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Local dynamics in decision making: The evolution of preference within and across decisions.

O'Hora D, Dale R, Piiroinen PT, Connolly F - Sci Rep (2013)

Bottom Line: Within decisions, perceived alternatives compete until one is preferred.These decision spaces evolved through the experiments, as participants learned which options to choose.This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.

View Article: PubMed Central - PubMed

Affiliation: School of Psychology, National University of Ireland, Galway, University Road, Galway, Ireland. denis.ohora@nuigalway.ie

ABSTRACT
Within decisions, perceived alternatives compete until one is preferred. Across decisions, the playing field on which these alternatives compete evolves to favor certain alternatives. Mouse cursor trajectories provide rich continuous information related to such cognitive processes during decision making. In three experiments, participants learned to choose symbols to earn points in a discrimination learning paradigm and the cursor trajectories of their responses were recorded. Decisions between two choices that earned equally high-point rewards exhibited far less competition than decisions between choices that earned equally low-point rewards. Using positional coordinates in the trajectories, it was possible to infer a potential field in which the choice locations occupied areas of minimal potential. These decision spaces evolved through the experiments, as participants learned which options to choose. This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.

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Interpolated mean trajectories and decision spaces for blocks of 12 trials within each experiment.(A) The left column depicts the 20% trimmed mean trajectories for the final 18 trials in each experiment. (B) Surface plots depict inferred potential fields based on momentary velocities and accelerations derived from positional coordinates within response trajectories (see text for details). The positions of the circles depicted on the decision spaces indicate the approximate starting point of trajectories (i.e., 0,0) and the colors of the circles denote the decision type.
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f4: Interpolated mean trajectories and decision spaces for blocks of 12 trials within each experiment.(A) The left column depicts the 20% trimmed mean trajectories for the final 18 trials in each experiment. (B) Surface plots depict inferred potential fields based on momentary velocities and accelerations derived from positional coordinates within response trajectories (see text for details). The positions of the circles depicted on the decision spaces indicate the approximate starting point of trajectories (i.e., 0,0) and the colors of the circles denote the decision type.

Mentions: If it is harder to make a given response because participants are experiencing conflict, then the trajectories of those responses should be more divergent: They should spend more time between choices, and in some cases may even move towards the alternative choice before making a response. We interpolated each trajectory into 101 time steps so they could be overlaid into an average plot (see2526). Trajectories of decisions to the left-hand choice were reflected in the vertical axis at the origin so that all trajectories ended at the right-hand choice for ease of comparison. The final 18 decisions were used because, by this point in all three experiments, participants were choosing the high point choice on 80% of all High/Low decisions. This is shown separately for each experiment in the lefthand column of Fig. 4. In all three experiments, trajectories during Low/Low decisions were very different to those observed in High/Low and High/High decisions. In decisions that included a high-point choice, trajectories were relatively direct, whereas trajectories in Low/Low decisions exhibited considerably larger deflections towards the unchosen symbol. These deflections suggest stronger and more persistent competition between the available response options during Low/Low decisions.


Local dynamics in decision making: The evolution of preference within and across decisions.

O'Hora D, Dale R, Piiroinen PT, Connolly F - Sci Rep (2013)

Interpolated mean trajectories and decision spaces for blocks of 12 trials within each experiment.(A) The left column depicts the 20% trimmed mean trajectories for the final 18 trials in each experiment. (B) Surface plots depict inferred potential fields based on momentary velocities and accelerations derived from positional coordinates within response trajectories (see text for details). The positions of the circles depicted on the decision spaces indicate the approximate starting point of trajectories (i.e., 0,0) and the colors of the circles denote the decision type.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3713532&req=5

f4: Interpolated mean trajectories and decision spaces for blocks of 12 trials within each experiment.(A) The left column depicts the 20% trimmed mean trajectories for the final 18 trials in each experiment. (B) Surface plots depict inferred potential fields based on momentary velocities and accelerations derived from positional coordinates within response trajectories (see text for details). The positions of the circles depicted on the decision spaces indicate the approximate starting point of trajectories (i.e., 0,0) and the colors of the circles denote the decision type.
Mentions: If it is harder to make a given response because participants are experiencing conflict, then the trajectories of those responses should be more divergent: They should spend more time between choices, and in some cases may even move towards the alternative choice before making a response. We interpolated each trajectory into 101 time steps so they could be overlaid into an average plot (see2526). Trajectories of decisions to the left-hand choice were reflected in the vertical axis at the origin so that all trajectories ended at the right-hand choice for ease of comparison. The final 18 decisions were used because, by this point in all three experiments, participants were choosing the high point choice on 80% of all High/Low decisions. This is shown separately for each experiment in the lefthand column of Fig. 4. In all three experiments, trajectories during Low/Low decisions were very different to those observed in High/Low and High/High decisions. In decisions that included a high-point choice, trajectories were relatively direct, whereas trajectories in Low/Low decisions exhibited considerably larger deflections towards the unchosen symbol. These deflections suggest stronger and more persistent competition between the available response options during Low/Low decisions.

Bottom Line: Within decisions, perceived alternatives compete until one is preferred.These decision spaces evolved through the experiments, as participants learned which options to choose.This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.

View Article: PubMed Central - PubMed

Affiliation: School of Psychology, National University of Ireland, Galway, University Road, Galway, Ireland. denis.ohora@nuigalway.ie

ABSTRACT
Within decisions, perceived alternatives compete until one is preferred. Across decisions, the playing field on which these alternatives compete evolves to favor certain alternatives. Mouse cursor trajectories provide rich continuous information related to such cognitive processes during decision making. In three experiments, participants learned to choose symbols to earn points in a discrimination learning paradigm and the cursor trajectories of their responses were recorded. Decisions between two choices that earned equally high-point rewards exhibited far less competition than decisions between choices that earned equally low-point rewards. Using positional coordinates in the trajectories, it was possible to infer a potential field in which the choice locations occupied areas of minimal potential. These decision spaces evolved through the experiments, as participants learned which options to choose. This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.

Show MeSH