Luc P. Beaudoin

Intermittent rewards raise self-stimulation thresholds

Rats implanted with lateral hypothalamic electrodes pressed a lever to obtain 0.5 s bursts of pulses under the four combinations of fixed or variable, interval or ratio, schedules of reinforcement. Along with continuous reinforcement schedules, intervals of 1, 2, 5, and 10 s, or ratios of 2, 5, and 10 responses per stimulation were used in sessions wherein the frequency thresholds, defined as pulse frequencies that would support half-maximum rates of response, were estimated. Thresholds rose systematically under both ratio and interval schedules of reinforcement, and there was no difference between fixed and variable variations. When normalized data were plotted as a function of reinforcement density, thresholds from both interval and ratio schedules followed the same pattern, suggesting that the common factor was time between rewards. An increase in the current with a corresponding decrease in pulse frequency increased the rate at which time between rewards augmented thresholds.

Developing Expertise with Objective Knowledge: Motive Generators and Productive Practice

Experts seek to derive manifold benefits from objective knowledge. Viewed as progressive problem solvers (Bereiter and Scardamalia 1993), they are not immune to psychological and practical challenges to learning in depth, particularly given demands for breadth and a lack of cognitive productivity tools. What mental changes occur when one understands deeply and develops new skills, new attitudes and implicit knowledge? With a few scenarios, I propose that deep understanding of conceptual artifacts, in the sense of Bereiter (2002), establishes and configures diverse motive generators that enable the valenced detection of gaps of understanding, cognitive infelicities and opportunities (cognitive itches). This proposal, derived from a designer-based approach to motivation (Sloman 1987; Beaudoin and Sloman 1993), is significantly different from how motivation is typically treated in psychology. It raises many questions about how motivational mechanisms develop and operate in the propensities of expertise. I suggest that experts facing great cognitive productivity demands can benefit from productive practice.

Attachment Modelling: From Observations to Scenarios to Designs

The purpose of the research programme detailed in this paper is to update the attachment control system framework that John Bowlby set out in his formulation of Attachment Theory. It does this by reconceptualising it as a cognitive architecture that can operate within multi-agent simulations. This is relevant to computational psychiatry because attachment phenomena are broad in scope and range from healthy everyday interactions to psychopathology. The process of attachment modelling involves three stages and this paper makes contributions in each of these stages. Firstly, a survey of attachment research is presented which focuses on two important attachment behavioural measures: the Strange Situation Procedure and the Adult Attachment Interview (AAI). These studies are reviewed to draw out key behavioural patterns and dependencies. Secondly, the empirical observations that are to be explained in this research programme are abstracted into scenarios which capture key behavioural elements. The value of behavioural scenarios is that they can guide the simulation design process and help evaluate simulations which are produced. Thirdly, whilst the implementation of these scenarios is still a work in progress, several designs are described that have been created and implemented as simulations. These include normative and non-pathological infant behaviour patterns observed across the first year of life in naturalistic observations and ‘Strange Situation’ studies. Future work is described which includes simulating dysfunctional infant behaviour patterns and a range of adult attachment behaviour patterns observed in the Adult Attachment Interview. In conclusion, this modelling approach is distinguished from other approaches in computational psychiatry because of the psychologically high level at which it models phenomena of interest.