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      A History of Spike-Timing-Dependent Plasticity

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          Abstract

          How learning and memory is achieved in the brain is a central question in neuroscience. Key to today’s research into information storage in the brain is the concept of synaptic plasticity, a notion that has been heavily influenced by Hebb's ( 1949) postulate. Hebb conjectured that repeatedly and persistently co-active cells should increase connective strength among populations of interconnected neurons as a means of storing a memory trace, also known as an engram. Hebb certainly was not the first to make such a conjecture, as we show in this history. Nevertheless, literally thousands of studies into the classical frequency-dependent paradigm of cellular learning rules were directly inspired by the Hebbian postulate. But in more recent years, a novel concept in cellular learning has emerged, where temporal order instead of frequency is emphasized. This new learning paradigm – known as spike-timing-dependent plasticity (STDP) – has rapidly gained tremendous interest, perhaps because of its combination of elegant simplicity, biological plausibility, and computational power. But what are the roots of today’s STDP concept? Here, we discuss several centuries of diverse thinking, beginning with philosophers such as Aristotle, Locke, and Ribot, traversing, e.g., Lugaro’s plasticità and Rosenblatt’s perceptron, and culminating with the discovery of STDP. We highlight interactions between theoretical and experimental fields, showing how discoveries sometimes occurred in parallel, seemingly without much knowledge of the other field, and sometimes via concrete back-and-forth communication. We point out where the future directions may lie, which includes interneuron STDP, the functional impact of STDP, its mechanisms and its neuromodulatory regulation, and the linking of STDP to the developmental formation and continuous plasticity of neuronal networks.

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          Most cited references181

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          Neural networks and physical systems with emergent collective computational abilities.

          J Hopfield (1982)
          Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.
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            Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs.

            Activity-driven modifications in synaptic connections between neurons in the neocortex may occur during development and learning. In dual whole-cell voltage recordings from pyramidal neurons, the coincidence of postsynaptic action potentials (APs) and unitary excitatory postsynaptic potentials (EPSPs) was found to induce changes in EPSPs. Their average amplitudes were differentially up- or down-regulated, depending on the precise timing of postsynaptic APs relative to EPSPs. These observations suggest that APs propagating back into dendrites serve to modify single active synaptic connections, depending on the pattern of electrical activity in the pre- and postsynaptic neurons.
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              Competitive Hebbian learning through spike-timing-dependent synaptic plasticity.

              Hebbian models of development and learning require both activity-dependent synaptic plasticity and a mechanism that induces competition between different synapses. One form of experimentally observed long-term synaptic plasticity, which we call spike-timing-dependent plasticity (STDP), depends on the relative timing of pre- and postsynaptic action potentials. In modeling studies, we find that this form of synaptic modification can automatically balance synaptic strengths to make postsynaptic firing irregular but more sensitive to presynaptic spike timing. It has been argued that neurons in vivo operate in such a balanced regime. Synapses modifiable by STDP compete for control of the timing of postsynaptic action potentials. Inputs that fire the postsynaptic neuron with short latency or that act in correlated groups are able to compete most successfully and develop strong synapses, while synapses of longer-latency or less-effective inputs are weakened.
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                Author and article information

                Journal
                Front Synaptic Neurosci
                Front. Syn. Neurosci.
                Frontiers in Synaptic Neuroscience
                Frontiers Research Foundation
                1663-3563
                19 April 2011
                29 August 2011
                2011
                : 3
                : 4
                Affiliations
                [1] 1simpleBrain Mind Institute, Ecole Polytechnique Fédérale de Lausanne Lausanne, Switzerland
                [2] 2simpleDepartment of Neuroscience, Physiology and Pharmacology, University College London London, UK
                [3] 3simpleDepartment of Neurology and Neurosurgery, Centre for Research in Neuroscience, The Research Institute of the McGill University Health Centre, Montreal General Hospital Montreal, QC, Canada
                Author notes

                Edited by: Mary B. Kennedy, Caltech, USA

                Reviewed by: Kei Cho, University of Bristol, UK; Takeshi Sakaba, Max Planck Institute for Biophysical Chemistry, Germany; Yves Frégnac, CNRS UNIC, France; Larry Abbott, Columbia University, USA

                *Correspondence: Henry Markram, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland. e-mail: henry.markram@ 123456epfl.ch
                Article
                10.3389/fnsyn.2011.00004
                3187646
                22007168
                b2d855dc-b1aa-4ea9-9ee9-66c0dde20f3f
                Copyright © 2011 Markram, Gerstner and Sjöström.

                This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.

                History
                : 20 February 2011
                : 25 July 2011
                Page count
                Figures: 7, Tables: 0, Equations: 0, References: 261, Pages: 24, Words: 23490
                Categories
                Neuroscience
                Review Article

                Neurosciences
                memory,long term depression,synaptic plasticity,long term plasticity,spike-timing-dependent plasticity,bidirectional plasticity,history,learning

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