Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures

The presence of Long Distance Dependencies (LDDs) in sequential data poses significant challenges for computational models. Various recurrent neural architectures have been designed to mitigate this issue. In order to test these state-of-the-art architectures, there is growing need for rich benchmarking datasets. However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs. This lack of control limits the analysis of model performance in relation to the specific challenge posed by LDDs. One way to address this is to use synthetic data having the properties of subregular languages. The degree of LDDs within the generated data can be controlled through the k parameter, length of the generated strings, and by choosing appropriate forbidden strings. In this paper, we explore the capacity of different RNN extensions to model LDDs, by evaluating these models on a sequence of SPk synthesized datasets, where each subsequent dataset exhibits a longer degree of LDD. Even though SPk are simple languages, the presence of LDDs does have significant impact on the performance of recurrent neural architectures, thus making them prime candidate in benchmarking tasks.Comment: International Conference of Artificial Neural Networks (ICANN) 201

The CBC theory and its entailments : Why current models of the origin of consciousness fail

Copyright © 2023 The Author(s). The Cellular Basis of Consciousness (CBC) model of biological consciousness is based on the assumption that life and conscious sentience are coterminus. All living organisms, are conscious, self-aware, and have valenced sensory and perceptual experiences

Understanding the Effect of Information Presentation Order and Orientation on Information Search and Treatment Evaluation

Background. Past research finds that treatment evaluations are more negative when risks are presented after benefits. This study investigates this order effect: manipulating tabular orientation and order of risk–benefit information, and examining information search order and gaze duration via eye-tracking. Design. 108 (Study 1) and 44 (Study 2) participants viewed information about treatment risks and benefits, in either a horizontal (left-right) or vertical (above-below) orientation, with the benefits or risks presented first (left side or at top). For 4 scenarios, participants answered 6 treatment evaluation questions (1–7 scales) that were combined into overall evaluation scores. In addition, Study 2 collected eye-tracking data during the benefit–risk presentation. Results. Participants tended to read one set of information (i.e., all risks or all benefits) before transitioning to the other. Analysis of order of fixations showed this tendency was stronger in the vertical (standardized mean rank difference further from 0, M = ±.88) than horizontal orientation (M = ± 0.71). Approximately 50% of the time was spent reading benefits when benefits were shown first, but this was reduced to ~40% when risks were presented first (regression coefficient: B = −4.52, p <.001). Eye-tracking measures did not strongly predict treatment evaluations, although time percentage reading benefits positively predicted evaluation when holding other variables constant (B = 0.02, p =.023). Conclusion. These results highlight the impact of seemingly arbitrary design choices on inspection order. For instance, presenting risks where they will be seen first leads to relatively less time spent considering treatment benefits. Other research suggests these changes to inspection order can influence multi-option and multi-attribute choices, and represent an area for future research

Development of a generic activities model of command and control

This paper reports on five different models of command and control. Four different models are reviewed: a process model, a contextual control model, a decision ladder model and a functional model. Further to this, command and control activities are analysed in three distinct domains: armed forces, emergency services and civilian services. From this analysis, taxonomies of command and control activities are developed that give rise to an activities model of command and control. This model will be used to guide further research into technological support of command and control activities

The Epistemic Status of Processing Fluency as Source for Judgments of Truth

This article combines findings from cognitive psychology on the role of processing fluency in truth judgments with epistemological theory on justification of belief. We first review evidence that repeated exposure to a statement increases the subjective ease with which that statement is processed. This increased processing fluency, in turn, increases the probability that the statement is judged to be true. The basic question discussed here is whether the use of processing fluency as a cue to truth is epistemically justified. In the present analysis, based on Bayes’ Theorem, we adopt the reliable-process account of justification presented by Goldman (1986) and show that fluency is a reliable cue to truth, under the assumption that the majority of statements one has been exposed to are true. In the final section, we broaden the scope of this analysis and discuss how processing fluency as a potentially universal cue to judged truth may contribute to cultural differences in commonsense beliefs

