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Related Experiment Video

Updated: May 12, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

Automaticity and control in prospective memory: a computational model.

Sam J Gilbert1, Nicola Hadjipavlou, Matthieu Raoelison

  • 1Institute of Cognitive Neuroscience, University College London, London, United Kingdom. sam.gilbert@ucl.ac.uk

Plos One
|April 5, 2013
PubMed
Summary
This summary is machine-generated.

Prospective memory (PM), remembering to perform intended actions, can be triggered by environmental cues or deliberate monitoring. Our model shows PM arises from both bottom-up cue detection and top-down attention.

Related Experiment Videos

Last Updated: May 12, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

Area of Science:

  • Cognitive Psychology
  • Computational Neuroscience

Background:

  • Prospective memory (PM) involves executing delayed intentions, often triggered by specific cues.
  • A key debate exists whether PM requires active monitoring or can be automatically triggered by perceptual input.

Purpose of the Study:

  • To present a computational model explaining PM responding via direct cue triggering.
  • To investigate the interplay between bottom-up and top-down processes in PM.

Main Methods:

  • Utilized a parallel distributed processing (interactive activation) framework for a computational model.
  • Developed a model where PM responses are triggered by perceptual input spreading activation.
  • Tested model predictions against existing empirical data and conducted new experiments.

Main Results:

  • The model successfully replicated various PM paradigm findings, including intention superiority and effects on ongoing task performance.
  • Novel predictions regarding stimulus degradation and response time distributions were empirically validated.
  • Demonstrated that both bottom-up perceptual triggering and top-down monitoring contribute to PM.

Conclusions:

  • PM performance results from an interaction between bottom-up cue processing and top-down attentional monitoring.
  • The model provides a framework for understanding intention encoding, deactivation, and potential neuroimaging correlates.