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Neurally-informed modelling of static and dynamic decision biases

Ms. L. Alexandra Martinez Rodriguez
University College Dublin ~ School of Electrical and Electronic Engineering
Elaine A. Corbett
Trinity College Dublin, Ireland
Redmond G. O'Connell
Trinity College Dublin, Ireland
Simon P. Kelly
University College Dublin, Ireland

Different accounts have been developed to explain the mechanisms underlying value biases during perceptual decision-making, within the model framework of bounded accumulation. The starting point bias account suggests a shift in the starting point of evidence accumulation, in the direction of the more valuable alternative. The drift rate bias account suggests that the mean rate of accumulation is steepened for the more valuable alternative. While most studies have supported a starting point bias (SPB) approach, recent work (Afacan-Seref et al., 2018) suggests that drift rate biases (DRB) may also be applied in certain circumstances. Here, we used human EEG signatures of competitive motor preparation to construct a cognitive decision model that can explain the biasing mechanisms through which participants perform a value-biased orientation discrimination task under a strict deadline. Motor preparation dynamics showed signs of a value bias that emerged prior to evidence onset and increased steadily with time. Accordingly, we constructed a model that included an anticipatory dynamic urgency signal towards the High Value alternative. This model provided a better fit to behaviour than models with either a starting point or a drift rate bias but no anticipatory dynamics. These results point to a role for value-modulated, anticipatory motor preparation in fast-paced decision-making tasks, and suggest a unitary mechanism that can generate both static (starting point) and dynamic (drift rate) biases at the same time.


Very interesting work! I was wondering how your conclusions depend on your choice of outcome variable. Since the LRP is close to the motor system, it is not surprising that it would locate the bias at the motor level. What if instead of looking at the LRP you look at the LPP or theta oscillations? Does that lead to similar conclusions about the neu...

Dr. Marieke Van Vugt 1 comment
Cite this as:

Martinez Rodriguez, L., Corbett, E., O'Connell, R., & Kelly, S. (2020, July). Neurally-informed modelling of static and dynamic decision biases. Paper presented at Virtual MathPsych/ICCM 2020. Via