ArticleNetwork neuroscience (Cambridge, Mass.)2019
Optimal modularity and memory capacity of neural reservoirs.
Article in Network neuroscience (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Neuromorphic hierarchical modular reservoirs.Nature communications · 2026Article
- Association-sensory spatiotemporal hierarchy and functional gradient-regularised recurrent neural network with implications for schizophrenia.NPJ systems biology and applications · 2026Article
- Competitive interactions shape mammalian brain network dynamics and computation.Nature neuroscience · 2026Article
- Boosting reservoir computing with brain-inspired adaptive control of E-I balance.Nature communications · 2025Article
- Brain-inspired wiring economics for artificial neural networks.PNAS nexus · 2025Article
- Emergence and reconfiguration of modular structure for artificial neural networks during continual familiarity detection.Science advances · 2024Article
- The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition.Cerebral cortex (New York, N.Y. : 1991) · 2024Review
- Brain-inspired modular echo state network for EEG-based emotion recognition.Frontiers in neuroscience · 2024Article
- Segregation-to-integration transformation model of memory evolution.Network neuroscience (Cambridge, Mass.) · 2024Article
- Reservoir computing using self-sustained oscillations in a locally connected neural network.Scientific reports · 2023Article
- Biological neurons act as generalization filters in reservoir computing.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A natural cortical axis connecting the outside and inside of the human brain.Network neuroscience (Cambridge, Mass.) · 2022Article
- A Connectomic Hypothesis for the Hominization of the Brain.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Network architectures supporting learnability.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Article
- Optimal Interplay between Synaptic Strengths and Network Structure Enhances Activity Fluctuations and Information Propagation in Hierarchical Modular Networks.Brain sciences · 2020Article
- Long-range temporal correlations in scale-free neuromorphic networks.Network neuroscience (Cambridge, Mass.) · 2020Article
- Optimal modularity and memory capacity of neural reservoirs.Network neuroscience (Cambridge, Mass.) · 2019Article
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Authors and funding
3 authors.
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Abstract
The neural network is a powerful computing framework that has been exploited by biological evolution and by humans for solving diverse problems. Although the computational capabilities of neural networks are determined by their structure, the current understanding of the relationships between a neural network's architecture and function is still primitive. Here we reveal that a neural network's modular architecture plays a vital role in determining the neural dynamics and memory performance of the network of threshold neurons. In particular, we demonstrate that there exists an optimal modularity for memory performance, where a balance between local cohesion and global connectivity is established, allowing optimally modular networks to remember longer. Our results suggest that insights from dynamical analysis of neural networks and information-spreading processes can be leveraged to better design neural networks and may shed light on the brain's modular organization.
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