2016/09/19 by Moritz Deger, Alexander Seeholzer, Wulfram Gerstner · 1 citation
Biochemistry, Genetics and Molecular Biology · Engineering · Neuroscience · #Advanced Memory and Neural Computing #Barrel cortex #Biology #Dendritic spine #Excitatory postsynaptic potential #Inhibitory postsynaptic potential #Metaplasticity #Neocortex #Neural dynamics and brain function #Neuroscience #Neuroscience and Neuropharmacology Research #Nonsynaptic plasticity #Postsynaptic potential #Sensory system #Synaptic augmentation #Synaptic plasticity #q-bio.NC
paper · pdf · doi:10.1093/cercor/bhx339
published as Cerebral Cortex 28-4 (2018) 1396-1415 · 28 pages, 9 figures
arxiv created 2016/09/19 · openalex publication_date 2017/12/01 · arxiv updated 2018/03/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Excitatory synaptic connections in the adult neocortex consist of multiple synaptic contacts, almost exclusively formed on dendritic spines. Changes of spine volume, a correlate of synaptic strength, can be tracked in vivo for weeks. Here, we present a combined model of structural and spike-timing-dependent plasticity that explains the multicontact configuration of synapses in adult neocortical networks under steady-state and lesion-induced conditions. Our plasticity rule with Hebbian and anti-Hebbian terms stabilizes both the postsynaptic firing rate and correlations between the pre- and postsynaptic activity at an active synaptic contact. Contacts appear spontaneously at a low rate and disappear if their strength approaches zero. Many presynaptic neurons compete to make strong synaptic connections onto a postsynaptic neuron, whereas the synaptic contacts of a given presynaptic neuron co-operate via postsynaptic firing. We find that co-operation of multiple synaptic contacts is crucial for stable, long-term synaptic memories. In simulations of a simplified network model of barrel cortex, our plasticity rule reproduces whisker-trimming-induced rewiring of thalamocortical and recurrent synaptic connectivity on realistic time scales.