of state) is not supported by the available data.
The rapidity dependence of the single- and double- neutron to proton ratios of nucleon emission from isospin-asymmetric but mass-symmetric reactions Zr+Ru and Ru+Zr at energy range 100 ~ 800 A MeV and impact parameter range 0 ~ 8 fm is investigated. The reaction system with isospin-asymmetry and mass-symmetry has the advantage of simultaneously showing up the dependence on the symmetry energy and the degree of the isospin equilibrium. We find that the beam energy- and the impact parameter dependence of the slope parameter of the double neutron to proton ratio (F_D) as function of rapidity are quite sensitive to the density dependence of symmetry energy, especially at energies E_b ~ 400 A MeV and reduced impact parameters around 0.5. Here the symmetry energy effect on the F_D is enhanced, as compared to the single neutron to proton ratio. The degree of the equilibrium with respect to isospin (isospin mixing) in terms of the F_D is addressed and its dependence on the symmetry energy is also discussed.
Probing the density dependence of the symmetry potential in intermediate energy heavy ion collisions
(2005)
Based on the ultrarelativistic quantum molecular dynamics (UrQMD) model, the effects of the density-dependent symmetry potential for baryons and of the Coulomb potential for produced mesons are investigated for neutron-rich heavy ion collisions at intermediate energies. The calculated results of the Delta-/Delta++ and pi -/pi + production ratios show a clear beam-energy dependence on the density-dependent symmetry potential, which is stronger for the pi -/pi + ratio close to the pion production threshold. The Coulomb potential of the mesons changes the transverse momentum distribution of the pi -/pi + ratio significantly, though it alters only slightly the pi- and pi+ total yields. The pi- yields, especially at midrapidity or at low transverse momenta and the p-/pi+ ratios at low transverse momenta, are shown to be sensitive probes of the density-dependent symmetry potential in dense nuclear matter. The effect of the density-dependent symmetry potential on the production of both, K0 and K+ mesons, is also investigated.
The influence of the isospin-independent, isospin- and momentum-dependent equation of state (EoS), as well as the Coulomb interaction on the pion production in intermediate energy heavy ion collisions (HICs) is studied for both isospin-symmetric and neutron-rich systems. The Coulomb interaction plays an important role in the reaction dynamics, and strongly influences the rapidity and transverse momentum distributions of charged pions. It even leads to the pi- pi+ ratio deviating slightly from unity for isospin-symmetric systems. The Coulomb interaction between mesons and baryons is also crucial for reproducing the proper pion flow since it changes the behavior of the directed and the elliptic flow components of pions visibly. The EoS can be better investigated in neutron-rich system if multiple probes are measured simultaneously. For example, the rapidity and the transverse momentum distributions of the charged pions, the pi- pi+ ratio, the various pion flow components, as well as the difference of pi+-pi- flows. A new sensitive observable is proposed to probe the symmetry potential energy at high densities, namely the transverse momentum distribution of the elliptic flow difference [Delta v_2^pi+ - pi-(p_t rm c.m.].
We investigate the sensitivity of several observables to the density dependence of the symmetry potential within the microscopic transport model UrQMD (ultrarelativistic quantum molecular dynamics model). The same systems are used to probe the symmetry potential at both low and high densities. The influence of the symmetry potentials on the yields of pi-, pi+, the pi-/pi+ ratio, the n/p ratio of free nucleons and the t/3He ratio are studied for neutron-rich heavy ion collisions (208Pb+208Pb, 132Sn+124Sn, 96Zr+96Zr) at E_b=0.4A GeV. We find that these multiple probes provides comprehensive information on the density dependence of the symmetry potential.
Several observables of unbound nucleons which are to some extent sensitive to the medium modifications of nucleon-nucleon elastic cross sections in neutron-rich intermediate energy heavy ion collisions are investigated. The splitting effect of neutron and proton effective masses on cross sections is discussed. It is found that the transverse flow as a function of rapidity, the Q_zz as a function of momentum, and the ratio of halfwidths of the transverse to that of longitudinal rapidity distribution R_t/l are very sensitive to the medium modifications of the cross sections. The transverse momentum distribution of correlation functions of two-nucleons does not yield information on the in-medium cross section.
