title: Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning.
abstract: Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. We show that spike-timing-dependent plasticity with both pre- and postsynaptic expression develops receptive fields with reduced variability and improved discriminability compared to postsynaptic plasticity alone. These long-term modifications in receptive field statistics match recent sensory perception experiments. Moreover, learning with this form of plasticity leaves a hidden postsynaptic memory trace that enables fast relearning of previously stored information, providing a cellular substrate for memory savings. Our results reveal essential roles for presynaptic plasticity that are missed when only postsynaptic expression of long-term plasticity is considered, and suggest an experience-dependent distribution of pre- and postsynaptic strength changes.
authors: Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|Neuroinformatics Doctoral Training Centre, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.|The Research Institute of the McGill University Health Centre, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.|Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, United Kingdom.
authors: Rui Ponte
authors: http://orcid.org/0000-0003-2595-2027
authors: RP
authors: Costa
authors: Skirball Institute for Biomolecular Medicine, Departments of Otolaryngology, Neuroscience and Physiology, New York University School of Medicine, New York, United States.|Center for Neural Science, New York University, New York, United States.
authors: Robert C
authors: RC
authors: Froemke
authors: The Research Institute of the McGill University Health Centre, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.
authors: P Jesper
authors: http://orcid.org/0000-0001-7085-2223
authors: PJ
authors: Sjöström
authors: Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom.
authors: Mark C W
authors: http://orcid.org/0000-0001-6525-6814
authors: MCW
authors: van Rossum
mesh_terms: D000200:Action Potentials; D000818:Animals; D007858:Learning; D008962:Models, Theoretical; D009473:Neuronal Plasticity; D013997:Time Factors
keywords: computational biology; learning rules; memory savings; neuroscience; pre- and postsynaptic long-term plasticity; rat; receptive fields; spike-timing-dependent plasticity; synaptic transmission; systems biology