Individual Differences and Memory Aging Concerns of Older Adults

The present research was designed to address two issues with respect to the self-reported memory functioning of older adults. The first issue concerns older adults’ practical memory concerns, defined as self-appraisals of one’s own memory that include worries, apprehension, and fears about aging that relate to memory. We used a mixed method approach in this study to provide a comprehensive assessment of self-reported memory functioning based on quantitative (the Memory Functioning Questionnaire, the Memory Controllability Inventory) and qualitative (the Practical Memory Concerns survey) indicators. The second issue concerns the contribution of individual difference to older adults’ self-perceived memory functioning. The particular individual difference factors that were expected to influence memory aging concerns included: age, presence or absence of family members with Alzheimer\u27s disease as indicated by self report, knowledge of memory aging (indexed by the Knowledge of Memory Aging Questionnaire), cognitive status (indexed by the Mini-Mental State Exam), and affective status (indexed by the Geriatric Depression Scale). Regarding specific memory aging concerns, obligations to others, spatial information, and important dates were most frequently reported as bothersome to forget. Fear of developing disease (e.g. dementia or Alzheimer’s disease) and fear of losing independence were the most frequently reported fears of memory aging. Of the individual difference factors expected to influence memory aging concerns, affective status and knowledge of memory aging were significant predictors of memory aging concerns. Age, family history of Alzheimer’s disease, and cognitive status were not significantly related to memory aging concerns

The distracted robot: what happens when artificial agents behave like us

In everyday life, we are frequently exposed to different smart technologies. From our smartphones to avatars in computer games, and soon perhaps humanoid robots, we are surrounded by artificial agents created to interact with us. Already during the design phase of an artificial agent, engineers often endow it with functions aimed to promote the interaction and engagement with it, ranging from its \u201ccommunicative\u201d abilities to the movements it produces. Still, whether an artificial agent that can behave like a human could boost the spontaneity and naturalness of interaction is still an open question. Even during the interaction with conspecifics, humans rely partially on motion cues when they need to infer the mental states underpinning behavior. Similar processes may be activated during the interaction with embodied artificial agents, such as humanoid robots. At the same time, a humanoid robot that can faithfully reproduce human-like behavior may undermine the interaction, causing a shift in attribution: from being endearing to being uncanny. Furthermore, it is still not clear whether individual biases and prior knowledge related to artificial agents can override perceptual evidence of human-like traits. A relatively new area of research emerged in the context of investigating individuals\u2019 reactions towards robots, widely referred to as Human-Robot Interaction (HRI). HRI is a multidisciplinary community that comprises psychologists, neuroscientists, philosophers as well as roboticists, and engineers. However, HRI research has been often based on explicit measures (i.e. self-report questionnaires, a-posteriori interviews), while more implicit social cognitive processes that are elicited during the interaction with artificial agents took second place behind more qualitative and anecdotal results. The present work aims to demonstrate the usefulness of combining the systematic approach of cognitive neuroscience with HRI paradigms to further investigate social cognition processes evoked by artificial agents. Thus, this thesis aimed at exploring human sensitivity to anthropomorphic characteristics of a humanoid robot's (i.e. iCub robot) behavior, based on motion cues, under different conditions of prior knowledge. To meet this aim, we manipulated the human-likeness of the behaviors displayed by the robot and the explicitness of instructions provided to the participants, in both screen-based and real-time interaction scenarios. Furthermore, we explored some of the individual differences that affect general attitudes towards robots, and the attribution of human-likeness consequently

Simulations in statistical physics and biology: some applications

One of the most active areas of physics in the last decades has been that of critical phenomena, and Monte Carlo simulations have played an important role as a guide for the validation and prediction of system properties close to the critical points. The kind of phase transitions occurring for the Betts lattice (lattice constructed removing 1/7 of the sites from the triangular lattice) have been studied before with the Potts model for the values q=3, ferromagnetic and antiferromagnetic regime. Here, we add up to this research line the ferromagnetic case for q=4 and 5. In the first case, the critical exponents are estimated for the second order transition, whereas for the latter case the histogram method is applied for the occurring first order transition. Additionally, Domany's Monte Carlo based clustering technique mainly used to group genes similar in their expression levels is reviewed. Finally, a control theory tool --an adaptive observer-- is applied to estimate the exponent parameter involved in the well-known Gompertz curve. By treating all these subjects our aim is to stress the importance of cooperation between distinct disciplines in addressing the complex problems arising in biology. Contents: Chapter 1 - Monte Carlo simulations in stat. physics; Chapter 2: MC simulations in biology; Chapter 3: Gompertz equationComment: 82 pages, 33 figures, 4 tables, somewhat reduced version of the M.Sc. thesis defended in Jan. 2006 at IPICyT, San Luis Potosi, Mx. (Supervisers: Drs. R. Lopez-Sandoval and H.C. Rosu). Last sections 3.3 and 3.4 can be found at http://lanl.arxiv.org/abs/physics/041108

