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Memory is the retention of information or experiences over time, facilitated through three main processes: encoding, storage, and retrieval. Encoding is the process of inputting information into the memory system. For instance, when listening to a lecture, watching a play, reading a book, or having a conversation, the brain is actively encoding information. This initial stage involves transforming sensory input into a form that can be processed and stored by the brain. Various factors, such as...
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Memory and Markov Blankets.

Thomas Parr1, Lancelot Da Costa1,2, Conor Heins3,4,5,6

  • 1Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK.

Entropy (Basel, Switzerland)
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Summary
This summary is machine-generated.

This study resolves the paradox of memory in biological systems by distinguishing steady-state dependencies from time-dependent dynamics. Conditional independence does not preclude memory, even in systems with a Markov blanket.

Keywords:
Laplace assumptionMarkov blanketconditional dependencedensity dynamicsmemorystochastic

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Area of Science:

  • Theoretical Biology
  • Computational Neuroscience
  • Information Theory

Background:

  • Random dynamical systems, such as the brain, model their environments through steady states.
  • A Markov blanket (conditioning set) creates conditional independence between a system and its surroundings, enabling vicarious synchrony.
  • This raises a paradox: how can systems possess memory if all dependencies are mediated by the Markov blanket?

Purpose of the Study:

  • To resolve the apparent paradox between conditional independence and mnemonic capacity in biological systems.
  • To demonstrate that conditional independence does not preclude memory.
  • To investigate the time scales of information 'forgetting' in stochastic systems.

Main Methods:

  • Distinguishing dependencies implied by steady-state density from time-dependent system dynamics.
  • Analyzing the density dynamics conditioned upon previous system configurations.
  • Numerical analysis of an example system with a steady-state density possessing a Markov blanket.

Main Results:

  • Conditional independence, as defined by a Markov blanket, does not inherently prevent memory.
  • The apparent paradox is resolved by considering the temporal dynamics of information decay.
  • The study explores factors influencing the time required for stochastic systems to lose memory of initial conditions.

Conclusions:

  • Memory in biological systems is compatible with the principles of conditional independence and Markov blankets.
  • Understanding the temporal dynamics of stochastic systems is crucial for explaining memory.
  • The findings have implications for memory in cognitive systems.