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Confidence Is the Bridge between Multi-stage Decisions.

Ronald van den Berg1, Ariel Zylberberg2, Roozbeh Kiani3

  • 1Computational and Biological Learning Laboratory, Department of Engineering, Cambridge University, Cambridge CB2 1PZ, UK.

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|November 22, 2016
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Summary

Subjects adjust their decision-making strategy based on confidence from previous choices. This research explores how confidence influences sequential perceptual decisions and brain mechanisms.

Keywords:
confidencedecision bounddecision-makingpsychophysicsreachingsensorimotor controlsequential choicespeed-accuracy trade-off

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Area of Science:

  • Cognitive Neuroscience
  • Decision Science

Background:

  • Complex tasks involve sequential decisions, often studied within bounded evidence accumulation frameworks.
  • Decision strategies, like speed-accuracy trade-offs, ideally adapt to prior decision accuracy, which is often unknown to the individual.

Purpose of the Study:

  • To investigate if and how confidence from a prior decision influences the strategy for a subsequent decision.
  • To explore the neural mechanisms underlying adaptive decision-making strategies.

Main Methods:

  • Subjects performed two sequential perceptual decisions, with rewards contingent on both being correct.
  • Decision-making was modeled using noisy evidence accumulation to a terminating bound.
  • Speed, accuracy, and confidence of each decision were recorded and analyzed.

Main Results:

  • Decision speed and accuracy were accurately predicted by the bounded evidence accumulation model.
  • Individuals adjusted their speed-accuracy settings for the second decision based on their confidence in the first decision.
  • This adjustment was achieved by modifying the termination bound for the second decision.

Conclusions:

  • Confidence in previous decisions plays a crucial role in adapting strategies for subsequent choices.
  • The brain exhibits flexibility in modifying decision-termination mechanisms based on confidence.
  • This provides new insights into the dynamic control of decision-making processes.