Is Information in the Brain Represented in Continuous or Discrete Form?

@article{Tee2020IsII,
  title={Is Information in the Brain Represented in Continuous or Discrete Form?},
  author={James S. K. Tee and Desmond P. Taylor},
  journal={IEEE Transactions on Molecular, Biological and Multi-Scale Communications},
  year={2020},
  volume={6},
  pages={199-209}
}
The question of continuous-versus-discrete information representation in the brain is a fundamental yet unresolved question. Historically, most analyses assume a continuous representation without considering the discrete alternative. Our work explores the plausibility of both, answering the question from a communications systems engineering perspective. Using Shannon’s communications theory, we posit that information in the brain is represented in discrete form. We address this hypothesis using… 

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References

SHOWING 1-10 OF 89 REFERENCES

A Quantized Representation of Probability in the Brain

TLDR
The brain is very likely to be employing a quantized representation of probability, and this discovery demonstrates a major precision limitation of the brain’s representational and decision-making ability.

Is perception discrete or continuous?

Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition

TLDR
This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience.

The Coding Question

A Mathematical Theory of Energy Efficient Neural Computation and Communication

  • T. BergerW. Levy
  • Computer Science, Biology
    IEEE Transactions on Information Theory
  • 2010
TLDR
A neuroscience-based mathematical model of how a neuron stochastically processes data and communicates information is introduced and analyzed and largely characterize j as an engine of computation and communication.

Spikes: Exploring the Neural Code

TLDR
Spikes provides a self-contained review of relevant concepts in information theory and statistical decision theory about the representation of sensory signals in neural spike trains and a quantitative framework is used to pose precise questions about the structure of the neural code.

Visual working memory capacity: from psychophysics and neurobiology to individual differences

The Computational Theory of Mind

TLDR
CCTM holds that a suitable abstract computational model offers a literally true description of core mental processes, and argues that addressable memory gives a better model of the mind than non-addressable memory.

Single-trial spike trains in parietal cortex reveal discrete steps during decision-making

TLDR
Examination of single-trial responses in LIP using statistical methods for fitting and comparing latent dynamical spike-train models found that choice-selective neurons were better described by the stepping model, and the inferred steps carried more information about the animal’s choice than spike counts.

The magical number seven plus or minus two: some limits on our capacity for processing information.

TLDR
The theory provides us with a yardstick for calibrating the authors' stimulus materials and for measuring the performance of their subjects, and the concepts and measures provided by the theory provide a quantitative way of getting at some of these questions.
...