Extragalactic Radio Continuum Surveys and the Transformation of Radio Astronomy

Next-generation radio surveys are about to transform radio astronomy by discovering and studying tens of millions of previously unknown radio sources. These surveys will provide new insights to understand the evolution of galaxies, measuring the evolution of the cosmic star formation rate, and rivalling traditional techniques in the measurement of fundamental cosmological parameters. By observing a new volume of observational parameter space, they are also likely to discover unexpected new phenomena. This review traces the evolution of extragalactic radio continuum surveys from the earliest days of radio astronomy to the present, and identifies the challenges that must be overcome to achieve this transformational change.Comment: To be published in Nature Astronomy 18 Sept 201

Rapidly Measuring the Speed of Unconscious Learning: Amnesics Learn Quickly and Happy People Slowly

BACKGROUND We introduce a method for quickly determining the rate of implicit learning. METHODOLOGY/PRINCIPAL FINDINGS The task involves making a binary prediction for a probabilistic sequence over 10 minutes; from this it is possible to determine the influence of events of a different number of trials in the past on the current decision. This profile directly reflects the learning rate parameter of a large class of learning algorithms including the delta and Rescorla-Wagner rules. To illustrate the use of the method, we compare a person with amnesia with normal controls and we compare people with induced happy and sad moods. CONCLUSIONS/SIGNIFICANCE Learning on the task is likely both associative and implicit. We argue theoretically and demonstrate empirically that both amnesia and also transient negative moods can be associated with an especially large learning rate: People with amnesia can learn quickly and happy people slowl

The Endogenous Th17 Response in NO<inf>2</inf>-Promoted Allergic Airway Disease Is Dispensable for Airway Hyperresponsiveness and Distinct from Th17 Adoptive Transfer

Severe, glucocorticoid-resistant asthma comprises 5-7% of patients with asthma. IL-17 is a biomarker of severe asthma, and the adoptive transfer of Th17 cells in mice is sufficient to induce glucocorticoid-resistant allergic airway disease. Nitrogen dioxide (NO2) is an environmental toxin that correlates with asthma severity, exacerbation, and risk of adverse outcomes. Mice that are allergically sensitized to the antigen ovalbumin by exposure to NO2 exhibit a mixed Th2/Th17 adaptive immune response and eosinophil and neutrophil recruitment to the airway following antigen challenge, a phenotype reminiscent of severe clinical asthma. Because IL-1 receptor (IL-1R) signaling is critical in the generation of the Th17 response in vivo, we hypothesized that the IL-1R/Th17 axis contributes to pulmonary inflammation and airway hyperresponsiveness (AHR) in NO2-promoted allergic airway disease and manifests in glucocorticoid-resistant cytokine production. IL-17A neutralization at the time of antigen challenge or genetic deficiency in IL-1R resulted in decreased neutrophil recruitment to the airway following antigen challenge but did not protect against the development of AHR. Instead, IL-1R-/- mice developed exacerbated AHR compared to WT mice. Lung cells from NO2-allergically inflamed mice that were treated in vitro with dexamethasone (Dex) during antigen restimulation exhibited reduced Th17 cytokine production, whereas Th17 cytokine production by lung cells from recipient mice of in vitro Th17-polarized OTII T-cells was resistant to Dex. These results demonstrate that the IL-1R/Th17 axis does not contribute to AHR development in NO2-promoted allergic airway disease, that Th17 adoptive transfer does not necessarily reflect an endogenously-generated Th17 response, and that functions of Th17 responses are contingent on the experimental conditions in which they are generated. © 2013 Martin et al

BLISS: an artificial language for learnability studies

To explore neurocognitive mechanisms underlying the human language faculty, cognitive scientists use artificial languages to control more precisely the language learning environment and to study selected aspects of natural languages. Artificial languages applied in cognitive studies are usually designed ad hoc, to only probe a specific hypothesis, and they include a miniature grammar and a very small vocabulary. The aim of the present study is the construction of an artificial language incorporating both syntax and semantics, BLISS. Of intermediate complexity, BLISS mimics natural languages by having a vocabulary, syntax, and some semantics, as defined by a degree of non-syntactic statistical dependence between words. We quantify, using information theoretical measures, dependencies between words in BLISS sentences as well as differences between the distinct models we introduce for semantics. While modeling English syntax in its basic version, BLISS can be easily varied in its internal parametric structure, thus allowing studies of the relative learnability of different parameter sets