Neural Dynamics Underlying Impaired Autonomic and Conditioned Responses Following Amygdala and Orbitofrontal Lesions

A neural model is presented that explains how outcome-specific learning modulates affect, decision-making and Pavlovian conditioned approach responses. The model addresses how brain regions responsible for affective learning and habit learning interact, and answers a central question: What are the relative contributions of the amygdala and orbitofrontal cortex to emotion and behavior? In the model, the amygdala calculates outcome value while the orbitofrontal cortex influences attention and conditioned responding by assigning value information to stimuli. Model simulations replicate autonomic, electrophysiological, and behavioral data associated with three tasks commonly used to assay these phenomena: Food consumption, Pavlovian conditioning, and visual discrimination. Interactions of the basal ganglia and amygdala with sensory and orbitofrontal cortices enable the model to replicate the complex pattern of spared and impaired behavioral and emotional capacities seen following lesions of the amygdala and orbitofrontal cortex.

Autonomic cardiovascular dysregulation as a potential mechanism underlying depression and coronary artery bypass grafting surgery outcomes.

BACKGROUND: Coronary artery bypass grafting (CABG) is often used to treat patients with significant coronary heart disease (CHD). To date, multiple longitudinal and cross-sectional studies have examined the association between depression and CABG outcomes. Although this relationship is well established, the mechanism underlying this relationship remains unclear. The purpose of this study was twofold. First, we compared three markers of autonomic nervous system (ANS) function in four groups of patients: 1) Patients with coronary heart disease and depression (CHD/Dep), 2) Patients without CHD but with depression (NonCHD/Dep), 3) Patients with CHD but without depression (CHD/NonDep), and 4) Patients without CHD and depression (NonCHD/NonDep). Second, we investigated the impact of depression and autonomic nervous system activity on CABG outcomes. METHODS: Patients were screened to determine whether they met some of the study's inclusion or exclusion criteria. ANS function (i.e., heart rate, heart rate variability, and plasma norepinephrine levels) were measured. Chi-square and one-way analysis of variance were performed to evaluate group differences across demographic, medical variables, and indicators of ANS function. Logistic regression and multiple regression analyses were used to assess impact of depression and autonomic nervous system activity on CABG outcomes. RESULTS: The results of the study provide some support to suggest that depressed patients with CHD have greater ANS dysregulation compared to those with only CHD or depression. Furthermore, independent predictors of in-hospital length of stay and non-routine discharge included having a diagnosis of depression and CHD, elevated heart rate, and low heart rate variability. CONCLUSIONS: The current study presents evidence to support the hypothesis that ANS dysregulation might be one of the underlying mechanisms that links depression to cardiovascular CABG surgery outcomes. Thus, future studies should focus on developing and testing interventions that targets modifying ANS dysregulation, which may lead to improved patient outcomes.

The Representation of Emotion in Autonomic and Central Nervous System Activity

Phenomenologically, humans effectively label and report feeling distinct emotions, yet the extent to which emotions are represented categorically in nervous system activity is controversial. Theoretical accounts differ in this regard, some positing distinct emotional experiences emerge from a dimensional representation (e.g., along axes of valence and arousal) whereas others propose emotions are natural categories, with dedicated neural bases and associated response profiles. This dissertation aims to empirically assess these theoretical accounts by examining how emotions are represented (either as disjoint categories or as points along continuous dimensions) in autonomic and central nervous system activity by integrating psychophysiological recording and functional neuroimaging with machine-learning based analytical methods. Results demonstrate that experientially, emotional events are well-characterized both along dimensional and categorical frameworks. Measures of central and peripheral responding discriminate among emotion categories, but are largely independent of valence and arousal. These findings suggest dimensional and categorical aspects of emotional experience are driven by separable neural substrates and demonstrate that emotional states can be objectively quantified on the basis of nervous system activity.

Self-adaptability and man-in-the-loop: a dilemma in autonomic computing systems

This paper addresses some controversial issues relating to two main questions. Firstly, we discuss 'man-in-the loop' issues in SAACS. Some people advocate this must always be so that man's decisions can override autonomic components. In this case, the system has two subsystems - man and machine. Can we, however, have a fully autonomic machine - with no man in sight; even for short periods of time? What kinds of systems require man to always be in the loop? What is the optimum balance in self-to-human control? How do we determine the optimum? How far can we go in describing self-behaviour? How does a SAACS system handle unexpected behaviour? Secondly, what are the challenges/obstacles in testing SAACS in the context of self/human dilemma? Are there any lesson to be learned from other programmes e.g. Star-wars, aviation and space explorations? What role human factors and behavioural models play whilst in interacting with SAACS?.

A policy-definition language and prototype implementation library for policy-based autonomic systems

This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility

Exploring adaptation & self-adaptation in autonomic computing systems

This panel paper sets out to discuss what self-adaptation means, and to explore the extent to which current autonomic systems exhibit truly self-adaptive behaviour. Many of the currently cited examples are clearly adaptive, but debate remains as to what extent they are simply following prescribed adaptation rules within preset bounds, and to what extent they have the ability to truly learn new behaviour. Is there a standard test that can be applied to differentiate? Is adaptive behaviour sufficient anyway? Other autonomic computing issues are also discussed.

The AGILE policy expression language for autonomic systems

This paper presents the AGILE policy expression language. The language enables powerful expression of self-managing behaviours and facilitates policy-based autonomic computing in which the policies themselves can be adapted dynamically and automatically. The language is generic so as to be deployable across a wide spectrum of application domains, and is very flexible through the use of simple yet expressive syntax and semantics. The development of AGILE is motivated by the need for adaptive policy mechanisms that are easy to deploy into legacy code and can be used by non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk. A library implementation of the policy language is described. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and higher-level ‘meta-policies’ to dynamically select between differently configured business-logic policy instances and templates. Two dissimilar example deployment scenarios are examined.

Policy-centric integration and dynamic composition of autonomic computing techniques

This paper presents innovative work in the development of policy-based autonomic computing. The core of the work is a powerful and flexible policy-expression language AGILE, which facilitates run-time adaptable policy configuration of autonomic systems. AGILE also serves as an integrating platform for other self-management technologies including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. The various technologies are implemented as object components. Self-management behaviour is specified using the policy language semantics to bind the various components together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. Additional benefits include the standardisation of the application programmer interface, terminology and semantics, and only a single point of embedding is required.

Developing “middle leaders” in the public services? The realities of management and leadership development for public managers

Purpose – This paper aims to assess the actual contribution to organisational change of management and leadership development (MLD) activity for middle managers (MMs) in public service organisations (PSOs). Design/methodology/approach – Using the case study approach, the paper compares the content and outcomes of management and leadership training interventions for MMs in two large PSOs. The organisations, a fire brigade and a train operating company, are leaders in their sectors with respect to management development and “modernisation” of their services. Findings – The paper demonstrates how, in one case, MM development was largely an exercise in regulatory compliance, with little effect on individual MMs' performance or organisational outcomes. The second case demonstrates how MMs were effectively trained to enforce specific human resource policies which contributed to the successful implementation of top-down strategy yet paid little attention to the potential leadership role of MMs. Research limitations/implications – The paper highlights the need for further contextualised research at organisational level into the outcomes of MLD, especially in terms of different public service contexts. Practical implications – The paper demonstrates the dangers of designing and implementing development programmes without sufficient regard to professional practice and the realities of managerial discretion in PSOs. Originality/value – The paper provides an in-depth and contextualised insight into the conditions for success and failure in management development interventions in PSOs.