The goal-dependent automaticity of drinking habits

In recent treatments of habitual social behaviour, habits are conceptualized as a form of goal-directed automatic behaviour that are mentally represented as goal-action links. Three experiments tested this conceptualization in the context of students' drinking (alcohol consumption)habits. Participants were randomly assigned to conditions where either a goal related to drinking behaviour (socializing) was activated, or an unrelated goal was activated. In addition, participants' drinking habits were measured. The dependent variable in Experiments 1 and 2 was readiness to drink, operationalized by speed of responding to the action concept 'drinking' in a verb verification task. Experiment 3 used the uptake of a voucher to measure drinking behaviour. Findings supported the view that when habits are established, simply activating a goal related to the focal behaviour automatically elicits that behaviour. These findings are consistent with a goal-dependent conception of habit. Possibilities for interventions designed to attenuate undesirable habitual behaviours are considered.

Task-based annotation and retrieval for image information management

Continuing advances in digital image capture and storage are resulting in a proliferation of imagery and associated problems of information overload in image domains. In this work we present a framework that supports image management using an interactive approach that captures and reuses task-based contextual information. Our framework models the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. During image analysis, interactions are captured and a task context is dynamically constructed so that human expertise, proficiency and knowledge can be leveraged to support other users in carrying out similar domain tasks using case-based reasoning techniques. In this article we present our framework for capturing task context and describe how we have implemented the framework as two image retrieval applications in the geo-spatial and medical domains. We present an evaluation that tests the efficiency of our algorithms for retrieving image context information and the effectiveness of the framework for carrying out goal-directed image tasks. © 2010 Springer Science+Business Media, LLC.

Cortical dynamics and synchronization related to multiple target consolidation under rapid-serial-visual-presentation conditions

The present report reviews behavioural, electroencephalographic, and especially magnetoencephalographic findings on the cortical mechanisms underlying attentional processes that separate targets from distractors and that ensure durable target representations for goal-directed action. A common way of investigation is to observe the system’s overt and covert behaviour when capacity limitations are reached. Here we focus on the aspect of temporally enhanced processing load, namely on performance deficits occurring under rapid-serial-visual-presentation (RSVP) conditions. The most prominent of these deficits is the so-called “attentional blink” (AB) effect. We first report MEG findings with respect to the time course of activation that shows modulations around 300 ms after target onset which reflect demands and success of target consolidation. Then, findings regarding long-range inter-area phase synchronization are reported that are hypothesized to mediate communication within the attentional network. Changes in synchronization reflect changes in the attentional demands of the task and are directly related to behavioural performance. Furthermore, enhanced vigilance of the system elicits systematically increased synchronization indices. A hypothetical framework is sketched out that aims at explaining limitations in multiple target consolidation under RSVP conditions.

Task-based image annotation and retrieval

In order to address problems of information overload in digital imagery task domains we have developed an interactive approach to the capture and reuse of image context information. Our framework models different aspects of the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. The approach allows us to gauge a measure of a user's intentions as they complete goal-directed image tasks. As users analyze retrieved imagery their interactions are captured and an expert task context is dynamically constructed. This human expertise, proficiency, and knowledge can then be leveraged to support other users in carrying out similar domain tasks. We have applied our techniques to two multimedia retrieval applications for two different image domains, namely the geo-spatial and medical imagery domains. © Springer-Verlag Berlin Heidelberg 2007.