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Brain computation by assemblies of neurons.

Christos H Papadimitriou1, Santosh S Vempala2, Daniel Mitropolsky3

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Neural assemblies, large neuron groups, can perform cognitive functions like memory and language. This study introduces the Assembly Calculus, a computational model showing how these assemblies could enable complex computations in the brain.

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Area of Science:

  • Computational neuroscience
  • Cognitive science
  • Systems neuroscience

Background:

  • Neural assemblies are hypothesized to store cognitive information.
  • Understanding their computational capabilities is crucial for neuroscience.
  • Existing models often focus on lower (synaptic) or higher (whole-brain) levels.

Purpose of the Study:

  • To identify and analyze operations performed by neural assemblies.
  • To propose a computational model, the Assembly Calculus, based on these operations.
  • To investigate the potential of this model for higher cognitive functions.

Main Methods:

  • Analytical derivations and computational simulations.
  • Modeling generic, randomly connected neuronal populations with Hebbian plasticity and inhibition.
  • Developing the Assembly Calculus as an intermediate-level computational framework.

Main Results:

  • A repertoire of assembly operations was identified and shown to be realizable by neuronal networks.
  • The Assembly Calculus was established as a computational model.
  • The model demonstrates potential for arbitrary computations.

Conclusions:

  • Neural assemblies and their operations provide a viable computational framework for the brain.
  • The Assembly Calculus offers a potential explanation for higher cognitive functions like reasoning and language.
  • A brain architecture for syntactic language processing based on assemblies is proposed and aligns with experimental data.