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Related Experiment Videos

How to measure the information gained from one symbol.

M R DeWeese1, M Meister

  • 1The Salk Institute, Sloan Center, La Jolla, CA 92037, USA. deweese@salk.edu

Network (Bristol, England)
|March 1, 2000
PubMed
Summary

Researchers found a flaw in how neural information is measured, as it doesn't add up correctly. They propose a new, additive measure for neuronal response information, crucial for understanding brain codes.

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Area of Science:

  • Computational Neuroscience
  • Information Theory
  • Systems Neuroscience

Background:

  • Information theory is widely used to quantify neuronal representation of stimuli and behavior.
  • A key question is determining the information conveyed by neuronal responses.
  • Current methods for measuring accumulated information in neural activity lack additivity.

Purpose of the Study:

  • To identify and address the non-additive flaw in the commonly used measure of neuronal information.
  • To propose and validate a novel, additive measure for information per neuronal observation.
  • To re-interpret existing findings on neural coding using the new additive measure.

Main Methods:

  • Theoretical analysis of information measures in the context of neural coding.
  • Development of a new definition for information per observation that guarantees additivity.
  • Empirical validation using electrophysiological recordings of visual responses from primate cortical neurons.

Main Results:

  • The standard definition of accumulated information in neural activity is shown to be non-additive.
  • A unique, additive measure for information per observation is derived and proven.
  • Application to primate visual cortex data reveals distinct interpretations of neural coding efficiency.

Conclusions:

  • The proposed additive measure is the only definition satisfying this critical property for analyzing population codes.
  • The findings suggest that neurons, particularly those studied in primate visual cortex, operate substantially below their theoretical information capacity.
  • This work provides a more accurate framework for quantifying information processing in the brain.

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