Fingerprinting Agent-Environment Interaction via Information Theory

In this paper, we investigate by means of statistical and information-theoretic measures, to what extent sensory-motor coordinated activity can generate and structure information in the sensory channels of a simulated agent interacting with its surrounding environment. We show how the usage of correlation, entropy, and mutual information can be employed (a) to segment an observed behavior into distinct behavioral states, (b) to quantify (fingerprint) the agent-environment interaction, and (c) to analyze the informational relationship between the different components of the sensory-motor apparatus. We hypothesize that a deeper understanding of the information-theoretic implications of sensory-motor coordination can help us endow our robots with better sensory morphologies, and with better strategies for exploring their surrounding environment

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

A Theory of Cheap Control in Embodied Systems

We present a framework for designing cheap control architectures for embodied agents. Our derivation is guided by the classical problem of universal approximation, whereby we explore the possibility of exploiting the agent's embodiment for a new and more efficient universal approximation of behaviors generated by sensorimotor control. This embodied universal approximation is compared with the classical non-embodied universal approximation. To exemplify our approach, we present a detailed quantitative case study for policy models defined in terms of conditional restricted Boltzmann machines. In contrast to non-embodied universal approximation, which requires an exponential number of parameters, in the embodied setting we are able to generate all possible behaviors with a drastically smaller model, thus obtaining cheap universal approximation. We test and corroborate the theory experimentally with a six-legged walking machine. The experiments show that the sufficient controller complexity predicted by our theory is tight, which means that the theory has direct practical implications. Keywords: cheap design, embodiment, sensorimotor loop, universal approximation, conditional restricted Boltzmann machineComment: 27 pages, 10 figure

Cellular automata modelling of slime mould actin network signalling

© 2016, The Author(s). Actin is a cytoskeletal protein which forms dense, highly interconnected networks within eukaryotic cells. A growing body of evidence suggests that actin-mediated intra- and extracellular signalling is instrumental in facilitating organism-level emergent behaviour patterns which, crucially, may be characterised as natural expressions of computation. We use excitable cellular automata modelling to simulate signal transmission through cell arrays whose topology was extracted from images of Watershed transformation-derived actin network reconstructions; the actin networks sampled were from laboratory experimental observations of a model organism, slime mould Physarum polycephalum. Our results indicate that actin networks support directional transmission of generalised energetic phenomena, the amplification and trans-network speed of which of which is proportional to network density (whose primary determinant is the anatomical location of the network sampled). Furthermore, this model also suggests the ability of such networks for supporting signal-signal interactions which may be characterised as Boolean logical operations, thus indicating that a cell’s actin network may function as a nanoscale data transmission and processing network. We conclude by discussing the role of the cytoskeleton in facilitating intracellular computing, how computation can be implemented in such a network and practical considerations for designing ‘useful’ actin circuitry

Evaluation of the Performance of Information Theory-Based Methods and Cross-Correlation to Estimate the Functional Connectivity in Cortical Networks

Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these “connectivity methods” on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings

Qualia: The Geometry of Integrated Information

According to the integrated information theory, the quantity of consciousness is the amount of integrated information generated by a complex of elements, and the quality of experience is specified by the informational relationships it generates. This paper outlines a framework for characterizing the informational relationships generated by such systems. Qualia space (Q) is a space having an axis for each possible state (activity pattern) of a complex. Within Q, each submechanism specifies a point corresponding to a repertoire of system states. Arrows between repertoires in Q define informational relationships. Together, these arrows specify a quale—a shape that completely and univocally characterizes the quality of a conscious experience. Φ— the height of this shape—is the quantity of consciousness associated with the experience. Entanglement measures how irreducible informational relationships are to their component relationships, specifying concepts and modes. Several corollaries follow from these premises. The quale is determined by both the mechanism and state of the system. Thus, two different systems having identical activity patterns may generate different qualia. Conversely, the same quale may be generated by two systems that differ in both activity and connectivity. Both active and inactive elements specify a quale, but elements that are inactivated do not. Also, the activation of an element affects experience by changing the shape of the quale. The subdivision of experience into modalities and submodalities corresponds to subshapes in Q. In principle, different aspects of experience may be classified as different shapes in Q, and the similarity between experiences reduces to similarities between shapes. Finally, specific qualities, such as the “redness” of red, while generated by a local mechanism, cannot be reduced to it, but require considering the entire quale. Ultimately, the present framework may offer a principled way for translating qualitative properties of experience into mathematics

Effect of roflumilast on inflammatory cells in the lungs of cigarette smoke-exposed mice