Based on the UrQMD transport model, the transverse momentum and the rapidity dependence of the Hanbury-Brown-Twiss (HBT) radii R_L, R_O, R_S as well as the cross term R_OL at SPS energies are investigated and compared with the experimental NA49 and CERES data. The rapidity dependence of the R_L, R_O, R_S is weak while the R_OL is significantly increased at large rapidities and small transverse momenta. The HBT "life-time" issue (the phenomenon that the calculated sqrt R_O^2-R_S^2 value is larger than the correspondingly extracted experimental data) is also present at SPS energies.
The pion source as seen through HBT correlations at RHIC energies is investigated within the UrQMD approach. We find that the calculated transverse momentum, centrality, and system size dependence of the Pratt-HBT radii R_L and R_S are reasonably well in line with experimental data. The predicted R_O values in central heavy ion collisions are larger as compared to experimental data. The corresponding quantity sqrt R_O^2-R_S^2 of the pion emission source is somewhat larger than experimental estimates.
The Δ-isobar degrees of freedom are included in the covariant density functional (CDF) theory to study the equation of state (EoS) and composition of dense matter in compact stars. In addition to Δ's we include the full octet of baryons, which allows us to study the interplay between the onset of delta isobars and hyperonic degrees of freedom. Using both the Hartree and Hartree–Fock approximation we find that Δ's appear already at densities slightly above the saturation density of nuclear matter for a wide range of the meson–Δ coupling constants. This delays the appearance of hyperons and significantly affects the gross properties of compact stars. Specifically, Δ's soften the EoS at low densities but stiffen it at high densities. This softening reduces the radius of a canonical 1.4M⊙ star by up to 2 km for a reasonably attractive Δ potential in matter, while the stiffening results in larger maximum masses of compact stars. We conclude that the hypernuclear CDF parametrizations that satisfy the 2M⊙ maximum mass constraint remain valid when Δ isobars are included, with the important consequence that the resulting stellar radii are shifted toward lower values, which is in agreement with the analysis of neutron star radii.
We compute the fermion spin distribution in the vortical fluid created in off-central high energy heavy-ion collisions. We employ the event-by-event (3+1)D viscous hydrodynamic model. The spin polarization density is proportional to the local fluid vorticity in quantum kinetic theory. As a result of strong collectivity, the spatial distribution of the local vorticity on the freeze-out hyper-surface strongly correlates to the rapidity and azimuthal angle distribution of fermion spins. We investigate the sensitivity of the local polarization to the initial fluid velocity in the hydrodynamic model and compute the global polarization of Λ hyperons by the AMPT model. The energy dependence of the global polarization agrees with the STAR data.
The production of hypernuclei is investigated for p̅+A→Λ‾+ΛA reactions in a covariant meson exchange approach. Besides the conventional pseudo-scalar (K) and vector (K*) channels, we study for the first time also contributions from the correlated πK scalar channel, described by the k/K*0 meson. Initial and final state interactions are considered by eikonal theory. The total and angular differential cross sections of the coherent process p̅+AZ→ΛA(Z−1)+Λ̅ are evaluated at the beam momenta 1:5…20 GeV/c within the meson exchange model with bound proton and Λ-hyperon wave functions. It is shown that the shape of the beam momentum dependence of the hypernucleus production cross sections with various discrete Λ states is strongly sensitive to the presence of the scalar k meson exchange in the p̅p→Λ̅Λ amplitude. This can be used as a clean test of the exchange by scalar πK correlation in coherent p̅A reactions.
