TY - JOUR
T1 - A threshold-free model of numerosity comparisons
AU - Alonso-Diaz, Santiago
AU - Cantlon, Jessica F.
AU - Piantadosi, Steven T.
N1 - Publisher Copyright:
© 2018 Alonso-Diaz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2018/4
Y1 - 2018/4
N2 - A dominant mechanism in the Judgment and Decision Making literature States that information is accumulated about each choice option until a decision threshold is met. Only after that threshold does a subject start to execute a motor response to indicate their choice. However, recent research has revealed spatial gradients in motor responses as a function of comparison difficulty as well as changes-of-mind in the middle of an action, both suggesting continued accumulation and processing of decision-related signals after the decision boundary. Here we present a formal model and supporting data from a number comparison task that a continuous motor planner, combined with a simple statistical inference scheme, can model detailed behavioral effects without assuming a threshold. This threshold-free model reproduces subjects’ sensitivity to numerical distance in reaching, accuracy, reaction time, and changes of mind. We argue that the motor system positions the effectors using an optimal biomechanical feedback controller, and continuous statistical inference on outputs from cognitive processes.
AB - A dominant mechanism in the Judgment and Decision Making literature States that information is accumulated about each choice option until a decision threshold is met. Only after that threshold does a subject start to execute a motor response to indicate their choice. However, recent research has revealed spatial gradients in motor responses as a function of comparison difficulty as well as changes-of-mind in the middle of an action, both suggesting continued accumulation and processing of decision-related signals after the decision boundary. Here we present a formal model and supporting data from a number comparison task that a continuous motor planner, combined with a simple statistical inference scheme, can model detailed behavioral effects without assuming a threshold. This threshold-free model reproduces subjects’ sensitivity to numerical distance in reaching, accuracy, reaction time, and changes of mind. We argue that the motor system positions the effectors using an optimal biomechanical feedback controller, and continuous statistical inference on outputs from cognitive processes.
UR - http://www.scopus.com/inward/record.url?scp=85045150857&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0195188
DO - 10.1371/journal.pone.0195188
M3 - Article
C2 - 29621275
AN - SCOPUS:85045150857
SN - 1932-6203
VL - 13
JO - PLoS ONE
JF - PLoS ONE
IS - 4
M1 - e0195188
ER -