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Neural criticality from effective latent variables.

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This summary is machine-generated.

Brain activity may exhibit avalanche criticality, a critical state, due to coupling with multiple latent dynamical variables. This critical behavior emerges naturally without fine-tuning parameters, suggesting a general mechanism in neural systems.

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Area of Science:

  • Neuroscience
  • Complex Systems Science
  • Computational Neuroscience

Background:

  • Power laws in neural activity suggest the brain operates in a critical state, exemplified by avalanche criticality observed across various species and systems.
  • Recent studies link power laws in mouse neural populations to coupling with multiple latent dynamical variables.
  • The emergence of avalanche criticality from such latent variables remains an open question.

Approach:

  • Investigated the conditions under which latent dynamical variables induce avalanche criticality in neural population models.
  • Compared systems coupled to multiple latent variables versus those coupled to a single, quasi-static variable.
  • Analyzed the parameter space and information transfer within different avalanche regimes.

Key Points:

  • Avalanche criticality arises from neural populations coupled to multiple latent dynamical variables, without requiring fine-tuning.
  • Critical behavior is observed across a broader parameter range when coupled to multiple variables compared to a single variable.
  • Two distinct critical avalanche regimes were identified, differing in their information content about the latent variables.

Conclusions:

  • Latent dynamical variables provide a unifying mechanism for avalanche criticality in neural systems.
  • Neural systems exhibiting avalanche criticality may be effectively modeled as populations driven by a few inferable dynamical variables.
  • This finding offers insights into the fundamental principles governing brain function and information processing.