
Journal of Computational Neuroscience, Journal Year: 2025, Volume and Issue: unknown
Published: March 18, 2025
Abstract The brain modifies synaptic strengths to store new information via long-term potentiation (LTP) and depression (LTD). Evidence has mounted that plasticity is controlled concentrations of calcium ([Ca 2+ ]) in postsynaptic dendritic spines. Several mathematical models describe this phenomenon, including those Shouval, Bear, Cooper (SBC) (Shouval et al., 2002, 2010) Graupner Brunel (GB) (Graupner & Brunel, 2012). Here we suggest a generalized version the SBC GB models, fixed point – learning rate (FPLR) framework, where [Ca ] specifies toward which weight approaches asymptotically at ]-dependent rate. FPLR framework offers straightforward phenomenological interpretation calcium-based plasticity: concentration tells it going how quickly goes there. can flexibly incorporate various experimental findings, existence multiple regions no occurs, or observed experimentally cerebellar Purkinje cells, directionality changes reversed relative cortical hippocampal neurons. We also modeling approach captures dependency late-phase stabilization on protein synthesis. demonstrate due asymptotic nature rule, plastic induced by frequency- spike-timing-dependent protocols are weight-dependent. Finally, show explain weight-dependence behavioral time scale (BTSP).
Language: Английский