We present a model for the autonomous and simultaneous learning of active binocular and motion vision. The model is based on the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model learns how to efficiently encode the incoming visual signals generated by an object moving in 3-D through sparse coding. Simultaneously, it learns how to produce eye movements that further improve the efficiency of the sensory coding. This learning is driven by an intrinsic motivation to maximize the system's coding efficiency. We test our approach on the humanoid robot iCub using simulations. The model demonstrates self-calibration of accurate object fixation and tracking of moving objects. Our results show that the model keeps improving until it hits physical constraints such as camera or motor resolution, or limits on its internal coding capacity. Furthermore, we show that the emerging sensory tuning properties are in line with results on disparity, motion, and motion-in-depth tuning in the visual cortex of mammals. The model suggests that vergence and tracking eye movements can be viewed as fundamentally having the same objective of maximizing the coding efficiency of the visual system and that they can be learned and calibrated jointly through AEC.
Synesthesia is a phenomenon in which additional perceptual experiences are elicited by sensory stimuli or cognitive concepts. Synesthetes possess a unique type of phenomenal experiences not directly triggered by sensory stimulation. Therefore, for better understanding of consciousness it is relevant to identify the mental and physiological processes that subserve synesthetic experience. In the present work we suggest several reasons why synesthesia has merit for research on consciousness. We first review the research on the dynamic and rapidly growing field of the studies of synesthesia. We particularly draw attention to the role of semantics in synesthesia, which is important for establishing synesthetic associations in the brain. We then propose that the interplay between semantics and sensory input in synesthesia can be helpful for the study of the neural correlates of consciousness, especially when making use of ambiguous stimuli for inducing synesthesia. Finally, synesthesia-related alterations of brain networks and functional connectivity can be of merit for the study of consciousness.
Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in e.g. perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Different perceptual phenotypes may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients, synesthetes, and controls. Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors – introduced during the hysteresis experiment – lowered thresholds but did not normalize perception. Our results imply that distinct perceptual phenotypes might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.
During meditation, practitioners are required to center their attention on a specific object for extended periods of time. When their thoughts get diverted, they learn to quickly disengage from the distracter. We hypothesized that learning to respond to the dual demand of engaging attention on specific objects and disengaging quickly from distracters enhances the efficiency by which meditation practitioners can allocate attention. We tested this hypothesis in a global-to-local task while measuring electroencephalographic activity from a group of eight highly trained Buddhist monks and nuns and a group of eight age and education matched controls with no previous meditation experience. Specifically, we investigated the effect of attentional training on the global precedence effect, i.e., faster detection of targets on a global than on a local level. We expected to find a reduced global precedence effect in meditation practitioners but not in controls, reflecting that meditators can more quickly disengage their attention from the dominant global level. Analysis of reaction times confirmed this prediction. To investigate the underlying changes in brain activity and their time course, we analyzed event-related potentials. Meditators showed an enhanced ability to select the respective target level, as reflected by enhanced processing of target level information. In contrast with control group, which showed a local target selection effect only in the P1 and a global target selection effect in the P3 component, meditators showed effects of local information processing in the P1, N2, and P3 and of global processing for the N1, N2, and P3. Thus, meditators seem to display enhanced depth of processing. In addition, meditation altered the uptake of information such that meditators selected target level information earlier in the processing sequence than controls. In a longitudinal experiment, we could replicate the behavioral effects, suggesting that meditation modulates attention already after a 4-day meditation retreat. Together, these results suggest that practicing meditation enhances the speed with which attention can be allocated and relocated, thus increasing the depth of information processing and reducing response latency.
Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models. Here we introduce SORN, a self-organizing recurrent network. It combines three distinct forms of local plasticity to learn spatio-temporal patterns in its input while maintaining its dynamics in a healthy regime suitable for learning. The SORN learns to encode information in the form of trajectories through its high-dimensional state space reminiscent of recent biological findings on cortical coding. All three forms of plasticity are shown to be essential for the network's success. Keywords: synaptic plasticity, intrinsic plasticity, recurrent neural networks, reservoir computing, time series prediction
The brain adapts to the sensory environment. For example, simple sensory exposure can modify the response properties of early sensory neurons. How these changes affect the overall encoding and maintenance of stimulus information across neuronal populations remains unclear. We perform parallel recordings in the primary visual cortex of anesthetized cats and find that brief, repetitive exposure to structured visual stimuli enhances stimulus encoding by decreasing the selectivity and increasing the range of the neuronal responses that persist after stimulus presentation. Low-dimensional projection methods and simple classifiers demonstrate that visual exposure increases the segregation of persistent neuronal population responses into stimulus-specific clusters. These observed refinements preserve the representational details required for stimulus reconstruction and are detectable in postexposure spontaneous activity. Assuming response facilitation and recurrent network interactions as the core mechanisms underlying stimulus persistence, we show that the exposure-driven segregation of stimulus responses can arise through strictly local plasticity mechanisms, also in the absence of firing rate changes. Our findings provide evidence for the existence of an automatic, unguided optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.
The brain adapts to the sensory environment. For example, simple sensory exposure can modify the response properties of early sensory neurons. How these changes affect the overall encoding and maintenance of stimulus information across neuronal populations remains unclear. We perform parallel recordings in the primary visual cortex of anesthetized cats and find that brief, repetitive exposure to structured visual stimuli enhances stimulus encoding by decreasing the selectivity and increasing the range of the neuronal responses that persist after stimulus presentation. Low-dimensional projection methods and simple classifiers demonstrate that visual exposure increases the segregation of persistent neuronal population responses into stimulus-specific clusters. These observed refinements preserve the representational details required for stimulus reconstruction and are detectable in post-exposure spontaneous activity. Assuming response facilitation and recurrent network interactions as the core mechanisms underlying stimulus persistence, we show that the exposure-driven segregation of stimulus responses can arise through strictly local plasticity mechanisms, also in the absence of firing rate changes. Our findings provide evidence for the existence of an automatic, unguided optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.
Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. Here, we hypothesized that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Population analysis revealed that neuronal responses converged to a low dimensional subspace for natural but not for synthetic images. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the dominant low dimensional subspace, suggesting an alignment between the attentional and natural stimulus variance. The alignment was pronounced for late evoked responses but not for early transient responses of V1 neurons, supporting the notion that top-down feedback was required. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.
Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. We hypothesize that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we show that attention enhances the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Attentional enhancement of stimulus decodability from population responses occurs in low dimensional spaces, as revealed by principal component analysis, suggesting an alignment between the attentional and the natural stimulus variance. Moreover, natural scenes produce stimulus-specific oscillatory responses in V1, whose power undergoes a global shift from low to high frequencies with attention. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.
The production of charmonia in the antiproton-nucleus reactions at plab = 3 − 10 GeV/c is studied within the Glauber model and the generalized eikonal approximation. The main reaction channel is charmonium formation in an antiproton-proton collision. The target mass dependence of the charmonium transparency ratio allows to determine the charmonium-nucleon cross section. The polarization effects in the production of χc2 states are evaluated.
An incoming or outgoing hadron in a hard collision with large momentum transfer gets squeezed in the transverse direction to its momentum. In the case of nuclear targets, this leads to the reduced interaction of such hadrons with surrounding nucleons which is known as color transparency (CT). The identification of CT in exclusive processes on nuclear targets is of significant interest not only by itself but also due to the fact that CT is a necessary condition for the applicability of factorization for the description of the corresponding elementary process. In this paper we discuss the semiexclusive processes A(e,e′π+) , A(π−,l−l+) and A(γ,π−p) . Since CT is closely related to hadron formation mechanism, the reduced interaction of ’pre-hadrons’ with nucleons is a common feature of generic high-energy inclusive processes on nuclear targets, such as hadron attenuation in deep inelastic scattering (DIS). We will discuss the novel way to study hadron formation via slow neutron production induced by a hard photon interaction with a nucleus. Finally, the opportunity to study hadron formation effects in heavy-ion collisions in the NICA regime will be considered.
