Attentional capture by meaning: A multi-level modelling study

We present a computational study of attentional capture by meaning, based on Barnard et al's key-distractor attentional blink task. We highlight a sequence of models, from an abstract black-box to a structurally detailed white-box model. Each of these models reproduces the major findings from the key-distractor blink task. We argue that such multi-level modelling gives greater confidence in the theoretical position encapsulated by these models

What Do We Mean by the Meanings of Music?

Drawing upon a recent review of the topic by Cross and Tolbert (2009), this paper briefly illustrates the diversity of theories concerning the nature of meanings in music and the challenges that need to be resolved to advance the field. A scheme for layered macro- and micro-theories for neural, mental and behavioural systems is outlined to facilitate the development of a systematic and coherent body of theory. The core of the paper charts the evolutionary origins of a specific macro- theory of the organisation all the components of the human mind. This “mental architecture,” known as Interacting Cognitive Subsystems (Barnard, 1985), incorporates not one, but two qualitatively distinct forms of meaning. Propositional meanings represent referentially specific ideas while implicational meanings encapsulate a yet more abstract and holistic form of meaning that blends conceptual material with the products of immediate distal and bodily sensations. While both forms of meaning interact in the interpretation and expression of musical meaning, such meanings are argued to be primarily implicational in nature. The paper concludes with a short discussion of how this approach might usefully be applied in the development of more precise specification of what music might mean in its various facets

Systems, interactions and macrotheory

A significant proportion of early HCI research was guided by one very clear vision: that the existing theory base in psychology and cognitive science could be developed to yield engineering tools for use in the interdisciplinary context of HCI design. While interface technologies and heuristic methods for behavioral evaluation have rapidly advanced in both capability and breadth of application, progress toward deeper theory has been modest, and some now believe it to be unnecessary. A case is presented for developing new forms of theory, based around generic “systems of interactors.” An overlapping, layered structure of macro- and microtheories could then serve an explanatory role, and could also bind together contributions from the different disciplines. Novel routes to formalizing and applying such theories provide a host of interesting and tractable problems for future basic research in HCI

Disgust Enhances the Recollection of Negative Emotional Images

Memory is typically better for emotional relative to neutral images, an effect generally considered to be mediated by arousal. However, this explanation cannot explain the full pattern of findings in the literature. Two experiments are reported that investigate the differential effects of categorical affective states upon emotional memory and the contributions of stimulus dimensions other than pleasantness and arousal to any memory advantage. In Experiment 1, disgusting images were better remembered than equally unpleasant frightening ones, despite the disgusting images being less arousing. In Experiment 2, regression analyses identified affective impact – a factor shown previously to influence the allocation of visual attention and amygdala response to negative emotional images – as the strongest predictor of remembering. These findings raise significant issues that the arousal account of emotional memory cannot readily address. The term impact refers to an undifferentiated emotional response to a stimulus, without requiring detailed consideration of specific dimensions of image content. We argue that ratings of impact relate to how the self is affected. The present data call for further consideration of the theoretical specifications of the mechanisms that lead to enhanced memory for emotional stimuli and their neural substrates

Emotional Complexity and the Neural Representation of Emotion in Motion

According to theories of emotional complexity, individuals low in emotional complexity encode and represent emotions in visceral or action-oriented terms, whereas individuals high in emotional complexity encode and represent emotions in a differentiated way, using multiple emotion concepts. During functional magnetic resonance imaging, participants viewed valenced animated scenarios of simple ball-like figures attending either to social or spatial aspects of the interactions. Participant’s emotional complexity was assessed using the Levels of Emotional Awareness Scale. We found a distributed set of brain regions previously implicated in processing emotion from facial, vocal and bodily cues, in processing social intentions, and in emotional response, were sensitive to emotion conveyed by motion alone. Attention to social meaning amplified the influence of emotion in a subset of these regions. Critically, increased emotional complexity correlated with enhanced processing in a left temporal polar region implicated in detailed semantic knowledge; with a diminished effect of social attention; and with increased differentiation of brain activity between films of differing valence. Decreased emotional complexity was associated with increased activity in regions of pre-motor cortex. Thus, neural coding of emotion in semantic vs action systems varies as a function of emotional complexity, helping reconcile puzzling inconsistencies in neuropsychological investigations of emotion recognition

Kinetics analysis and automated online screening of aminocarbonylation of aryl halides in flow

Temperature, pressure, gas stoichiometry, and residence time were varied to control the yield and product distribution of the palladium-catalyzed aminocarbonylation of aromatic bromides in both a silicon microreactor and a packed-bed tubular reactor. Automation of the system set points and product sampling enabled facile and repeatable reaction analysis with minimal operator supervision. It was observed that the reaction was divided into two temperature regimes. An automated system was used to screen steady-state conditions for offline analysis by gas chromatography to fit a reaction rate model. Additionally, a transient temperature ramp method utilizing online infrared analysis was used, leading to more rapid determination of the reaction activation energy of the lower temperature regimes. The entire reaction spanning both regimes was modeled in good agreement with the experimental data