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Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test.

van Ravenzwaaij D, Mulder MJ, Tuerlinckx F, Wagenmakers EJ - Front Psychol (2012)

Bottom Line: In this model, prior information or advance knowledge about the correct response can manifest itself as a shift in starting point or as a shift in drift rate criterion.These two mechanisms lead to qualitatively different choice behavior.Firstly, we demonstrate that optimal behavior for biased decision problems is prescribed by a shift in starting point, irrespective of variability in stimulus difficulty.

View Article: PubMed Central - PubMed

Affiliation: Psychological Methods, University of Amsterdam Amsterdam, Netherlands.

ABSTRACT
In speeded two-choice tasks, optimal performance is prescribed by the drift diffusion model. In this model, prior information or advance knowledge about the correct response can manifest itself as a shift in starting point or as a shift in drift rate criterion. These two mechanisms lead to qualitatively different choice behavior. Analyses of optimal performance (i.e., Bogacz et al., 2006; Hanks et al., 2011) have suggested that bias should manifest itself in starting point when difficulty is fixed over trials, whereas bias should (additionally) manifest itself in drift rate criterion when difficulty is variable over trials. In this article, we challenge the claim that a shift in drift criterion is necessary to perform optimally in a biased decision environment with variable stimulus difficulty. This paper consists of two parts. Firstly, we demonstrate that optimal behavior for biased decision problems is prescribed by a shift in starting point, irrespective of variability in stimulus difficulty. Secondly, we present empirical data which show that decision makers do not adopt different strategies when dealing with bias in conditions of fixed or variable across-trial stimulus difficulty. We also perform a test of specific influence for drift rate variability.

No MeSH data available.


Schematic representation of bias due to a shift in starting point z (top panel) or a shift in drift rate criterion vc (bottom panel). The gray lines represent neutral stimuli for comparison.
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Figure 2: Schematic representation of bias due to a shift in starting point z (top panel) or a shift in drift rate criterion vc (bottom panel). The gray lines represent neutral stimuli for comparison.

Mentions: Recall from the introduction that decision makers may implement bias in two ways. A decision maker may decide prior to the start of the decision process that less evidence is required for a response in favor of the biased alternative than for the non-biased alternative. This type of bias, which we call prior bias, is manifested in the DDM as a shift in starting point (see the top panel of Figure 2, see also Ratcliff, 1985; Ratcliff and McKoon, 2008; Mulder et al., 2012). Prior bias is most pronounced at the onset of the decision process, but dissipates over time due to the effects of the diffusion noise s. Edwards (1965) showed that when across-trial stimulus difficulty is fixed, it is optimal to shift the starting point an amount proportional to the odds of the prior probabilities of each response alternative.


Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test.

van Ravenzwaaij D, Mulder MJ, Tuerlinckx F, Wagenmakers EJ - Front Psychol (2012)

Schematic representation of bias due to a shift in starting point z (top panel) or a shift in drift rate criterion vc (bottom panel). The gray lines represent neutral stimuli for comparison.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3351677&req=5

Figure 2: Schematic representation of bias due to a shift in starting point z (top panel) or a shift in drift rate criterion vc (bottom panel). The gray lines represent neutral stimuli for comparison.
Mentions: Recall from the introduction that decision makers may implement bias in two ways. A decision maker may decide prior to the start of the decision process that less evidence is required for a response in favor of the biased alternative than for the non-biased alternative. This type of bias, which we call prior bias, is manifested in the DDM as a shift in starting point (see the top panel of Figure 2, see also Ratcliff, 1985; Ratcliff and McKoon, 2008; Mulder et al., 2012). Prior bias is most pronounced at the onset of the decision process, but dissipates over time due to the effects of the diffusion noise s. Edwards (1965) showed that when across-trial stimulus difficulty is fixed, it is optimal to shift the starting point an amount proportional to the odds of the prior probabilities of each response alternative.

Bottom Line: In this model, prior information or advance knowledge about the correct response can manifest itself as a shift in starting point or as a shift in drift rate criterion.These two mechanisms lead to qualitatively different choice behavior.Firstly, we demonstrate that optimal behavior for biased decision problems is prescribed by a shift in starting point, irrespective of variability in stimulus difficulty.

View Article: PubMed Central - PubMed

Affiliation: Psychological Methods, University of Amsterdam Amsterdam, Netherlands.

ABSTRACT
In speeded two-choice tasks, optimal performance is prescribed by the drift diffusion model. In this model, prior information or advance knowledge about the correct response can manifest itself as a shift in starting point or as a shift in drift rate criterion. These two mechanisms lead to qualitatively different choice behavior. Analyses of optimal performance (i.e., Bogacz et al., 2006; Hanks et al., 2011) have suggested that bias should manifest itself in starting point when difficulty is fixed over trials, whereas bias should (additionally) manifest itself in drift rate criterion when difficulty is variable over trials. In this article, we challenge the claim that a shift in drift criterion is necessary to perform optimally in a biased decision environment with variable stimulus difficulty. This paper consists of two parts. Firstly, we demonstrate that optimal behavior for biased decision problems is prescribed by a shift in starting point, irrespective of variability in stimulus difficulty. Secondly, we present empirical data which show that decision makers do not adopt different strategies when dealing with bias in conditions of fixed or variable across-trial stimulus difficulty. We also perform a test of specific influence for drift rate variability.

No MeSH data available.