<p>Abstract</p> <p>Background</p> <p>We reported that roflumilast, a phosphodiesterase 4 inhibitor, given orally at 5 mg/kg to mice prevented the development of emphysema in a chronic model of cigarette smoke exposure, while at 1 mg/kg was ineffective. Here we investigated the effects of roflumilast on the volume density (V_V) of the inflammatory cells present in the lungs after chronic cigarette smoke exposure.</p> <p>Methods</p> <p>Slides were obtained from blocks of the previous study and V_Vwas assessed immunohistochemically and by point counting using a grid with 48 points, a 20× objective and a computer screen for a final magnification of 580×. Neutrophils were marked with myeloperoxidase antibody, macrophages with Mac-3, dendritic cells with fascin, B-lymphocytes with B220, CD4+ T-cells with CD4+ antibody, and CD8+T-cells with CD8-α. The significance of the differences was calculated using one-way analysis of variance.</p> <p>Results</p> <p>Chronic smoke exposure increased neutrophil V_Vby 97%, macrophage by 107%, dendritic cell by 217%, B-lymphocyte by 436%, CD4+ by 524%, and CD8+ by 417%. The higher dose of roflumilast prevented the increase in neutrophil V_Vby 78%, macrophage by 82%, dendritic cell by 48%, B-lymphocyte by 100%, CD4+ by 98% and CD8+ V_Vby 88%. The lower dose of roflumilast did not prevent the increase in neutrophil, macrophage and B-cell V_Vbut prevented dendritic cells by 42%, CD4+ by 55%, and CD8+ by 91%.</p> <p>Conclusion</p> <p>These results indicate (<it>i</it>) chronic exposure to cigarette smoke in mice results in a significant recruitment into the lung of inflammatory cells of both the innate and adaptive immune system; (<it>ii</it>) roflumilast at the higher dose exerts a protective effect against the recruitment of all these cells and at the lower dose against the recruitment of dendritic cells and T-lymphocytes; (<it>iii</it>) these findings underline the role of innate immunity in the development of pulmonary emphysema and (<it>iiii</it>) support previous results indicating that the inflammatory cells of the adaptive immune system do not play a central role in the development of cigarette smoke induced emphysema in mice.</p

Decomposing Neural Synchrony: Toward an Explanation for Near-Zero Phase-Lag in Cortical Oscillatory Networks

Background: Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles. Methodology/Principal Findings: Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1) positively correlated common input with no significant relative time delay and (2) bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys. Conclusion/Significance: The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at al

Systemic Inhibition of NF-κB Activation Protects from Silicosis

Background: Silicosis is a complex lung disease for which no successful treatment is available and therefore lung transplantation is a potential alternative. Tumor necrosis factor alpha (TNFα) plays a central role in the pathogenesis of silicosis. TNFα signaling is mediated by the transcription factor, Nuclear Factor (NF)-κB, which regulates genes controlling several physiological processes including the innate immune responses, cell death, and inflammation. Therefore, inhibition of NF-κB activation represents a potential therapeutic strategy for silicosis. Methods/Findings: In the present work we evaluated the lung transplant database (May 1986-July 2007) at the University of Pittsburgh to study the efficacy of lung transplantation in patients with silicosis (n = 11). We contrasted the overall survival and rate of graft rejection in these patients to that of patients with idiopathic pulmonary fibrosis (IPF, n = 79) that was selected as a control group because survival benefit of lung transplantation has been identified for these patients. At the time of lung transplantation, we found the lungs of silica-exposed subjects to contain multiple foci of inflammatory cells and silicotic nodules with proximal TNFα expressing macrophage and NF-κB activation in epithelial cells. Patients with silicosis had poor survival (median survival 2.4 yr; confidence interval (CI): 0.16-7.88 yr) compared to IPF patients (5.3 yr; CI: 2.8-15 yr; p = 0.07), and experienced early rejection of their lung grafts (0.9 yr; CI: 0.22-0.9 yr) following lung transplantation (2.4 yr; CI:1.5-3.6 yr; p<0.05). Using a mouse experimental model in which the endotracheal instillation of silica reproduces the silica-induced lung injury observed in humans we found that systemic inhibition of NF-κB activation with a pharmacologic inhibitor (BAY 11-7085) of IκBα phosphorylation decreased silica-induced inflammation and collagen deposition. In contrast, transgenic mice expressing a dominant negative IκBα mutant protein under the control of epithelial cell specific promoters demonstrate enhanced apoptosis and collagen deposition in their lungs in response to silica. Conclusions: Although limited by its size, our data support that patients with silicosis appear to have poor outcome following lung transplantation. Experimental data indicate that while the systemic inhibition of NF-κB protects from silica-induced lung injury, epithelial cell specific NF-κB inhibition appears to aggravate the outcome of experimental silicosis. © 2009 Di Giuseppe et al

When Two Become One: The Limits of Causality Analysis of Brain Dynamics

Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand the functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of these interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such interacting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural causal effect. This new concept takes into account that when studying interactions in biological systems, one is often not interested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections participate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal connections that determine the existence of natural causal effects. In particular, we show that the influence of the causal connections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem on another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We note that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be quantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be characterized when they exist. Our work also has important consequences for the interpretation of other approaches commonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be combined with Granger causality and Dynamic Causal Modeling (DCM). Our results are generic and the concept of natural causal effects is relevant in all areas where the effects of interactions between subsystems are of interest