Bella Z. Veksler, Rachel Boyd, Christopher W. Myers, Glenn Gunzelmann, Hansjörg Neth, Wayne D. Gray
Abstract: Visual working memory (VWM) is a construct hypothesized to store a small amount of accurate perceptual information that can be brought to bear on a task. Much research concerns the construct’s capacity and the precision of the information stored. Two prominent theories of VWM representation have emerged: slot-based and continuous-resource mechanisms. Prior modeling work suggests that a continuous resource that varies over trials with variable capacity and a potential to make localization errors best accounts for the empirical data. Questions remain regarding the variability in VWM capacity and precision. Using a novel eye-tracking paradigm, we demonstrate that VWM facilitates search and exhibits effects of fixation frequency and recency, particularly for prior targets. Whereas slot-based memory models cannot account for the human data, a novel continuous-resource model does capture the behavioral and eye tracking data, and identifies the relevant resource as item activation.
|‘Can you do Addition?’ the White Queen asked.
‘What’s one and one and one and one and one
and one and one and one and one and one?’
‘I don’t know,’ said Alice. ‘I lost count.’
|Lewis Carroll, Through the Looking-Glass, Chapter IX.|
[Copyright neth.de, 1999–2014]:
Hans Neth and Steve Payne (2011): Interactive coin addition: How hands can help us think. Paper presented at CogSci2011.
Hansjörg Neth, Stephen J. Payne
|The truths about numbers are in us; but still we learn them.|
|G.W. Leibniz (1765), Nouveaux essais sur l’entendement humain, p. 85|
[Copyright neth.de, 2010]:
Helen De Cruz, Hans Neth, Dirk Schlimm (2010). The cognitive basis of arithmetic.
Overview: Arithmetic is the theory of the natural numbers and one of the oldest areas of mathematics. Since almost all other mathematical theories make use of numbers in some way or other, arithmetic is also one of the most fundamental theories of mathematics. But numbers are not just abstract entities that are subject to mathematical ruminations — they are represented, used, embodied, and manipulated in order to achieve many different goals, e.g., to count or denote the size of a collection of objects, to trade goods, to balance bank accounts, or to play the lottery. Consequently, numbers are both abstract and intimately connected to language and to our interactions with the world. In the present paper we provide an overview of research that has addressed the question of how animals and humans learn, represent, and process numbers.
|If an organism is confronted with the problem of behaving approximately rationally,
or adaptively, in a particular environment, the kinds of simplifications that are suitable
may depend not only on the characteristics—sensory, neural, and other—of the organism,
but equally on the nature of the environment.
|H.A. Simon (1956), Rational choice and the structure of the environment, p. 130|
[Copyright neth.de, 2008]:
Hans Neth, Sunny Khemlani, Wayne Gray (2008)
Feedback design for the control of a dynamic multitasking system: Dissociating outcome feedback from control feedback. Human Factors Journal, 2008.
Objective: We distinguish outcome feedback from control feedback to show that suboptimal performance in a dynamic multitasking system may be caused by limits inherent to the information provided rather than human resource limits.