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Neurogenesis and Regeneration of Nervous Tissue

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In the CNS, neurogenesis, the birth of new neurons from stem cells, is limited to the hippocampus in adults. In other regions of the brain and spinal cord, neurogenesis is almost non-existent due to inhibitory influences from neuroglia, especially oligodendrocytes, and the absence of growth-stimulating cues. The myelin produced by oligodendrocytes in the CNS inhibits neuronal regeneration. Furthermore, astrocytes proliferate rapidly after neuronal damage, forming scar tissue that physically...

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An Invasive Method for the Activation of the Mouse Dentate Gyrus by High-frequency Stimulation

An Invasive Method for the Activation of the Mouse Dentate Gyrus by High-frequency Stimulation

Published on: June 2, 2018

Additive neurogenesis as a strategy for avoiding interference in a sparsely-coding dentate gyrus.

Peter A Appleby¹, Laurenz Wiskott

¹Institute for Theoretical Biology, Humboldt Universität zu Berlin, Berlin 10115, Germany. p.appleby@biologie.hu-berlin.de

Network (Bristol, England)

|September 5, 2009

Summary

Additive neurogenesis in neural networks enhances memory adaptation. Growing networks adapt to changing environments while preserving past information, outperforming fixed-size networks.

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Area of Science:

Computational neuroscience
Neurobiology

Background:

Adult neurogenesis in the hippocampus is proposed to play a computational role in memory.
Previous models showed additive neurogenesis in feedforward networks aids adaptation to changing environments.

Purpose of the Study:

To explicitly evaluate the hypothesis that additive neurogenesis serves a similar computational role in the hippocampus.
To compare additive neurogenesis with neuronal turnover in a simplified hippocampal memory model.

Main Methods:

Developed a simplified hippocampal memory model incorporating entorhinal cortex to dentate gyrus divergence and sparse coding.
Evaluated two adaptation strategies: neuronal turnover (fixed size, unit replacement) and additive neurogenesis (network growth).
Quantified network performance across adaptation levels from zero to full adaptation.

Main Results:

Additive neurogenesis consistently outperformed neuronal turnover.
Additive neurogenesis enabled networks to adapt to new input statistics.
Additive neurogenesis preserved representations of earlier environments.

Conclusions:

Additive neurogenesis is a superior strategy for neural network adaptation in memory tasks compared to neuronal turnover.
The findings support the hypothesis that adult neurogenesis in the dentate gyrus facilitates adaptive memory processing.