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Updated: May 5, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Autoshaped impulsivity: Some explorations with a neural network model
Miguel Aguayo-Mendoza1, Jonathan Buriticá1, José E Burgos1
1Centro de Estudios e Investigación en Comportamiento, University of Guadalajara, Mexico.
Abstract:
This study evaluated the effect of delay and magnitude of reinforcement in Pavlovian contingencies, extending the understanding of the phenomenon of autoshaped impulsivity as described in Alcalá's thesis (2017) and Burgos and García-Leal (2015). The effects of adding a trace interval were analyzed on the maintained responses of impulsive choice, seen as the preference of a small and immediate reinforcer over a larger and delayed one, and the role of the contextual unit, as well as the inhibitory units according to the Diffuse Discrepancy Model. In the Simulation, the model with inhibitory units was used, trained in two signals with different delays and reinforcement magnitudes, and subsequently presented concurrently in choice tasks without reinforcement nor learning, using an ABA within-subject design. In general, the DD model successfully simulated the phenomenon of autoshaped impulsivity, consistent with studies from Alcalá's thesis (2017), Burgos and García-Leal (2015), and Picker and Poling (1982). It also predicted the elimination of this effect (autoshaped impulsivity) after introducing a trace interval. The observed results and their implications are discussed, as well as possible future studies with animals and humans.
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