title: Spike-timing dependent inhibitory plasticity to learn a selective gating of backpropagating action potentials.
abstract: Inhibition is known to influence the forward-directed flow of information within neurons. However, also regulation of backward-directed signals, such as backpropagating action potentials (bAPs), can enrich the functional repertoire of local circuits. Inhibitory control of bAP spread, for example, can provide a switch for the plasticity of excitatory synapses. Although such a mechanism is possible, it requires a precise timing of inhibition to annihilate bAPs without impairment of forward-directed excitatory information flow. Here, we propose a specific learning rule for inhibitory synapses to automatically generate the correct timing to gate bAPs in pyramidal cells when embedded in a local circuit of feedforward inhibition. Based on computational modeling of multi-compartmental neurons with physiological properties, we demonstrate that a learning rule with anti-Hebbian shape can establish the required temporal precision. In contrast to classical spike-timing dependent plasticity of excitatory synapses, the proposed inhibitory learning mechanism does not necessarily require the definition of an upper bound of synaptic weights because of its tendency to self-terminate once annihilation of bAPs has been reached. Our study provides a functional context in which one of the many time-dependent learning rules that have been observed experimentally - specifically, a learning rule with anti-Hebbian shape - is assigned a relevant role for inhibitory synapses. Moreover, the described mechanism is compatible with an upregulation of excitatory plasticity by disinhibition.
authors.affiliation: Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Philippstr. 13, 10115, Berlin, Germany.|Bernstein Center for Computational Neuroscience, Berlin, Germany.
authors.forename: Katharina Anna
authors.initials: KA
authors.lastname: Wilmes
authors.affiliation: Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Philippstr. 13, 10115, Berlin, Germany.|Bernstein Center for Computational Neuroscience, Berlin, Germany.
authors.forename: Jan-Hendrik
authors.initials: JH
authors.lastname: Schleimer
authors.affiliation: Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Philippstr. 13, 10115, Berlin, Germany.|Bernstein Center for Computational Neuroscience, Berlin, Germany.
authors.forename: Susanne
authors.initials: S
authors.lastname: Schreiber
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology; D003198:Computer Simulation; D019706:Excitatory Postsynaptic Potentials / Q000502:physiology; D008959:Models, Neurological; D009433:Neural Inhibition / Q000502:physiology*; D009434:Neural Pathways / Q000166:cytology / Q000502:physiology; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D017966:Pyramidal Cells / Q000502:physiology; D013997:Time Factors
keywords: dendritic inhibition; dendritic signaling; feedforward circuit; metaplasticity