SOUND SYNTHESIS WITH CELLULAR AUTOMATA

This thesis reports on new music technology research which investigates the use of cellular automata (CA) for the digital synthesis of dynamic sounds. The research addresses the problem of the sound design limitations of synthesis techniques based on CA. These limitations fundamentally stem from the unpredictable and autonomous nature of these computational models. Therefore, the aim of this thesis is to develop a sound synthesis technique based on CA capable of allowing a sound design process. A critical analysis of previous research in this area will be presented in order to justify that this problem has not been previously solved. Also, it will be discussed why this problem is worthwhile to solve. In order to achieve such aim, a novel approach is proposed which considers the output of CA as digital signals and uses DSP procedures to analyse them. This approach opens a large variety of possibilities for better understanding the self-organization process of CA with a view to identifying not only mapping possibilities for making the synthesis of sounds possible, but also control possibilities which enable a sound design process. As a result of this approach, this thesis presents a technique called Histogram Mapping Synthesis (HMS), which is based on the statistical analysis of CA evolutions by histogram measurements. HMS will be studied with four different automatons, and a considerable number of control mechanisms will be presented. These will show that HMS enables a reasonable sound design process. With these control mechanisms it is possible to design and produce in a predictable and controllable manner a variety of timbres. Some of these timbres are imitations of sounds produced by acoustic means and others are novel. All the sounds obtained present dynamic features and many of them, including some of those that are novel, retain important characteristics of sounds produced by acoustic means

Artificial societies and information theory: modelling of sub system formation based on Luhmann's autopoietic theory

This thesis develops a theoretical framework for the generation of artificial societies. In particular it shows how sub-systems emerge when the agents are able to learn and have the ability to communicate. This novel theoretical framework integrates the autopoietic hypothesis of human societies, formulated originally by the German sociologist Luhmann, with concepts of Shannon's information theory applied to adaptive learning agents. Simulations were executed using Multi-Agent-Based Modelling (ABM), a relatively new computational modelling paradigm involving the modelling of phenomena as dynamical systems of interacting agents. The thesis in particular, investigates the functions and properties necessary to reproduce the paradigm of society by using the mentioned ABM approach. Luhmann has proposed that in society subsystems are formed to reduce uncertainty. Subsystems can then be composed by agents with a reduced behavioural complexity. For example in society there are people who produce goods and other who distribute them. Both the behaviour and communication is learned by the agent and not imposed. The simulated task is to collect food, keep it and eat it until sated. Every agent communicates its energy state to the neighbouring agents. This results in two subsystems whereas agents in the first collect food and in the latter steal food from others. The ratio between the number of agents that belongs to the first system and to the second system, depends on the number of food resources. Simulations are in accordance with Luhmann, who suggested that adaptive agents self-organise by reducing the amount of sensory information or, equivalently, reducing the complexity of the perceived environment from the agent's perspective. Shannon's information theorem is used to assess the performance of the simulated learning agents. A practical measure, based on the concept of Shannon's information ow, is developed and applied to adaptive controllers which use Hebbian learning, input correlation learning (ICO/ISO) and temporal difference learning. The behavioural complexity is measured with a novel information measure, called Predictive Performance, which is able to measure at a subjective level how good an agent is performing a task. This is then used to quantify the social division of tasks in a social group of honest, cooperative food foraging, communicating agents

Motion-Based Video Games for Stroke Rehabilitation with Reduced Compensatory Motions

