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Related Concept Videos

Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Decoding and perturbing decision states in real time.

Diogo Peixoto1,2,3, Jessica R Verhein4,5,6, Roozbeh Kiani7

  • 1Neurobiology Department, Stanford University, Stanford, CA, USA. dpeixoto@stanford.edu.

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|January 21, 2021
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Summary
This summary is machine-generated.

Neural activity fluctuations (DV) in macaques predict choices in real-time, offering new insights into decision-making processes and changes of mind.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Decision Making

Background:

  • Subjects integrate multiple signal samples for categorical judgments.
  • Decision variables (DV) from neural activity predict choices but within-trial fluctuations are poorly understood.

Purpose of the Study:

  • Investigate the behavioral significance of within-trial decision variable fluctuations.
  • Examine the relationship between neural activity, decision states, and behavioral choices in real-time.

Main Methods:

  • Utilized real-time neural feedback control of stimulus duration in macaques.
  • Decoded decision variables from motor cortex neural population activity.
  • Applied weak stimulus pulses to probe decision dynamics on single trials.

Main Results:

  • Within-trial DV fluctuations from motor cortex strongly predicted behavioral choices.
  • DV fluctuations were more predictive than condition-averaged DV or visual stimulus alone.
  • Observed changes in DV sign consistent with behavioral "changes of mind".

Conclusions:

  • Within-trial neural fluctuations are critical for predicting decisions in dynamic environments.
  • Demonstrated time-varying decision bounds, differentiating between decision-making models.
  • Provides a novel method for probing single-trial decision dynamics.