A Malleable Metaphor: Physarum polycephalum as artistic and educational medium

The slime mold Physarum polycephalum is a well-established model organism within fields of biology, physics and computing. It is also increasingly employed within art and design disciplines, pedagogic practices and public engagement activities as a vehicle for exploring questions of intelligence, agency and emergence. This work was presented at PhysNet 2015

Menagerie of Microbes

Menagerie of Microbes celebrates the microbial world, bringing together the work of artists, designers and scientists who share a passion for microorganisms, which exist in and around us. Menagerie of Microbes presents work by Heather Barnett, Anna Dumitriu, ecoLogicStudio, Patrick Hickey, Simon Park, Sarah Roberts, Urban Morphogenesis Lab and the ASCUS Lab, and is part of Bio and Beyond, the visual art exhibition at Summerhall for the Edinburgh International Science Festival 2016. Menagerie of Microbes is curated by Heather Barnett and James Howie (ASCUS Lab)

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the inferences’ policy relevance, which is particularly dramatic at the broadest (M3) level of aggregation. Indeed, as Belongia (1996) has observed in this regard, “measurement matters.”Measurement Error, Divisia Index, Aggregation, State Space, Markov Switching, Monetary Policy

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of simple sum monetary aggregates and the Divisia indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although the traditional comparison of the series may suggest that they share similar dynamics, there are important differences during certain times and around turning points that can not be evaluated by their average behavior. We use a factor model with regime switching that offers several ways in which these differences can be analyzed. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each one series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors represent exactly where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We also find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginning and end of economic recessions, and during some high interest rate phases.Measurement Error, Divisia Index, Aggregation, State Space, Markov Switching, Monetary Policy

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the inferences’ policy relevance, which is particularly dramatic at the broadest (M3) level of aggregation. Indeed, as Belongia (1996) has observed in this regard, “measurement matters.”Measurement Error, Divisia Index, Aggregation, State Space, Markov Switching, Monetary Policy

Measurement Error in Monetary Aggregates: A Markov Switching Factor Approach

This paper compares the different dynamics of the simple sum monetary aggregates and the Divisia monetary aggregate indexes over time, over the business cycle, and across high and low inflation and interest rate phases. Although traditional comparisons of the series sometimes suggest that simple sum and Divisia monetary aggregates share similar dynamics, there are important differences during certain periods, such as around turning points. These differences cannot be evaluated by their average behavior. We use a factor model with regime switching. The model separates out the common movements underlying the monetary aggregate indexes, summarized in the dynamic factor, from individual variations in each individual series, captured by the idiosyncratic terms. The idiosyncratic terms and the measurement errors reveal where the monetary indexes differ. We find several new results. In general, the idiosyncratic terms for both the simple sum aggregates and the Divisia indexes display a business cycle pattern, especially since 1980. They generally rise around the end of high interest rate phases – a couple of quarters before the beginning of recessions – and fall during recessions to subsequently converge to their average in the beginning of expansions. We find that the major differences between the simple sum aggregates and Divisia indexes occur around the beginnings and ends of economic recessions, and during some high interest rate phases. We note the policy relevance of the inferences. Indeed, as Belongia (1996) has observed in this regard, "measurement matters."Measurement error; monetary aggregation; Divisia index; aggregation; state space; Markov switching; monetary policy; index number theory; factor models

Enhanced sensitivity and response bias for male anger in women with borderline personality disorder

Interpersonal difficulties, which are characteristic of Borderline personality disorder (BPD), may be related to problems with social cognition. We explored facial emotion recognition in 44 women (15 with BPD, 15 healthy controls, and 14 with a history of childhood trauma but no BPD) examining the role of BPD and abuse history in the ability to detect fearful, angry and happy cues in emotional faces. In Task 1, participants viewed pictures of morphed faces containing different percentages of specific emotions and reported the emotion they saw. In Task 2, participants were asked to increase the intensity of a specific emotion on an initially neutral face until they could detect that emotion in the face. Across both tasks, BPD predicted the earlier detection of anger in male faces. BPD symptoms also predicted the misidentification of anger in male faces containing no anger cues. Although participants with BPD were slower to recognize happiness in male faces, their overall ability to recognize happiness was unimpaired. Abuse history did predict problems with happiness recognition. Finally, recognition of fear was unrelated to abuse history and BPD. Findings suggest that BPD is associated with a bias toward seeing anger in males and that this is independent of abuse history.Psycholog

Broad Vision: the Art & Science of Looking

Undergraduate students and academic staff from diverse disciplines in the arts and sciences investigated questions of mediated vision through a year-long interdisciplinary research project at the University of Westminster, London, United Kingdom. The Broad Vision project explored the perception and interpretation of microscopic worlds, and investigated the benefits and challenges of working across disciplinary divides in a university setting. This article describes the three-phase model for interdisciplinary learning and research developed through the project, providing a valuable case study for inquiry based art/science education

The Physarum Experiments

This portfolio presents a body of work created with a classic model organism - the slime mould Physarum polycephalum. Within a studio setting, the slime mould is staged within novel environments and its growth trajectories captured as it navigates: calculating routes, making decisions and responding to encounters. Through the representation of emergent growth trajectories and behavioural responses to given interventions the work aims to ‘draw out’ fundamental processes of life as a relational exercise. Imaging technologies – specifically macro and time-lapse photography – mediate between spatiotemporal subjectivities, amplifying slime mould behaviour to human scale

Drawing Out the Superorganism: Artistic Intervention and the Amplification of Processes of Life

The true slime mould, Physarum polycephalum, is a single-celled organism which spends much of its life creeping around the forest floor feeding on rotting vegetation. Comprised of many cells, all operating within a single cell membrane, this many-headed amoeba possesses a form of proto-intelligence which enables it to operate far beyond its physiological means. Despite having no sensory organs or a brain, the slime mould has demonstrated that it can recognize pattern by anticipating events and is entirely self-organizing, with no centralized control system – purely a mass of cellular cytoplasm pulsing in a synchronous flow. This chapter examines the behaviours of this intriguing organism as mediated through a series of time-lapse studies designed to draw out inherent processes of life. Responding to given interventions – a series of invitations and interruptions utilizing known attractants and repellents – a performative stimulus/response emerges. The imaging technologies employed amplify the biological world of the slime mould to human spatio-temporal scale. The intention of the studies is to reveal the underlying processes at play within this fascinating and beautiful organism and, through the aesthetic and technological devices employed, to entice other humans to observe and take note. The edited collection Drawing Processes of Life is the product of artists, biologists and philosophers working together to formulate new ways of representing a new approach to life. It shows how better to represent biological process through drawing and to demonstrate the scientific value of drawing as a method. 78 b/w and 36 colour illustrations. A PDF version of this book is available for free in Open Access. It has been made available under a Creative Commons Attribution 4.0 International Public License