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Theoretical and empirical integration of process- and parameter-based accounts of visual perception

English title Theoretical and empirical integration of process- and parameter-based accounts of visual perception
Applicant Krummenacher Joseph
Number 114415
Funding scheme ProDoc
Research institution Département de Psychologie Université de Fribourg
Institution of higher education University of Fribourg - FR
Main discipline Psychology
Start/End 01.10.2006 - 31.01.2010
Approved amount 144'368.00
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Keywords (9)

Selection; Attention; Visual perception; Mechanisms of selection; Feature integration; Guided search; Dimension weighting; Theory of visual attention; Parameter-based modelling

Lay Summary (English)

Lead
Lay summary
A key function of the human cognitive system is the selection of information relevant for the control of current thoughts or behavioural goals and the de-selection of irrelevant information. The underlying mechanisms are referred to as “selective” or “attentional” processes, and three main categories of theories on how selection works were proposed:space-, object-, and feature-based accounts.In terms of feature and object-based accounts, evolving from the first theory of selection, Broadbent’s (1958) “filter theory”, and seminal work on research methods by (Luce, 1959) theoretical frameworks as well as experimental research methods have evolved in different directions.Two of the main developments can be characterized as process- and parameter-based with the Feature Integration Theory (FIT; Treisman et al.,1980) and the Theory of Visual Attention (TVA; Bundesen, 1990) representing instances of the first and second category, respectively. FIT and its sibling Guided Search (GS; Wolfe, 1994) focus on identifying the processes underlying selection. Their main distinction is in pre-attentive and attentive processes which can be likened to automatic and controlled processes. The accounts explain the seemingly effortless selection of conspicuous visual features and objects and, respectively, the limitations constraining the integration of features into coherent object representations. TVA models mechanisms of selective processing in a mathematical framework and attempts to explain and predict perceptual behaviour with the use of a limited set of parameters. FIT and GS are crucial frameworks in basic research; TVA has become the theory of choice in neuropsychology.However, both theoretical frameworks have their limitations: Feature-based accounts, specifically FIT, make strong predictions regarding the mechanisms underlying the performance in the detection of features vs.feature conjunctions. Parameter-based theories are incomplete as to the mechanisms accounting for phenomena of bottom-up control of selection such as attention capture by salient objects.The present research project aims at mapping the theoretical ground common to process- and parameter-based accounts and to develop new or adopt existing experimental procedures in order to experimentally combine the two strands of research. Experimentally, in one of several planned studies, it is proposed to transform the partial report procedure used for assessing the TVA parameters of top-down control into a singleton search task used to investigate bottom-up processes.The theoretical challenge of the Pro*Doc PhD project involves the appraisal of the different theoretical developments and the critical discussion of the possibilities and limitations of amalgamating the two accounts into a common conception. Experimentally, the development of novel research procedures integrating the paradigms is required.It is expected that the research will yield important new insights into the formalization of the mechanisms of feature extraction and extend the parameter-based description of the processes controlling selective visual attention.
Direct link to Lay Summary Last update: 21.02.2013

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Associated projects

Number Title Start Funding scheme
125205 Development of the mechanisms underlying feature-based selective perception in children and young adults 01.06.2009 Project funding (Div. I-III)

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