A model for structured information representation in Neural Networks of the Brain

Michael Günther Müller, Christos H. Papadimitriou, Wolfgang Maass, Robert Legenstein*

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Humans can reason at an abstract level and structure information into abstract categories, but the underlying neural processes have remained unknown. Recent experimental data provide the hint that this is likely to involve specific subareas of the brain from which structural information can be decoded. Based on this data, we introduce the concept of assembly projections, a general principle for attaching structural information to content in generic networks of spiking neurons. According to the assembly projections principle, structure-encoding assemblies emerge and are dynamically attached to content representations through Hebbian plasticity mechanisms. This model provides the basis for explaining a number of experimental data and provides a basis for modeling abstract computational operations of the brain.
Original languageEnglish
Article numberENEURO.0533-19.2020
Number of pages17
JournaleNeuro
Volume7
Issue number3
DOIs
Publication statusPublished - 7 May 2020

Keywords

  • assemblies
  • cognition
  • factorized codes
  • Hebbian plasticity
  • spiking neural networks
  • structurl knowledge

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