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A Quantized Representation of Probability in the Brain.

James Tee1, Desmond P Taylor2

  • 1Department of Psychology, New York University. He is now with the Communications Research Group, Department of Electrical & Computer Engineering, University of Canterbury, Private Bag 4800, Christchurch 8020, New Zealand.

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|March 22, 2021
PubMed
Summary
This summary is machine-generated.

The brain likely uses discrete, quantized probability representations, not continuous numbers. This finding suggests a fundamental precision limit in how the brain processes probability and makes decisions.

Keywords:
Brain modelingbehavioral sciencecognitive scienceinformation representationprobabilityquantization

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Area of Science:

  • Cognitive Neuroscience
  • Information Theory
  • Decision Science

Background:

  • The brain's representation of probability is traditionally assumed to be continuous.
  • Finite neural resources make continuous probability representation potentially implausible.
  • Quantization, a process of encoding information into discrete categories, offers an alternative model.

Purpose of the Study:

  • To investigate if the brain employs quantized (discrete) probability representations.
  • To develop and test a novel quantized probability distortion function.
  • To challenge the assumption of continuous probability processing in the brain.

Main Methods:

  • Development of three conjunction probability gambling tasks.
  • Application of information theoretic concepts to model probability representation.
  • Analysis of participant choices to identify best-fit models (quantized vs. continuous).

Main Results:

  • Strong evidence supports a quantized representation of probability in the brain.
  • 78% of participants (59/76) best fit 4-bit quantized models over continuous models.
  • Observed indifference to distinct probabilities suggests probability ranges are lumped into categories.

Conclusions:

  • The brain likely utilizes a quantized, discrete system for representing probability.
  • This quantized representation imposes a significant precision limitation on neural decision-making.
  • The findings necessitate a re-evaluation of how probability is encoded and processed in the brain.