ArticleJournal of neurophysiology2019
Stable memory and computation in randomly rewiring neural networks.
Article in Journal of neurophysiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Statistics of cortical representational drift can enable robust readout.PLoS computational biology · 2026Article
- Behavioral Timescale Synaptic Plasticity: A Burst in the Field of Learning and Memory.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Review
- Antifragile control systems in neuronal processing: a sensorimotor perspective.Biological cybernetics · 2025Review
- Self-healing codes: How stable neural populations can track continually reconfiguring neural representations.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Training a spiking neuronal network model of visual-motor cortex to play a virtual racket-ball game using reinforcement learning.PloS one · 2022Article
- Drifting assemblies for persistent memory: Neuron transitions and unsupervised compensation.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Article
- A computational grid-to-place-cell transformation model indicates a synaptic driver of place cell impairment in early-stage Alzheimer's Disease.PLoS computational biology · 2021Article
- Identification of Neuronal Pentraxins as Synaptic Binding Partners of C1q and the Involvement of NP1 in Synaptic Pruning in Adult Mice.Frontiers in immunology · 2020Article
- Aversive conditioning in the tardigrade, Dactylobiotus dispar.Journal of experimental psychology. Animal learning and cognition · 2019Article
- Self-organized reactivation maintains and reinforces memories despite synaptic turnover.eLife · 2019Article
- Hippocampal-Cortical Memory Trace Transfer and Reactivation Through Cell-Specific Stimulus and Spontaneous Background Noise.Frontiers in computational neuroscience · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Our brains must maintain a representation of the world over a period of time much longer than the typical lifetime of the biological components producing that representation. For example, recent research suggests that dendritic spines in the adult mouse hippocampus are transient with an average lifetime of ~10 days. If this is true, and if turnover is equally likely for all spines, ~95% of excitatory synapses onto a particular neuron will turn over within 30 days; however, a neuron's receptive field can be relatively stable over this period. Here, we use computational modeling to ask how memories can persist in neural circuits such as the hippocampus and visual cortex in the face of synapse turnover. We demonstrate that Hebbian plasticity during replay of presynaptic activity patterns can integrate newly formed synapses into pre-existing memories. Furthermore, we find that Hebbian plasticity during replay is sufficient to stabilize the receptive fields of hippocampal place cells in a model of the grid-cell-to-place-cell transformation in CA1 and of orientation-selective cells in a model of the center-surround-to-simple-cell transformation in V1. Together, these data suggest that a simple plasticity rule, correlative Hebbian plasticity of synaptic strengths, is sufficient to preserve neural representations in the face of synapse turnover, even in the absence of activity-dependent structural plasticity.
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Registered trials
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.