308 research outputs found

    Neural differences in self-perception during illness and after weight-recovery in anorexia nervosa

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    Anorexia nervosa (AN) is a severe mental illness characterized by problems with self-perception. Whole-brain neural activations in healthy women, women with AN and women in long-term weight recovery following AN were compared using two functional magnetic resonance imaging tasks probing different aspects of self-perception. The Social Identity-V2 task involved consideration about oneself and others using socially descriptive adjectives. Both the ill and weight-recovered women with AN engaged medial prefrontal cortex less than healthy women for self-relevant cognitions, a potential biological trait difference. Weight-recovered women also activated the inferior frontal gyri and dorsal anterior cingulate more for direct self-evaluations than for reflected self-evaluations, unlike both other groups, suggesting that recovery may include compensatory neural changes related to social perspectives. The Faces task compared viewing oneself to a stranger. Participants with AN showed elevated activity in the bilateral fusiform gyri for self-images, unlike the weight-recovered and healthy women, suggesting cognitive distortions about physical appearance are a state rather than trait problem in this disease. Because both ill and recovered women showed neural differences related to social self-perception, but only recovered women differed when considering social perspectives, these neurocognitive targets may be particularly important for treatment

    Three Dimensional Electrical Impedance Tomography

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    The electrical resistivity of mammalian tissues varies widely and is correlated with physiological function. Electrical impedance tomography (EIT) can be used to probe such variations in vivo, and offers a non-invasive means of imaging the internal conductivity distribution of the human body. But the computational complexity of EIT has severe practical limitations, and previous work has been restricted to considering image reconstruction as an essentially two-dimensional problem. This simplification can limit significantly the imaging capabilities of EIT, as the electric currents used to determine the conductivity variations will not in general be confined to a two-dimensional plane. A few studies have attempted three-dimensional EIT image reconstruction, but have not yet succeeded in generating images of a quality suitable for clinical applications. Here we report the development of a three-dimensional EIT system with greatly improved imaging capabilities, which combines our 64-electrode data-collection apparatus with customized matrix inversion techniques. Our results demonstrate the practical potential of EIT for clinical applications, such as lung or brain imaging and diagnostic screening

    A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

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    Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

    Biased Competition in Visual Processing Hierarchies: A Learning Approach Using Multiple Cues

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    In this contribution, we present a large-scale hierarchical system for object detection fusing bottom-up (signal-driven) processing results with top-down (model or task-driven) attentional modulation. Specifically, we focus on the question of how the autonomous learning of invariant models can be embedded into a performing system and how such models can be used to define object-specific attentional modulation signals. Our system implements bi-directional data flow in a processing hierarchy. The bottom-up data flow proceeds from a preprocessing level to the hypothesis level where object hypotheses created by exhaustive object detection algorithms are represented in a roughly retinotopic way. A competitive selection mechanism is used to determine the most confident hypotheses, which are used on the system level to train multimodal models that link object identity to invariant hypothesis properties. The top-down data flow originates at the system level, where the trained multimodal models are used to obtain space- and feature-based attentional modulation signals, providing biases for the competitive selection process at the hypothesis level. This results in object-specific hypothesis facilitation/suppression in certain image regions which we show to be applicable to different object detection mechanisms. In order to demonstrate the benefits of this approach, we apply the system to the detection of cars in a variety of challenging traffic videos. Evaluating our approach on a publicly available dataset containing approximately 3,500 annotated video images from more than 1 h of driving, we can show strong increases in performance and generalization when compared to object detection in isolation. Furthermore, we compare our results to a late hypothesis rejection approach, showing that early coupling of top-down and bottom-up information is a favorable approach especially when processing resources are constrained

    Attention-dependent modulation of cortical taste circuits revealed by granger causality with signal-dependent noise

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    We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention

    Specific and individuated death reflection fosters identity integration

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    Identity integration is the process wherein a person assimilates multiple or conflicting identities (e.g., beliefs, values, needs) into a coherent, unified self-concept. Three experiments examined whether contemplating mortality in a specific and individuated manner (i.e., via the death reflection manipulation) facilitated outcomes indicative of identity integration. Participants in the death reflection condition (vs. control conditions) considered positive and negative life experiences as equally important in shaping their current identity (Experiment 1), regarded self-serving values and other-serving values as equally important life principles (Experiment 2), and were equally motivated to pursue growth-oriented and security-oriented needs (Experiment 3). Death reflection motivates individuals to integrate conflicting aspects of their identity into a coherent self-concept. Given that identity integration is associated with higher well-being, the findings have implications for understanding the psychological benefits of existential contemplation

    Spontaneous and deliberate future thinking: A dual process account

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    © 2019 Springer Nature.This is the final published version of an article published in Psychological Research, licensed under a Creative Commons Attri-bution 4.0 International License. Available online at: https://doi.org/10.1007/s00426-019-01262-7.In this article, we address an apparent paradox in the literature on mental time travel and mind-wandering: How is it possible that future thinking is both constructive, yet often experienced as occurring spontaneously? We identify and describe two ‘routes’ whereby episodic future thoughts are brought to consciousness, with each of the ‘routes’ being associated with separable cognitive processes and functions. Voluntary future thinking relies on controlled, deliberate and slow cognitive processing. The other, termed involuntary or spontaneous future thinking, relies on automatic processes that allows ‘fully-fledged’ episodic future thoughts to freely come to mind, often triggered by internal or external cues. To unravel the paradox, we propose that the majority of spontaneous future thoughts are ‘pre-made’ (i.e., each spontaneous future thought is a re-iteration of a previously constructed future event), and therefore based on simple, well-understood, memory processes. We also propose that the pre-made hypothesis explains why spontaneous future thoughts occur rapidly, are similar to involuntary memories, and predominantly about upcoming tasks and goals. We also raise the possibility that spontaneous future thinking is the default mode of imagining the future. This dual process approach complements and extends standard theoretical approaches that emphasise constructive simulation, and outlines novel opportunities for researchers examining voluntary and spontaneous forms of future thinking.Peer reviewe
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