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      Opposing Effects of Neuronal Activity on Structural Plasticity

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          Abstract

          The connectivity of the brain is continuously adjusted to new environmental influences by several activity-dependent adaptive processes. The most investigated adaptive mechanism is activity-dependent functional or synaptic plasticity regulating the transmission efficacy of existing synapses. Another important but less prominently discussed adaptive process is structural plasticity, which changes the connectivity by the formation and deletion of synapses. In this review, we show, based on experimental evidence, that structural plasticity can be classified similar to synaptic plasticity into two categories: (i) Hebbian structural plasticity, which leads to an increase (decrease) of the number of synapses during phases of high (low) neuronal activity and (ii) homeostatic structural plasticity, which balances these changes by removing and adding synapses. Furthermore, based on experimental and theoretical insights, we argue that each type of structural plasticity fulfills a different function. While Hebbian structural changes enhance memory lifetime, storage capacity, and memory robustness, homeostatic structural plasticity self-organizes the connectivity of the neural network to assure stability. However, the link between functional synaptic and structural plasticity as well as the detailed interactions between Hebbian and homeostatic structural plasticity are more complex. This implies even richer dynamics requiring further experimental and theoretical investigations.

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          Most cited references198

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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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              Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type.

              Q Bi, G Bi, M Poo (1998)
              In cultures of dissociated rat hippocampal neurons, persistent potentiation and depression of glutamatergic synapses were induced by correlated spiking of presynaptic and postsynaptic neurons. The relative timing between the presynaptic and postsynaptic spiking determined the direction and the extent of synaptic changes. Repetitive postsynaptic spiking within a time window of 20 msec after presynaptic activation resulted in long-term potentiation (LTP), whereas postsynaptic spiking within a window of 20 msec before the repetitive presynaptic activation led to long-term depression (LTD). Significant LTP occurred only at synapses with relatively low initial strength, whereas the extent of LTD did not show obvious dependence on the initial synaptic strength. Both LTP and LTD depended on the activation of NMDA receptors and were absent in cases in which the postsynaptic neurons were GABAergic in nature. Blockade of L-type calcium channels with nimodipine abolished the induction of LTD and reduced the extent of LTP. These results underscore the importance of precise spike timing, synaptic strength, and postsynaptic cell type in the activity-induced modification of central synapses and suggest that Hebb's rule may need to incorporate a quantitative consideration of spike timing that reflects the narrow and asymmetric window for the induction of synaptic modification.
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                Author and article information

                Contributors
                Journal
                Front Neuroanat
                Front Neuroanat
                Front. Neuroanat.
                Frontiers in Neuroanatomy
                Frontiers Media S.A.
                1662-5129
                28 June 2016
                2016
                : 10
                : 75
                Affiliations
                [1] 1Department of Computational Neuroscience, Third Institute of Physics - Biophysics, Georg-August University Göttingen, Germany
                [2] 2Bernstein Center for Computational Neuroscience Göttingen, Germany
                [3] 3Max Planck Institute for Dynamics and Self-Organization Göttingen, Germany
                Author notes

                Edited by: Arjen Van Ooyen, Vrije Universiteit (VU), Netherlands

                Reviewed by: Jochen Triesch, Johann Wolfgang Goethe University, Germany; Andreas Vlachos, Heinrich-Heine-University, Germany

                *Correspondence: Michael Fauth mfauth@ 123456gwdg.de
                Article
                10.3389/fnana.2016.00075
                4923203
                27445713
                464cd778-57e7-482c-9565-fe29db072577
                Copyright © 2016 Fauth and Tetzlaff.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 08 September 2015
                : 16 June 2016
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 252, Pages: 18, Words: 16519
                Funding
                Funded by: Federal Ministry of Education and Research 10.13039/501100002347
                Award ID: 01GQ1005A
                Award ID: 01GQ1005B
                Funded by: Göttinger Graduiertenschule für Neurowissenschaften, Biophysik und Molekulare Biowissenschaften 10.13039/501100004939
                Award ID: GSC226/2
                Categories
                Neuroscience
                Review

                Neurosciences
                structural plasticity,architectural plasticity,timescales,synaptic plasticity,network topology

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