ArticlePLoS computational biology2015
Stability of Neuronal Networks with Homeostatic Regulation.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 35 citations in OpenAlex.
- Homeostatic dendritic neuron based on co-integrated volatile and non-volatile memristors for neuromorphic processing.Nature communications · 2026Article
- Dynamic recovery of piriform cortex function and its impact on cognitive processing speed following mild COVID-19.BMC neurology · 2026Article
- Synaptic homeostasis transiently leverages Hebbian mechanisms for a multiphasic response to inactivity.Cell reports · 2024Article
- Time-dependent homeostatic mechanisms underlie brain-derived neurotrophic factor action on neural circuitry.Communications biology · 2023Article
- Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education.eNeuro · 2023Article
- Internet-connected cortical organoids for project-based stem cell and neuroscience education.bioRxiv : the preprint server for biology · 2023Article
- Sub-Optimality of the Early Visual System Explained Through Biologically Plausible Plasticity.Frontiers in neuroscience · 2021Article
- Removing uncertainty in neural networks.Cognitive neurodynamics · 2020Article
- Training and Spontaneous Reinforcement of Neuronal Assemblies by Spike Timing Plasticity.Cerebral cortex (New York, N.Y. : 1991) · 2019Article
- Chaos in homeostatically regulated neural systems.Chaos (Woodbury, N.Y.) · 2018Article
- Landau-Ginzburg theory of cortex dynamics: Scale-free avalanches emerge at the edge of synchronization.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- The dialectic of Hebb and homeostasis.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Review
- Hebbian plasticity requires compensatory processes on multiple timescales.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Review
- Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurons are equipped with homeostatic mechanisms that counteract long-term perturbations of their average activity and thereby keep neurons in a healthy and information-rich operating regime. While homeostasis is believed to be crucial for neural function, a systematic analysis of homeostatic control has largely been lacking. The analysis presented here analyses the necessary conditions for stable homeostatic control. We consider networks of neurons with homeostasis and show that homeostatic control that is stable for single neurons, can destabilize activity in otherwise stable recurrent networks leading to strong non-abating oscillations in the activity. This instability can be prevented by slowing down the homeostatic control. The stronger the network recurrence, the slower the homeostasis has to be. Next, we consider how non-linearities in the neural activation function affect these constraints. Finally, we consider the case that homeostatic feedback is mediated via a cascade of multiple intermediate stages. Counter-intuitively, the addition of extra stages in the homeostatic control loop further destabilizes activity in single neurons and networks. Our theoretical framework for homeostasis thus reveals previously unconsidered constraints on homeostasis in biological networks, and identifies conditions that require the slow time-constants of homeostatic regulation observed experimentally.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.