Distillation of scalar exchange by coherent hypernucleus production in antiproton–nucleus collisions
(2017)
The total and angular differential cross sections of the coherent process p¯ + A Z → A (Z − 1) + ¯ are evaluated at the beam momenta 1.5 ÷ 20 GeV/c within the meson exchange model with bound proton and -hyperon wave functions. It is shown that the shape of the beam momentum dependence of the hypernucleus production cross sections with various discrete states is strongly sensitive to the presence of the scalar κ-meson exchange in the p p¯ → ¯ amplitude. This can be used as a clean test of the exchange by scalar π K correlation in coherent p A¯ reactions.
The results of the microscopic transport calculations of -nucleus interactions within a GiBUU model are presented. The dominating mechanism of hyperon production is the strangeness exchange processes → γπ and → ΞK. The calculated rapidity spectra of Ξ hyperons are significantly shifted to forward rapidities with respect to the spectra of S = −1 hyperons. We argue that this shift should be a sensitive test for the possible exotic mechanisms of -nucleus annihilation. The production of the double Λ-hypernuclei by Ξ− interaction with a secondary target is calculated.
The QGP that might be created in ultrarelativistic heavy-ion collisions is expected to radiate thermal dilepton radiation. However, this thermal dilepton radiation interferes with dileptons originating from hadron decays. In the invariant mass region between the f and J=y peak (1GeV <= M l+l <=. 3GeV) the most substantial background of hadron decays originates from correlated DD¯ -meson decays. We evaluate this background using a Langevin simulation for charm quarks. As background medium we utilize the well-tested UrQMD-hybrid model. The required drag and diffusion coefficients are taken from a resonance approach. The decoupling of the charm quarks from the hot medium is performed at a temperature of 130MeV and as hadronization mechanism a coalescence approach is chosen. This model for charm quark interactions with the medium has already been successfully applied to the study of the medium modification and the elliptic flow at FAIR, RHIC and LHC energies. In this proceeding we present our results for the dilepton radiation from correlated D¯D decays at RHIC energy in comparison to PHENIX measurements in the invariant mass range between 1 and 3 GeV using different interaction scenarios. These results can be utilized to estimate the thermal QGP radiation.
Correction to: Nature Communications https://doi.org/10.1038/s41467-017-01045-x, published online 31 October 2017
It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Fig. 11. The corrected figures are now properly calibrated to 1mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section ‘Intensity ranged from 0.5 to 2.5 mA (current density 0.125–0.625 mA mA/cm2), which is stronger than in previous reports’, should have read ‘Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625–0.3125 mA/cm2), which is stronger than in previous reports.’ These errors do not affect any of the Article’s conclusions. Correct versions of Fig. 2 and Supplementary Fig. 11 are presented below as Figs. 1, 2.
Transcranial electrical stimulation has widespread clinical and research applications, yet its effect on ongoing neural activity in humans is not well established. Previous reports argue that transcranial alternating current stimulation (tACS) can entrain and enhance neural rhythms related to memory, but the evidence from non-invasive recordings has remained inconclusive. Here, we measure endogenous spindle and theta activity intracranially in humans during low-frequency tACS and find no stable entrainment of spindle power during non-REM sleep, nor of theta power during resting wakefulness. As positive controls, we find robust entrainment of spindle activity to endogenous slow-wave activity in 66% of electrodes as well as entrainment to rhythmic noise-burst acoustic stimulation in 14% of electrodes. We conclude that low-frequency tACS at common stimulation intensities neither acutely modulates spindle activity during sleep nor theta activity during waking rest, likely because of the attenuated electrical fields reaching the cortical surface.
We suggest a new method to compute the spectrum and wave functions of excited states. We construct a stochastic basis of Bargmann link states, drawn from a physical probability density distribution and compute transition amplitudes between stochastic basis states. From such transition matrix we extract wave functions and the energy spectrum. We apply this method toU(1)2+1 lattice gauge theory. As a test we compute the energy spectrum, wave functions and thermodynamical functions of the electric Hamiltonian and compare it with analytical results. We find excellent agreement. We observe scaling of energies and wave functions in the variable of time. We also present first results on a small lattice for the full Hamiltonian including the magnetic term.
