Signal denoising through topographic modularity of neural circuits
- Forschungszentrum Jülich, Germany
- Radboud University Nijmegen, Netherlands
Abstract
Information from the sensory periphery is conveyed to the cortex via structured projection pathways that spatially segregate stimulus features, providing a robust and efficient encoding strategy. Beyond sensory encoding, this prominent anatomical feature extends throughout the neocortex. However, the extent to which it influences cortical processing is unclear. In this study, we combine cortical circuit modeling with network theory to demonstrate that the sharpness of topographic projections acts as a bifurcation parameter, controlling the macroscopic dynamics and representational precision across a modular network. By shifting the balance of excitation and inhibition, topographic modularity gradually increases task performance and improves the signal-to-noise ratio across the system. We demonstrate that in biologically constrained networks, such a denoising behavior is contingent on recurrent inhibition. We show that this is a robust and generic structural feature that enables a broad range of behaviorally-relevant operating regimes, and provide an in-depth theoretical analysis unravelling the dynamical principles underlying the mechanism.
Data availability
The current manuscript is a computational study, so no data have been generated for this manuscript. Modelling code can be found at https://doi.org/10.5281/zenodo.6326496.
Article and author information
Author details
Funding
Initiative and Networking Fund of the Helmholtz Association
- Barna Zajzon
- Abigail Morrison
- Renato Duarte
Helmholtz Portfolio theme Supercomputing and Modeling for the Human Brain
- Barna Zajzon
- Abigail Morrison
- Renato Duarte
Excellence Initiative of the German federal and state governments (G:(DE-82)EXS-SF-neuroIC002)
- Barna Zajzon
- Abigail Morrison
- Renato Duarte
Helmholtz Association (VH-NG-1028)
- David Dahmen
European Commission HBP (945539)
- David Dahmen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, Zajzon et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Signal denoising through topographic modularity of neural circuits
eLife 12:e77009.
https://doi.org/10.7554/eLife.77009
Further reading
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- Neuroscience
When navigating environments with changing rules, human brain circuits flexibly adapt how and where we retain information to help us achieve our immediate goals.
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- Neuroscience
Human-specific cognitive abilities depend on information processing in the cerebral cortex, where the neurons are significantly larger and their processes longer and sparser compared to rodents. We found that, in synaptically connected layer 2/3 pyramidal cells (L2/3 PCs), the delay in signal propagation from soma to soma is similar in humans and rodents. To compensate for the longer processes of neurons, membrane potential changes in human axons and/or dendrites must propagate faster. Axonal and dendritic recordings show that the propagation speed of action potentials (APs) is similar in human and rat axons, but the forward propagation of excitatory postsynaptic potentials (EPSPs) and the backward propagation of APs are 26 and 47% faster in human dendrites, respectively. Experimentally-based detailed biophysical models have shown that the key factor responsible for the accelerated EPSP propagation in human cortical dendrites is the large conductance load imposed at the soma by the large basal dendritic tree. Additionally, larger dendritic diameters and differences in cable and ion channel properties in humans contribute to enhanced signal propagation. Our integrative experimental and modeling study provides new insights into the scaling rules that help maintain information processing speed albeit the large and sparse neurons in the human cortex.
