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A model of individualized canonical microcircuits supporting cognitive operations
Tim Kunze1,2, Andre D H Peterson3, Jens Haueisen1,2
1Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Plos One
|December 5, 2017
Summary
This study introduces a novel canonical microcircuit model supporting gating and working memory. This framework aids in building realistic neural networks for cognitive functions like language processing.
Area of Science:
- Computational Neuroscience
- Theoretical Neuroscience
- Cognitive Science
Background:
- Cognitive functions rely on distributed networks of canonical microcircuits.
- Understanding these microcircuits is key to modeling brain operations.
Purpose of the Study:
- Propose a novel canonical microcircuit model.
- Investigate its computational capabilities and dynamical behavior.
- Link microcircuit dynamics to cognitive processes.
Main Methods:
- Theoretical modeling of a canonical microcircuit.
- Bifurcation analysis to study dynamical behavior.
- Network construction of interacting microcircuits.
Main Results:
- The proposed model supports gating and working memory.
- Dynamical behavior is dependent on excitation-inhibition balance and feedback architecture.
- Networks of these microcircuits can form spatiotemporal sequences for syntax parsing.
Conclusions:
- The novel canonical microcircuit model offers a framework for understanding cognitive functions.
- Enables the construction of biologically realistic neural networks.
- Provides insights into neural mechanisms of language comprehension.
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