The study of hidden charm production is an important part of the heavy ion program. The standard approach to this problem [1] assumes that c¯c bound states are created only at the initial stage of the reaction and then partially destroyed at later stages due to interactions with the medium [2, 3, 4].
Event-by-event multiplicity fluctuations in nucleus-nucleus collisions are studied within the HSD and UrQMD transport models. The scaled variances of negative, positive, and all charged hadrons in Pb+Pb at 158 AGeV are analyzed in comparison to the data from the NA49 Collaboration. We find a dominant role of the fluctuations in the nucleon participant number for the final hadron multiplicity fluctuations. This fact can be used to check di erent scenarios of nucleus-nucleus collisions by measuring the final multiplicity fluctuations as a function of collision centrality. The analysis reveals surprising e ects in the recent NA49 data which indicate a rather strong mixing of the projectile and target hadron production sources even in peripheral collisions. PACS numbers: 25.75.-q,25.75.Gz,24.60.-k
Event-by-event fluctuations of the net baryon number and electric charge in nucleus-nucleus collisions are studied in Pb+Pb at SPS energies within the HSD transport model. We reveal an important role of the fluctuations in the number of target nucleon participants. They strongly influence all measured fluctuations even in the samples of events with rather rigid centrality trigger. This fact can be used to check different scenarios of nucleus-nucleus collisions by measuring the multiplicity fluctuations as a function of collision centrality in fixed kinematical regions of the projectile and target hemispheres. The HSD results for the event-by-event fluctuations of electric charge in central Pb+Pb collisions at 20, 30, 40, 80 and 158 A GeV are in a good agreement with the NA49 experimental data and considerably larger than expected in a quark-gluon plasma. This demonstrate that the distortions of the initial fluctuations by the hadronization phase and, in particular, by the final resonance decays dominate the observable fluctuations.
Event-by-event multiplicity fluctuations in nucleus-nucleus collisions from low SPS up to RHIC energies have been studied within the HSD transport approach. Fluctuations of baryonic number and electric charge also have been explored for Pb+Pb collisions at SPS energies in comparison to the experimental data from NA49. We find a dominant role of the fluctuations in the nucleon participant number for the final hadron multiplicity fluctuations and a strong influence of the experimental acceptance on the final results. Critical Point and Onset of Deconfinement - 4th International Workshop July 9 - 13, 2007 Darmstadt, Germany
The YaeJ protein is a codon-independent release factor with peptidyl-tRNA hydrolysis (PTH) activity, and functions as a stalled-ribosome rescue factor in Escherichia coli. To identify residues required for YaeJ function, we performed mutational analysis for in vitro PTH activity towards rescue of ribosomes stalled on a non-stop mRNA, and for ribosome-binding efficiency. We focused on residues conserved among bacterial YaeJ proteins. Additionally, we determined the solution structure of the GGQ domain of YaeJ from E. coli using nuclear magnetic resonance spectroscopy. YaeJ and a human homolog, ICT1, had similar levels of PTH activity, despite various differences in sequence and structure. While no YaeJ-specific residues important for PTH activity occur in the structured GGQ domain, Arg118, Leu119, Lys122, Lys129 and Arg132 in the following C-terminal extension were required for PTH activity. All of these residues are completely conserved among bacteria. The equivalent residues were also found in the C-terminal extension of ICT1, allowing an appropriate sequence alignment between YaeJ and ICT1 proteins from various species. Single amino acid substitutions for each of these residues significantly decreased ribosome-binding efficiency. These biochemical findings provide clues to understanding how YaeJ enters the A-site of stalled ribosomes.
We review the composition and the equation of state of the hyperonic core of neutron stars at finite temperature within a relativistic mean-field approach. We make use of the new FSU2H∗ model, which is built upon the FSU2H scheme by improving on the Ξ potential according to the recent analysis on the Ξ atoms, and we extend it to include finite temperature corrections. The calculations are done for a wide range of densities, temperatures and charge fractions, thus exploring the different conditions that can be found in protoneutron stars, binary mergers remnants and supernovae explosions. The inclusion of hyperons has a strong effect on the composition and the equation of state at finite temperature, which consequently would lead to significant changes in the properties and evolution of hot neutron stars.
