Two-factor synaptic plasticity enables memory consolidation during neuronal burst firing
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ID: 317097
2026
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Abstract
Abstract How can brain circuits remain plastic enough to encode new information while still stabilizing synaptic changes that support long-term memory? Many circuits switch between tonic spiking, which encodes external inputs, and burst firing, which is generated collectively; yet how these state changes interact with synaptic plasticity to support consolidation remains unclear. Here, we ask whether burst epochs can provide a minimal, mechanistically interpretable route to stabilizing memories encoded during tonic firing. We introduce a two-factor synaptic plasticity rule in a conductance-based spiking network that switches robustly between tonic and burst regimes. The effective synaptic strength is expressed as the product of two factors: a primary, flexible factor updated by a Hebbian mechanism, and a secondary factor that captures stabilizing processes. The secondary factor is adjusted according to the rate of change of the primary factor. In a pattern recognition case study, the network encodes new inputs during tonic firing and undergoes burst epochs. This two-factor rule stabilizes previously learned patterns, integrates information across samples to support generalization, and improves robustness to noise. Ablation experiments show that these outcomes require a synergy between neural bursting activity and the two-factor plasticity rule: blocking secondary plasticity prevents stable retention, replacing bursts with quiescence leads to fading memories, and replacing bursts with additional tonic firing causes interference and noise sensitivity. Finally, a signal-to-noise ratio analysis across tonic–burst cycles identifies parameter regimes in which bursts either sharpen or weaken synaptic representations, consistent with consolidation or pruning, respectively.
| Reference Key |
openalex_W7164503266
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| Authors | Kathleen Jacquerie, Danil Tyulmankov, Pierre Sacré, Guillaume Drion |
| Journal | PNAS nexus |
| Year | 2026 |
| DOI |
10.1093/pnasnexus/pgag213
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| URL | |
| Keywords | Keywords not found |
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