Response of the multiple-demand network during simple stimulus discriminations

The multiple-demand (MD) network is sensitive to many aspects of task difficulty, including such factors as rule complexity, memory load, attentional switching and inhibition. Many accounts link MD activity to top-down task control, raising the question of response when performance is limited by the quality of sensory input, and indeed, some prior results suggest little effect of sensory manipulations. Here we examined judgments of motion direction, manipulating difficulty by either motion coherence or salience of irrelevant dots. We manipulated each difficulty type across six levels, from very easy to very hard, and additionally manipulated whether difficulty level was blocked, and thus known in advance, or randomized. Despite the very large manipulations employed, difficulty had little effect on MD activity, especially for the coherence manipulation. Contrasting with these small or absent effects, we observed the usual increase of MD activity with increased rule complexity. We suggest that, for simple sensory discriminations, it may be impossible to compensate for reduced stimulus information by increased top-down control

Hierarchical Representation of Multistep Tasks in Multiple-Demand and Default Mode Networks

Task episodes consist of sequences of steps that are performed to achieve a goal. We used fMRI to examine neural representation of task identity, component items, and sequential position, focusing on two major cortical systems—the multipledemand (MD) and default mode networks (DMN). Human participants (20 males, 22 females) learned six tasks each consisting of four steps. Inside the scanner, participants were cued which task to perform and then sequentially identified the target item of each step in the correct order. Univariate time course analyses indicated that intra-episode progress was tracked by a tonically increasing global response, plus an increasing phasic step response specific to MD regions. Inter-episode boundaries evoked a widespread response at episode onset, plus a marked offset response specific to DMN regions. Representational similarity analysis (RSA) was used to examine representation of task identity and component steps. Both networks represented the content and position of individual steps, however the DMN preferentially represented task identity while the MD network preferentially represented step-level information. Thus, although both MD and DMN networks are sensitive to step-level and episode-level information in the context of hierarchical task performance, they exhibit dissociable profiles in terms of both temporal dynamics and representational content. The results suggest collaboration of multiple brain regions in control of multistep behavior, with MD regions particularly involved in processing the detail of individual steps, and DMN adding representation of broad task context

The Functional Convergence and Heterogeneity of Social, Episodic, and Self-Referential Thought in the Default Mode Network

The default mode network (DMN) is engaged in a variety of cognitive settings, including social, semantic, temporal, spatial, and self-related tasks. Andrews-Hanna et al. (2010; Andrews-Hanna 2012) proposed that the DMN consists of three distinct functional–anatomical subsystems—a dorsal medial prefrontal cortex (dMPFC) subsystem that supports social cognition; a medial temporal lobe (MTL) subsystem that contributes to memory-based scene construction; and a set of midline core hubs that are especially involved in processing self-referential information. We examined activity in the DMN subsystems during six different tasks: 1) theory of mind, 2) moral dilemmas, 3) autobiographical memory, 4) spatial navigation, 5) self/other adjective judgment, and 6) a rest condition. At a broad level, we observed similar whole-brain activity maps for the six contrasts, and some response to every contrast in each of the three subsystems. In more detail, both univariate analysis and multivariate activity patterns showed partial functional separation, especially between dMPFC and MTL subsystems, though with less support for common activity across the midline core. Integrating social, spatial, self-related, and other aspects of a cognitive situation or episode, multiple components of the DMN may work closely together to provide the broad context for current mental activity

The association of cytoplasmic overexpression of cyclin d1 and tumor metastasis in Hepatocellular Carcinoma

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Late Quaternary dynamics of the Lambert Glacier-Amery Ice Shelf system, East Antarctica

The Lambert Glacier-Amery Ice Shelf system (LGAISS) is the largest outlet glacier system in East Antarctica but its response to past climate variability is poorly constrained. In this study, we explore its dynamics over the last ∼520 thousand years using new high-resolution sedimentary records retrieved off Prydz Bay. Episodic occurrences of iceberg rafted debris indicate a dynamic ice sheet throughout this interval, while changes in clay mineral compositions provide detailed evidence on the waxing and waning of the LGAISS. Our data indicate that advance and retreat of the LGAISS was sensitive to oceanic forcing, but also responded to local summer insolation when insolation peaks combined with interglacial sea level high stands. Subglacial bed topography may have played an additional role in modulating the LGAISS behaviour, which could explain sectoral differences in the response of the East Antarctic Ice Sheet to climate change. Overall, our records indicate that the LGAISS advanced more extensively during previous late Quaternary glacial periods than during Marine Isotope Stages 2 and 4. Furthermore, the LGAISS retreated more significantly than present during Marine Isotope Stage 13, and only moderately during Marine Isotope Stage 7, which suggests that the duration of warm climatic states could be a key factor affecting the dynamics of the East Antarctic Ice Sheet

Fractional quantum Hall effect in the absence of Landau levels

It has been well-known that topological phenomena with fractional excitations, i.e., the fractional quantum Hall effect (FQHE) \cite{Tsui1982} will emerge when electrons move in Landau levels. In this letter, we report the discovery of the FQHE in the absence of Landau levels in an interacting fermion model. The non-interacting part of our Hamiltonian is the recently proposed topologically nontrivial flat band model on the checkerboard lattice \cite{sun}. In the presence of nearest-neighboring repulsion ($U$), we find that at 1/3 filling, the Fermi-liquid state is unstable towards FQHE. At 1/5 filling, however, a next-nearest-neighboring repulsion is needed for the occurrence of the 1/5 FQHE when $U$ is not too strong. We demonstrate the characteristic features of these novel states and determine the phase diagram correspondingly.Comment: 6 pages and 4 figure

Thermodynamic Properties of Holographic Multiquark and the Multiquark Star

We study thermodynamic properties of the multiquark nuclear matter. The dependence of the equation of state on the colour charges is explored both analytically and numerically in the limits where the baryon density is small and large at fixed temperature between the gluon deconfinement and chiral symmetry restoration. The gravitational stability of the hypothetical multiquark stars are discussed using the Tolman-Oppenheimer-Volkoff equation. Since the equations of state of the multiquarks can be well approximated by different power laws for small and large density, the content of the multiquark stars has the core and crust structure. We found that most of the mass of the star comes from the crust region where the density is relatively small. The mass limit of the multiquark star is determined as well as its relation to the star radius. For typical energy density scale of $10\text{GeV}/\text{fm}^{3}$, the converging mass and radius of the hypothetical multiquark star in the limit of large central density are approximately $2.6-3.9$ solar mass and 15-27 km. The adiabatic index and sound speed distributions of the multiquark matter in the star are also calculated and discussed. The sound speed never exceeds the speed of light and the multiquark matters are thus compressible even at high density and pressure.Comment: 27 pages, 17 figures, 1 table, JHEP versio

Butterfly Detection and Classification Based on Integrated YOLO Algorithm

Insects are abundant species on the earth, and the task of identification and identification of insects is complex and arduous. How to apply artificial intelligence technology and digital image processing methods to automatic identification of insect species is a hot issue in current research. In this paper, the problem of automatic detection and classification recognition of butterfly photographs is studied, and a method of bio-labeling suitable for butterfly classification is proposed. On the basis of YOLO algorithm, by synthesizing the results of YOLO models with different training mechanisms, a butterfly automatic detection and classification recognition algorithm based on YOLO algorithm is proposed. It greatly improves the generalization ability of YOLO algorithm and makes it have better ability to solve small sample problems. The experimental results show that the proposed annotation method and integrated YOLO algorithm have high accuracy and recognition rate in butterfly automatic detection and recognition.Comment: 13th ICGEC 2019: Qingdao, Chin

The last of the simple remainders

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