Stroke is the leading cause of long-term disability among adults in industrialized nations, with 80% of people who survive strokes experiencing motor disabilities. Recovery requires daily exercise with a high number of repetitions, often without therapist supervision. Motion-based video games can help motivate people with stroke to perform the necessary exercises to recover. We explore the design space of video games for stroke rehabilitation using Wii remotes and webcams as input devices, and share the lessons we learned about what makes games therapeutically useful. We demonstrate the feasibility of using games for home-based stroke therapy with a six-week case study. We show that exercise with games can help recovery even 17 years after the stroke, and share the lessons that we learned for game systems to be used at home as a part of outpatient therapy. As a major issue with home-based therapy, we identify that unsupervised exercises lead to compensatory motions that can impede recovery and create new health issues. We reliably detect torso compensation in shoulder exercises using a custom harness, and develop a game that meaningfully uses both exercise and compensation as inputs. We provide in-game feedback that reduces compensation in a number of ways. We evaluate alternative ways for reducing compensation in controlled experiments and show that using techniques from operant conditioning are effective in significantly reducing compensatory behavior compared to existing approaches

A treatise on language methods and language-games in autism

Although it is generally understood that autism is a developmental disability affecting social learning, my social constructionist perspective suggested to me that, strangely, current theories aimed at explaining the nature of autism appeared not to fully reflect the essential social aspects of autism. Given that typically developing human beings become fully socialised through learning a first language, it appeared to me that autism research has, especially of late, failed to give sufficient attention to language despite Kanner’s advice. In researching this thesis I have sought to make a contribution to knowledge of my subject by: (1) developing a synthesis of current knowledge of autistic language methods as a practical framework to guide future research focused on language in autism; (2) critiquing ‘established’ autism theory; (3) drawing attention to Ludwig Wittgenstein’s neglected contributions to the philosophy of mind; and (4) reviewing the contribution of ‘alternative’ theory, including Wittgenstein’s criteriological theory, to an understanding of autism. My research has involved reviewing: (a) the literature on autistic language methods; (b)Conversation Analysis of autistic conversation; (c) narrative writing by authors diagnosed or retrospectively diagnosed with autism; and (d) existing autism theory. I conclude that there are specific features of talk and writing that reflect autism with some features of autistic writing being a ‘mirror image’ of features of autistic talk. A further, important, conclusion is that there are strengths as well as weaknesses associated with autistic talk and writing i.e., from a linguistic stance, it is wrong to regard autism as a disability; rather, it involves a different way of communicating – both verbally and in writing – than is seen in typically developing people. I also conclude that alternative theory has much to contribute to an understanding of autism, and that the atypical nature of autistic social development results in autistic people failing to fully come to terms with language-games

The effects of success on task enjoyment and persistence

This thesis explored two issues. Firstly, how participants would respond,in terms of task persistence and task enjoyment, to differing levels of success, when a task was presented to them with a mastery-focus (Experiments 1-5). Secondly, whether improving at task caused participants to enjoy tasks more than achieving a constant level of success (Experiments 6-10). Experiments 1-3 provided evidence that when participants were given the opportunity to persist with a task for as long as they wanted, they persisted longer after performing poorly. However, despite persisting longer, they did not enjoy the task. Experiments 4-5 adopted the same paradigm as Experiments 1-3, but included a second free-choice persistence phase where participants were unaware their behaviour was being monitored. In Experiments 4 and 5, participants who performed poorly persisted longer initially, but less during the subsequent free-choice phase. Again, those who performed poorly during the initial phase reported that they did not enjoy the task. It was suggested that neither the achievement-goal theories of Nicholls (1984) and Dweck (1986) nor Deci's (1975) theory of intrinsic motivation could adequately account for the persistence behaviours observed in the second persistence phase in Experiments 4 and 5. Instead, it was suggested that participants persisted because of the pleasure derived from solving the problems. Experiments 6-10 examined the role of improvement in task enjoyment. Experiments 6 and 7 were control studies intended to establish wheter the paradigm was appropriate to examine improvement. Experiments 8-9 showed that relative to achieving a consistent level of performance, improvement increased task enjoyment. However, this result was found only when participants did well; when they did poorly at a task, improvemenpt produced less enjoyment(Experiment 10). Both results can be explained if participants' expectations are taken into account as well as their rate of success. The final conclusions chapter discusses the types of achievement targets individuals might set themselves when what constitutes good performance at a task is ambiguous, and relates this analysis to the findings from all ten experiments

The Influence of type D personality on the onset and maintenance of chronic illness

The thesis found that Type D personality is a risk factor for onset and protracted morbidity of a number of high-prevalence, high-impact chronic conditions within the Australian population. The findings have potential implications for Australian health determinate models, healthcare policy, and the allocation of clinical and research healthcare resources