Two rhesus macaques underproduced counted actions more often than overproduced them in a numerical task
Monkeys trained to produce a set number of actions showed a systematic bias toward stopping early. The authors explain it with an accumulation-to-bound model of termination.
Researchers trained two rhesus macaques to produce an instructed number of actions in response to sign numerals or dot arrays, according to a report in Proceedings of the National Academy of Sciences pnas.org
Proceedings of the National Academy of Sciencespnas.orgOpen source ↗. Action sequences were controlled for temporal parameters. Both monkeys performed accurately with both stimulus formats.
Accuracy showed a systematic asymmetry: underproduction occurred more often than overproduction. The authors report that this runs contrary to predictions from perceptual numerosity judgments governed by Weber–Fechner scaling. Reaction times mirrored the asymmetry, with longer latencies for underproduced sequences and shorter latencies for overproduced ones.
The authors describe a stochastic accumulation-to-bound model in which a decision variable evolves across counting steps and triggers termination when a threshold is reached. According to them, the model accounts for both the accuracy and the reaction-time patterns. They interpret the results as evidence for a sequential stopping process that contributes to numerical production, linking counting behavior to general principles of decision formation.