We present the novel finite-temperature FSU2H* equation-of-state model that covers a wide range of temperatures and lepton fractions for the conditions in proto-neutron stars, neutron star mergers and supernovae. The temperature effects on the thermodynamical observables and the composition of the neutron star core are stronger when the hyperonic degrees of freedom are considered. We pay a special attention to the temperature and density dependence of the thermal index in the presence of hyperons and conclude that the true thermal effects cannot be reproduced with the use of a constant Г law,
Quarkyonic or baryquark matter? On the dynamical generation of momentum space shell structure
(2023)
We study the equation of state of a mixture of (quasi-)free constituent quarks and nucleons with hard-core repulsion at zero temperature. Two opposite scenarios for the realization of the Pauli exclusion principle are considered: (i) a Fermi sea of quarks surrounded by a shell of baryons – the quarkyonic matter, and (ii) a Fermi sea of nucleons surrounded by a shell of quarks which we call baryquark matter. In both scenarios, the sizes of the Fermi sea and shell are fixed through energy minimization at fixed baryon number density. While both cases yield a qualitatively similar transition from hadronic to quark matter, we find that baryquark matter is energetically favored in this setup and yields a physically acceptable behavior of the speed of sound without the need to introduce an infrared regulator. In order to retain the theoretically more appealing quarkyonic matter as the preferred form of dense QCD matter will thus require modifications to the existing dynamical generation mechanisms, such as, for example, the introduction of momentum-dependent nuclear interactions.
The upcoming high energy experiments at the LHC are one of the most outstanding efforts for a better understanding of nature. It is associated with great hopes in the physics community. But there is also some fear in the public, that the conjectured production of mini black holes might lead to a dangerous chain reaction. In this Letter we summarize the most straightforward arguments that are necessary to rule out such doomsday scenarios.
In thesis I investigate the possibility that at the smallest length scale (Planck scale) the very notion of "dimension" needs to be revisited. Due to "quantum effects" spacetime might become very turbulent at these scales and properties like those of "fractals" emerge, including a "scale dependent dimension". It seems that this "spontaneous dimensional reduction" and the appearance of a minimal physical length are very general effects that most approaches to quantum gravity share. Main emphasis is given to the"spectral dimension" and its calculation for strings and p-branes.
Recent experiments have demonstrated that visual cortex engages in spatio-temporal sequence learning and prediction. The cellular basis of this learning remains unclear, however. Here we present a spiking neural network model that explains a recent study on sequence learning in the primary visual cortex of rats. The model posits that the sequence learning and prediction abilities of cortical circuits result from the interaction of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. It also reproduces changes in stimulus-evoked multi-unit activity during learning. Furthermore, it makes precise predictions regarding how training shapes network connectivity to establish its prediction ability. Finally, it predicts that the adapted connectivity gives rise to systematic changes in spontaneous network activity. Taken together, our model establishes a new conceptual bridge between the structure and function of cortical circuits in the context of sequence learning and prediction.
Afterimages result from a prolonged exposure to still visual stimuli. They are best detectable when viewed against uniform backgrounds and can persist for multiple seconds. Consequently, the dynamics of afterimages appears to be slow by their very nature. To the contrary, we report here that about 50% of an afterimage intensity can be erased rapidly—within less than a second. The prerequisite is that subjects view a rich visual content to erase the afterimage; fast erasure of afterimages does not occur if subjects view a blank screen. Moreover, we find evidence that fast removal of afterimages is a skill learned with practice as our subjects were always more effective in cleaning up afterimages in later parts of the experiment. These results can be explained by a tri-level hierarchy of adaptive mechanisms, as has been proposed by the theory of practopoiesis.
The development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereogramms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.
The development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions with naturalistic input, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereograms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.